From e3924a2bd4f2df75fec1ee129e5051511d266dfc Mon Sep 17 00:00:00 2001
From: PetervDooren <19806646+PetervDooren@users.noreply.github.com>
Date: Fri, 29 Oct 2021 12:21:21 +0200
Subject: [PATCH 001/136] create laser subscriber (example, does not work)

---
 ed_sensor_integration/tools/image_saver.cpp | 1 +
 1 file changed, 1 insertion(+)

diff --git a/ed_sensor_integration/tools/image_saver.cpp b/ed_sensor_integration/tools/image_saver.cpp
index 96d36ae1..7fe0a2bd 100644
--- a/ed_sensor_integration/tools/image_saver.cpp
+++ b/ed_sensor_integration/tools/image_saver.cpp
@@ -58,6 +58,7 @@ int main(int argc, char **argv)
     ros::init(argc, argv, "ed_image_saver");
     ros::NodeHandle nh;
     ros::ServiceClient cl_get_image = nh.serviceClient<ed_sensor_integration_msgs::GetImage>("ed/kinect/get_image");
+    ros::Subscriber laser_sub = nh.subscribe("base_laser/measurements", 1, LaserCallback);
 
     double fps = 1;
 

From ed2d9376c3759ffa77902fff68abb2f4976bca1a Mon Sep 17 00:00:00 2001
From: PetervDooren <19806646+PetervDooren@users.noreply.github.com>
Date: Fri, 29 Oct 2021 12:22:47 +0200
Subject: [PATCH 002/136] Create table_modeler.cpp

---
 ed_sensor_integration/tools/table_modeler.cpp | 1 +
 1 file changed, 1 insertion(+)
 create mode 100644 ed_sensor_integration/tools/table_modeler.cpp

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
new file mode 100644
index 00000000..1498a7fc
--- /dev/null
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -0,0 +1 @@
+// insert table modeller here

From f1c62a170ea35ba68e45b7272160454f677d025c Mon Sep 17 00:00:00 2001
From: PetervDooren <19806646+PetervDooren@users.noreply.github.com>
Date: Fri, 29 Oct 2021 12:25:19 +0200
Subject: [PATCH 003/136] Update CMakeLists.txt

---
 ed_sensor_integration/CMakeLists.txt | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index ffa0a8dc..9cc2cc75 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -102,6 +102,8 @@ add_dependencies(ed_image_saver ${catkin_EXPORTED_TARGETS})
 add_executable(ed_segmenter tools/segmenter.cpp)
 target_link_libraries(ed_segmenter ed_kinect)
 
+add_executable(ed_table_modeler tools/table_modeler.cpp)
+
 # ------------------------------------------------------------------------------------------------
 #                                           TESTS
 # ------------------------------------------------------------------------------------------------

From 0abc6a1f6f54012795e1b9ff1196f6b07c4ffffb Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Mon, 1 Nov 2021 15:43:42 +0100
Subject: [PATCH 004/136] Start work on loading files, library not working yet

---
 ed_sensor_integration/CMakeLists.txt          |  3 +-
 ed_sensor_integration/package.xml             |  1 +
 ed_sensor_integration/tools/image_saver.cpp   |  2 +-
 ed_sensor_integration/tools/table_modeler.cpp | 40 ++++++++++++++++++-
 4 files changed, 43 insertions(+), 3 deletions(-)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index 9cc2cc75..59d748ba 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -5,6 +5,7 @@ find_package(catkin REQUIRED COMPONENTS
   ed
   ed_sensor_integration_msgs
   geolib2
+  pcl_ros
   sensor_msgs
   tue_config
   tue_filesystem
@@ -19,7 +20,7 @@ catkin_package(
   INCLUDE_DIRS include
   LIBRARIES ed_kinect
   # DEPENDS
-  CATKIN_DEPENDS ed ed_sensor_integration_msgs tue_config
+  CATKIN_DEPENDS ed ed_sensor_integration_msgs pcl_ros tue_config
 )
 
 # ------------------------------------------------------------------------------------------------
diff --git a/ed_sensor_integration/package.xml b/ed_sensor_integration/package.xml
index f1a4f656..000ba9fe 100644
--- a/ed_sensor_integration/package.xml
+++ b/ed_sensor_integration/package.xml
@@ -16,6 +16,7 @@
   <depend>ed</depend>
   <depend>ed_sensor_integration_msgs</depend>
   <depend>geolib2</depend>
+  <depend>pcl_ros</depend>
   <depend>sensor_msgs</depend>
   <depend>tue_config</depend>
   <depend>tue_filesystem</depend>
diff --git a/ed_sensor_integration/tools/image_saver.cpp b/ed_sensor_integration/tools/image_saver.cpp
index 7fe0a2bd..54920754 100644
--- a/ed_sensor_integration/tools/image_saver.cpp
+++ b/ed_sensor_integration/tools/image_saver.cpp
@@ -58,7 +58,7 @@ int main(int argc, char **argv)
     ros::init(argc, argv, "ed_image_saver");
     ros::NodeHandle nh;
     ros::ServiceClient cl_get_image = nh.serviceClient<ed_sensor_integration_msgs::GetImage>("ed/kinect/get_image");
-    ros::Subscriber laser_sub = nh.subscribe("base_laser/measurements", 1, LaserCallback);
+    //ros::Subscriber laser_sub = nh.subscribe("base_laser/measurements", 1, LaserCallback);
 
     double fps = 1;
 
diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 1498a7fc..6a1be71f 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -1 +1,39 @@
-// insert table modeller here
+#include <pcl/io/pcd_io.h>
+#include <pcl/point_types.h>
+
+int main(int argc, char **argv) {
+
+    if (argc < 2)
+        {
+            std::cout << "Usage:\n\n   table_modeler FILENAME1 FILENAME2 ...\n\n";
+            return 1;
+        }
+
+        pcl::PointCloud<pcl::PointXYZRGB> inputs [argc-1];
+
+        for (int i = 1; i < argc; ++i)
+        {
+            std::string name = std::string(argv[i]);
+
+            // open pcd file
+            if (pcl::io::loadPCDFile<pcl::PointXYZRGB> (name, inputs[i-1]) == -1) //* load the file
+            {
+                //PCL_ERROR ("Couldn't read file" + name + "\n");
+            }
+            else
+            {
+
+            // read json metadata
+
+
+            // align to world model coordinates
+
+
+            // align to previous file
+
+            }
+        }
+
+
+    return 0;
+}

From c6be97f74ebac688f0c2a69dc12f863ee4112a91 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Fri, 5 Nov 2021 09:42:08 +0100
Subject: [PATCH 005/136] Fix target linking to pcl

---
 ed_sensor_integration/CMakeLists.txt | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index 59d748ba..f228a18f 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -20,7 +20,7 @@ catkin_package(
   INCLUDE_DIRS include
   LIBRARIES ed_kinect
   # DEPENDS
-  CATKIN_DEPENDS ed ed_sensor_integration_msgs pcl_ros tue_config
+  CATKIN_DEPENDS ed ed_sensor_integration_msgs tue_config
 )
 
 # ------------------------------------------------------------------------------------------------
@@ -104,7 +104,7 @@ add_executable(ed_segmenter tools/segmenter.cpp)
 target_link_libraries(ed_segmenter ed_kinect)
 
 add_executable(ed_table_modeler tools/table_modeler.cpp)
-
+target_link_libraries (ed_table_modeler ${catkin_LIBRARIES})
 # ------------------------------------------------------------------------------------------------
 #                                           TESTS
 # ------------------------------------------------------------------------------------------------

From d2c3d1b911d349856fe7cd8e59b744056368a56e Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Mon, 15 Nov 2021 15:01:52 +0100
Subject: [PATCH 006/136] Implement registration algorithm

---
 ed_sensor_integration/tools/table_modeler.cpp | 123 +++++++++++++++---
 1 file changed, 103 insertions(+), 20 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 6a1be71f..9c773882 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -1,39 +1,122 @@
-#include <pcl/io/pcd_io.h>
 #include <pcl/point_types.h>
+#include <pcl/point_cloud.h>
+#include <pcl/point_representation.h>
+
+#include <pcl/io/pcd_io.h>
+
+#include <pcl/filters/filter.h>
+
+#include <pcl/features/normal_3d.h>
+
+#include <pcl/registration/icp.h>
+#include <pcl/registration/icp_nl.h>
+#include <pcl/registration/transforms.h>
+
+void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, pcl::PointCloud<pcl::PointXYZRGB>::Ptr output, Eigen::Matrix4f &final_transform)
+{
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr src (new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr tgt (new pcl::PointCloud<pcl::PointXYZRGB>);
+
+    src = cloud_src;
+    tgt = cloud_tgt;
+
+
+    //
+    // Align
+    pcl::IterativeClosestPointNonLinear<pcl::PointXYZRGB, pcl::PointXYZRGB> reg;
+    reg.setTransformationEpsilon (1e-6);
+    // Set the maximum distance between two correspondences (src<->tgt) to 10cm
+    // Note: adjust this based on the size of your datasets
+    reg.setMaxCorrespondenceDistance (0.1);
+    // Set the point representation
+    // reg.setPointRepresentation (pcl::make_shared<const MyPointRepresentation> (point_representation));
+
+    reg.setInputSource (src);
+    reg.setInputTarget (tgt);
+
+
+
+    //
+    // Run the optimization
+    Eigen::Matrix4f targetToSource;
+    reg.setMaximumIterations (60);
+
+    reg.align (*src);
+
+
+        //
+    // Get the transformation from target to source
+    targetToSource = reg.getFinalTransformation().inverse();
+
+    //
+    // Transform target back in source frame
+    pcl::transformPointCloud (*cloud_tgt, *output, targetToSource);
+
+
+
+    //add the source to the transformed target
+    *output += *cloud_src;
+
+    final_transform = targetToSource;
+ }
+
 
 int main(int argc, char **argv) {
 
+    // open pcd files
+
     if (argc < 2)
-        {
-            std::cout << "Usage:\n\n   table_modeler FILENAME1 FILENAME2 ...\n\n";
-            return 1;
-        }
+    {
+        std::cout << "Usage:\n\n   table_modeler FILENAME1 FILENAME2 ...\n\n";
+        return 1;
+    }
+
+    //pcl::PointCloud<pcl::PointXYZRGB>::Ptr inputs[argc-1]; //(new pcl::PointCloud<pcl::PointXYZRGB>);
+    std::vector <pcl::PointCloud<pcl::PointXYZRGB>::Ptr, Eigen::aligned_allocator <pcl::PointCloud <pcl::PointXYZRGB>::Ptr > > inputs;
+
+    std::vector<int> indices;
 
-        pcl::PointCloud<pcl::PointXYZRGB> inputs [argc-1];
+    std::cout << "starting to open" << std::endl;
 
-        for (int i = 1; i < argc; ++i)
+    for (int i = 1; i < argc; ++i)
+    {
+        std::string name = std::string(argv[i]);
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr m(new pcl::PointCloud<pcl::PointXYZRGB>);
+        std::cout << "attempting to open " << name << std::endl;
+        if (pcl::io::loadPCDFile<pcl::PointXYZRGB> (name, *m) == -1) //* load the file
         {
-            std::string name = std::string(argv[i]);
+            //PCL_ERROR ("Couldn't read file" + name + "\n");
+            return -1;
+        }
+        std::cout << "opened " << name << std::endl;
+        pcl::removeNaNFromPointCloud(*m, *m, indices);
+        std::cout << "removed NAN from " << name << std::endl;
+        inputs.push_back(m);
+    }
 
-            // open pcd file
-            if (pcl::io::loadPCDFile<pcl::PointXYZRGB> (name, inputs[i-1]) == -1) //* load the file
-            {
-                //PCL_ERROR ("Couldn't read file" + name + "\n");
-            }
-            else
-            {
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr result (new pcl::PointCloud<pcl::PointXYZRGB>), source, target;
+    Eigen::Matrix4f GlobalTransform = Eigen::Matrix4f::Identity (), pairTransform;
 
-            // read json metadata
+    for (int i = 1; i < argc-1; ++i)
+    {
+        // read json metadata
 
+        // align to world model coordinates
 
-            // align to world model coordinates
+        // align to previous file
 
+        source = inputs[i-1];
+        target = inputs[i];
 
-            // align to previous file
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr temp (new pcl::PointCloud<pcl::PointXYZRGB>);
+        pairAlign (source, target, temp, pairTransform);
 
-            }
-        }
+        pcl::transformPointCloud (*temp, *result, GlobalTransform);
+
+        GlobalTransform *= pairTransform;
 
+        pcl::io::savePCDFileASCII ("combined.pcd", *result);
+    }
 
     return 0;
 }

From d17ffa17eae0e0871c9f7ce3474d386201b85494 Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Thu, 18 Nov 2021 12:21:52 +0100
Subject: [PATCH 007/136] implement transformation matrix, json file not loaded

---
 ed_sensor_integration/tools/table_modeler.cpp | 41 ++++++++++++++++++-
 1 file changed, 40 insertions(+), 1 deletion(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 9c773882..642026d1 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -12,6 +12,11 @@
 #include <pcl/registration/icp_nl.h>
 #include <pcl/registration/transforms.h>
 
+#include <boost/filesystem/convenience.hpp>
+
+#include <fstream>
+#include <jsoncpp/json/json.h>
+
 void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, pcl::PointCloud<pcl::PointXYZRGB>::Ptr output, Eigen::Matrix4f &final_transform)
 {
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr src (new pcl::PointCloud<pcl::PointXYZRGB>);
@@ -94,12 +99,44 @@ int main(int argc, char **argv) {
         inputs.push_back(m);
     }
 
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr result (new pcl::PointCloud<pcl::PointXYZRGB>), source, target;
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr result (new pcl::PointCloud<pcl::PointXYZRGB>), source, target;
     Eigen::Matrix4f GlobalTransform = Eigen::Matrix4f::Identity (), pairTransform;
 
     for (int i = 1; i < argc-1; ++i)
     {
         // read json metadata
+        /*
+        std::ifstream metadata_file(boost::filesystem::change_extension(argv[i-1], ".json").string(), std::ifstream::binary);
+        Json::Value metadata;
+        metadata_file >> metadata;
+        */
+        float x, y, z, qx, qy, qz, qw;
+
+        const float n = 2.0f/(qx*qx+qy*qy+qz*qz+qw*qw);
+        Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();/* {
+            {1.0f - n*qy*qy - n*qz*qz, n*qx*qy - n*qz*qw, n*qx*qz + n*qy*qw, x},
+            {n*qx*qy + n*qz*qw, 1.0f - n*qx*qx - n*qz*qz, n*qy*qz - n*qx*qw, y},
+            {n*qx*qz - n*qy*qw, n*qy*qz + n*qx*qw, 1.0f - n*qx*qx - n*qy*qy, z},
+            {0.0f, 0.0f, 0.0f, 1.0f}}; */
+
+        Transform(0,0) = 1.0f - n*qy*qy - n*qz*qz;
+        Transform(0,1) = n*qx*qy - n*qz*qw;
+        Transform(0,2) = n*qx*qz + n*qy*qw;
+        Transform(0,3) = x;
+        Transform(1,0) = n*qx*qy + n*qz*qw;
+        Transform(1,1) = 1.0f - n*qx*qx - n*qz*qz;
+        Transform(1,2) = n*qy*qz - n*qx*qw;
+        Transform(1,3) = y;
+        Transform(2,0) = n*qx*qz - n*qy*qw;
+        Transform(2,1) = n*qy*qz + n*qx*qw;
+        Transform(2,2) = 1.0f - n*qx*qx - n*qy*qy;
+        Transform(2,3) = z;
+
+        Transform = Transform.inverse();
+
+        pcl::transformPointCloud (*inputs[i], *inputs[i], Transform);
+
+        //std::cout << metadata["rgbd_filename"] << std::endl;
 
         // align to world model coordinates
 
@@ -109,6 +146,8 @@ int main(int argc, char **argv) {
         target = inputs[i];
 
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr temp (new pcl::PointCloud<pcl::PointXYZRGB>);
+
+        std::cout << "aligning cloud " << i << " to cloud " << i - 1 << std::endl;
         pairAlign (source, target, temp, pairTransform);
 
         pcl::transformPointCloud (*temp, *result, GlobalTransform);

From c32c1a161af964a5457f1b5a2ac6aa1cf58587c7 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Thu, 18 Nov 2021 14:11:05 +0100
Subject: [PATCH 008/136] Read out json start

---
 ed_sensor_integration/tools/table_modeler.cpp | 46 ++++++++++++++++---
 1 file changed, 39 insertions(+), 7 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 642026d1..4de85c0f 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -14,8 +14,14 @@
 
 #include <boost/filesystem/convenience.hpp>
 
+#include <ed/io/json_reader.h>
+#include <ed/serialization/serialization.h>
+
+#include <tue/config/read.h>
+#include <tue/config/reader.h>
+#include <tue/config/data_pointer.h>
+
 #include <fstream>
-#include <jsoncpp/json/json.h>
 
 void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, pcl::PointCloud<pcl::PointXYZRGB>::Ptr output, Eigen::Matrix4f &final_transform)
 {
@@ -104,13 +110,39 @@ int main(int argc, char **argv) {
 
     for (int i = 1; i < argc-1; ++i)
     {
+        std::cout << "iteration " << i << std::endl;
+
+        std::string pcd_filename = argv[i];
+        std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();
         // read json metadata
-        /*
-        std::ifstream metadata_file(boost::filesystem::change_extension(argv[i-1], ".json").string(), std::ifstream::binary);
-        Json::Value metadata;
-        metadata_file >> metadata;
-        */
-        float x, y, z, qx, qy, qz, qw;
+        tue::config::DataPointer meta_data;
+
+        try
+        {
+            meta_data = tue::config::fromFile(json_filename);
+        }
+        catch (tue::config::ParseException& e)
+        {
+            std::cerr << "Could not open '" << json_filename << "'.\n\n" << e.what() << std::endl;
+            return 0;
+        }
+
+        tue::config::Reader r(meta_data);
+        // Read sensor pose
+        geo::Pose3D sensor_pose;
+        if (!ed::deserialize(r, "sensor_pose", sensor_pose))
+        {
+            std::cerr << "No field 'sensor_pose' specified." << std::endl;
+            return 0;
+        }
+
+        std::cout << "x: " << sensor_pose.t.x << ", y: " << sensor_pose.t.y << std::endl;
+        float x = sensor_pose.t.x;
+        float y = sensor_pose.t.y;
+        float z = sensor_pose.t.z;
+
+
+        float qx, qy, qz, qw;
 
         const float n = 2.0f/(qx*qx+qy*qy+qz*qz+qw*qw);
         Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();/* {

From feb29c7aaa48b254d26db34cb0fee413b5de1f1b Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Fri, 19 Nov 2021 13:12:45 +0100
Subject: [PATCH 009/136] apply rotation matrix WIP

---
 ed_sensor_integration/tools/table_modeler.cpp | 133 ++++++++++--------
 1 file changed, 75 insertions(+), 58 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 4de85c0f..f95ca970 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -71,6 +71,73 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
     final_transform = targetToSource;
  }
 
+Eigen::Matrix4f ReadJson(std::string pcd_filename) {
+
+    std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();
+    // read json metadata
+    tue::config::DataPointer meta_data;
+
+    try
+    {
+        meta_data = tue::config::fromFile(json_filename);
+    }
+    catch (tue::config::ParseException& e)
+    {
+        std::cerr << "Could not open '" << json_filename << "'.\n\n" << e.what() << std::endl;
+        //return 0;
+    }
+
+    tue::config::Reader r(meta_data);
+    // Read sensor pose
+    geo::Pose3D sensor_pose;
+    if (!ed::deserialize(r, "sensor_pose", sensor_pose))
+    {
+        std::cerr << "No field 'sensor_pose' specified." << std::endl;
+        //return 0;
+    }
+
+    std::cout << "x: " << sensor_pose.t.x << ", y: " << sensor_pose.t.y << std::endl;
+    float x = sensor_pose.t.x;
+    float y = sensor_pose.t.y;
+    float z = sensor_pose.t.z;
+    float xx = sensor_pose.R.xx;
+    float xy = sensor_pose.R.xy;
+    float xz = sensor_pose.R.xz;
+    float yx = sensor_pose.R.yx;
+    float yy = sensor_pose.R.yy;
+    float yz = sensor_pose.R.yz;
+    float zx = sensor_pose.R.zx;
+    float zy = sensor_pose.R.zy;
+    float zz = sensor_pose.R.zz;
+
+
+    //float qx, qy, qz, qw;
+
+    //const float n = 2.0f/(qx*qx+qy*qy+qz*qz+qw*qw);
+    Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();/* {
+        {1.0f - n*qy*qy - n*qz*qz, n*qx*qy - n*qz*qw, n*qx*qz + n*qy*qw, x},
+        {n*qx*qy + n*qz*qw, 1.0f - n*qx*qx - n*qz*qz, n*qy*qz - n*qx*qw, y},
+        {n*qx*qz - n*qy*qw, n*qy*qz + n*qx*qw, 1.0f - n*qx*qx - n*qy*qy, z},
+        {0.0f, 0.0f, 0.0f, 1.0f}}; */
+
+    Transform(0,0) = xx;//1.0f - n*qy*qy - n*qz*qz;
+    Transform(0,1) = xy;//n*qx*qy - n*qz*qw;
+    Transform(0,2) = xz;//n*qx*qz + n*qy*qw;
+    Transform(0,3) = x;
+    Transform(1,0) = yx;//n*qx*qy + n*qz*qw;
+    Transform(1,1) = yy;//1.0f - n*qx*qx - n*qz*qz;
+    Transform(1,2) = yz;//n*qy*qz - n*qx*qw;
+    Transform(1,3) = y;
+    Transform(2,0) = zx;//n*qx*qz - n*qy*qw;
+    Transform(2,1) = zy;//n*qy*qz + n*qx*qw;
+    Transform(2,2) = zz;//1.0f - n*qx*qx - n*qy*qy;
+    Transform(2,3) = z;
+
+    Transform = Transform.inverse();
+
+    return Transform;
+}
+
 
 int main(int argc, char **argv) {
 
@@ -108,65 +175,15 @@ int main(int argc, char **argv) {
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr result (new pcl::PointCloud<pcl::PointXYZRGB>), source, target;
     Eigen::Matrix4f GlobalTransform = Eigen::Matrix4f::Identity (), pairTransform;
 
-    for (int i = 1; i < argc-1; ++i)
-    {
-        std::cout << "iteration " << i << std::endl;
+    pcl::transformPointCloud (*inputs[0], *inputs[0], ReadJson(argv[1]));
 
-        std::string pcd_filename = argv[i];
-        std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();
-        // read json metadata
-        tue::config::DataPointer meta_data;
+    *result = *inputs[0];
 
-        try
-        {
-            meta_data = tue::config::fromFile(json_filename);
-        }
-        catch (tue::config::ParseException& e)
-        {
-            std::cerr << "Could not open '" << json_filename << "'.\n\n" << e.what() << std::endl;
-            return 0;
-        }
-
-        tue::config::Reader r(meta_data);
-        // Read sensor pose
-        geo::Pose3D sensor_pose;
-        if (!ed::deserialize(r, "sensor_pose", sensor_pose))
-        {
-            std::cerr << "No field 'sensor_pose' specified." << std::endl;
-            return 0;
-        }
-
-        std::cout << "x: " << sensor_pose.t.x << ", y: " << sensor_pose.t.y << std::endl;
-        float x = sensor_pose.t.x;
-        float y = sensor_pose.t.y;
-        float z = sensor_pose.t.z;
-
-
-        float qx, qy, qz, qw;
-
-        const float n = 2.0f/(qx*qx+qy*qy+qz*qz+qw*qw);
-        Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();/* {
-            {1.0f - n*qy*qy - n*qz*qz, n*qx*qy - n*qz*qw, n*qx*qz + n*qy*qw, x},
-            {n*qx*qy + n*qz*qw, 1.0f - n*qx*qx - n*qz*qz, n*qy*qz - n*qx*qw, y},
-            {n*qx*qz - n*qy*qw, n*qy*qz + n*qx*qw, 1.0f - n*qx*qx - n*qy*qy, z},
-            {0.0f, 0.0f, 0.0f, 1.0f}}; */
-
-        Transform(0,0) = 1.0f - n*qy*qy - n*qz*qz;
-        Transform(0,1) = n*qx*qy - n*qz*qw;
-        Transform(0,2) = n*qx*qz + n*qy*qw;
-        Transform(0,3) = x;
-        Transform(1,0) = n*qx*qy + n*qz*qw;
-        Transform(1,1) = 1.0f - n*qx*qx - n*qz*qz;
-        Transform(1,2) = n*qy*qz - n*qx*qw;
-        Transform(1,3) = y;
-        Transform(2,0) = n*qx*qz - n*qy*qw;
-        Transform(2,1) = n*qy*qz + n*qx*qw;
-        Transform(2,2) = 1.0f - n*qx*qx - n*qy*qy;
-        Transform(2,3) = z;
-
-        Transform = Transform.inverse();
+    for (int i = 1; i < argc-1; ++i)
+    {
+        std::cout << "iteration " << i << std::endl;   
 
-        pcl::transformPointCloud (*inputs[i], *inputs[i], Transform);
+        pcl::transformPointCloud (*inputs[i], *inputs[i], ReadJson(argv[i+1]));pcl::transformPointCloud (*inputs[i], *inputs[i], ReadJson(argv[i+1]));
 
         //std::cout << metadata["rgbd_filename"] << std::endl;
 
@@ -185,9 +202,9 @@ int main(int argc, char **argv) {
         pcl::transformPointCloud (*temp, *result, GlobalTransform);
 
         GlobalTransform *= pairTransform;
-
-        pcl::io::savePCDFileASCII ("combined.pcd", *result);
     }
 
+    pcl::io::savePCDFileASCII ("combined.pcd", *result);
+
     return 0;
 }

From 9164ad8361a4dcdbc93b765b4a6a3146b25a2b47 Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Sat, 20 Nov 2021 20:09:35 +0100
Subject: [PATCH 010/136] Finish rotation matrix

---
 ed_sensor_integration/tools/table_modeler.cpp | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index f95ca970..59c08b25 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -133,8 +133,8 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename) {
     Transform(2,2) = zz;//1.0f - n*qx*qx - n*qy*qy;
     Transform(2,3) = z;
 
-    Transform = Transform.inverse();
-
+    //Transform = Transform.inverse();
+    std::cout << Transform << std::endl;
     return Transform;
 }
 
@@ -183,9 +183,7 @@ int main(int argc, char **argv) {
     {
         std::cout << "iteration " << i << std::endl;   
 
-        pcl::transformPointCloud (*inputs[i], *inputs[i], ReadJson(argv[i+1]));pcl::transformPointCloud (*inputs[i], *inputs[i], ReadJson(argv[i+1]));
-
-        //std::cout << metadata["rgbd_filename"] << std::endl;
+        pcl::transformPointCloud (*inputs[i], *inputs[i], ReadJson(argv[i+1]));
 
         // align to world model coordinates
 

From 84ce07927cddd374d5d6effecd78e6b2f0f82d7d Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Mon, 22 Nov 2021 15:14:35 +0100
Subject: [PATCH 011/136] Implement temporary fix rotation matrix, start on
 segmentation

---
 ed_sensor_integration/tools/table_modeler.cpp | 42 ++++++++++++++++++-
 1 file changed, 40 insertions(+), 2 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 59c08b25..19fe85d8 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -70,7 +70,40 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
 
     final_transform = targetToSource;
  }
-
+/*
+void Segment (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud) {
+
+    // Creating the KdTree object for the search method of the extraction
+    pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
+    tree->setInputCloud (cloud);
+
+    std::vector<pcl::PointIndices> cluster_indices;
+    pcl::EuclideanClusterExtraction<pcl::PointXYZ> ec;
+    ec.setClusterTolerance (0.02); // 2cm
+    ec.setMinClusterSize (100);
+    ec.setMaxClusterSize (25000);
+    ec.setSearchMethod (tree);
+    ec.setInputCloud (cloud_filtered);
+    ec.extract (cluster_indices);
+
+    int j = 0;
+    for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it != cluster_indices.end (); ++it)
+    {
+        pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZ>);
+        for (const auto& idx : it->indices)
+        cloud_cluster->push_back ((*cloud_filtered)[idx]); //*
+        cloud_cluster->width = cloud_cluster->size ();
+        cloud_cluster->height = 1;
+        cloud_cluster->is_dense = true;
+
+        std::cout << "PointCloud representing the Cluster: " << cloud_cluster->size () << " data points." << std::endl;
+        std::stringstream ss;
+        ss << "cloud_cluster_" << j << ".pcd";
+        writer.write<pcl::PointXYZ> (ss.str (), *cloud_cluster, false); //*
+        j++;
+     }
+}
+*/
 Eigen::Matrix4f ReadJson(std::string pcd_filename) {
 
     std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();
@@ -133,7 +166,12 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename) {
     Transform(2,2) = zz;//1.0f - n*qx*qx - n*qy*qy;
     Transform(2,3) = z;
 
-    //Transform = Transform.inverse();
+    //Temporary fix for wrong rotational matrix
+    Eigen::Matrix4f Correction = Eigen::Matrix4f::Identity();
+    Correction(1,1) = -1;
+    Correction(2,2) = -1;
+    Transform = Transform * Correction.inverse();
+
     std::cout << Transform << std::endl;
     return Transform;
 }

From af77594a9fb3e77b89213cf8e5f4be132161132a Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Mon, 22 Nov 2021 16:09:40 +0100
Subject: [PATCH 012/136] transform from geolib camera pose to ros camera pose

---
 ed_sensor_integration/tools/table_modeler.cpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 19fe85d8..5bdb458d 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -128,6 +128,8 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename) {
         std::cerr << "No field 'sensor_pose' specified." << std::endl;
         //return 0;
     }
+    // convert from geolib coordinates to ros coordinates #TODO remove geolib coordinates for camera pose
+    sensor_pose.R = sensor_pose.R * geo::Mat3(1, 0, 0, 0, -1, 0, 0, 0, -1);
 
     std::cout << "x: " << sensor_pose.t.x << ", y: " << sensor_pose.t.y << std::endl;
     float x = sensor_pose.t.x;

From 447f15c83efa0adea44782314eb9e9094ae0fc2e Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Fri, 26 Nov 2021 20:11:18 +0100
Subject: [PATCH 013/136] Finish segmentation

---
 ed_sensor_integration/tools/table_modeler.cpp | 124 ++++++++++++------
 1 file changed, 83 insertions(+), 41 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 19fe85d8..da68e797 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -5,6 +5,8 @@
 #include <pcl/io/pcd_io.h>
 
 #include <pcl/filters/filter.h>
+#include <pcl/filters/extract_indices.h>
+#include <pcl/filters/conditional_removal.h>
 
 #include <pcl/features/normal_3d.h>
 
@@ -12,6 +14,8 @@
 #include <pcl/registration/icp_nl.h>
 #include <pcl/registration/transforms.h>
 
+#include <pcl/segmentation/extract_clusters.h>
+
 #include <boost/filesystem/convenience.hpp>
 
 #include <ed/io/json_reader.h>
@@ -23,13 +27,13 @@
 
 #include <fstream>
 
-void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, pcl::PointCloud<pcl::PointXYZRGB>::Ptr output, Eigen::Matrix4f &final_transform)
+void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, Eigen::Matrix4f &final_transform)
 {
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr src (new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr tgt (new pcl::PointCloud<pcl::PointXYZRGB>);
 
-    src = cloud_src;
-    tgt = cloud_tgt;
+    *src = *cloud_src;
+    *tgt = *cloud_tgt;
 
 
     //
@@ -57,54 +61,61 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
 
         //
     // Get the transformation from target to source
-    targetToSource = reg.getFinalTransformation().inverse();
-
-    //
-    // Transform target back in source frame
-    pcl::transformPointCloud (*cloud_tgt, *output, targetToSource);
-
-
-
-    //add the source to the transformed target
-    *output += *cloud_src;
+    targetToSource = reg.getFinalTransformation();//.inverse();
 
     final_transform = targetToSource;
  }
-/*
-void Segment (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud) {
+
+void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z) {
+    std::cout << "starting segmentation" << std::endl;
+    std::cout << "x = " << x << ", y = " << y << ", z = " << z << std::endl;
 
     // Creating the KdTree object for the search method of the extraction
-    pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
+    pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZRGB>);
     tree->setInputCloud (cloud);
 
     std::vector<pcl::PointIndices> cluster_indices;
-    pcl::EuclideanClusterExtraction<pcl::PointXYZ> ec;
-    ec.setClusterTolerance (0.02); // 2cm
-    ec.setMinClusterSize (100);
-    ec.setMaxClusterSize (25000);
+    pcl::EuclideanClusterExtraction<pcl::PointXYZRGB> ec;
+    ec.setClusterTolerance (0.1);
+    ec.setMinClusterSize ((*cloud).size()/100);
+    ec.setMaxClusterSize ((*cloud).size());
     ec.setSearchMethod (tree);
-    ec.setInputCloud (cloud_filtered);
+    ec.setInputCloud (cloud);
     ec.extract (cluster_indices);
 
-    int j = 0;
+    std::cout << "obtained cluster indices" <<std::endl;
+
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out;
+    float mindist = -1;
     for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it != cluster_indices.end (); ++it)
     {
-        pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZ>);
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZRGB>);
         for (const auto& idx : it->indices)
-        cloud_cluster->push_back ((*cloud_filtered)[idx]); //*
+        cloud_cluster->push_back ((*cloud)[idx]); //*
         cloud_cluster->width = cloud_cluster->size ();
         cloud_cluster->height = 1;
         cloud_cluster->is_dense = true;
-
-        std::cout << "PointCloud representing the Cluster: " << cloud_cluster->size () << " data points." << std::endl;
-        std::stringstream ss;
-        ss << "cloud_cluster_" << j << ".pcd";
-        writer.write<pcl::PointXYZ> (ss.str (), *cloud_cluster, false); //*
-        j++;
-     }
+        float sumx = 0, sumy = 0, sumz = 0, dist = 0;
+        for (uint j=0; j < (*cloud_cluster).width; ++j)
+        {
+            sumx += (*cloud_cluster)[j].x;
+            sumy += (*cloud_cluster)[j].y;
+            sumz += (*cloud_cluster)[j].z;
+        }
+        dist = pow((sumx/(*cloud_cluster).width-x),2) + pow((sumy/(*cloud_cluster).width-y),2) + pow((sumz/(*cloud_cluster).width-z),2);
+        std::cout << "distance is " << sqrt(dist) << std::endl;
+        if ((dist < mindist)||(mindist<0))
+        {
+            std::cout << "updating closest cluster" << std::endl;
+            mindist = dist;
+            cloud_out = cloud_cluster;
+        }
+    }
+    std::cout << "writing closest cluster" << std::endl;
+    *cloud = *cloud_out;
 }
-*/
-Eigen::Matrix4f ReadJson(std::string pcd_filename) {
+
+Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, float *zout) {
 
     std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();
     // read json metadata
@@ -129,7 +140,6 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename) {
         //return 0;
     }
 
-    std::cout << "x: " << sensor_pose.t.x << ", y: " << sensor_pose.t.y << std::endl;
     float x = sensor_pose.t.x;
     float y = sensor_pose.t.y;
     float z = sensor_pose.t.z;
@@ -143,6 +153,9 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename) {
     float zy = sensor_pose.R.zy;
     float zz = sensor_pose.R.zz;
 
+    *xout = x;
+    *yout = y;
+    *zout = z;
 
     //float qx, qy, qz, qw;
 
@@ -213,7 +226,24 @@ int main(int argc, char **argv) {
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr result (new pcl::PointCloud<pcl::PointXYZRGB>), source, target;
     Eigen::Matrix4f GlobalTransform = Eigen::Matrix4f::Identity (), pairTransform;
 
-    pcl::transformPointCloud (*inputs[0], *inputs[0], ReadJson(argv[1]));
+
+    float x, y, z;//used to store camera position
+    pcl::transformPointCloud (*inputs[0], *inputs[0], ReadJson(argv[1], &x, &y, &z));
+
+    // Filter out floor
+    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+    range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, 0.1)));
+    // build the filter
+    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+    condrem.setCondition (range_cond);
+    condrem.setInputCloud (inputs[0]);
+    condrem.setKeepOrganized(true);
+    // apply filter
+    condrem.filter (*inputs[0]);
+    (*inputs[0]).is_dense = false;
+    pcl::removeNaNFromPointCloud(*inputs[0], *inputs[0], indices);
+
+    Segment(inputs[0], x, y, z);
 
     *result = *inputs[0];
 
@@ -221,23 +251,35 @@ int main(int argc, char **argv) {
     {
         std::cout << "iteration " << i << std::endl;   
 
-        pcl::transformPointCloud (*inputs[i], *inputs[i], ReadJson(argv[i+1]));
+        pcl::transformPointCloud (*inputs[i], *inputs[i], ReadJson(argv[i+1], &x, &y, &z));
+
+        //filter out floor
+        condrem.setInputCloud (inputs[i]);
+        // apply filter
+        condrem.filter (*inputs[i]);
+        (*inputs[i]).is_dense = false;
+        pcl::removeNaNFromPointCloud(*inputs[i], *inputs[i], indices);
+
+        Segment(inputs[i], x, y, z);
 
         // align to world model coordinates
 
         // align to previous file
 
-        source = inputs[i-1];
-        target = inputs[i];
+        source = inputs[i];
+        //target = inputs[i];
 
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr temp (new pcl::PointCloud<pcl::PointXYZRGB>);
 
         std::cout << "aligning cloud " << i << " to cloud " << i - 1 << std::endl;
-        pairAlign (source, target, temp, pairTransform);
-
-        pcl::transformPointCloud (*temp, *result, GlobalTransform);
+        pairAlign (source, result, pairTransform);
+        std::cout << "transformation matrix =" << std::endl << pairTransform << std::endl;
 
         GlobalTransform *= pairTransform;
+
+        pcl::transformPointCloud (*source, *temp, pairTransform);
+
+        *result += *temp;
     }
 
     pcl::io::savePCDFileASCII ("combined.pcd", *result);

From 4491ba1bb74e420daa0dda6c82adc5afde2d232c Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Fri, 26 Nov 2021 20:14:26 +0100
Subject: [PATCH 014/136] Remove temporary fix

---
 ed_sensor_integration/tools/table_modeler.cpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 5f2704c4..70c3e3a1 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -181,11 +181,13 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, flo
     Transform(2,2) = zz;//1.0f - n*qx*qx - n*qy*qy;
     Transform(2,3) = z;
 
+    /*
     //Temporary fix for wrong rotational matrix
     Eigen::Matrix4f Correction = Eigen::Matrix4f::Identity();
     Correction(1,1) = -1;
     Correction(2,2) = -1;
     Transform = Transform * Correction.inverse();
+    */
 
     std::cout << Transform << std::endl;
     return Transform;

From 5fd99bc0db2b29e01a2684d6c246fa6876242f8f Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Mon, 6 Dec 2021 16:54:16 +0100
Subject: [PATCH 015/136] Implement concave hull & table height

---
 ed_sensor_integration/tools/table_modeler.cpp | 64 ++++++++++++++++---
 1 file changed, 56 insertions(+), 8 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 70c3e3a1..e3772dac 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -16,6 +16,9 @@
 
 #include <pcl/segmentation/extract_clusters.h>
 
+#include <pcl/surface/convex_hull.h>
+#include <pcl/surface/concave_hull.h>
+
 #include <boost/filesystem/convenience.hpp>
 
 #include <ed/io/json_reader.h>
@@ -66,7 +69,7 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
     final_transform = targetToSource;
  }
 
-void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z) {
+void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z, float* tableHeight) {
     std::cout << "starting segmentation" << std::endl;
     std::cout << "x = " << x << ", y = " << y << ", z = " << z << std::endl;
 
@@ -86,7 +89,7 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
     std::cout << "obtained cluster indices" <<std::endl;
 
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out;
-    float mindist = -1;
+    float mindist = INFINITY;
     for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it != cluster_indices.end (); ++it)
     {
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZRGB>);
@@ -95,20 +98,28 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
         cloud_cluster->width = cloud_cluster->size ();
         cloud_cluster->height = 1;
         cloud_cluster->is_dense = true;
-        float sumx = 0, sumy = 0, sumz = 0, dist = 0;
+        float sumx = 0, sumy = 0, sumz = 0, dist = 0, maxz = -INFINITY;
         for (uint j=0; j < (*cloud_cluster).width; ++j)
         {
             sumx += (*cloud_cluster)[j].x;
             sumy += (*cloud_cluster)[j].y;
             sumz += (*cloud_cluster)[j].z;
+            if ((*cloud_cluster)[j].z > maxz)
+            {
+                maxz = (*cloud_cluster)[j].z;
+            }
         }
         dist = pow((sumx/(*cloud_cluster).width-x),2) + pow((sumy/(*cloud_cluster).width-y),2) + pow((sumz/(*cloud_cluster).width-z),2);
         std::cout << "distance is " << sqrt(dist) << std::endl;
-        if ((dist < mindist)||(mindist<0))
+        if (dist < mindist)
         {
             std::cout << "updating closest cluster" << std::endl;
             mindist = dist;
             cloud_out = cloud_cluster;
+            if (maxz < *tableHeight)
+            {
+                *tableHeight = maxz;
+            }
         }
     }
     std::cout << "writing closest cluster" << std::endl;
@@ -193,6 +204,36 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, flo
     return Transform;
 }
 
+pcl::PointCloud<pcl::PointXYZ> Fit(pcl::PointCloud<pcl::PointXYZRGB> cloud) {
+    float totx = 0, toty = 0, avgx, avgy;
+
+    pcl::PointCloud<pcl::PointXYZ>::Ptr flat(new pcl::PointCloud<pcl::PointXYZ>);
+    Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity ();
+    std::cout << "Cloud width = " << (cloud).width << std::endl;
+    (*flat).width = (cloud).width;
+    (*flat).resize((*flat).width);
+    for (uint i=0; i < (cloud).width; ++i)
+    {
+        //std::cout << "Writing point " << i << std::endl;
+        (*flat)[i].x = cloud[i].x;
+        (*flat)[i].y = cloud[i].y;
+        (*flat)[i].z = 0;
+
+        totx += (*flat)[i].x;
+        toty += (*flat)[i].y;
+    }
+    Transform(0,3) = -totx/(*flat).width;
+    Transform(1,3) = -toty/(*flat).width;
+
+    pcl::transformPointCloud (*flat, *flat, Transform);
+
+    pcl::ConcaveHull<pcl::PointXYZ> CHull;
+    CHull.setInputCloud(flat);
+    CHull.setAlpha (0.1);
+    CHull.setDimension(2);
+    CHull.reconstruct(*flat);
+    return *flat;
+}
 
 int main(int argc, char **argv) {
 
@@ -230,6 +271,7 @@ int main(int argc, char **argv) {
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr result (new pcl::PointCloud<pcl::PointXYZRGB>), source, target;
     Eigen::Matrix4f GlobalTransform = Eigen::Matrix4f::Identity (), pairTransform;
 
+    float tableHeight = INFINITY;//used to keep track of the table height
 
     float x, y, z;//used to store camera position
     pcl::transformPointCloud (*inputs[0], *inputs[0], ReadJson(argv[1], &x, &y, &z));
@@ -247,7 +289,7 @@ int main(int argc, char **argv) {
     (*inputs[0]).is_dense = false;
     pcl::removeNaNFromPointCloud(*inputs[0], *inputs[0], indices);
 
-    Segment(inputs[0], x, y, z);
+    Segment(inputs[0], x, y, z, &tableHeight);
 
     *result = *inputs[0];
 
@@ -255,6 +297,7 @@ int main(int argc, char **argv) {
     {
         std::cout << "iteration " << i << std::endl;   
 
+        // align to world model coordinates
         pcl::transformPointCloud (*inputs[i], *inputs[i], ReadJson(argv[i+1], &x, &y, &z));
 
         //filter out floor
@@ -264,9 +307,7 @@ int main(int argc, char **argv) {
         (*inputs[i]).is_dense = false;
         pcl::removeNaNFromPointCloud(*inputs[i], *inputs[i], indices);
 
-        Segment(inputs[i], x, y, z);
-
-        // align to world model coordinates
+        Segment(inputs[i], x, y, z, &tableHeight);
 
         // align to previous file
 
@@ -286,7 +327,14 @@ int main(int argc, char **argv) {
         *result += *temp;
     }
 
+    pcl::PointCloud<pcl::PointXYZ> flat;
+    flat = Fit(*result);
+    std::cout << flat.width << std::endl;
+
+    std::cout << "Writing clouds" << std::endl;
     pcl::io::savePCDFileASCII ("combined.pcd", *result);
+    pcl::io::savePCDFileASCII ("flat.pcd", flat);
+    std::cout << "The table is " << tableHeight << "m tall" << std::endl;
 
     return 0;
 }

From 061a44386e2bd54670674d51e9f3c8b0205cdea4 Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Fri, 17 Dec 2021 20:39:42 +0100
Subject: [PATCH 016/136] Implement rectangle sac model

---
 .../sac_model_rectangle.h                     | 333 ++++++++++
 .../sac_model_rectangle.hpp                   | 584 ++++++++++++++++++
 ed_sensor_integration/tools/table_modeler.cpp |  39 +-
 3 files changed, 954 insertions(+), 2 deletions(-)
 create mode 100644 ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.h
 create mode 100644 ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.h
new file mode 100644
index 00000000..f3a73dc4
--- /dev/null
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.h
@@ -0,0 +1,333 @@
+ /*
+  * Software License Agreement (BSD License)
+  *
+  *  Point Cloud Library (PCL) - www.pointclouds.org
+  *  Copyright (c) 2010-2011, Willow Garage, Inc.
+  *  Copyright (c) 2012-, Open Perception, Inc.
+  *
+  *  All rights reserved.
+  *
+  *  Redistribution and use in source and binary forms, with or without
+  *  modification, are permitted provided that the following conditions
+  *  are met:
+  *
+  *   * Redistributions of source code must retain the above copyright
+  *     notice, this list of conditions and the following disclaimer.
+  *   * Redistributions in binary form must reproduce the above
+  *     copyright notice, this list of conditions and the following
+  *     disclaimer in the documentation and/or other materials provided
+  *     with the distribution.
+  *   * Neither the name of the copyright holder(s) nor the names of its
+  *     contributors may be used to endorse or promote products derived
+  *     from this software without specific prior written permission.
+  *
+  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+  *  POSSIBILITY OF SUCH DAMAGE.
+  *
+  * $Id$
+  *
+  */
+  
+ #pragma once
+  
+ #include <pcl/sample_consensus/sac_model.h>
+ #include <pcl/sample_consensus/model_types.h>
+ #include <pcl/common/distances.h>
+  
+ namespace pcl
+ {
+   /** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
+     * The model coefficients are defined as:
+     *   - \b point_on_axis.x  : the X coordinate of a point located on the cylinder axis
+     *   - \b point_on_axis.y  : the Y coordinate of a point located on the cylinder axis
+     *   - \b point_on_axis.z  : the Z coordinate of a point located on the cylinder axis
+     *   - \b axis_direction.x : the X coordinate of the cylinder's axis direction
+     *   - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
+     *   - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
+     *   - \b radius           : the cylinder's radius
+     * 
+     * \author Radu Bogdan Rusu
+     * \ingroup sample_consensus
+     */
+   template <typename PointT>
+   class SampleConsensusModelRectangle : public SampleConsensusModel<PointT>
+   {
+     public:
+       using SampleConsensusModel<PointT>::model_name_;
+       using SampleConsensusModel<PointT>::input_;
+       using SampleConsensusModel<PointT>::indices_;
+       using SampleConsensusModel<PointT>::radius_min_;
+       using SampleConsensusModel<PointT>::radius_max_;
+       using SampleConsensusModel<PointT>::error_sqr_dists_;
+  
+       using PointCloud = typename SampleConsensusModel<PointT>::PointCloud;
+       using PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr;
+       using PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr;
+  
+       using Ptr = shared_ptr<SampleConsensusModelRectangle<PointT> >;
+       using ConstPtr = shared_ptr<const SampleConsensusModelRectangle<PointT>>;
+  
+       /** \brief Constructor for base SampleConsensusModelCylinder.
+         * \param[in] cloud the input point cloud dataset
+         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+         */
+       SampleConsensusModelRectangle (const PointCloudConstPtr &cloud, bool random = false) 
+         : SampleConsensusModel<PointT> (cloud, random)
+         , axis_ (Eigen::Vector3f::Zero ())
+         , eps_angle_ (0)
+       {
+         model_name_ = "SampleConsensusModelRectangle";
+         sample_size_ = 3;
+         model_size_ = 5;
+       }
+  
+       /** \brief Constructor for base SampleConsensusModelCylinder.
+         * \param[in] cloud the input point cloud dataset
+         * \param[in] indices a vector of point indices to be used from \a cloud
+         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+         */
+       SampleConsensusModelRectangle (const PointCloudConstPtr &cloud, 
+                                     const Indices &indices,
+                                     bool random = false) 
+         : SampleConsensusModel<PointT> (cloud, indices, random)
+         , axis_ (Eigen::Vector3f::Zero ())
+         , eps_angle_ (0)
+       {
+         model_name_ = "SampleConsensusModelRectangle";
+         sample_size_ = 3;
+         model_size_ = 5;
+       }
+  
+       /** \brief Copy constructor.
+         * \param[in] source the model to copy into this
+         */
+       SampleConsensusModelRectangle (const SampleConsensusModelRectangle &source) :
+         SampleConsensusModel<PointT> (),
+         axis_ (Eigen::Vector3f::Zero ()),
+         eps_angle_ (0)
+       {
+         *this = source;
+         model_name_ = "SampleConsensusModelRectangle";
+       }
+       
+       /** \brief Empty destructor */
+       ~SampleConsensusModelRectangle () {}
+  
+       /** \brief Copy constructor.
+         * \param[in] source the model to copy into this
+         */
+       inline SampleConsensusModelRectangle&
+       operator = (const SampleConsensusModelRectangle &source)
+       {
+         SampleConsensusModel<PointT>::operator=(source);
+         axis_ = source.axis_;
+         eps_angle_ = source.eps_angle_;
+         return (*this);
+       }
+  
+       /** \brief Set the angle epsilon (delta) threshold.
+         * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
+         */
+       inline void 
+       setEpsAngle (const double ea) { eps_angle_ = ea; }
+  
+       /** \brief Get the angle epsilon (delta) threshold. */
+       inline double 
+       getEpsAngle () const { return (eps_angle_); }
+  
+       /** \brief Set the axis along which we need to search for a cylinder direction.
+         * \param[in] ax the axis along which we need to search for a cylinder direction
+         */
+       inline void 
+       setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
+  
+       /** \brief Get the axis along which we need to search for a cylinder direction. */
+       inline Eigen::Vector3f 
+       getAxis () const { return (axis_); }
+  
+       /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
+         * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
+         * axis_direction, cylinder_radius_R
+         * \param[in] samples the point indices found as possible good candidates for creating a valid model
+         * \param[out] model_coefficients the resultant model coefficients
+         */
+       bool
+       computeModelCoefficients (const Indices &samples,
+                                 Eigen::VectorXf &model_coefficients) const override;
+  
+       /** \brief Compute all distances from the cloud data to a given cylinder model.
+         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
+         * \param[out] distances the resultant estimated distances
+         */
+       void
+       getDistancesToModel (const Eigen::VectorXf &model_coefficients,
+                            std::vector<double> &distances) const override;
+  
+       /** \brief Select all the points which respect the given model coefficients as inliers.
+         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
+         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+         * \param[out] inliers the resultant model inliers
+         */
+       void 
+       selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
+                             const double threshold, 
+                             Indices &inliers) override;
+  
+       /** \brief Count all the points which respect the given model coefficients as inliers. 
+         * 
+         * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
+         * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
+         * \return the resultant number of inliers
+         */
+       std::size_t
+       countWithinDistance (const Eigen::VectorXf &model_coefficients,
+                            const double threshold) const override;
+  
+       /** \brief Recompute the cylinder coefficients using the given inlier set and return them to the user.
+         * @note: these are the coefficients of the cylinder model after refinement (e.g. after SVD)
+         * \param[in] inliers the data inliers found as supporting the model
+         * \param[in] model_coefficients the initial guess for the optimization
+         * \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization
+         */
+       void
+       optimizeModelCoefficients (const Indices &inliers,
+                                  const Eigen::VectorXf &model_coefficients,
+                                  Eigen::VectorXf &optimized_coefficients) const override;
+  
+  
+       /** \brief Create a new point cloud with inliers projected onto the cylinder model.
+         * \param[in] inliers the data inliers that we want to project on the cylinder model
+         * \param[in] model_coefficients the coefficients of a cylinder model
+         * \param[out] projected_points the resultant projected points
+         * \param[in] copy_data_fields set to true if we need to copy the other data fields
+         */
+       void
+       projectPoints (const Indices &inliers,
+                      const Eigen::VectorXf &model_coefficients,
+                      PointCloud &projected_points,
+                      bool copy_data_fields = true) const override;
+  
+       /** \brief Verify whether a subset of indices verifies the given cylinder model coefficients.
+         * \param[in] indices the data indices that need to be tested against the cylinder model
+         * \param[in] model_coefficients the cylinder model coefficients
+         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+         */
+       bool
+       doSamplesVerifyModel (const std::set<int> &indices,
+                             const Eigen::VectorXf &model_coefficients,
+                             const double threshold) const override;
+  
+       /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
+       inline pcl::SacModel 
+       getModelType () const override { return (SACMODEL_CYLINDER); } //cannot add a unique identifier for rectangle
+  
+     protected:
+       using SampleConsensusModel<PointT>::sample_size_;
+       using SampleConsensusModel<PointT>::model_size_;
+  
+       /** \brief Get the distance from a point to a line (represented by a point and a direction)
+         * \param[in] pt a point
+         * \param[in] model_coefficients the line coefficients (a point on the line, line direction)
+         */
+       double
+       pointToLineDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const;
+  
+       /** \brief Project a point onto a line given by a point and a direction vector
+         * \param[in] pt the input point to project
+         * \param[in] line_pt the point on the line (make sure that line_pt[3] = 0 as there are no internal checks!)
+         * \param[in] line_dir the direction of the line (make sure that line_dir[3] = 0 as there are no internal checks!)
+         * \param[out] pt_proj the resultant projected point
+         */
+       inline void
+       projectPointToLine (const Eigen::Vector4f &pt,
+                           const Eigen::Vector4f &line_pt,
+                           const Eigen::Vector4f &line_dir,
+                           Eigen::Vector4f &pt_proj) const
+       {
+         float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
+         // Calculate the projection of the point on the line
+         pt_proj = line_pt + k * line_dir;
+       }
+  
+       /** \brief Project a point onto a cylinder given by its model coefficients (point_on_axis, axis_direction,
+         * cylinder_radius_R)
+         * \param[in] pt the input point to project
+         * \param[in] model_coefficients the coefficients of the cylinder (point_on_axis, axis_direction, cylinder_radius_R)
+         * \param[out] pt_proj the resultant projected point
+         */
+       void
+       projectPointToRectangle (const Eigen::Vector4f &pt,
+                               const Eigen::VectorXf &model_coefficients,
+                               Eigen::Vector4f &pt_proj) const;
+  
+       /** \brief Check whether a model is valid given the user constraints.
+         * \param[in] model_coefficients the set of model coefficients
+         */
+       bool
+       isModelValid (const Eigen::VectorXf &model_coefficients) const override;
+  
+       /** \brief Check if a sample of indices results in a good sample of points
+         * indices. Pure virtual.
+         * \param[in] samples the resultant index samples
+         */
+       bool
+       isSampleGood (const Indices &samples) const override;
+  
+     private:
+       /** \brief The axis along which we need to search for a cylinder direction. */
+       Eigen::Vector3f axis_;
+     
+       /** \brief The maximum allowed difference between the cylinder direction and the given axis. */
+       double eps_angle_;
+  
+       /** \brief Functor for the optimization function */
+       struct OptimizationFunctor : pcl::Functor<float>
+       {
+         /** Functor constructor
+           * \param[in] indices the indices of data points to evaluate
+           * \param[in] estimator pointer to the estimator object
+           */
+         OptimizationFunctor (const pcl::SampleConsensusModelRectangle<PointT> *model, const Indices& indices) :
+           pcl::Functor<float> (indices.size ()), model_ (model), indices_ (indices) {}
+  
+         /** Cost function to be minimized
+           * \param[in] x variables array
+           * \param[out] fvec resultant functions evaluations
+           * \return 0
+           */
+         int 
+         operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
+         {
+           Eigen::Vector4f line_pt  (x[0], x[1], x[2], 0);
+           Eigen::Vector4f line_dir (x[3], x[4], x[5], 0);
+           
+           for (int i = 0; i < values (); ++i)
+           {
+             // dist = f - r
+             Eigen::Vector4f pt = (*model_->input_)[indices_[i]].getVector4fMap();
+             pt[3] = 0;
+  
+             fvec[i] = static_cast<float> (pcl::sqrPointToLineDistance (pt, line_pt, line_dir) - x[6]*x[6]);
+           }
+           return (0);
+         }
+  
+         const pcl::SampleConsensusModelRectangle<PointT> *model_;
+         const Indices &indices_;
+       };
+   };
+ }
+  
+ //#ifdef PCL_NO_PRECOMPILE
+ #include "ed_sensor_integration/sac_model_rectangle.hpp"
+ //#endif
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp
new file mode 100644
index 00000000..91a6acff
--- /dev/null
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp
@@ -0,0 +1,584 @@
+ /*
+  * Software License Agreement (BSD License)
+  *
+  *  Point Cloud Library (PCL) - www.pointclouds.org
+  *  Copyright (c) 2009-2010, Willow Garage, Inc.
+  *  Copyright (c) 2012-, Open Perception, Inc.
+  *
+  *  All rights reserved.
+  *
+  *  Redistribution and use in source and binary forms, with or without
+  *  modification, are permitted provided that the following conditions
+  *  are met:
+  *
+  *   * Redistributions of source code must retain the above copyright
+  *     notice, this list of conditions and the following disclaimer.
+  *   * Redistributions in binary form must reproduce the above
+  *     copyright notice, this list of conditions and the following
+  *     disclaimer in the documentation and/or other materials provided
+  *     with the distribution.
+  *   * Neither the name of the copyright holder(s) nor the names of its
+  *     contributors may be used to endorse or promote products derived
+  *     from this software without specific prior written permission.
+  *
+  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+  *  POSSIBILITY OF SUCH DAMAGE.
+  *
+  * $Id$
+  *
+  */
+  
+ #ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_RECTANGLE_H_
+ #define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_RECTANGLE_H_
+  
+ #include <unsupported/Eigen/NonLinearOptimization> // for LevenbergMarquardt
+ #include "ed_sensor_integration/sac_model_rectangle.h"
+ #include <pcl/common/common.h> // for getAngle3D
+ #include <pcl/common/concatenate.h>
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool
+ pcl::SampleConsensusModelRectangle<PointT>::isSampleGood (const Indices &samples) const
+ {
+   if (samples.size () != sample_size_)
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelRectangle::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
+     return (false);
+   }
+   return (true);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool
+ pcl::SampleConsensusModelRectangle<PointT>::computeModelCoefficients (
+       const Indices &samples, Eigen::VectorXf &model_coefficients) const
+ {
+   // Need 3 samples
+   if (samples.size () != sample_size_)
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelRectangle::computeModelCoefficients] Invalid set of samples given (%lu)!\n", samples.size ());
+     return (false);
+   }
+  
+   if (std::abs ((*input_)[samples[0]].x - (*input_)[samples[1]].x) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].y - (*input_)[samples[1]].y) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].z - (*input_)[samples[1]].z) <= std::numeric_limits<float>::epsilon () ||
+       std::abs ((*input_)[samples[1]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[1]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[1]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon () ||
+       std::abs ((*input_)[samples[0]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon ()) 
+   {
+     return (false);
+   }
+   Eigen::Vector2f p1 ((*input_)[samples[0]].x, (*input_)[samples[0]].y);
+   Eigen::Vector2f p2 ((*input_)[samples[1]].x, (*input_)[samples[1]].y);
+   Eigen::Vector2f p3 ((*input_)[samples[2]].x, (*input_)[samples[2]].y);
+   
+   float x = p1(0), y = p1(1); //output: x and y values
+   
+   Eigen::Vector2f c1 = p2 - p1; //vector between point 1 and 2
+   
+   float l = sqrt(c1.dot(c1)); //output: initially define length as distance between point 1 and 2
+   
+   Eigen::Vector2f c2 = p1 - p3; //vector between point 3 and 1
+   
+   float w = (c1(0)*c2(1)-c2(0)*c1(1))/l; //output: width defined as distance between c1 and point 3, signed
+   
+   Eigen::Matrix2f transform = Eigen::Matrix2f::Identity().transpose();
+   transform(1,0) = -1;
+   transform = transform*w/l;
+   
+   Eigen::Vector2f c3 = transform * c1; //vector perpendicular to c1 with length w, pointing from c1 to point 3
+   
+   // determine rotation:
+   
+   float r = std::atan2(c1(1), c1(0)); //output: rotation of the rectangle
+   
+   //now check if p3 lies outside the described rectangle:
+   
+   Eigen::Vector2f t1 = p1+c3-p3, t2 = p2+c3-p3;
+   float d1 = sqrt(t1.dot(t1)), d2 = sqrt(t2.dot(t2));
+   if (d1 < l && d2 < d1)
+   {
+	   l = d1; //update only length
+   }
+   else if (d2 < l && d1 < d2)
+   {
+	   l = d2; //update both length and origin
+	   x = (p3-c3)(0);
+	   y = (p3-c3)(1);
+   }
+   
+   if (w < 0)
+   {
+	   x += c3(0);
+	   y += c3(1);
+	   w = std::abs(w);
+   }
+   
+   //save model coefficients
+   model_coefficients.resize (model_size_);
+   model_coefficients[0] = x;
+   model_coefficients[1] = y;
+   model_coefficients[2] = l;
+   model_coefficients[3] = w;
+   model_coefficients[4] = r;
+   
+   PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::computeModelCoefficients] Model is (%g,%g,%g,%g,%g).\n",
+              model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
+              model_coefficients[4]);
+   return (true);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelRectangle<PointT>::getDistancesToModel (
+       const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
+ {
+   // Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+   {
+     distances.clear ();
+     return;
+   }
+  
+   distances.resize (indices_->size ());
+   
+   float x = model_coefficients[0], y = model_coefficients[1], l = model_coefficients[2], w = model_coefficients[3], r = model_coefficients[4];
+   float d1, d2, d3, d4;
+
+   Eigen::Vector2f p1, p2, p3, p4, c1, c2;
+   
+   //define edge vectors
+   c1(0)=std::cos(r)*l;
+   c1(1)=std::sin(r)*l;
+
+   c2(0)= std::sin(r)*w;
+   c2(1)=-std::cos(r)*w;
+
+   //define corner vectors
+   p1(0)=x;
+   p1(1)=y;
+   p2 = p1 + c1;
+   p3 = p2 + c2;
+   p4 = p1 + c2;
+   
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+	   Eigen::Vector2f in ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y);
+	   
+	   //compute distances to lines
+		d1 = ( c1(0)*(p1(1)-in(1))-( p1(0)-in(0))*c1(1))/l; //Distance between line 1 and the point
+		d2 = ( c2(0)*(p2(1)-in(1))-( p2(0)-in(0))*c1(1))/w; //Distance between line 2 and the point
+		d3 = (-c1(0)*(p3(1)-in(1))-(-p3(0)-in(0))*c1(1))/l; //Distance between line 3 and the point
+		d4 = (-c1(0)*(p4(1)-in(1))-(-p4(0)-in(0))*c1(1))/w; //Distance between line 4 and the point
+		//note: these distances are signed, such that points lying inside the rectangle have positive distance to all lines
+
+		if (d1>0 && d2>0 && d3>0 && d4>0) //inside the rectangle
+		{
+			distances[i] = std::min(d1, std::min(d2, std::min(d3, d4))); //smallest of d1, d2, d3 and d4
+		}
+		else if (d1<=0 && d2>=0 && d4>=0) //closest to line 1
+		{
+			distances[i] = std::abs(d1);
+		}
+		else if (d2<=0 && d3>=0 && d1>=0) //closest to line 2
+		{
+			distances[i] = std::abs(d2);
+		}
+		else if (d3<=0 && d4>=0 && d2>=0) //closest to line 3
+		{
+			distances[i] = std::abs(d3);
+		}
+		else if (d4<=0 && d1>=0 && d3>=0) //closest to line 4
+		{
+			distances[i] = std::abs(d4);
+		}
+		else if (d1<0 && d4<0) //closest to corner 1
+		{
+			Eigen::Vector2f v = in - p1;
+			distances[i] = sqrt(v.dot(v)); //distance between corner 1 and the point
+		}
+		else if (d2<0 && d1<0) //closest to corner 2
+		{
+			Eigen::Vector2f v = in - p2;
+			distances[i] = sqrt(v.dot(v)); //distance between corner 2 and the point
+		}
+		else if (d3<0 && d2<0) //closest to corner 3
+		{
+			Eigen::Vector2f v = in - p3;
+			distances[i] = sqrt(v.dot(v)); //distance between corner 3 and the point
+		}
+		else if (d4<0 && d3<0) //closest to corner 4
+		{
+			Eigen::Vector2f v = in - p4;
+			distances[i] = sqrt(v.dot(v)); //distance between corner 4 and the point
+		}
+   }
+   
+  /*
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+   // Iterate through the 3d points and calculate the distances from them to the sphere
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     // @note need to revise this.
+     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
+  
+     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
+  
+     // Calculate the point's projection on the cylinder axis
+     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
+     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
+     Eigen::Vector4f dir = pt - pt_proj;
+     dir.normalize ();
+  
+     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
+     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
+     double d_normal = std::abs (getAngle3D (n, dir));
+     d_normal = (std::min) (d_normal, M_PI - d_normal);
+  
+     distances[i] = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);*/
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelRectangle<PointT>::selectWithinDistance (
+       const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
+ {
+   /*
+   // Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+   {
+     inliers.clear ();
+     return;
+   }
+  
+   inliers.clear ();
+   error_sqr_dists_.clear ();
+   inliers.reserve (indices_->size ());
+   error_sqr_dists_.reserve (indices_->size ());
+  
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+   // Iterate through the 3d points and calculate the distances from them to the sphere
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
+     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
+     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
+       continue;
+  
+     // Calculate the point's projection on the cylinder axis
+     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
+     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
+     Eigen::Vector4f dir = pt - pt_proj;
+     dir.normalize ();
+  
+     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
+     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
+     double d_normal = std::abs (getAngle3D (n, dir));
+     d_normal = (std::min) (d_normal, M_PI - d_normal);
+  
+     double distance = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);
+     if (distance < threshold)
+     {
+       // Returns the indices of the points whose distances are smaller than the threshold
+       inliers.push_back ((*indices_)[i]);
+       error_sqr_dists_.push_back (distance);
+     }
+   }*/
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> std::size_t
+ pcl::SampleConsensusModelRectangle<PointT>::countWithinDistance (
+       const Eigen::VectorXf &model_coefficients, const double threshold) const
+ {
+   std::vector<double> distances;
+   getDistancesToModel (model_coefficients, distances);
+   int count = 0;
+   for (int i = 0; i < distances.size(); i++)
+   {
+	   if (distances[i] <= threshold) {count++;}
+   }
+   return (count);
+   /*// Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+     return (0);
+  
+   std::size_t nr_p = 0;
+  
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+   // Iterate through the 3d points and calculate the distances from them to the sphere
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
+     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
+     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
+       continue;
+  
+     // Calculate the point's projection on the cylinder axis
+     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
+     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
+     Eigen::Vector4f dir = pt - pt_proj;
+     dir.normalize ();
+  
+     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
+     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
+     double d_normal = std::abs (getAngle3D (n, dir));
+     d_normal = (std::min) (d_normal, M_PI - d_normal);
+  
+     if (std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist) < threshold)
+       nr_p++;
+   }
+   return (nr_p);*/
+   return (0);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelRectangle<PointT>::optimizeModelCoefficients (
+       const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
+ {
+   optimized_coefficients = model_coefficients;
+  
+   // Needs a set of valid model coefficients
+   if (!isModelValid (model_coefficients))
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelRectangle::optimizeModelCoefficients] Given model is invalid!\n");
+     return;
+   }
+  
+   // Need more than the minimum sample size to make a difference
+   if (inliers.size () <= sample_size_)
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelRectangle:optimizeModelCoefficients] Not enough inliers found to optimize model coefficients (%lu)! Returning the same coefficients.\n", inliers.size ());
+     return;
+   }
+  
+   OptimizationFunctor functor (this, inliers);
+   Eigen::NumericalDiff<OptimizationFunctor > num_diff (functor);
+   Eigen::LevenbergMarquardt<Eigen::NumericalDiff<OptimizationFunctor>, float> lm (num_diff);
+   int info = lm.minimize (optimized_coefficients);
+   
+   // Compute the L2 norm of the residuals
+   PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::optimizeModelCoefficients] LM solver finished with exit code %i, having a residual norm of %g. \nInitial solution: %g %g %g %g %g %g %g \nFinal solution: %g %g %g %g %g %g %g\n",
+              info, lm.fvec.norm (), model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
+              model_coefficients[4], model_coefficients[5], model_coefficients[6], optimized_coefficients[0], optimized_coefficients[1], optimized_coefficients[2], optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5], optimized_coefficients[6]);
+     
+   Eigen::Vector3f line_dir (optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5]);
+   line_dir.normalize ();
+   optimized_coefficients[3] = line_dir[0];
+   optimized_coefficients[4] = line_dir[1];
+   optimized_coefficients[5] = line_dir[2];
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelRectangle<PointT>::projectPoints (
+       const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
+ {
+   // Needs a valid set of model coefficients
+   if (!isModelValid (model_coefficients))
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelRectangle::projectPoints] Given model is invalid!\n");
+     return;
+   }
+  
+   projected_points.header = input_->header;
+   projected_points.is_dense = input_->is_dense;
+  
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+  
+   // Copy all the data fields from the input cloud to the projected one?
+   if (copy_data_fields)
+   {
+     // Allocate enough space and copy the basics
+     projected_points.resize (input_->size ());
+     projected_points.width    = input_->width;
+     projected_points.height   = input_->height;
+  
+     using FieldList = typename pcl::traits::fieldList<PointT>::type;
+     // Iterate over each point
+     for (std::size_t i = 0; i < projected_points.size (); ++i)
+       // Iterate over each dimension
+       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
+  
+     // Iterate through the 3d points and calculate the distances from them to the cylinder
+     for (const auto &inlier : inliers)
+     {
+       Eigen::Vector4f p ((*input_)[inlier].x,
+                          (*input_)[inlier].y,
+                          (*input_)[inlier].z,
+                          1);
+  
+       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
+  
+       pcl::Vector4fMap pp = projected_points[inlier].getVector4fMap ();
+       pp.matrix () = line_pt + k * line_dir;
+  
+       Eigen::Vector4f dir = p - pp;
+       dir[3] = 0.0f;
+       dir.normalize ();
+  
+       // Calculate the projection of the point onto the cylinder
+       pp += dir * model_coefficients[6];
+     }
+   }
+   else
+   {
+     // Allocate enough space and copy the basics
+     projected_points.resize (inliers.size ());
+     projected_points.width    = inliers.size ();
+     projected_points.height   = 1;
+  
+     using FieldList = typename pcl::traits::fieldList<PointT>::type;
+     // Iterate over each point
+     for (std::size_t i = 0; i < inliers.size (); ++i)
+       // Iterate over each dimension
+       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
+  
+     // Iterate through the 3d points and calculate the distances from them to the cylinder
+     for (std::size_t i = 0; i < inliers.size (); ++i)
+     {
+       pcl::Vector4fMap pp = projected_points[i].getVector4fMap ();
+       pcl::Vector4fMapConst p = (*input_)[inliers[i]].getVector4fMap ();
+  
+       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
+       // Calculate the projection of the point on the line
+       pp.matrix () = line_pt + k * line_dir;
+  
+       Eigen::Vector4f dir = p - pp;
+       dir[3] = 0.0f;
+       dir.normalize ();
+  
+       // Calculate the projection of the point onto the cylinder
+       pp += dir * model_coefficients[6];
+     }
+   }
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool
+ pcl::SampleConsensusModelRectangle<PointT>::doSamplesVerifyModel (
+       const std::set<int> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
+ {
+   // Needs a valid model coefficients
+   if (!isModelValid (model_coefficients))
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelRectangle::doSamplesVerifyModel] Given model is invalid!\n");
+     return (false);
+   }
+  
+   for (const auto &index : indices)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     // @note need to revise this.
+     Eigen::Vector4f pt ((*input_)[index].x, (*input_)[index].y, (*input_)[index].z, 0.0f);
+     if (std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]) > threshold)
+       return (false);
+   }
+  
+   return (true);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> double
+ pcl::SampleConsensusModelRectangle<PointT>::pointToLineDistance (
+       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const
+ {
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   return sqrt(pcl::sqrPointToLineDistance (pt, line_pt, line_dir));
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelRectangle<PointT>::projectPointToRectangle (
+       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients, Eigen::Vector4f &pt_proj) const
+ {
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+  
+   float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) * line_dir.dot (line_dir);
+   pt_proj = line_pt + k * line_dir;
+  
+   Eigen::Vector4f dir = pt - pt_proj;
+   dir.normalize ();
+  
+   // Calculate the projection of the point onto the cylinder
+   pt_proj += dir * model_coefficients[6];
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool 
+ pcl::SampleConsensusModelRectangle<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
+ {
+   if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
+     return (false);
+  
+   // Check against template, if given
+   if (eps_angle_ > 0.0)
+   {
+     // Obtain the cylinder direction
+     const Eigen::Vector3f coeff(model_coefficients[3], model_coefficients[4], model_coefficients[5]);
+  
+     double angle_diff = std::abs (getAngle3D (axis_, coeff));
+     angle_diff = (std::min) (angle_diff, M_PI - angle_diff);
+     // Check whether the current cylinder model satisfies our angle threshold criterion with respect to the given axis
+     if (angle_diff > eps_angle_)
+     {
+       PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::isModelValid] Angle between cylinder direction and given axis is too large.\n");
+       return (false);
+     }
+   }
+  
+   if (radius_min_ != -std::numeric_limits<double>::max() && model_coefficients[6] < radius_min_)
+   {
+     PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::isModelValid] Radius is too small: should be larger than %g, but is %g.\n",
+                radius_min_, model_coefficients[6]);
+     return (false);
+   }
+   if (radius_max_ != std::numeric_limits<double>::max() && model_coefficients[6] > radius_max_)
+   {
+     PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::isModelValid] Radius is too big: should be smaller than %g, but is %g.\n",
+                radius_max_, model_coefficients[6]);
+     return (false);
+   }
+  
+   return (true);
+ }
+  
+ #define PCL_INSTANTIATE_SampleConsensusModelRectangle(PointT) template class PCL_EXPORTS pcl::SampleConsensusModelRectangle<PointT>;
+  
+ #endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_RECTANGLE_H_
diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index e3772dac..8594a9da 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -14,6 +14,8 @@
 #include <pcl/registration/icp_nl.h>
 #include <pcl/registration/transforms.h>
 
+#include <pcl/sample_consensus/ransac.h>
+
 #include <pcl/segmentation/extract_clusters.h>
 
 #include <pcl/surface/convex_hull.h>
@@ -30,6 +32,8 @@
 
 #include <fstream>
 
+#include "ed_sensor_integration/sac_model_rectangle.h"
+
 void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, Eigen::Matrix4f &final_transform)
 {
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr src (new pcl::PointCloud<pcl::PointXYZRGB>);
@@ -204,7 +208,7 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, flo
     return Transform;
 }
 
-pcl::PointCloud<pcl::PointXYZ> Fit(pcl::PointCloud<pcl::PointXYZRGB> cloud) {
+pcl::PointCloud<pcl::PointXYZ> Flatten(pcl::PointCloud<pcl::PointXYZRGB> cloud) {
     float totx = 0, toty = 0, avgx, avgy;
 
     pcl::PointCloud<pcl::PointXYZ>::Ptr flat(new pcl::PointCloud<pcl::PointXYZ>);
@@ -235,6 +239,31 @@ pcl::PointCloud<pcl::PointXYZ> Fit(pcl::PointCloud<pcl::PointXYZRGB> cloud) {
     return *flat;
 }
 
+Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
+	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_ptr (new pcl::PointCloud<pcl::PointXYZ>);
+	*cloud_ptr = cloud;
+	float threshold = 0.02;
+	// Create SAC model
+	pcl::SampleConsensusModelRectangle<pcl::PointXYZ>::Ptr model (new pcl::SampleConsensusModelRectangle<pcl::PointXYZ>(cloud_ptr));
+
+	// Create SAC method
+	pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr sac (new pcl::RandomSampleConsensus<pcl::PointXYZ> (model, threshold));
+	sac->setMaxIterations(1000000);
+	//sac->setProbability (success_probability_);
+
+	// Fit model
+	sac->computeModel();
+
+	// Get inliers
+	std::vector<int> inliers;
+	sac->getInliers(inliers);
+
+	// Get the model coefficients
+	Eigen::VectorXf coeff;
+	sac->getModelCoefficients (coeff);
+	return (coeff);
+}
+
 int main(int argc, char **argv) {
 
     // open pcd files
@@ -328,13 +357,19 @@ int main(int argc, char **argv) {
     }
 
     pcl::PointCloud<pcl::PointXYZ> flat;
-    flat = Fit(*result);
+    flat = Flatten(*result);
     std::cout << flat.width << std::endl;
+    
+    Eigen::VectorXf model = Fit(flat);
+    
+    std::cout << "model coefficients: " << std::endl << model << std::endl;
 
     std::cout << "Writing clouds" << std::endl;
     pcl::io::savePCDFileASCII ("combined.pcd", *result);
     pcl::io::savePCDFileASCII ("flat.pcd", flat);
     std::cout << "The table is " << tableHeight << "m tall" << std::endl;
+    
+    
 
     return 0;
 }

From 4d05c2e32ba2e1ff4a7f2ae547ae2925424dfd48 Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Mon, 20 Dec 2021 15:12:24 +0100
Subject: [PATCH 017/136] rectangle fix

---
 .../include/ed_sensor_integration/sac_model_rectangle.hpp | 8 +++++---
 ed_sensor_integration/tools/table_modeler.cpp             | 6 +++---
 2 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp
index 91a6acff..e8096da6 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp
@@ -96,10 +96,9 @@
    
    float w = (c1(0)*c2(1)-c2(0)*c1(1))/l; //output: width defined as distance between c1 and point 3, signed
    
-   Eigen::Matrix2f transform = Eigen::Matrix2f::Identity().transpose();
+   Eigen::Matrix2f transform = Eigen::Matrix2f::Identity().colwise().reverse().eval();
    transform(1,0) = -1;
    transform = transform*w/l;
-   
    Eigen::Vector2f c3 = transform * c1; //vector perpendicular to c1 with length w, pointing from c1 to point 3
    
    // determine rotation:
@@ -139,6 +138,7 @@
    PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::computeModelCoefficients] Model is (%g,%g,%g,%g,%g).\n",
               model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
               model_coefficients[4]);
+   //std::cout << "P1: " << std::endl << p1 << std::endl << "P2: " << std::endl << p2 << std::endl << "P3: " << std::endl << p3 << std::endl << model_coefficients << std::endl;
    return (true);
  }
   
@@ -226,8 +226,9 @@
 			Eigen::Vector2f v = in - p4;
 			distances[i] = sqrt(v.dot(v)); //distance between corner 4 and the point
 		}
+		//std::cout << distances[i] << std::endl;
    }
-   
+   //std::cout << std::accumulate(distances.begin(), distances.end(), 0.0) / distances.size() << ", ";
   /*
    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
@@ -322,6 +323,7 @@
    {
 	   if (distances[i] <= threshold) {count++;}
    }
+   //std::cout << count << std::endl;
    return (count);
    /*// Check if the model is valid given the user constraints
    if (!isModelValid (model_coefficients))
diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 8594a9da..219a9eb9 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -242,14 +242,14 @@ pcl::PointCloud<pcl::PointXYZ> Flatten(pcl::PointCloud<pcl::PointXYZRGB> cloud)
 Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
 	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_ptr (new pcl::PointCloud<pcl::PointXYZ>);
 	*cloud_ptr = cloud;
-	float threshold = 0.02;
+	float threshold = 0.01;
 	// Create SAC model
 	pcl::SampleConsensusModelRectangle<pcl::PointXYZ>::Ptr model (new pcl::SampleConsensusModelRectangle<pcl::PointXYZ>(cloud_ptr));
 
 	// Create SAC method
 	pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr sac (new pcl::RandomSampleConsensus<pcl::PointXYZ> (model, threshold));
-	sac->setMaxIterations(1000000);
-	//sac->setProbability (success_probability_);
+	sac->setMaxIterations(10000000);
+	sac->setProbability(1);
 
 	// Fit model
 	sac->computeModel();

From 0879a041cc4e0a610a3aea275021555dd5742b31 Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Mon, 20 Dec 2021 21:28:43 +0100
Subject: [PATCH 018/136] implement double line sac model

---
 .../sac_model_double_line.h                   | 333 +++++++++++
 .../sac_model_double_line.hpp                 | 537 ++++++++++++++++++
 ed_sensor_integration/tools/table_modeler.cpp |  62 +-
 3 files changed, 923 insertions(+), 9 deletions(-)
 create mode 100644 ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
 create mode 100644 ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
new file mode 100644
index 00000000..42d46dcc
--- /dev/null
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
@@ -0,0 +1,333 @@
+ /*
+  * Software License Agreement (BSD License)
+  *
+  *  Point Cloud Library (PCL) - www.pointclouds.org
+  *  Copyright (c) 2010-2011, Willow Garage, Inc.
+  *  Copyright (c) 2012-, Open Perception, Inc.
+  *
+  *  All rights reserved.
+  *
+  *  Redistribution and use in source and binary forms, with or without
+  *  modification, are permitted provided that the following conditions
+  *  are met:
+  *
+  *   * Redistributions of source code must retain the above copyright
+  *     notice, this list of conditions and the following disclaimer.
+  *   * Redistributions in binary form must reproduce the above
+  *     copyright notice, this list of conditions and the following
+  *     disclaimer in the documentation and/or other materials provided
+  *     with the distribution.
+  *   * Neither the name of the copyright holder(s) nor the names of its
+  *     contributors may be used to endorse or promote products derived
+  *     from this software without specific prior written permission.
+  *
+  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+  *  POSSIBILITY OF SUCH DAMAGE.
+  *
+  * $Id$
+  *
+  */
+  
+ #pragma once
+  
+ #include <pcl/sample_consensus/sac_model.h>
+ #include <pcl/sample_consensus/model_types.h>
+ #include <pcl/common/distances.h>
+  
+ namespace pcl
+ {
+   /** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
+     * The model coefficients are defined as:
+     *   - \b point_on_axis.x  : the X coordinate of a point located on the cylinder axis
+     *   - \b point_on_axis.y  : the Y coordinate of a point located on the cylinder axis
+     *   - \b point_on_axis.z  : the Z coordinate of a point located on the cylinder axis
+     *   - \b axis_direction.x : the X coordinate of the cylinder's axis direction
+     *   - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
+     *   - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
+     *   - \b radius           : the cylinder's radius
+     * 
+     * \author Radu Bogdan Rusu
+     * \ingroup sample_consensus
+     */
+   template <typename PointT>
+   class SampleConsensusModelDoubleLine : public SampleConsensusModel<PointT>
+   {
+     public:
+       using SampleConsensusModel<PointT>::model_name_;
+       using SampleConsensusModel<PointT>::input_;
+       using SampleConsensusModel<PointT>::indices_;
+       using SampleConsensusModel<PointT>::radius_min_;
+       using SampleConsensusModel<PointT>::radius_max_;
+       using SampleConsensusModel<PointT>::error_sqr_dists_;
+  
+       using PointCloud = typename SampleConsensusModel<PointT>::PointCloud;
+       using PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr;
+       using PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr;
+  
+       using Ptr = shared_ptr<SampleConsensusModelDoubleLine<PointT> >;
+       using ConstPtr = shared_ptr<const SampleConsensusModelDoubleLine<PointT>>;
+  
+       /** \brief Constructor for base SampleConsensusModelCylinder.
+         * \param[in] cloud the input point cloud dataset
+         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+         */
+       SampleConsensusModelDoubleLine (const PointCloudConstPtr &cloud, bool random = false) 
+         : SampleConsensusModel<PointT> (cloud, random)
+         , axis_ (Eigen::Vector3f::Zero ())
+         , eps_angle_ (INFINITY)
+       {
+         model_name_ = "SampleConsensusModelDoubleLine";
+         sample_size_ = 3;
+         model_size_ = 4;
+       }
+  
+       /** \brief Constructor for base SampleConsensusModelCylinder.
+         * \param[in] cloud the input point cloud dataset
+         * \param[in] indices a vector of point indices to be used from \a cloud
+         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+         */
+       SampleConsensusModelDoubleLine (const PointCloudConstPtr &cloud, 
+                                     const Indices &indices,
+                                     bool random = false) 
+         : SampleConsensusModel<PointT> (cloud, indices, random)
+         , axis_ (Eigen::Vector3f::Zero ())
+         , eps_angle_ (0)
+       {
+         model_name_ = "SampleConsensusModelDoubleLine";
+         sample_size_ = 3;
+         model_size_ = 4;
+       }
+  
+       /** \brief Copy constructor.
+         * \param[in] source the model to copy into this
+         */
+       SampleConsensusModelDoubleLine (const SampleConsensusModelDoubleLine &source) :
+         SampleConsensusModel<PointT> (),
+         axis_ (Eigen::Vector3f::Zero ()),
+         eps_angle_ (0)
+       {
+         *this = source;
+         model_name_ = "SampleConsensusModelDoubleLine";
+       }
+       
+       /** \brief Empty destructor */
+       ~SampleConsensusModelDoubleLine () {}
+  
+       /** \brief Copy constructor.
+         * \param[in] source the model to copy into this
+         */
+       inline SampleConsensusModelDoubleLine&
+       operator = (const SampleConsensusModelDoubleLine &source)
+       {
+         SampleConsensusModel<PointT>::operator=(source);
+         axis_ = source.axis_;
+         eps_angle_ = source.eps_angle_;
+         return (*this);
+       }
+  
+       /** \brief Set the angle epsilon (delta) threshold.
+         * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
+         */
+       inline void 
+       setEpsAngle (const double ea) { eps_angle_ = ea; }
+  
+       /** \brief Get the angle epsilon (delta) threshold. */
+       inline double 
+       getEpsAngle () const { return (eps_angle_); }
+  
+       /** \brief Set the axis along which we need to search for a cylinder direction.
+         * \param[in] ax the axis along which we need to search for a cylinder direction
+         */
+       inline void 
+       setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
+  
+       /** \brief Get the axis along which we need to search for a cylinder direction. */
+       inline Eigen::Vector3f 
+       getAxis () const { return (axis_); }
+  
+       /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
+         * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
+         * axis_direction, cylinder_radius_R
+         * \param[in] samples the point indices found as possible good candidates for creating a valid model
+         * \param[out] model_coefficients the resultant model coefficients
+         */
+       bool
+       computeModelCoefficients (const Indices &samples,
+                                 Eigen::VectorXf &model_coefficients) const override;
+  
+       /** \brief Compute all distances from the cloud data to a given cylinder model.
+         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
+         * \param[out] distances the resultant estimated distances
+         */
+       void
+       getDistancesToModel (const Eigen::VectorXf &model_coefficients,
+                            std::vector<double> &distances) const override;
+  
+       /** \brief Select all the points which respect the given model coefficients as inliers.
+         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
+         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+         * \param[out] inliers the resultant model inliers
+         */
+       void 
+       selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
+                             const double threshold, 
+                             Indices &inliers) override;
+  
+       /** \brief Count all the points which respect the given model coefficients as inliers. 
+         * 
+         * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
+         * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
+         * \return the resultant number of inliers
+         */
+       std::size_t
+       countWithinDistance (const Eigen::VectorXf &model_coefficients,
+                            const double threshold) const override;
+  
+       /** \brief Recompute the cylinder coefficients using the given inlier set and return them to the user.
+         * @note: these are the coefficients of the cylinder model after refinement (e.g. after SVD)
+         * \param[in] inliers the data inliers found as supporting the model
+         * \param[in] model_coefficients the initial guess for the optimization
+         * \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization
+         */
+       void
+       optimizeModelCoefficients (const Indices &inliers,
+                                  const Eigen::VectorXf &model_coefficients,
+                                  Eigen::VectorXf &optimized_coefficients) const override;
+  
+  
+       /** \brief Create a new point cloud with inliers projected onto the cylinder model.
+         * \param[in] inliers the data inliers that we want to project on the cylinder model
+         * \param[in] model_coefficients the coefficients of a cylinder model
+         * \param[out] projected_points the resultant projected points
+         * \param[in] copy_data_fields set to true if we need to copy the other data fields
+         */
+       void
+       projectPoints (const Indices &inliers,
+                      const Eigen::VectorXf &model_coefficients,
+                      PointCloud &projected_points,
+                      bool copy_data_fields = true) const override;
+  
+       /** \brief Verify whether a subset of indices verifies the given cylinder model coefficients.
+         * \param[in] indices the data indices that need to be tested against the cylinder model
+         * \param[in] model_coefficients the cylinder model coefficients
+         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+         */
+       bool
+       doSamplesVerifyModel (const std::set<int> &indices,
+                             const Eigen::VectorXf &model_coefficients,
+                             const double threshold) const override;
+  
+       /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
+       inline pcl::SacModel 
+       getModelType () const override { return (SACMODEL_CYLINDER); } //cannot add a unique identifier for double line
+  
+     protected:
+       using SampleConsensusModel<PointT>::sample_size_;
+       using SampleConsensusModel<PointT>::model_size_;
+  
+       /** \brief Get the distance from a point to a line (represented by a point and a direction)
+         * \param[in] pt a point
+         * \param[in] model_coefficients the line coefficients (a point on the line, line direction)
+         */
+       double
+       pointToLineDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const;
+  
+       /** \brief Project a point onto a line given by a point and a direction vector
+         * \param[in] pt the input point to project
+         * \param[in] line_pt the point on the line (make sure that line_pt[3] = 0 as there are no internal checks!)
+         * \param[in] line_dir the direction of the line (make sure that line_dir[3] = 0 as there are no internal checks!)
+         * \param[out] pt_proj the resultant projected point
+         */
+       inline void
+       projectPointToLine (const Eigen::Vector4f &pt,
+                           const Eigen::Vector4f &line_pt,
+                           const Eigen::Vector4f &line_dir,
+                           Eigen::Vector4f &pt_proj) const
+       {
+         float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
+         // Calculate the projection of the point on the line
+         pt_proj = line_pt + k * line_dir;
+       }
+  
+       /** \brief Project a point onto a cylinder given by its model coefficients (point_on_axis, axis_direction,
+         * cylinder_radius_R)
+         * \param[in] pt the input point to project
+         * \param[in] model_coefficients the coefficients of the cylinder (point_on_axis, axis_direction, cylinder_radius_R)
+         * \param[out] pt_proj the resultant projected point
+         */
+       void
+       projectPointToRectangle (const Eigen::Vector4f &pt,
+                               const Eigen::VectorXf &model_coefficients,
+                               Eigen::Vector4f &pt_proj) const;
+  
+       /** \brief Check whether a model is valid given the user constraints.
+         * \param[in] model_coefficients the set of model coefficients
+         */
+       bool
+       isModelValid (const Eigen::VectorXf &model_coefficients) const override;
+  
+       /** \brief Check if a sample of indices results in a good sample of points
+         * indices. Pure virtual.
+         * \param[in] samples the resultant index samples
+         */
+       bool
+       isSampleGood (const Indices &samples) const override;
+  
+     private:
+       /** \brief The axis along which we need to search for a cylinder direction. */
+       Eigen::Vector3f axis_;
+     
+       /** \brief The maximum allowed difference between the cylinder direction and the given axis. */
+       double eps_angle_;
+  
+       /** \brief Functor for the optimization function */
+       struct OptimizationFunctor : pcl::Functor<float>
+       {
+         /** Functor constructor
+           * \param[in] indices the indices of data points to evaluate
+           * \param[in] estimator pointer to the estimator object
+           */
+         OptimizationFunctor (const pcl::SampleConsensusModelDoubleLine<PointT> *model, const Indices& indices) :
+           pcl::Functor<float> (indices.size ()), model_ (model), indices_ (indices) {}
+  
+         /** Cost function to be minimized
+           * \param[in] x variables array
+           * \param[out] fvec resultant functions evaluations
+           * \return 0
+           */
+         int 
+         operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
+         {
+           Eigen::Vector4f line_pt  (x[0], x[1], x[2], 0);
+           Eigen::Vector4f line_dir (x[3], x[4], x[5], 0);
+           
+           for (int i = 0; i < values (); ++i)
+           {
+             // dist = f - r
+             Eigen::Vector4f pt = (*model_->input_)[indices_[i]].getVector4fMap();
+             pt[3] = 0;
+  
+             fvec[i] = static_cast<float> (pcl::sqrPointToLineDistance (pt, line_pt, line_dir) - x[6]*x[6]);
+           }
+           return (0);
+         }
+  
+         const pcl::SampleConsensusModelDoubleLine<PointT> *model_;
+         const Indices &indices_;
+       };
+   };
+ }
+  
+ //#ifdef PCL_NO_PRECOMPILE
+ #include "ed_sensor_integration/sac_model_double_line.hpp"
+ //#endif
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
new file mode 100644
index 00000000..f00ae3e9
--- /dev/null
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
@@ -0,0 +1,537 @@
+ /*
+  * Software License Agreement (BSD License)
+  *
+  *  Point Cloud Library (PCL) - www.pointclouds.org
+  *  Copyright (c) 2009-2010, Willow Garage, Inc.
+  *  Copyright (c) 2012-, Open Perception, Inc.
+  *
+  *  All rights reserved.
+  *
+  *  Redistribution and use in source and binary forms, with or without
+  *  modification, are permitted provided that the following conditions
+  *  are met:
+  *
+  *   * Redistributions of source code must retain the above copyright
+  *     notice, this list of conditions and the following disclaimer.
+  *   * Redistributions in binary form must reproduce the above
+  *     copyright notice, this list of conditions and the following
+  *     disclaimer in the documentation and/or other materials provided
+  *     with the distribution.
+  *   * Neither the name of the copyright holder(s) nor the names of its
+  *     contributors may be used to endorse or promote products derived
+  *     from this software without specific prior written permission.
+  *
+  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+  *  POSSIBILITY OF SUCH DAMAGE.
+  *
+  * $Id$
+  *
+  */
+  
+ #ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_DOUBLE_LINE_H_
+ #define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_DOUBLE_LINE_H_
+  
+ #include <unsupported/Eigen/NonLinearOptimization> // for LevenbergMarquardt
+ #include "ed_sensor_integration/sac_model_double_line.h"
+ #include <pcl/common/common.h> // for getAngle3D
+ #include <pcl/common/concatenate.h>
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool
+ pcl::SampleConsensusModelDoubleLine<PointT>::isSampleGood (const Indices &samples) const
+ {
+   if (samples.size () != sample_size_)
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
+     return (false);
+   }
+   return (true);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool
+ pcl::SampleConsensusModelDoubleLine<PointT>::computeModelCoefficients (
+       const Indices &samples, Eigen::VectorXf &model_coefficients) const
+ {
+   // Need 3 samples
+   if (samples.size () != sample_size_)
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::computeModelCoefficients] Invalid set of samples given (%lu)!\n", samples.size ());
+     return (false);
+   }
+  
+   if (std::abs ((*input_)[samples[0]].x - (*input_)[samples[1]].x) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].y - (*input_)[samples[1]].y) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].z - (*input_)[samples[1]].z) <= std::numeric_limits<float>::epsilon () ||
+       std::abs ((*input_)[samples[1]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[1]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[1]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon () ||
+       std::abs ((*input_)[samples[0]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon ()) 
+   {
+     return (false);
+   }
+   Eigen::Vector2f p1 ((*input_)[samples[0]].x, (*input_)[samples[0]].y);
+   Eigen::Vector2f p2 ((*input_)[samples[1]].x, (*input_)[samples[1]].y);
+   Eigen::Vector2f p3 ((*input_)[samples[2]].x, (*input_)[samples[2]].y);
+   
+   float x, y, l, w, r;
+   
+   x = p1(0), y = p1(1); //output: x and y values
+   
+   Eigen::Vector2f c1, c2;
+   
+   if (/*eps_angle_ == INFINITY*/true) //if angle is given, only 2 points are required
+   {
+	   c1 = p2 - p1; //vector between point 1 and 2
+	   l = sqrt(c1.dot(c1)); //define length as distance between point 1 and 2
+	   // determine rotation:
+	   r = std::atan2(c1(1), c1(0)); //output: rotation of the double_line
+   }
+   else
+   {
+	   r = eps_angle_; //output: rotation of the double_line
+	   c1(0)=std::cos(r);
+	   c1(1)=std::sin(r);
+	   l = 1;
+   }
+   c2 = p1 - p3; //vector between point 3 and 1
+   w = (c1(0)*c2(1)-c2(0)*c1(1))/l; //output: width defined as distance between c1 and point 3, signed
+	   
+   //save model coefficients
+   model_coefficients.resize (model_size_);
+   model_coefficients[0] = x;
+   model_coefficients[1] = y;
+   model_coefficients[2] = w;
+   model_coefficients[3] = r;
+   
+   std::cout << w << std::endl;
+   
+   PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::computeModelCoefficients] Model is (%g,%g,%g,%g,%g).\n",
+              model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3]);
+   //std::cout << "P1: " << std::endl << p1 << std::endl << "P2: " << std::endl << p2 << std::endl << "P3: " << std::endl << p3 << std::endl << model_coefficients << std::endl;
+   return (true);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelDoubleLine<PointT>::getDistancesToModel (
+       const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
+ {
+   // Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+   {
+     distances.clear ();
+     return;
+   }
+  
+   distances.resize (indices_->size ());
+   
+   float x = model_coefficients[0], y = model_coefficients[1], w = model_coefficients[2], r = model_coefficients[3];
+   float d1, d2;
+
+   Eigen::Vector2f p1, p2, p3, p4, c1, c2;
+   
+   //define edge vectors
+   c1(0)=std::cos(r);
+   c1(1)=std::sin(r);
+
+   c2(0)= std::sin(r)*w;
+   c2(1)=-std::cos(r)*w;
+   
+   std::cout << "c2 = " << std::endl << c2 << std::endl;
+
+   //define corner vectors
+   p1(0)=x;
+   p1(1)=y;
+   p2 = p1 + c1;
+   p3 = p2 + c2;
+   p4 = p1 + c2;
+   
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+	   Eigen::Vector2f in ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y);
+	   
+	   //compute distances to lines
+		d1 = std::abs(c1(0)*(p1(1)-in(1))-(p1(0)-in(0))*c1(1)); //Distance between line 1 and the point
+		d2 = std::abs(c1(0)*(p3(1)-in(1))-(p3(0)-in(0))*c1(1)); //Distance between line 2 and the point
+
+		distances[i] = std::min(d1, d2); //smallest of d1 and d2
+		
+		//std::cout << distances[i] << std::endl;
+   }
+   //std::cout << std::accumulate(distances.begin(), distances.end(), 0.0) / distances.size() << ", ";
+  /*
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+   // Iterate through the 3d points and calculate the distances from them to the sphere
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     // @note need to revise this.
+     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
+  
+     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
+  
+     // Calculate the point's projection on the cylinder axis
+     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
+     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
+     Eigen::Vector4f dir = pt - pt_proj;
+     dir.normalize ();
+  
+     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
+     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
+     double d_normal = std::abs (getAngle3D (n, dir));
+     d_normal = (std::min) (d_normal, M_PI - d_normal);
+  
+     distances[i] = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);*/
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelDoubleLine<PointT>::selectWithinDistance (
+       const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
+ {
+   std::vector<double> distances;
+   getDistancesToModel (model_coefficients, distances);
+   for (int i = 0; i < distances.size(); i++)
+   {
+	   if (distances[i] < threshold) {inliers.push_back ((*indices_)[i]);}
+   }
+   
+   std::cout << model_coefficients[2] << std::endl;
+   /*
+   // Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+   {
+     inliers.clear ();
+     return;
+   }
+  
+   inliers.clear ();
+   error_sqr_dists_.clear ();
+   inliers.reserve (indices_->size ());
+   error_sqr_dists_.reserve (indices_->size ());
+  
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+   // Iterate through the 3d points and calculate the distances from them to the sphere
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
+     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
+     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
+       continue;
+  
+     // Calculate the point's projection on the cylinder axis
+     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
+     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
+     Eigen::Vector4f dir = pt - pt_proj;
+     dir.normalize ();
+  
+     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
+     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
+     double d_normal = std::abs (getAngle3D (n, dir));
+     d_normal = (std::min) (d_normal, M_PI - d_normal);
+  
+     double distance = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);
+     if (distance < threshold)
+     {
+       // Returns the indices of the points whose distances are smaller than the threshold
+       inliers.push_back ((*indices_)[i]);
+       error_sqr_dists_.push_back (distance);
+     }
+   }*/
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> std::size_t
+ pcl::SampleConsensusModelDoubleLine<PointT>::countWithinDistance (
+       const Eigen::VectorXf &model_coefficients, const double threshold) const
+ {
+   std::vector<double> distances;
+   getDistancesToModel (model_coefficients, distances);
+   int count = 0;
+   for (int i = 0; i < distances.size(); i++)
+   {
+	   if (distances[i] <= threshold) {count++;}
+   }
+   //std::cout << count << std::endl;
+   return (count);
+   /*// Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+     return (0);
+  
+   std::size_t nr_p = 0;
+  
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+   // Iterate through the 3d points and calculate the distances from them to the sphere
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
+     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
+     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
+       continue;
+  
+     // Calculate the point's projection on the cylinder axis
+     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
+     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
+     Eigen::Vector4f dir = pt - pt_proj;
+     dir.normalize ();
+  
+     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
+     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
+     double d_normal = std::abs (getAngle3D (n, dir));
+     d_normal = (std::min) (d_normal, M_PI - d_normal);
+  
+     if (std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist) < threshold)
+       nr_p++;
+   }
+   return (nr_p);*/
+   return (0);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelDoubleLine<PointT>::optimizeModelCoefficients (
+       const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
+ {
+   optimized_coefficients = model_coefficients;
+  
+   // Needs a set of valid model coefficients
+   if (!isModelValid (model_coefficients))
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::optimizeModelCoefficients] Given model is invalid!\n");
+     return;
+   }
+  
+   // Need more than the minimum sample size to make a difference
+   if (inliers.size () <= sample_size_)
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine:optimizeModelCoefficients] Not enough inliers found to optimize model coefficients (%lu)! Returning the same coefficients.\n", inliers.size ());
+     return;
+   }
+  
+   OptimizationFunctor functor (this, inliers);
+   Eigen::NumericalDiff<OptimizationFunctor > num_diff (functor);
+   Eigen::LevenbergMarquardt<Eigen::NumericalDiff<OptimizationFunctor>, float> lm (num_diff);
+   int info = lm.minimize (optimized_coefficients);
+   
+   // Compute the L2 norm of the residuals
+   PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::optimizeModelCoefficients] LM solver finished with exit code %i, having a residual norm of %g. \nInitial solution: %g %g %g %g %g %g %g \nFinal solution: %g %g %g %g %g %g %g\n",
+              info, lm.fvec.norm (), model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
+              model_coefficients[4], model_coefficients[5], model_coefficients[6], optimized_coefficients[0], optimized_coefficients[1], optimized_coefficients[2], optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5], optimized_coefficients[6]);
+     
+   Eigen::Vector3f line_dir (optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5]);
+   line_dir.normalize ();
+   optimized_coefficients[3] = line_dir[0];
+   optimized_coefficients[4] = line_dir[1];
+   optimized_coefficients[5] = line_dir[2];
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelDoubleLine<PointT>::projectPoints (
+       const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
+ {
+   // Needs a valid set of model coefficients
+   if (!isModelValid (model_coefficients))
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::projectPoints] Given model is invalid!\n");
+     return;
+   }
+  
+   projected_points.header = input_->header;
+   projected_points.is_dense = input_->is_dense;
+  
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+  
+   // Copy all the data fields from the input cloud to the projected one?
+   if (copy_data_fields)
+   {
+     // Allocate enough space and copy the basics
+     projected_points.resize (input_->size ());
+     projected_points.width    = input_->width;
+     projected_points.height   = input_->height;
+  
+     using FieldList = typename pcl::traits::fieldList<PointT>::type;
+     // Iterate over each point
+     for (std::size_t i = 0; i < projected_points.size (); ++i)
+       // Iterate over each dimension
+       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
+  
+     // Iterate through the 3d points and calculate the distances from them to the cylinder
+     for (const auto &inlier : inliers)
+     {
+       Eigen::Vector4f p ((*input_)[inlier].x,
+                          (*input_)[inlier].y,
+                          (*input_)[inlier].z,
+                          1);
+  
+       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
+  
+       pcl::Vector4fMap pp = projected_points[inlier].getVector4fMap ();
+       pp.matrix () = line_pt + k * line_dir;
+  
+       Eigen::Vector4f dir = p - pp;
+       dir[3] = 0.0f;
+       dir.normalize ();
+  
+       // Calculate the projection of the point onto the cylinder
+       pp += dir * model_coefficients[6];
+     }
+   }
+   else
+   {
+     // Allocate enough space and copy the basics
+     projected_points.resize (inliers.size ());
+     projected_points.width    = inliers.size ();
+     projected_points.height   = 1;
+  
+     using FieldList = typename pcl::traits::fieldList<PointT>::type;
+     // Iterate over each point
+     for (std::size_t i = 0; i < inliers.size (); ++i)
+       // Iterate over each dimension
+       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
+  
+     // Iterate through the 3d points and calculate the distances from them to the cylinder
+     for (std::size_t i = 0; i < inliers.size (); ++i)
+     {
+       pcl::Vector4fMap pp = projected_points[i].getVector4fMap ();
+       pcl::Vector4fMapConst p = (*input_)[inliers[i]].getVector4fMap ();
+  
+       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
+       // Calculate the projection of the point on the line
+       pp.matrix () = line_pt + k * line_dir;
+  
+       Eigen::Vector4f dir = p - pp;
+       dir[3] = 0.0f;
+       dir.normalize ();
+  
+       // Calculate the projection of the point onto the cylinder
+       pp += dir * model_coefficients[6];
+     }
+   }
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool
+ pcl::SampleConsensusModelDoubleLine<PointT>::doSamplesVerifyModel (
+       const std::set<int> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
+ {
+   // Needs a valid model coefficients
+   if (!isModelValid (model_coefficients))
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::doSamplesVerifyModel] Given model is invalid!\n");
+     return (false);
+   }
+  
+   for (const auto &index : indices)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     // @note need to revise this.
+     Eigen::Vector4f pt ((*input_)[index].x, (*input_)[index].y, (*input_)[index].z, 0.0f);
+     if (std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]) > threshold)
+       return (false);
+   }
+  
+   return (true);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> double
+ pcl::SampleConsensusModelDoubleLine<PointT>::pointToLineDistance (
+       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const
+ {
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   return sqrt(pcl::sqrPointToLineDistance (pt, line_pt, line_dir));
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelDoubleLine<PointT>::projectPointToRectangle (
+       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients, Eigen::Vector4f &pt_proj) const
+ {
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+  
+   float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) * line_dir.dot (line_dir);
+   pt_proj = line_pt + k * line_dir;
+  
+   Eigen::Vector4f dir = pt - pt_proj;
+   dir.normalize ();
+  
+   // Calculate the projection of the point onto the cylinder
+   pt_proj += dir * model_coefficients[6];
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool 
+ pcl::SampleConsensusModelDoubleLine<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
+ {
+   if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
+     return (false);
+  /*
+   // Check against template, if given
+   if (eps_angle_ > 0.0)
+   {
+     // Obtain the cylinder direction
+     const Eigen::Vector3f coeff(model_coefficients[3], model_coefficients[4], model_coefficients[5]);
+  
+     double angle_diff = std::abs (getAngle3D (axis_, coeff));
+     angle_diff = (std::min) (angle_diff, M_PI - angle_diff);
+     // Check whether the current cylinder model satisfies our angle threshold criterion with respect to the given axis
+     if (angle_diff > eps_angle_)
+     {
+       PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::isModelValid] Angle between cylinder direction and given axis is too large.\n");
+       return (false);
+     }
+   }
+  
+   if (radius_min_ != -std::numeric_limits<double>::max() && model_coefficients[6] < radius_min_)
+   {
+     PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::isModelValid] Radius is too small: should be larger than %g, but is %g.\n",
+                radius_min_, model_coefficients[6]);
+     return (false);
+   }
+   if (radius_max_ != std::numeric_limits<double>::max() && model_coefficients[6] > radius_max_)
+   {
+     PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::isModelValid] Radius is too big: should be smaller than %g, but is %g.\n",
+                radius_max_, model_coefficients[6]);
+     return (false);
+   }*/
+  
+   return (true);
+ }
+  
+ #define PCL_INSTANTIATE_SampleConsensusModelDoubleLine(PointT) template class PCL_EXPORTS pcl::SampleConsensusModelDoubleLine<PointT>;
+  
+ #endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_DOUBLE_LINE_H_
diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 219a9eb9..1d1a6f2b 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -33,6 +33,7 @@
 #include <fstream>
 
 #include "ed_sensor_integration/sac_model_rectangle.h"
+#include "ed_sensor_integration/sac_model_double_line.h"
 
 void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, Eigen::Matrix4f &final_transform)
 {
@@ -242,26 +243,69 @@ pcl::PointCloud<pcl::PointXYZ> Flatten(pcl::PointCloud<pcl::PointXYZRGB> cloud)
 Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
 	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_ptr (new pcl::PointCloud<pcl::PointXYZ>);
 	*cloud_ptr = cloud;
-	float threshold = 0.01;
+	float threshold = 0.03;
 	// Create SAC model
-	pcl::SampleConsensusModelRectangle<pcl::PointXYZ>::Ptr model (new pcl::SampleConsensusModelRectangle<pcl::PointXYZ>(cloud_ptr));
+	pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>::Ptr line1 (new pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>(cloud_ptr));
 
 	// Create SAC method
-	pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr sac (new pcl::RandomSampleConsensus<pcl::PointXYZ> (model, threshold));
-	sac->setMaxIterations(10000000);
-	sac->setProbability(1);
+	pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr sac1 (new pcl::RandomSampleConsensus<pcl::PointXYZ> (line1, threshold));
+	sac1->setMaxIterations(10000);
+	sac1->setProbability(1);
 
 	// Fit model
-	sac->computeModel();
+	sac1->computeModel();
 
 	// Get inliers
 	std::vector<int> inliers;
-	sac->getInliers(inliers);
+	sac1->getInliers(inliers);
 
 	// Get the model coefficients
 	Eigen::VectorXf coeff;
-	sac->getModelCoefficients (coeff);
-	return (coeff);
+	sac1->getModelCoefficients (coeff);
+	
+	float w = coeff[2];
+	float r = coeff[3];
+	
+	//extract the inliers and fit second set of lines perpendicular
+	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud2 (new pcl::PointCloud<pcl::PointXYZ>);
+	pcl::PointIndices::Ptr line1_inliers (new pcl::PointIndices);
+	line1_inliers->indices = inliers;
+	pcl::ExtractIndices<pcl::PointXYZ> extract;
+	extract.setInputCloud (cloud_ptr);
+	extract.setIndices (line1_inliers);
+	extract.setNegative (true);
+	extract.filter (*cloud2);
+	// Create second SAC model
+	pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>::Ptr line2 (new pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>(cloud2));
+	// Create SAC method
+	pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr sac2 (new pcl::RandomSampleConsensus<pcl::PointXYZ> (line2, threshold));
+	sac2->setMaxIterations(10000);
+	sac2->setProbability(1);
+	// Fit model
+	sac2->computeModel();
+	// Get inliers
+	sac2->getInliers(inliers);
+	// Get the model coefficients
+	Eigen::VectorXf coeff2;
+	sac2->getModelCoefficients (coeff2);
+	
+	float l = coeff2[2];
+	r = r - coeff2[3]; //difference in angle: if not 90 degrees, model is a parallellogram	
+	pcl::io::savePCDFileASCII ("lines.pcd", *cloud2);
+	Eigen::VectorXf output;
+	output.resize(3);
+	output[0] = l;
+	output[1] = w;
+	output[2] = r;
+	
+	pcl::PointIndices::Ptr line2_inliers (new pcl::PointIndices);
+	line2_inliers->indices = inliers;
+	extract.setInputCloud (cloud2);
+	extract.setIndices (line2_inliers);
+	extract.filter (*cloud2);
+	pcl::io::savePCDFileASCII ("outliers.pcd", *cloud2);
+	
+	return (output);
 }
 
 int main(int argc, char **argv) {

From f63aca0bf7551bd42798a0f806caf4ee49a87b58 Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Mon, 20 Dec 2021 21:45:19 +0100
Subject: [PATCH 019/136] fix distance function in rectangle

---
 .../include/ed_sensor_integration/sac_model_rectangle.hpp | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp
index e8096da6..00c740a3 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp
@@ -180,10 +180,10 @@
 	   Eigen::Vector2f in ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y);
 	   
 	   //compute distances to lines
-		d1 = ( c1(0)*(p1(1)-in(1))-( p1(0)-in(0))*c1(1))/l; //Distance between line 1 and the point
-		d2 = ( c2(0)*(p2(1)-in(1))-( p2(0)-in(0))*c1(1))/w; //Distance between line 2 and the point
-		d3 = (-c1(0)*(p3(1)-in(1))-(-p3(0)-in(0))*c1(1))/l; //Distance between line 3 and the point
-		d4 = (-c1(0)*(p4(1)-in(1))-(-p4(0)-in(0))*c1(1))/w; //Distance between line 4 and the point
+		d1 = ( c1(0)*(p1(1)-in(1))-(p1(0)-in(0))* c1(1))/l; //Distance between line 1 and the point
+		d2 = ( c2(0)*(p2(1)-in(1))-(p2(0)-in(0))* c1(1))/w; //Distance between line 2 and the point
+		d3 = (-c1(0)*(p3(1)-in(1))-(p3(0)-in(0))*-c1(1))/l; //Distance between line 3 and the point
+		d4 = (-c1(0)*(p4(1)-in(1))-(p4(0)-in(0))*-c1(1))/w; //Distance between line 4 and the point
 		//note: these distances are signed, such that points lying inside the rectangle have positive distance to all lines
 
 		if (d1>0 && d2>0 && d3>0 && d4>0) //inside the rectangle

From 39794093b9995d612a10f3e47430d3fdaf52d8bc Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Thu, 23 Dec 2021 12:57:28 +0100
Subject: [PATCH 020/136] Implement circle sac model

---
 .../ed_sensor_integration/sac_model_circle.h  | 333 ++++++++++++
 .../sac_model_circle.hpp                      | 503 ++++++++++++++++++
 .../sac_model_double_line.hpp                 |   6 +-
 ed_sensor_integration/tools/table_modeler.cpp |  65 ++-
 4 files changed, 887 insertions(+), 20 deletions(-)
 create mode 100644 ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
 create mode 100644 ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
new file mode 100644
index 00000000..e0531b3d
--- /dev/null
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
@@ -0,0 +1,333 @@
+ /*
+  * Software License Agreement (BSD License)
+  *
+  *  Point Cloud Library (PCL) - www.pointclouds.org
+  *  Copyright (c) 2010-2011, Willow Garage, Inc.
+  *  Copyright (c) 2012-, Open Perception, Inc.
+  *
+  *  All rights reserved.
+  *
+  *  Redistribution and use in source and binary forms, with or without
+  *  modification, are permitted provided that the following conditions
+  *  are met:
+  *
+  *   * Redistributions of source code must retain the above copyright
+  *     notice, this list of conditions and the following disclaimer.
+  *   * Redistributions in binary form must reproduce the above
+  *     copyright notice, this list of conditions and the following
+  *     disclaimer in the documentation and/or other materials provided
+  *     with the distribution.
+  *   * Neither the name of the copyright holder(s) nor the names of its
+  *     contributors may be used to endorse or promote products derived
+  *     from this software without specific prior written permission.
+  *
+  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+  *  POSSIBILITY OF SUCH DAMAGE.
+  *
+  * $Id$
+  *
+  */
+  
+ #pragma once
+  
+ #include <pcl/sample_consensus/sac_model.h>
+ #include <pcl/sample_consensus/model_types.h>
+ #include <pcl/common/distances.h>
+  
+ namespace pcl
+ {
+   /** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
+     * The model coefficients are defined as:
+     *   - \b point_on_axis.x  : the X coordinate of a point located on the cylinder axis
+     *   - \b point_on_axis.y  : the Y coordinate of a point located on the cylinder axis
+     *   - \b point_on_axis.z  : the Z coordinate of a point located on the cylinder axis
+     *   - \b axis_direction.x : the X coordinate of the cylinder's axis direction
+     *   - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
+     *   - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
+     *   - \b radius           : the cylinder's radius
+     * 
+     * \author Radu Bogdan Rusu
+     * \ingroup sample_consensus
+     */
+   template <typename PointT>
+   class SampleConsensusModelCircle : public SampleConsensusModel<PointT>
+   {
+     public:
+       using SampleConsensusModel<PointT>::model_name_;
+       using SampleConsensusModel<PointT>::input_;
+       using SampleConsensusModel<PointT>::indices_;
+       using SampleConsensusModel<PointT>::radius_min_;
+       using SampleConsensusModel<PointT>::radius_max_;
+       using SampleConsensusModel<PointT>::error_sqr_dists_;
+  
+       using PointCloud = typename SampleConsensusModel<PointT>::PointCloud;
+       using PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr;
+       using PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr;
+  
+       using Ptr = shared_ptr<SampleConsensusModelCircle<PointT> >;
+       using ConstPtr = shared_ptr<const SampleConsensusModelCircle<PointT>>;
+  
+       /** \brief Constructor for base SampleConsensusModelCylinder.
+         * \param[in] cloud the input point cloud dataset
+         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+         */
+       SampleConsensusModelCircle (const PointCloudConstPtr &cloud, bool random = false) 
+         : SampleConsensusModel<PointT> (cloud, random)
+         , axis_ (Eigen::Vector3f::Zero ())
+         , eps_angle_ (INFINITY)
+       {
+         model_name_ = "SampleConsensusModelCircle";
+         sample_size_ = 3;
+         model_size_ = 3;
+       }
+  
+       /** \brief Constructor for base SampleConsensusModelCylinder.
+         * \param[in] cloud the input point cloud dataset
+         * \param[in] indices a vector of point indices to be used from \a cloud
+         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+         */
+       SampleConsensusModelCircle (const PointCloudConstPtr &cloud, 
+                                     const Indices &indices,
+                                     bool random = false) 
+         : SampleConsensusModel<PointT> (cloud, indices, random)
+         , axis_ (Eigen::Vector3f::Zero ())
+         , eps_angle_ (0)
+       {
+         model_name_ = "SampleConsensusModelCircle";
+         sample_size_ = 3;
+         model_size_ = 3;
+       }
+  
+       /** \brief Copy constructor.
+         * \param[in] source the model to copy into this
+         */
+       SampleConsensusModelCircle (const SampleConsensusModelCircle &source) :
+         SampleConsensusModel<PointT> (),
+         axis_ (Eigen::Vector3f::Zero ()),
+         eps_angle_ (0)
+       {
+         *this = source;
+         model_name_ = "SampleConsensusModelCircle";
+       }
+       
+       /** \brief Empty destructor */
+       ~SampleConsensusModelCircle () {}
+  
+       /** \brief Copy constructor.
+         * \param[in] source the model to copy into this
+         */
+       inline SampleConsensusModelCircle&
+       operator = (const SampleConsensusModelCircle &source)
+       {
+         SampleConsensusModel<PointT>::operator=(source);
+         axis_ = source.axis_;
+         eps_angle_ = source.eps_angle_;
+         return (*this);
+       }
+  
+       /** \brief Set the angle epsilon (delta) threshold.
+         * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
+         */
+       inline void 
+       setEpsAngle (const double ea) { eps_angle_ = ea; }
+  
+       /** \brief Get the angle epsilon (delta) threshold. */
+       inline double 
+       getEpsAngle () const { return (eps_angle_); }
+  
+       /** \brief Set the axis along which we need to search for a cylinder direction.
+         * \param[in] ax the axis along which we need to search for a cylinder direction
+         */
+       inline void 
+       setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
+  
+       /** \brief Get the axis along which we need to search for a cylinder direction. */
+       inline Eigen::Vector3f 
+       getAxis () const { return (axis_); }
+  
+       /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
+         * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
+         * axis_direction, cylinder_radius_R
+         * \param[in] samples the point indices found as possible good candidates for creating a valid model
+         * \param[out] model_coefficients the resultant model coefficients
+         */
+       bool
+       computeModelCoefficients (const Indices &samples,
+                                 Eigen::VectorXf &model_coefficients) const override;
+  
+       /** \brief Compute all distances from the cloud data to a given cylinder model.
+         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
+         * \param[out] distances the resultant estimated distances
+         */
+       void
+       getDistancesToModel (const Eigen::VectorXf &model_coefficients,
+                            std::vector<double> &distances) const override;
+  
+       /** \brief Select all the points which respect the given model coefficients as inliers.
+         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
+         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+         * \param[out] inliers the resultant model inliers
+         */
+       void 
+       selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
+                             const double threshold, 
+                             Indices &inliers) override;
+  
+       /** \brief Count all the points which respect the given model coefficients as inliers. 
+         * 
+         * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
+         * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
+         * \return the resultant number of inliers
+         */
+       std::size_t
+       countWithinDistance (const Eigen::VectorXf &model_coefficients,
+                            const double threshold) const override;
+  
+       /** \brief Recompute the cylinder coefficients using the given inlier set and return them to the user.
+         * @note: these are the coefficients of the cylinder model after refinement (e.g. after SVD)
+         * \param[in] inliers the data inliers found as supporting the model
+         * \param[in] model_coefficients the initial guess for the optimization
+         * \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization
+         */
+       void
+       optimizeModelCoefficients (const Indices &inliers,
+                                  const Eigen::VectorXf &model_coefficients,
+                                  Eigen::VectorXf &optimized_coefficients) const override;
+  
+  
+       /** \brief Create a new point cloud with inliers projected onto the cylinder model.
+         * \param[in] inliers the data inliers that we want to project on the cylinder model
+         * \param[in] model_coefficients the coefficients of a cylinder model
+         * \param[out] projected_points the resultant projected points
+         * \param[in] copy_data_fields set to true if we need to copy the other data fields
+         */
+       void
+       projectPoints (const Indices &inliers,
+                      const Eigen::VectorXf &model_coefficients,
+                      PointCloud &projected_points,
+                      bool copy_data_fields = true) const override;
+  
+       /** \brief Verify whether a subset of indices verifies the given cylinder model coefficients.
+         * \param[in] indices the data indices that need to be tested against the cylinder model
+         * \param[in] model_coefficients the cylinder model coefficients
+         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+         */
+       bool
+       doSamplesVerifyModel (const std::set<int> &indices,
+                             const Eigen::VectorXf &model_coefficients,
+                             const double threshold) const override;
+  
+       /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
+       inline pcl::SacModel 
+       getModelType () const override { return (SACMODEL_CYLINDER); } //cannot add a unique identifier for double line
+  
+     protected:
+       using SampleConsensusModel<PointT>::sample_size_;
+       using SampleConsensusModel<PointT>::model_size_;
+  
+       /** \brief Get the distance from a point to a line (represented by a point and a direction)
+         * \param[in] pt a point
+         * \param[in] model_coefficients the line coefficients (a point on the line, line direction)
+         */
+       double
+       pointToLineDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const;
+  
+       /** \brief Project a point onto a line given by a point and a direction vector
+         * \param[in] pt the input point to project
+         * \param[in] line_pt the point on the line (make sure that line_pt[3] = 0 as there are no internal checks!)
+         * \param[in] line_dir the direction of the line (make sure that line_dir[3] = 0 as there are no internal checks!)
+         * \param[out] pt_proj the resultant projected point
+         */
+       inline void
+       projectPointToLine (const Eigen::Vector4f &pt,
+                           const Eigen::Vector4f &line_pt,
+                           const Eigen::Vector4f &line_dir,
+                           Eigen::Vector4f &pt_proj) const
+       {
+         float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
+         // Calculate the projection of the point on the line
+         pt_proj = line_pt + k * line_dir;
+       }
+  
+       /** \brief Project a point onto a cylinder given by its model coefficients (point_on_axis, axis_direction,
+         * cylinder_radius_R)
+         * \param[in] pt the input point to project
+         * \param[in] model_coefficients the coefficients of the cylinder (point_on_axis, axis_direction, cylinder_radius_R)
+         * \param[out] pt_proj the resultant projected point
+         */
+       void
+       projectPointToRectangle (const Eigen::Vector4f &pt,
+                               const Eigen::VectorXf &model_coefficients,
+                               Eigen::Vector4f &pt_proj) const;
+  
+       /** \brief Check whether a model is valid given the user constraints.
+         * \param[in] model_coefficients the set of model coefficients
+         */
+       bool
+       isModelValid (const Eigen::VectorXf &model_coefficients) const override;
+  
+       /** \brief Check if a sample of indices results in a good sample of points
+         * indices. Pure virtual.
+         * \param[in] samples the resultant index samples
+         */
+       bool
+       isSampleGood (const Indices &samples) const override;
+  
+     private:
+       /** \brief The axis along which we need to search for a cylinder direction. */
+       Eigen::Vector3f axis_;
+     
+       /** \brief The maximum allowed difference between the cylinder direction and the given axis. */
+       double eps_angle_;
+  
+       /** \brief Functor for the optimization function */
+       struct OptimizationFunctor : pcl::Functor<float>
+       {
+         /** Functor constructor
+           * \param[in] indices the indices of data points to evaluate
+           * \param[in] estimator pointer to the estimator object
+           */
+         OptimizationFunctor (const pcl::SampleConsensusModelCircle<PointT> *model, const Indices& indices) :
+           pcl::Functor<float> (indices.size ()), model_ (model), indices_ (indices) {}
+  
+         /** Cost function to be minimized
+           * \param[in] x variables array
+           * \param[out] fvec resultant functions evaluations
+           * \return 0
+           */
+         int 
+         operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
+         {
+           Eigen::Vector4f line_pt  (x[0], x[1], x[2], 0);
+           Eigen::Vector4f line_dir (x[3], x[4], x[5], 0);
+           
+           for (int i = 0; i < values (); ++i)
+           {
+             // dist = f - r
+             Eigen::Vector4f pt = (*model_->input_)[indices_[i]].getVector4fMap();
+             pt[3] = 0;
+  
+             fvec[i] = static_cast<float> (pcl::sqrPointToLineDistance (pt, line_pt, line_dir) - x[6]*x[6]);
+           }
+           return (0);
+         }
+  
+         const pcl::SampleConsensusModelCircle<PointT> *model_;
+         const Indices &indices_;
+       };
+   };
+ }
+  
+ //#ifdef PCL_NO_PRECOMPILE
+ #include "ed_sensor_integration/sac_model_circle.hpp"
+ //#endif
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp
new file mode 100644
index 00000000..968cb988
--- /dev/null
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp
@@ -0,0 +1,503 @@
+ /*
+  * Software License Agreement (BSD License)
+  *
+  *  Point Cloud Library (PCL) - www.pointclouds.org
+  *  Copyright (c) 2009-2010, Willow Garage, Inc.
+  *  Copyright (c) 2012-, Open Perception, Inc.
+  *
+  *  All rights reserved.
+  *
+  *  Redistribution and use in source and binary forms, with or without
+  *  modification, are permitted provided that the following conditions
+  *  are met:
+  *
+  *   * Redistributions of source code must retain the above copyright
+  *     notice, this list of conditions and the following disclaimer.
+  *   * Redistributions in binary form must reproduce the above
+  *     copyright notice, this list of conditions and the following
+  *     disclaimer in the documentation and/or other materials provided
+  *     with the distribution.
+  *   * Neither the name of the copyright holder(s) nor the names of its
+  *     contributors may be used to endorse or promote products derived
+  *     from this software without specific prior written permission.
+  *
+  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+  *  POSSIBILITY OF SUCH DAMAGE.
+  *
+  * $Id$
+  *
+  */
+  
+ #ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_CIRCLE_H_
+ #define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_CIRCLE_H_
+  
+ #include <unsupported/Eigen/NonLinearOptimization> // for LevenbergMarquardt
+ #include "ed_sensor_integration/sac_model_circle.h"
+ #include <pcl/common/common.h> // for getAngle3D
+ #include <pcl/common/concatenate.h>
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool
+ pcl::SampleConsensusModelCircle<PointT>::isSampleGood (const Indices &samples) const
+ {
+   if (samples.size () != sample_size_)
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelCircle::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
+     return (false);
+   }
+   return (true);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool
+ pcl::SampleConsensusModelCircle<PointT>::computeModelCoefficients (
+       const Indices &samples, Eigen::VectorXf &model_coefficients) const
+ {
+   // Need 3 samples
+   if (samples.size () != sample_size_)
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelCircle::computeModelCoefficients] Invalid set of samples given (%lu)!\n", samples.size ());
+     return (false);
+   }
+  
+   if (std::abs ((*input_)[samples[0]].x - (*input_)[samples[1]].x) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].y - (*input_)[samples[1]].y) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].z - (*input_)[samples[1]].z) <= std::numeric_limits<float>::epsilon () ||
+       std::abs ((*input_)[samples[1]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[1]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[1]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon () ||
+       std::abs ((*input_)[samples[0]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
+       std::abs ((*input_)[samples[0]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon ()) 
+   {
+     return (false);
+   }
+   Eigen::Vector2f p1 ((*input_)[samples[0]].x, (*input_)[samples[0]].y);
+   Eigen::Vector2f p2 ((*input_)[samples[1]].x, (*input_)[samples[1]].y);
+   Eigen::Vector2f p3 ((*input_)[samples[2]].x, (*input_)[samples[2]].y);
+   
+   float x, y, l, r;
+   
+   float denominator = 2*(p1(0)*(p2(1)-p3(1)) - p1(1)*(p2(0)-p3(0)) + p2(0)*p3(1) - p3(0)*p2(1));
+   x = (p1.dot(p1)*(p2(1)-p3(1)) + p2.dot(p2)*(p3(1)-p1(1)) + p3.dot(p3)*(p1(1)-p2(1))) / denominator;
+   y = (p1.dot(p1)*(p2(0)-p3(0)) + p2.dot(p2)*(p3(0)-p1(0)) + p3.dot(p3)*(p1(0)-p2(0))) / denominator;
+   
+   Eigen::Vector2f d;
+   d(0) = x-p1(0);
+   d(1) = y-p1(1);
+   r = sqrt(d.dot(d));
+	   
+   //save model coefficients
+   model_coefficients.resize (model_size_);
+   model_coefficients[0] = x;
+   model_coefficients[1] = y;
+   model_coefficients[2] = r;
+   
+   PCL_DEBUG ("[pcl::SampleConsensusModelCircle::computeModelCoefficients] Model is (%g,%g,%g).\n",
+              model_coefficients[0], model_coefficients[1], model_coefficients[2]);
+   //std::cout << "P1: " << std::endl << p1 << std::endl << "P2: " << std::endl << p2 << std::endl << "P3: " << std::endl << p3 << std::endl << model_coefficients << std::endl;
+   return (true);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelCircle<PointT>::getDistancesToModel (
+       const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
+ {
+   // Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+   {
+     distances.clear ();
+     return;
+   }
+  
+   distances.resize (indices_->size ());
+   
+   float x = model_coefficients[0], y = model_coefficients[1], r = model_coefficients[2];
+
+   Eigen::Vector2f p1, c1;
+   p1(0) = x;
+   p1(1) = y;
+   
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+	   Eigen::Vector2f in ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y);
+	   c1 = p1 - in;
+	   distances[i] = std::abs(sqrt(c1.dot(c1))-r);
+		
+		//std::cout << distances[i] << std::endl;
+   }
+   //std::cout << std::accumulate(distances.begin(), distances.end(), 0.0) / distances.size() << ", ";
+  /*
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+   // Iterate through the 3d points and calculate the distances from them to the sphere
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     // @note need to revise this.
+     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
+  
+     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
+  
+     // Calculate the point's projection on the cylinder axis
+     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
+     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
+     Eigen::Vector4f dir = pt - pt_proj;
+     dir.normalize ();
+  
+     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
+     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
+     double d_normal = std::abs (getAngle3D (n, dir));
+     d_normal = (std::min) (d_normal, M_PI - d_normal);
+  
+     distances[i] = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);*/
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelCircle<PointT>::selectWithinDistance (
+       const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
+ {
+   std::vector<double> distances;
+   getDistancesToModel (model_coefficients, distances);
+   for (int i = 0; i < distances.size(); i++)
+   {
+	   if (distances[i] < threshold) {inliers.push_back ((*indices_)[i]);}
+   }
+   
+   //std::cout << model_coefficients[2] << std::endl;
+   /*
+   // Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+   {
+     inliers.clear ();
+     return;
+   }
+  
+   inliers.clear ();
+   error_sqr_dists_.clear ();
+   inliers.reserve (indices_->size ());
+   error_sqr_dists_.reserve (indices_->size ());
+  
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+   // Iterate through the 3d points and calculate the distances from them to the sphere
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
+     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
+     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
+       continue;
+  
+     // Calculate the point's projection on the cylinder axis
+     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
+     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
+     Eigen::Vector4f dir = pt - pt_proj;
+     dir.normalize ();
+  
+     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
+     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
+     double d_normal = std::abs (getAngle3D (n, dir));
+     d_normal = (std::min) (d_normal, M_PI - d_normal);
+  
+     double distance = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);
+     if (distance < threshold)
+     {
+       // Returns the indices of the points whose distances are smaller than the threshold
+       inliers.push_back ((*indices_)[i]);
+       error_sqr_dists_.push_back (distance);
+     }
+   }*/
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> std::size_t
+ pcl::SampleConsensusModelCircle<PointT>::countWithinDistance (
+       const Eigen::VectorXf &model_coefficients, const double threshold) const
+ {
+   std::vector<double> distances;
+   getDistancesToModel (model_coefficients, distances);
+   int count = 0;
+   for (int i = 0; i < distances.size(); i++)
+   {
+	   if (distances[i] <= threshold) {count++;}
+   }
+   //std::cout << count << std::endl;
+   return (count);
+   /*// Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+     return (0);
+  
+   std::size_t nr_p = 0;
+  
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+   // Iterate through the 3d points and calculate the distances from them to the sphere
+   for (std::size_t i = 0; i < indices_->size (); ++i)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
+     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
+     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
+       continue;
+  
+     // Calculate the point's projection on the cylinder axis
+     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
+     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
+     Eigen::Vector4f dir = pt - pt_proj;
+     dir.normalize ();
+  
+     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
+     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
+     double d_normal = std::abs (getAngle3D (n, dir));
+     d_normal = (std::min) (d_normal, M_PI - d_normal);
+  
+     if (std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist) < threshold)
+       nr_p++;
+   }
+   return (nr_p);*/
+   return (0);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelCircle<PointT>::optimizeModelCoefficients (
+       const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
+ {
+   optimized_coefficients = model_coefficients;
+  
+   // Needs a set of valid model coefficients
+   if (!isModelValid (model_coefficients))
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelCircle::optimizeModelCoefficients] Given model is invalid!\n");
+     return;
+   }
+  
+   // Need more than the minimum sample size to make a difference
+   if (inliers.size () <= sample_size_)
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelCircle:optimizeModelCoefficients] Not enough inliers found to optimize model coefficients (%lu)! Returning the same coefficients.\n", inliers.size ());
+     return;
+   }
+  
+   OptimizationFunctor functor (this, inliers);
+   Eigen::NumericalDiff<OptimizationFunctor > num_diff (functor);
+   Eigen::LevenbergMarquardt<Eigen::NumericalDiff<OptimizationFunctor>, float> lm (num_diff);
+   int info = lm.minimize (optimized_coefficients);
+   
+   // Compute the L2 norm of the residuals
+   PCL_DEBUG ("[pcl::SampleConsensusModelCircle::optimizeModelCoefficients] LM solver finished with exit code %i, having a residual norm of %g. \nInitial solution: %g %g %g %g %g %g %g \nFinal solution: %g %g %g %g %g %g %g\n",
+              info, lm.fvec.norm (), model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
+              model_coefficients[4], model_coefficients[5], model_coefficients[6], optimized_coefficients[0], optimized_coefficients[1], optimized_coefficients[2], optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5], optimized_coefficients[6]);
+     
+   Eigen::Vector3f line_dir (optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5]);
+   line_dir.normalize ();
+   optimized_coefficients[3] = line_dir[0];
+   optimized_coefficients[4] = line_dir[1];
+   optimized_coefficients[5] = line_dir[2];
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelCircle<PointT>::projectPoints (
+       const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
+ {
+   // Needs a valid set of model coefficients
+   if (!isModelValid (model_coefficients))
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelCircle::projectPoints] Given model is invalid!\n");
+     return;
+   }
+  
+   projected_points.header = input_->header;
+   projected_points.is_dense = input_->is_dense;
+  
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   float ptdotdir = line_pt.dot (line_dir);
+   float dirdotdir = 1.0f / line_dir.dot (line_dir);
+  
+   // Copy all the data fields from the input cloud to the projected one?
+   if (copy_data_fields)
+   {
+     // Allocate enough space and copy the basics
+     projected_points.resize (input_->size ());
+     projected_points.width    = input_->width;
+     projected_points.height   = input_->height;
+  
+     using FieldList = typename pcl::traits::fieldList<PointT>::type;
+     // Iterate over each point
+     for (std::size_t i = 0; i < projected_points.size (); ++i)
+       // Iterate over each dimension
+       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
+  
+     // Iterate through the 3d points and calculate the distances from them to the cylinder
+     for (const auto &inlier : inliers)
+     {
+       Eigen::Vector4f p ((*input_)[inlier].x,
+                          (*input_)[inlier].y,
+                          (*input_)[inlier].z,
+                          1);
+  
+       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
+  
+       pcl::Vector4fMap pp = projected_points[inlier].getVector4fMap ();
+       pp.matrix () = line_pt + k * line_dir;
+  
+       Eigen::Vector4f dir = p - pp;
+       dir[3] = 0.0f;
+       dir.normalize ();
+  
+       // Calculate the projection of the point onto the cylinder
+       pp += dir * model_coefficients[6];
+     }
+   }
+   else
+   {
+     // Allocate enough space and copy the basics
+     projected_points.resize (inliers.size ());
+     projected_points.width    = inliers.size ();
+     projected_points.height   = 1;
+  
+     using FieldList = typename pcl::traits::fieldList<PointT>::type;
+     // Iterate over each point
+     for (std::size_t i = 0; i < inliers.size (); ++i)
+       // Iterate over each dimension
+       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
+  
+     // Iterate through the 3d points and calculate the distances from them to the cylinder
+     for (std::size_t i = 0; i < inliers.size (); ++i)
+     {
+       pcl::Vector4fMap pp = projected_points[i].getVector4fMap ();
+       pcl::Vector4fMapConst p = (*input_)[inliers[i]].getVector4fMap ();
+  
+       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
+       // Calculate the projection of the point on the line
+       pp.matrix () = line_pt + k * line_dir;
+  
+       Eigen::Vector4f dir = p - pp;
+       dir[3] = 0.0f;
+       dir.normalize ();
+  
+       // Calculate the projection of the point onto the cylinder
+       pp += dir * model_coefficients[6];
+     }
+   }
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool
+ pcl::SampleConsensusModelCircle<PointT>::doSamplesVerifyModel (
+       const std::set<int> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
+ {
+   // Needs a valid model coefficients
+   if (!isModelValid (model_coefficients))
+   {
+     PCL_ERROR ("[pcl::SampleConsensusModelCircle::doSamplesVerifyModel] Given model is invalid!\n");
+     return (false);
+   }
+  
+   for (const auto &index : indices)
+   {
+     // Approximate the distance from the point to the cylinder as the difference between
+     // dist(point,cylinder_axis) and cylinder radius
+     // @note need to revise this.
+     Eigen::Vector4f pt ((*input_)[index].x, (*input_)[index].y, (*input_)[index].z, 0.0f);
+     if (std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]) > threshold)
+       return (false);
+   }
+  
+   return (true);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> double
+ pcl::SampleConsensusModelCircle<PointT>::pointToLineDistance (
+       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const
+ {
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+   return sqrt(pcl::sqrPointToLineDistance (pt, line_pt, line_dir));
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelCircle<PointT>::projectPointToRectangle (
+       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients, Eigen::Vector4f &pt_proj) const
+ {
+   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+  
+   float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) * line_dir.dot (line_dir);
+   pt_proj = line_pt + k * line_dir;
+  
+   Eigen::Vector4f dir = pt - pt_proj;
+   dir.normalize ();
+  
+   // Calculate the projection of the point onto the cylinder
+   pt_proj += dir * model_coefficients[6];
+ }
+  
+ //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool 
+ pcl::SampleConsensusModelCircle<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
+ {
+   if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
+     return (false);
+  /*
+   // Check against template, if given
+   if (eps_angle_ > 0.0)
+   {
+     // Obtain the cylinder direction
+     const Eigen::Vector3f coeff(model_coefficients[3], model_coefficients[4], model_coefficients[5]);
+  
+     double angle_diff = std::abs (getAngle3D (axis_, coeff));
+     angle_diff = (std::min) (angle_diff, M_PI - angle_diff);
+     // Check whether the current cylinder model satisfies our angle threshold criterion with respect to the given axis
+     if (angle_diff > eps_angle_)
+     {
+       PCL_DEBUG ("[pcl::SampleConsensusModelCircle::isModelValid] Angle between cylinder direction and given axis is too large.\n");
+       return (false);
+     }
+   }
+  
+   if (radius_min_ != -std::numeric_limits<double>::max() && model_coefficients[6] < radius_min_)
+   {
+     PCL_DEBUG ("[pcl::SampleConsensusModelCircle::isModelValid] Radius is too small: should be larger than %g, but is %g.\n",
+                radius_min_, model_coefficients[6]);
+     return (false);
+   }
+   if (radius_max_ != std::numeric_limits<double>::max() && model_coefficients[6] > radius_max_)
+   {
+     PCL_DEBUG ("[pcl::SampleConsensusModelCircle::isModelValid] Radius is too big: should be smaller than %g, but is %g.\n",
+                radius_max_, model_coefficients[6]);
+     return (false);
+   }*/
+  
+   return (true);
+ }
+  
+ #define PCL_INSTANTIATE_SampleConsensusModelCircle(PointT) template class PCL_EXPORTS pcl::SampleConsensusModelCircle<PointT>;
+  
+ #endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_CIRCLE_H_
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
index f00ae3e9..e83dd718 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
@@ -116,7 +116,7 @@
    model_coefficients[2] = w;
    model_coefficients[3] = r;
    
-   std::cout << w << std::endl;
+   //std::cout << w << std::endl;
    
    PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::computeModelCoefficients] Model is (%g,%g,%g,%g,%g).\n",
               model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3]);
@@ -150,7 +150,7 @@
    c2(0)= std::sin(r)*w;
    c2(1)=-std::cos(r)*w;
    
-   std::cout << "c2 = " << std::endl << c2 << std::endl;
+   //std::cout << "c2 = " << std::endl << c2 << std::endl;
 
    //define corner vectors
    p1(0)=x;
@@ -213,7 +213,7 @@
 	   if (distances[i] < threshold) {inliers.push_back ((*indices_)[i]);}
    }
    
-   std::cout << model_coefficients[2] << std::endl;
+   //std::cout << model_coefficients[2] << std::endl;
    /*
    // Check if the model is valid given the user constraints
    if (!isModelValid (model_coefficients))
diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 1d1a6f2b..72ce31c5 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -34,6 +34,7 @@
 
 #include "ed_sensor_integration/sac_model_rectangle.h"
 #include "ed_sensor_integration/sac_model_double_line.h"
+#include "ed_sensor_integration/sac_model_circle.h"
 
 void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, Eigen::Matrix4f &final_transform)
 {
@@ -256,20 +257,18 @@ Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
 	sac1->computeModel();
 
 	// Get inliers
-	std::vector<int> inliers;
-	sac1->getInliers(inliers);
+	std::vector<int> inliers1;
+	sac1->getInliers(inliers1);
 
 	// Get the model coefficients
-	Eigen::VectorXf coeff;
-	sac1->getModelCoefficients (coeff);
+	Eigen::VectorXf coeff1;
+	sac1->getModelCoefficients (coeff1);
 	
-	float w = coeff[2];
-	float r = coeff[3];
 	
 	//extract the inliers and fit second set of lines perpendicular
 	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud2 (new pcl::PointCloud<pcl::PointXYZ>);
 	pcl::PointIndices::Ptr line1_inliers (new pcl::PointIndices);
-	line1_inliers->indices = inliers;
+	line1_inliers->indices = inliers1;
 	pcl::ExtractIndices<pcl::PointXYZ> extract;
 	extract.setInputCloud (cloud_ptr);
 	extract.setIndices (line1_inliers);
@@ -284,27 +283,59 @@ Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
 	// Fit model
 	sac2->computeModel();
 	// Get inliers
-	sac2->getInliers(inliers);
+	std::vector<int> inliers2;
+	sac2->getInliers(inliers2);
 	// Get the model coefficients
 	Eigen::VectorXf coeff2;
 	sac2->getModelCoefficients (coeff2);
-	
-	float l = coeff2[2];
-	r = r - coeff2[3]; //difference in angle: if not 90 degrees, model is a parallellogram	
+
 	pcl::io::savePCDFileASCII ("lines.pcd", *cloud2);
-	Eigen::VectorXf output;
-	output.resize(3);
-	output[0] = l;
-	output[1] = w;
-	output[2] = r;
 	
 	pcl::PointIndices::Ptr line2_inliers (new pcl::PointIndices);
-	line2_inliers->indices = inliers;
+	line2_inliers->indices = inliers2;
 	extract.setInputCloud (cloud2);
 	extract.setIndices (line2_inliers);
 	extract.filter (*cloud2);
 	pcl::io::savePCDFileASCII ("outliers.pcd", *cloud2);
 	
+	
+	//repeat above steps for a circle
+	pcl::SampleConsensusModelCircle<pcl::PointXYZ>::Ptr circle (new pcl::SampleConsensusModelCircle<pcl::PointXYZ>(cloud_ptr));
+
+	// Create SAC method
+	pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr saccirc (new pcl::RandomSampleConsensus<pcl::PointXYZ> (circle, threshold));
+	saccirc->setMaxIterations(10000);
+	saccirc->setProbability(1);
+
+	// Fit model
+	saccirc->computeModel();
+
+	// Get inliers
+	std::vector<int> inliers3;
+	saccirc->getInliers(inliers3);
+
+	// Get the model coefficients
+	Eigen::VectorXf coeff3;
+	saccirc->getModelCoefficients (coeff3);
+	
+	float min_inliers = 0.0;
+	Eigen::VectorXf output;
+	if ((inliers1.size()+inliers2.size() >= inliers3.size()) && (static_cast<float>(inliers1.size()+inliers2.size())/static_cast<float>(cloud.size()) > min_inliers))
+	{
+		float w = coeff1[2];
+		float l = coeff2[2];
+		float r = coeff1[3] - coeff2[3];//difference in angle: if not 90 degrees, model is a parallellogram	
+		
+		output.resize(3);
+		output[0] = l;
+		output[1] = w;
+		output[2] = r;
+	}
+	else if ((inliers1.size()+inliers2.size() < inliers3.size()) && (static_cast<float>(inliers3.size())/static_cast<float>(cloud.size()) > min_inliers))
+	{
+		output.resize(1);
+		output[0] = coeff3[2];
+	}
 	return (output);
 }
 

From 06058250edd0897f31363b9abeb494a5b8ecbd8a Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Thu, 30 Dec 2021 18:53:25 +0100
Subject: [PATCH 021/136] Rewrite height estimation

---
 .../sac_model_horizontal_plane.h              | 194 ++++++++++++++++++
 .../sac_model_horizontal_plane.hpp            | 135 ++++++++++++
 ed_sensor_integration/tools/table_modeler.cpp | 129 ++++++++++--
 3 files changed, 437 insertions(+), 21 deletions(-)
 create mode 100644 ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.h
 create mode 100644 ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.hpp

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.h
new file mode 100644
index 00000000..11a7ddd1
--- /dev/null
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.h
@@ -0,0 +1,194 @@
+/*
+  * Software License Agreement (BSD License)
+  *
+  *  Point Cloud Library (PCL) - www.pointclouds.org
+  *  Copyright (c) 2010-2011, Willow Garage, Inc.
+  *  Copyright (c) 2012-, Open Perception, Inc.
+  *
+  *  All rights reserved.
+  *
+  *  Redistribution and use in source and binary forms, with or without
+  *  modification, are permitted provided that the following conditions
+  *  are met:
+  *
+  *   * Redistributions of source code must retain the above copyright
+  *     notice, this list of conditions and the following disclaimer.
+  *   * Redistributions in binary form must reproduce the above
+  *     copyright notice, this list of conditions and the following
+  *     disclaimer in the documentation and/or other materials provided
+  *     with the distribution.
+  *   * Neither the name of the copyright holder(s) nor the names of its
+  *     contributors may be used to endorse or promote products derived
+  *     from this software without specific prior written permission.
+  *
+  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+  *  POSSIBILITY OF SUCH DAMAGE.
+  *
+  * $Id$
+  *
+  */
+  
+ #pragma once
+  
+ #include <pcl/sample_consensus/sac_model_plane.h>
+  
+ namespace pcl
+ {
+   /** \brief @b SampleConsensusModelParallelPlane defines a model for 3D plane segmentation using additional
+     * angular constraints. The plane must be parallel to a user-specified axis
+     * (\ref setAxis) within a user-specified angle threshold (\ref setEpsAngle).
+     * In other words, the plane <b>normal</b> must be (nearly) <b>perpendicular</b> to the specified axis.
+     *
+     * Code example for a plane model, parallel (within a 15 degrees tolerance) with the Z axis:
+     * \code
+     * SampleConsensusModelParallelPlane<pcl::PointXYZ> model (cloud);
+     * model.setAxis (Eigen::Vector3f (0.0, 0.0, 1.0));
+     * model.setEpsAngle (pcl::deg2rad (15));
+     * \endcode
+     *
+     * \note Please remember that you need to specify an angle > 0 in order to activate the axis-angle constraint!
+     *
+     * \author Radu B. Rusu, Nico Blodow
+     * \ingroup sample_consensus
+     */
+   template <typename PointT>
+   class SampleConsensusModelHorizontalPlane : public SampleConsensusModelPlane<PointT>
+   {
+     public:
+       using SampleConsensusModel<PointT>::model_name_;
+       using SampleConsensusModel<PointT>::indices_;
+	   using SampleConsensusModel<PointT>::input_;
+	   
+       using PointCloud = typename SampleConsensusModelPlane<PointT>::PointCloud;
+       using PointCloudPtr = typename SampleConsensusModelPlane<PointT>::PointCloudPtr;
+       using PointCloudConstPtr = typename SampleConsensusModelPlane<PointT>::PointCloudConstPtr;
+  
+       using Ptr = shared_ptr<SampleConsensusModelHorizontalPlane<PointT> >;
+       using ConstPtr = shared_ptr<const SampleConsensusModelHorizontalPlane<PointT>>;
+  
+       /** \brief Constructor for base SampleConsensusModelHorizontalPlane.
+         * \param[in] cloud the input point cloud dataset
+         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+         */
+       SampleConsensusModelHorizontalPlane (const PointCloudConstPtr &cloud,
+                                          bool random = false) 
+         : SampleConsensusModelPlane<PointT> (cloud, random)
+         , axis_ (Eigen::Vector3f::Zero ())
+         , eps_angle_ (0.0)
+         , sin_angle_ (-1.0)
+       {
+         model_name_ = "SampleConsensusModelHorizontalPlane";
+         sample_size_ = 3;
+         model_size_ = 4;
+       }
+  
+       /** \brief Constructor for base SampleConsensusModelHorizontalPlane.
+         * \param[in] cloud the input point cloud dataset
+         * \param[in] indices a vector of point indices to be used from \a cloud
+         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+         */
+       SampleConsensusModelHorizontalPlane (const PointCloudConstPtr &cloud, 
+                                          const Indices &indices,
+                                          bool random = false) 
+         : SampleConsensusModelPlane<PointT> (cloud, indices, random)
+         , axis_ (Eigen::Vector3f::Zero ())
+         , eps_angle_ (0.0)
+         , sin_angle_ (-1.0)
+       {
+         model_name_ = "SampleConsensusModelHorizontalPlane";
+         sample_size_ = 3;
+         model_size_ = 4;
+       }
+       
+       /** \brief Empty destructor */
+       ~SampleConsensusModelHorizontalPlane () {}
+  
+       /** \brief Set the axis along which we need to search for a plane perpendicular to.
+         * \param[in] ax the axis along which we need to search for a plane perpendicular to
+         */
+       inline void
+       setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
+  
+       /** \brief Get the axis along which we need to search for a plane perpendicular to. */
+       inline Eigen::Vector3f
+       getAxis () const { return (axis_); }
+  
+       /** \brief Set the angle epsilon (delta) threshold.
+         * \param[in] ea the maximum allowed difference between the plane normal and the given axis.
+         * \note You need to specify an angle > 0 in order to activate the axis-angle constraint!
+         */
+       inline void
+       setEpsAngle (const double ea) { eps_angle_ = ea; sin_angle_ = std::abs (sin (ea));}
+  
+       /** \brief Get the angle epsilon (delta) threshold. */
+       inline double
+       getEpsAngle () const { return (eps_angle_); }
+       
+       bool
+       computeModelCoefficients (const Indices &samples,
+                                 Eigen::VectorXf &model_coefficients) const override;
+  
+       /** \brief Select all the points which respect the given model coefficients as inliers.
+         * \param[in] model_coefficients the coefficients of a plane model that we need to compute distances to
+         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+         * \param[out] inliers the resultant model inliers
+         */
+       void
+       selectWithinDistance (const Eigen::VectorXf &model_coefficients,
+                             const double threshold,
+                             Indices &inliers) override;
+  
+       /** \brief Count all the points which respect the given model coefficients as inliers.
+         *
+         * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
+         * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
+         * \return the resultant number of inliers
+         */
+       std::size_t
+       countWithinDistance (const Eigen::VectorXf &model_coefficients,
+                            const double threshold) const override;
+  
+       /** \brief Compute all distances from the cloud data to a given plane model.
+         * \param[in] model_coefficients the coefficients of a plane model that we need to compute distances to
+         * \param[out] distances the resultant estimated distances
+         */
+       void
+       getDistancesToModel (const Eigen::VectorXf &model_coefficients,
+                            std::vector<double> &distances) const override;
+  
+       /** \brief Return a unique id for this model (SACMODEL_HORIZONTAL_PLANE). */
+       inline pcl::SacModel
+       getModelType () const override { return (SACMODEL_PARALLEL_PLANE); }//cannot add unique identifier
+  
+     protected:
+       using SampleConsensusModel<PointT>::sample_size_;
+       using SampleConsensusModel<PointT>::model_size_;
+  
+       /** \brief Check whether a model is valid given the user constraints.
+         * \param[in] model_coefficients the set of model coefficients
+         */
+       bool
+       isModelValid (const Eigen::VectorXf &model_coefficients) const override;
+  
+       /** \brief The axis along which we need to search for a plane perpendicular to. */
+       Eigen::Vector3f axis_;
+  
+       /** \brief The maximum allowed difference between the plane and the given axis. */
+       double eps_angle_;
+  
+       /** \brief The sine of the angle*/
+       double sin_angle_;
+   };
+ }
+  
+ #include "ed_sensor_integration/sac_model_horizontal_plane.hpp"
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.hpp
new file mode 100644
index 00000000..ecbb95ff
--- /dev/null
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.hpp
@@ -0,0 +1,135 @@
+/*
+  * Software License Agreement (BSD License)
+  *
+  *  Point Cloud Library (PCL) - www.pointclouds.org
+  *  Copyright (c) 2010, Willow Garage, Inc.
+  *  Copyright (c) 2012-, Open Perception, Inc.
+  *
+  *  All rights reserved.
+  *
+  *  Redistribution and use in source and binary forms, with or without
+  *  modification, are permitted provided that the following conditions
+  *  are met:
+  *
+  *   * Redistributions of source code must retain the above copyright
+  *     notice, this list of conditions and the following disclaimer.
+  *   * Redistributions in binary form must reproduce the above
+  *     copyright notice, this list of conditions and the following
+  *     disclaimer in the documentation and/or other materials provided
+  *     with the distribution.
+  *   * Neither the name of the copyright holder(s) nor the names of its
+  *     contributors may be used to endorse or promote products derived
+  *     from this software without specific prior written permission.
+  *
+  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+  *  POSSIBILITY OF SUCH DAMAGE.
+  *
+  * $Id$
+  a
+  */
+  
+ #ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_HORIZONTAL_PLANE_H_
+ #define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_HORIZONTAL_PLANE_H_
+  
+ #include "ed_sensor_integration/sac_model_horizontal_plane.h"
+  
+ //////////////////////////////////////////////////////////////////////////
+ 
+ template <typename PointT> bool
+ pcl::SampleConsensusModelHorizontalPlane<PointT>::computeModelCoefficients (
+       const Indices &samples, Eigen::VectorXf &model_coefficients) const
+ {
+	 model_coefficients.resize (model_size_);
+	 model_coefficients[0] = 0;
+	 model_coefficients[1] = 0;
+	 model_coefficients[2] = -1;
+	 model_coefficients[3] = (*input_)[samples[0]].z;
+	 //std::cout <<model_coefficients << std::endl;
+	 return (true);
+ }
+ 
+ template <typename PointT> void
+ pcl::SampleConsensusModelHorizontalPlane<PointT>::selectWithinDistance (
+       const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
+ {
+   // Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+   {
+     inliers.clear ();
+     return;
+   }
+  
+   SampleConsensusModelPlane<PointT>::selectWithinDistance (model_coefficients, threshold, inliers);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////
+ template <typename PointT> std::size_t
+ pcl::SampleConsensusModelHorizontalPlane<PointT>::countWithinDistance (
+       const Eigen::VectorXf &model_coefficients, const double threshold) const
+ {
+   // Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+   {
+     return (0);
+   }
+   //std::cout << model_coefficients << std::endl;
+  //std::cout << SampleConsensusModelPlane<PointT>::countWithinDistance (model_coefficients, threshold) << std::endl;
+   return (SampleConsensusModelPlane<PointT>::countWithinDistance (model_coefficients, threshold));
+ }
+  
+ //////////////////////////////////////////////////////////////////////////
+ template <typename PointT> void
+ pcl::SampleConsensusModelHorizontalPlane<PointT>::getDistancesToModel (
+       const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
+ {
+   // Check if the model is valid given the user constraints
+   if (!isModelValid (model_coefficients))
+   {
+     distances.clear ();
+     return;
+   }
+  
+   SampleConsensusModelPlane<PointT>::getDistancesToModel (model_coefficients, distances);
+ }
+  
+ //////////////////////////////////////////////////////////////////////////
+ template <typename PointT> bool
+ pcl::SampleConsensusModelHorizontalPlane<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
+ {
+   if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
+   {
+     return (false);
+   }
+  /*
+   // Check against template, if given
+   if (eps_angle_ > 0.0)
+   {
+     // Obtain the plane normal
+     Eigen::Vector4f coeff = model_coefficients;
+     coeff[3] = 0.0f;
+     coeff.normalize ();
+  
+     Eigen::Vector4f axis (axis_[0], axis_[1], axis_[2], 0.0f);
+     if (std::abs (axis.dot (coeff)) > sin_angle_)
+     {
+       PCL_DEBUG ("[pcl::SampleConsensusModelHorizontalPlane::isModelValid] Angle between plane normal and given axis is too large.\n");
+       return  (false);
+     }
+   }
+  */
+   return (true);
+ }
+  
+ #define PCL_INSTANTIATE_SampleConsensusModelHorizontalPlane(T) template class PCL_EXPORTS pcl::SampleConsensusModelHorizontalPlane<T>;
+  
+ #endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_HORIZONTAL_PLANE_H_
diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 72ce31c5..31caa1d0 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -14,9 +14,12 @@
 #include <pcl/registration/icp_nl.h>
 #include <pcl/registration/transforms.h>
 
-#include <pcl/sample_consensus/ransac.h>
+#include <pcl/sample_consensus/method_types.h>
+#include <pcl/sample_consensus/model_types.h>
+//#include <pcl/sample_consensus/ransac.h>
 
 #include <pcl/segmentation/extract_clusters.h>
+#include <pcl/segmentation/sac_segmentation.h>
 
 #include <pcl/surface/convex_hull.h>
 #include <pcl/surface/concave_hull.h>
@@ -32,9 +35,10 @@
 
 #include <fstream>
 
-#include "ed_sensor_integration/sac_model_rectangle.h"
+//#include "ed_sensor_integration/sac_model_rectangle.h"
 #include "ed_sensor_integration/sac_model_double_line.h"
 #include "ed_sensor_integration/sac_model_circle.h"
+#include "ed_sensor_integration/sac_model_horizontal_plane.h"
 
 void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, Eigen::Matrix4f &final_transform)
 {
@@ -51,7 +55,7 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
     reg.setTransformationEpsilon (1e-6);
     // Set the maximum distance between two correspondences (src<->tgt) to 10cm
     // Note: adjust this based on the size of your datasets
-    reg.setMaxCorrespondenceDistance (0.1);
+    reg.setMaxCorrespondenceDistance (1);
     // Set the point representation
     // reg.setPointRepresentation (pcl::make_shared<const MyPointRepresentation> (point_representation));
 
@@ -75,7 +79,85 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
     final_transform = targetToSource;
  }
 
-void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z, float* tableHeight) {
+float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out) {
+	std::vector<int> indices;
+	float threshold = 0.03;
+	
+	std::cout << "starting ransac" << std::endl;
+	// Create SAC model
+	pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>::Ptr plane (new pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>(cloud));
+	std::cout << "created plane object" << std::endl;
+	// Create SAC method
+	pcl::RandomSampleConsensus<pcl::PointXYZRGB>::Ptr sac (new pcl::RandomSampleConsensus<pcl::PointXYZRGB> (plane, threshold));
+	std::cout << "created ransac object" << std::endl;
+	sac->setMaxIterations(10000);
+	sac->setProbability(0.99);
+	
+	// Fit model
+	sac->computeModel();
+
+	// Get inliers
+	std::vector<int> inliers;
+	sac->getInliers(inliers);
+
+	// Get the model coefficients
+	Eigen::VectorXf coeff;
+	sac->getModelCoefficients (coeff);
+	std::cout << "ransac complete" << std::endl;
+	
+	pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+    range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
+	*out = *cloud;
+	//filter out everything below plane
+    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+    condrem.setCondition (range_cond);
+    condrem.setInputCloud (out);
+    condrem.setKeepOrganized(true);
+    
+    condrem.filter (*out);
+    (*out).is_dense = false;
+    pcl::removeNaNFromPointCloud(*out, *out, indices);
+	
+	return(coeff[3]);
+	
+	
+	
+	/*
+	Eigen::Vector3f ax(0, 0, 1);	
+	pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients);
+	pcl::PointIndices::Ptr inliers (new pcl::PointIndices);
+	// Create the segmentation object
+	pcl::SACSegmentation<pcl::PointXYZRGB> seg;
+	// Optional
+	seg.setOptimizeCoefficients (true);
+	// Mandatory
+	seg.setModelType (pcl::SACMODEL_PARALLEL_PLANE);
+	seg.setMethodType (pcl::SAC_RANSAC);
+	seg.setDistanceThreshold (0.01);
+	seg.setAxis (ax);
+	seg.setEpsAngle (0);
+
+	seg.setInputCloud (cloud);
+	seg.segment (*inliers, *coefficients);
+
+	if (inliers->indices.size () == 0)
+	{
+		PCL_ERROR ("Could not estimate a planar model for the given dataset.\n");
+		*out = *cloud;
+		return(-1);
+	}
+	// Extract the inliers
+	pcl::ExtractIndices<pcl::PointXYZRGB> extract;
+    extract.setInputCloud (cloud);
+    extract.setIndices (inliers);
+    extract.setNegative (false);
+    extract.filter (*out);
+    
+	float Height = coefficients->values[3]; //final coefficient gives distance to the origin. normal vector is given as (0, 0, 1)
+	return(Height);*/
+}
+
+void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z, std::vector<float> &tableHeight) {
     std::cout << "starting segmentation" << std::endl;
     std::cout << "x = " << x << ", y = " << y << ", z = " << z << std::endl;
 
@@ -84,7 +166,7 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
     tree->setInputCloud (cloud);
 
     std::vector<pcl::PointIndices> cluster_indices;
-    pcl::EuclideanClusterExtraction<pcl::PointXYZRGB> ec;
+    pcl::EuclideanClusterExtraction<pcl::PointXYZRGB> ec; //using euclidian cluster extraction
     ec.setClusterTolerance (0.1);
     ec.setMinClusterSize ((*cloud).size()/100);
     ec.setMaxClusterSize ((*cloud).size());
@@ -93,41 +175,46 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
     ec.extract (cluster_indices);
 
     std::cout << "obtained cluster indices" <<std::endl;
-
+	
+	//find closest cluster
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out;
     float mindist = INFINITY;
-    for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it != cluster_indices.end (); ++it)
+	for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it != 
+	cluster_indices.end (); ++it) //iterate through all clusters
     {
+		//construct cluster
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZRGB>);
         for (const auto& idx : it->indices)
         cloud_cluster->push_back ((*cloud)[idx]); //*
         cloud_cluster->width = cloud_cluster->size ();
         cloud_cluster->height = 1;
         cloud_cluster->is_dense = true;
-        float sumx = 0, sumy = 0, sumz = 0, dist = 0, maxz = -INFINITY;
+        float sumx = 0, sumy = 0, sumz = 0, dist = 0;
         for (uint j=0; j < (*cloud_cluster).width; ++j)
         {
+			//sum up all points
             sumx += (*cloud_cluster)[j].x;
             sumy += (*cloud_cluster)[j].y;
             sumz += (*cloud_cluster)[j].z;
-            if ((*cloud_cluster)[j].z > maxz)
-            {
-                maxz = (*cloud_cluster)[j].z;
-            }
         }
+        //find distance from camera to the middle of the cluster
         dist = pow((sumx/(*cloud_cluster).width-x),2) + pow((sumy/(*cloud_cluster).width-y),2) + pow((sumz/(*cloud_cluster).width-z),2);
         std::cout << "distance is " << sqrt(dist) << std::endl;
-        if (dist < mindist)
+        if (dist < mindist) //check if closest so far
         {
             std::cout << "updating closest cluster" << std::endl;
             mindist = dist;
             cloud_out = cloud_cluster;
-            if (maxz < *tableHeight)
-            {
-                *tableHeight = maxz;
-            }
+            //currentTableHeight = maxz
         }
     }
+	
+	float height = FilterPlane(cloud_out, cloud_out);
+	if (height != -1)
+	{
+		tableHeight.push_back(height);
+	}
+	
     std::cout << "writing closest cluster" << std::endl;
     *cloud = *cloud_out;
 }
@@ -375,7 +462,7 @@ int main(int argc, char **argv) {
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr result (new pcl::PointCloud<pcl::PointXYZRGB>), source, target;
     Eigen::Matrix4f GlobalTransform = Eigen::Matrix4f::Identity (), pairTransform;
 
-    float tableHeight = INFINITY;//used to keep track of the table height
+    std::vector<float> tableHeight;//used to keep track of the table height
 
     float x, y, z;//used to store camera position
     pcl::transformPointCloud (*inputs[0], *inputs[0], ReadJson(argv[1], &x, &y, &z));
@@ -393,7 +480,7 @@ int main(int argc, char **argv) {
     (*inputs[0]).is_dense = false;
     pcl::removeNaNFromPointCloud(*inputs[0], *inputs[0], indices);
 
-    Segment(inputs[0], x, y, z, &tableHeight);
+    Segment(inputs[0], x, y, z, tableHeight);
 
     *result = *inputs[0];
 
@@ -411,7 +498,7 @@ int main(int argc, char **argv) {
         (*inputs[i]).is_dense = false;
         pcl::removeNaNFromPointCloud(*inputs[i], *inputs[i], indices);
 
-        Segment(inputs[i], x, y, z, &tableHeight);
+        Segment(inputs[i], x, y, z, tableHeight);
 
         // align to previous file
 
@@ -442,7 +529,7 @@ int main(int argc, char **argv) {
     std::cout << "Writing clouds" << std::endl;
     pcl::io::savePCDFileASCII ("combined.pcd", *result);
     pcl::io::savePCDFileASCII ("flat.pcd", flat);
-    std::cout << "The table is " << tableHeight << "m tall" << std::endl;
+    std::cout << "The table is " << std::accumulate(tableHeight.begin(), tableHeight.end(), 0.0) / tableHeight.size() << "m tall" << std::endl;
     
     
 

From 0345518fb3915df1289dcd51b02217de451722cd Mon Sep 17 00:00:00 2001
From: Thijs <t.m.h.beurskens@student.tue.nl>
Date: Mon, 17 Jan 2022 14:42:09 +0100
Subject: [PATCH 022/136] Add options to disable parts of the program

---
 ed_sensor_integration/tools/table_modeler.cpp | 57 +++++++------------
 1 file changed, 19 insertions(+), 38 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 31caa1d0..1bcb1d7d 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -42,6 +42,9 @@
 
 void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, Eigen::Matrix4f &final_transform)
 {
+	
+	//final_transform = Eigen::Matrix4f::Identity(); return; //activate to bypass alignment
+	
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr src (new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr tgt (new pcl::PointCloud<pcl::PointXYZRGB>);
 
@@ -80,6 +83,9 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
  }
 
 float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out) {
+	
+	//*out = *cloud; return(-1); //activate to bypass plane fitting and height estimation
+	
 	std::vector<int> indices;
 	float threshold = 0.03;
 	
@@ -107,6 +113,7 @@ float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud
 	
 	pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
     range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
+    //range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, (coeff[3]+0.01))));
 	*out = *cloud;
 	//filter out everything below plane
     pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
@@ -120,44 +127,12 @@ float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud
 	
 	return(coeff[3]);
 	
-	
-	
-	/*
-	Eigen::Vector3f ax(0, 0, 1);	
-	pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients);
-	pcl::PointIndices::Ptr inliers (new pcl::PointIndices);
-	// Create the segmentation object
-	pcl::SACSegmentation<pcl::PointXYZRGB> seg;
-	// Optional
-	seg.setOptimizeCoefficients (true);
-	// Mandatory
-	seg.setModelType (pcl::SACMODEL_PARALLEL_PLANE);
-	seg.setMethodType (pcl::SAC_RANSAC);
-	seg.setDistanceThreshold (0.01);
-	seg.setAxis (ax);
-	seg.setEpsAngle (0);
-
-	seg.setInputCloud (cloud);
-	seg.segment (*inliers, *coefficients);
-
-	if (inliers->indices.size () == 0)
-	{
-		PCL_ERROR ("Could not estimate a planar model for the given dataset.\n");
-		*out = *cloud;
-		return(-1);
-	}
-	// Extract the inliers
-	pcl::ExtractIndices<pcl::PointXYZRGB> extract;
-    extract.setInputCloud (cloud);
-    extract.setIndices (inliers);
-    extract.setNegative (false);
-    extract.filter (*out);
-    
-	float Height = coefficients->values[3]; //final coefficient gives distance to the origin. normal vector is given as (0, 0, 1)
-	return(Height);*/
 }
 
 void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z, std::vector<float> &tableHeight) {
+	
+	//return; //activate completely bypass segmentation and height estimation
+	
     std::cout << "starting segmentation" << std::endl;
     std::cout << "x = " << x << ", y = " << y << ", z = " << z << std::endl;
 
@@ -376,14 +351,14 @@ Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
 	Eigen::VectorXf coeff2;
 	sac2->getModelCoefficients (coeff2);
 
-	pcl::io::savePCDFileASCII ("lines.pcd", *cloud2);
+	//pcl::io::savePCDFileASCII ("lines.pcd", *cloud2);
 	
 	pcl::PointIndices::Ptr line2_inliers (new pcl::PointIndices);
 	line2_inliers->indices = inliers2;
 	extract.setInputCloud (cloud2);
 	extract.setIndices (line2_inliers);
 	extract.filter (*cloud2);
-	pcl::io::savePCDFileASCII ("outliers.pcd", *cloud2);
+	//pcl::io::savePCDFileASCII ("outliers.pcd", *cloud2);
 	
 	
 	//repeat above steps for a circle
@@ -407,6 +382,10 @@ Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
 	
 	float min_inliers = 0.0;
 	Eigen::VectorXf output;
+	
+	std::cout << "Parallelogram model, " << static_cast<float>(inliers1.size()+inliers2.size())/static_cast<float>(cloud.size()) << std::endl;
+	std::cout << "Circle model, " << static_cast<float>(inliers3.size())/static_cast<float>(cloud.size()) << std::endl;
+	
 	if ((inliers1.size()+inliers2.size() >= inliers3.size()) && (static_cast<float>(inliers1.size()+inliers2.size())/static_cast<float>(cloud.size()) > min_inliers))
 	{
 		float w = coeff1[2];
@@ -483,7 +462,9 @@ int main(int argc, char **argv) {
     Segment(inputs[0], x, y, z, tableHeight);
 
     *result = *inputs[0];
-
+	
+	pcl::io::savePCDFileASCII ("first.pcd", *inputs[0]);
+	
     for (int i = 1; i < argc-1; ++i)
     {
         std::cout << "iteration " << i << std::endl;   

From 5a20ea1d80f880ff6c1ca85faab8277a4d02a633 Mon Sep 17 00:00:00 2001
From: Pepijn Hundepool <p.c.j.hundepool@student.tue.nl>
Date: Thu, 28 Apr 2022 10:25:30 +0200
Subject: [PATCH 023/136] initial_commit

---
 ed_sensor_integration/src/kinect/code_v1.cpp | 159 +++++++++++++++++++
 1 file changed, 159 insertions(+)
 create mode 100644 ed_sensor_integration/src/kinect/code_v1.cpp

diff --git a/ed_sensor_integration/src/kinect/code_v1.cpp b/ed_sensor_integration/src/kinect/code_v1.cpp
new file mode 100644
index 00000000..e29cae99
--- /dev/null
+++ b/ed_sensor_integration/src/kinect/code_v1.cpp
@@ -0,0 +1,159 @@
+#include <iostream>
+#include <pcl/ModelCoefficients.h>
+#include <pcl/io/pcd_io.h>
+#include <pcl/point_types.h>
+#include <pcl/sample_consensus/method_types.h>
+#include <pcl/sample_consensus/model_types.h>
+#include <pcl/segmentation/sac_segmentation.h>
+#include <pcl/filters/voxel_grid.h>
+#include <pcl/filters/extract_indices.h>
+#include <ed/include/ed/io/json_reader.h>
+
+Eigen::Matrix4f ReadJson(std::string 2022-04-05-13-28-28, float *xout, float *yout, float *zout) {
+
+    std::string json_filename = boost::filesystem::change_extension(2022-04-05-13-28-28, ".json").string();
+    // read json metadata
+    tue::config::DataPointer meta_data;
+
+    try
+    {
+        meta_data = tue::config::fromFile(json_filename);
+    }
+    catch (tue::config::ParseException& e)
+    {
+        std::cerr << "Could not open '" << json_filename << "'.\n\n" << e.what() << std::endl;
+        //return 0;
+    }
+
+    tue::config::Reader r(meta_data);
+    // Read sensor pose
+    geo::Pose3D sensor_pose;
+    if (!ed::deserialize(r, "sensor_pose", sensor_pose))
+    {
+        std::cerr << "No field 'sensor_pose' specified." << std::endl;
+        //return 0;
+    }
+    // convert from geolib coordinates to ros coordinates #TODO remove geolib coordinates for camera pose
+    sensor_pose.R = sensor_pose.R * geo::Mat3(1, 0, 0, 0, -1, 0, 0, 0, -1);
+
+    float x = sensor_pose.t.x;
+    float y = sensor_pose.t.y;
+    float z = sensor_pose.t.z;
+    float xx = sensor_pose.R.xx;
+    float xy = sensor_pose.R.xy;
+    float xz = sensor_pose.R.xz;
+    float yx = sensor_pose.R.yx;
+    float yy = sensor_pose.R.yy;
+    float yz = sensor_pose.R.yz;
+    float zx = sensor_pose.R.zx;
+    float zy = sensor_pose.R.zy;
+    float zz = sensor_pose.R.zz;
+
+    *xout = x;
+    *yout = y;
+    *zout = z;
+
+    //float qx, qy, qz, qw;
+
+    //const float n = 2.0f/(qx*qx+qy*qy+qz*qz+qw*qw);
+    Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();/* {
+        {1.0f - n*qy*qy - n*qz*qz, n*qx*qy - n*qz*qw, n*qx*qz + n*qy*qw, x},
+        {n*qx*qy + n*qz*qw, 1.0f - n*qx*qx - n*qz*qz, n*qy*qz - n*qx*qw, y},
+        {n*qx*qz - n*qy*qw, n*qy*qz + n*qx*qw, 1.0f - n*qx*qx - n*qy*qy, z},
+        {0.0f, 0.0f, 0.0f, 1.0f}}; */
+
+    Transform(0,0) = xx; //1.0f - n*qy*qy - n*qz*qz;
+    Transform(0,1) = xy; //n*qx*qy - n*qz*qw;
+    Transform(0,2) = xz; //n*qx*qz + n*qy*qw;
+    Transform(0,3) = x;
+    Transform(1,0) = yx; //n*qx*qy + n*qz*qw;
+    Transform(1,1) = yy; //1.0f - n*qx*qx - n*qz*qz;
+    Transform(1,2) = yz; //n*qy*qz - n*qx*qw;
+    Transform(1,3) = y;
+    Transform(2,0) = zx; //n*qx*qz - n*qy*qw;
+    Transform(2,1) = zy; //n*qy*qz + n*qx*qw;
+    Transform(2,2) = zz; //1.0f - n*qx*qx - n*qy*qy;
+    Transform(2,3) = z;
+
+    std::cout << Transform << std::endl;
+    return Transform;
+}
+}
+
+
+int
+main ()
+{
+  pcl::PCLPointCloud2::Ptr cloud_blob (new pcl::PCLPointCloud2), cloud_filtered_blob (new pcl::PCLPointCloud2);
+  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>), cloud_p (new pcl::PointCloud<pcl::PointXYZ>), cloud_f (new pcl::PointCloud<pcl::PointXYZ>);
+
+  // Fill in the cloud data
+  pcl::PCDReader reader;
+  reader.read ("2022-04-05-13-28-28.pcd", *cloud_blob);
+
+  std::cerr << "PointCloud before filtering: " << cloud_blob->width * cloud_blob->height << " data points." << std::endl;
+
+  // Create the filtering object: downsample the dataset using a leaf size of 1cm
+  pcl::VoxelGrid<pcl::PCLPointCloud2> sor;
+  sor.setInputCloud (cloud_blob);
+  sor.setLeafSize (0.0025f, 0.0025f, 0.0025f);
+  sor.filter (*cloud_filtered_blob);
+
+  // Convert to the templated PointCloud
+  pcl::fromPCLPointCloud2 (*cloud_filtered_blob, *cloud_filtered);
+
+  std::cerr << "PointCloud after filtering: " << cloud_filtered->width * cloud_filtered->height << " data points." << std::endl;
+
+  // Write the downsampled version to disk
+  pcl::PCDWriter writer;
+  writer.write<pcl::PointXYZ> ("table_scene_lms400_downsampled.pcd", *cloud_filtered, false);
+
+  pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
+  pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
+  // Create the segmentation object
+  pcl::SACSegmentation<pcl::PointXYZ> seg;
+  // Optional
+  seg.setOptimizeCoefficients (true);
+  // Mandatory
+  seg.setModelType (pcl::SACMODEL_PLANE);
+  seg.setMethodType (pcl::SAC_RANSAC);
+  seg.setMaxIterations (1000);
+  seg.setDistanceThreshold (0.01);
+
+  // Create the filtering object
+  pcl::ExtractIndices<pcl::PointXYZ> extract;
+
+  int i = 0, nr_points = (int) cloud_filtered->size ();
+  // While 30% of the original cloud is still there
+  while (cloud_filtered->size () > 0.3 * nr_points)
+  {
+    // Segment the largest planar component from the remaining cloud
+    seg.setInputCloud (cloud_filtered);
+    seg.segment (*inliers, *coefficients);
+    if (inliers->indices.size () == 0)
+    {
+      std::cerr << "Could not estimate a planar model for the given dataset." << std::endl;
+      break;
+    }
+
+    // Extract the inliers
+    extract.setInputCloud (cloud_filtered);
+    extract.setIndices (inliers);
+    extract.setNegative (false);
+    extract.filter (*cloud_p);
+    std::cerr << "PointCloud representing the planar component: " << cloud_p->width * cloud_p->height << " data points." << std::endl;
+
+    std::stringstream ss;
+    ss << "table_scene_lms400_plane_" << i << ".pcd";
+    writer.write<pcl::PointXYZ> (ss.str (), *cloud_p, false);
+
+    // Create the filtering object
+    extract.setNegative (true);
+    extract.filter (*cloud_f);
+    cloud_filtered.swap (cloud_f);
+    i++;
+  }
+
+  return (0);
+  
+  

From 5b80acc397ab1af5383f23e3deffd0cb93e16920 Mon Sep 17 00:00:00 2001
From: Pepijn Hundepool <p.c.j.hundepool@student.tue.nl>
Date: Thu, 28 Apr 2022 10:45:53 +0200
Subject: [PATCH 024/136] hoi

---
 ed_sensor_integration/CMakeLists.txt         | 4 ++++
 ed_sensor_integration/src/kinect/code_v1.cpp | 2 +-
 2 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index 8483906c..87382260 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -6,6 +6,7 @@ find_package(catkin REQUIRED COMPONENTS
   ed_sensor_integration_msgs
   geolib2
   image_geometry
+  pcl_ros
   sensor_msgs
   tf2
   tf2_ros
@@ -116,6 +117,9 @@ target_link_libraries(ed_segmenter ed_kinect)
 add_executable(ed_fitter tools/fitter_viz.cpp)
 target_link_libraries(ed_fitter ed_kinect)
 
+add_executable(ed_table_modeler src/kinect/code_v1.cpp)
+target_link_libraries(ed_table_modeler ${catkin_LIBRARIES})
+
 # ------------------------------------------------------------------------------------------------
 #                                           TESTS
 # ------------------------------------------------------------------------------------------------
diff --git a/ed_sensor_integration/src/kinect/code_v1.cpp b/ed_sensor_integration/src/kinect/code_v1.cpp
index e29cae99..d329e3f9 100644
--- a/ed_sensor_integration/src/kinect/code_v1.cpp
+++ b/ed_sensor_integration/src/kinect/code_v1.cpp
@@ -7,7 +7,7 @@
 #include <pcl/segmentation/sac_segmentation.h>
 #include <pcl/filters/voxel_grid.h>
 #include <pcl/filters/extract_indices.h>
-#include <ed/include/ed/io/json_reader.h>
+#include <ed/io/json_reader.h>
 
 Eigen::Matrix4f ReadJson(std::string 2022-04-05-13-28-28, float *xout, float *yout, float *zout) {
 

From 012dba2d5ef8192f3e1e58932ad97d1681173620 Mon Sep 17 00:00:00 2001
From: Pepijn Hundepool <p.c.j.hundepool@student.tue.nl>
Date: Tue, 3 May 2022 22:41:07 +0200
Subject: [PATCH 025/136] horiontal plane attempt

---
 ed_sensor_integration/CMakeLists.txt         |  9 +++++
 ed_sensor_integration/src/kinect/code_v1.cpp | 41 ++++++++++++--------
 2 files changed, 34 insertions(+), 16 deletions(-)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index 87382260..d6e8bf22 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -2,6 +2,15 @@ cmake_minimum_required(VERSION 3.0.2)
 project(ed_sensor_integration)
 
 find_package(catkin REQUIRED COMPONENTS
+ # cv_bridge
+ # dynamic_reconfigure
+ # geometry_msgs
+ # actionlib_msgs
+ # image_transport
+
+ # rospy
+ # roscpp
+ # std_msgs
   ed
   ed_sensor_integration_msgs
   geolib2
diff --git a/ed_sensor_integration/src/kinect/code_v1.cpp b/ed_sensor_integration/src/kinect/code_v1.cpp
index d329e3f9..42231bda 100644
--- a/ed_sensor_integration/src/kinect/code_v1.cpp
+++ b/ed_sensor_integration/src/kinect/code_v1.cpp
@@ -1,17 +1,25 @@
 #include <iostream>
 #include <pcl/ModelCoefficients.h>
 #include <pcl/io/pcd_io.h>
+
 #include <pcl/point_types.h>
+#include <pcl/point_cloud.h>
+#include <pcl/point_representation.h>
+
 #include <pcl/sample_consensus/method_types.h>
 #include <pcl/sample_consensus/model_types.h>
+#include <pcl/sample_consensus/sac_model_parallel_plane.h>
+
 #include <pcl/segmentation/sac_segmentation.h>
+
 #include <pcl/filters/voxel_grid.h>
 #include <pcl/filters/extract_indices.h>
+
 #include <ed/io/json_reader.h>
 
-Eigen::Matrix4f ReadJson(std::string 2022-04-05-13-28-28, float *xout, float *yout, float *zout) {
+Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, float *zout) {
 
-    std::string json_filename = boost::filesystem::change_extension(2022-04-05-13-28-28, ".json").string();
+    std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();
     // read json metadata
     tue::config::DataPointer meta_data;
 
@@ -62,24 +70,22 @@ Eigen::Matrix4f ReadJson(std::string 2022-04-05-13-28-28, float *xout, float *yo
         {n*qx*qz - n*qy*qw, n*qy*qz + n*qx*qw, 1.0f - n*qx*qx - n*qy*qy, z},
         {0.0f, 0.0f, 0.0f, 1.0f}}; */
 
-    Transform(0,0) = xx; //1.0f - n*qy*qy - n*qz*qz;
-    Transform(0,1) = xy; //n*qx*qy - n*qz*qw;
-    Transform(0,2) = xz; //n*qx*qz + n*qy*qw;
+    Transform(0,0) = xx;//1.0f - n*qy*qy - n*qz*qz;
+    Transform(0,1) = xy;//n*qx*qy - n*qz*qw;
+    Transform(0,2) = xz;//n*qx*qz + n*qy*qw;
     Transform(0,3) = x;
-    Transform(1,0) = yx; //n*qx*qy + n*qz*qw;
-    Transform(1,1) = yy; //1.0f - n*qx*qx - n*qz*qz;
-    Transform(1,2) = yz; //n*qy*qz - n*qx*qw;
+    Transform(1,0) = yx;//n*qx*qy + n*qz*qw;
+    Transform(1,1) = yy;//1.0f - n*qx*qx - n*qz*qz;
+    Transform(1,2) = yz;//n*qy*qz - n*qx*qw;
     Transform(1,3) = y;
-    Transform(2,0) = zx; //n*qx*qz - n*qy*qw;
-    Transform(2,1) = zy; //n*qy*qz + n*qx*qw;
-    Transform(2,2) = zz; //1.0f - n*qx*qx - n*qy*qy;
+    Transform(2,0) = zx;//n*qx*qz - n*qy*qw;
+    Transform(2,1) = zy;//n*qy*qz + n*qx*qw;
+    Transform(2,2) = zz;//1.0f - n*qx*qx - n*qy*qy;
     Transform(2,3) = z;
 
     std::cout << Transform << std::endl;
     return Transform;
 }
-}
-
 
 int
 main ()
@@ -112,13 +118,16 @@ main ()
   pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
   // Create the segmentation object
   pcl::SACSegmentation<pcl::PointXYZ> seg;
+  pcl::SampleConsensusModelParallelPlane<pcl::PointXYZ> model (cloud_filtered);
   // Optional
   seg.setOptimizeCoefficients (true);
   // Mandatory
-  seg.setModelType (pcl::SACMODEL_PLANE);
+  seg.setModelType (pcl::SACMODEL_PARALLEL_PLANE);
   seg.setMethodType (pcl::SAC_RANSAC);
   seg.setMaxIterations (1000);
   seg.setDistanceThreshold (0.01);
+  model.setAxis(Eigen::Vector3f(1,0,0));
+  model.setEpsAngle(30*0.0174532925); //*0.0174532925 to radians
 
   // Create the filtering object
   pcl::ExtractIndices<pcl::PointXYZ> extract;
@@ -130,6 +139,7 @@ main ()
     // Segment the largest planar component from the remaining cloud
     seg.setInputCloud (cloud_filtered);
     seg.segment (*inliers, *coefficients);
+
     if (inliers->indices.size () == 0)
     {
       std::cerr << "Could not estimate a planar model for the given dataset." << std::endl;
@@ -155,5 +165,4 @@ main ()
   }
 
   return (0);
-  
-  
+}

From 0dc643ba1c53817b8ed92f537e3a752bfec0d532 Mon Sep 17 00:00:00 2001
From: Pepijn Hundepool <p.c.j.hundepool@student.tue.nl>
Date: Tue, 17 May 2022 09:52:24 +0200
Subject: [PATCH 026/136] Nieuwste versie

---
 ed_sensor_integration/src/kinect/code_v1.cpp | 68 +++++++++++++++++++-
 1 file changed, 66 insertions(+), 2 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/code_v1.cpp b/ed_sensor_integration/src/kinect/code_v1.cpp
index 42231bda..a5398a7b 100644
--- a/ed_sensor_integration/src/kinect/code_v1.cpp
+++ b/ed_sensor_integration/src/kinect/code_v1.cpp
@@ -14,8 +14,20 @@
 
 #include <pcl/filters/voxel_grid.h>
 #include <pcl/filters/extract_indices.h>
+#include <pcl/filters/conditional_removal.h>
+#include <pcl/filters/filter.h>
+
+#include <pcl/features/normal_3d.h>
 
 #include <ed/io/json_reader.h>
+#include <ed/serialization/serialization.h>
+
+#include <tue/config/read.h>
+#include <tue/config/reader.h>
+#include <tue/config/data_pointer.h>
+
+#include <fstream>
+#include <boost/filesystem/convenience.hpp>
 
 Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, float *zout) {
 
@@ -87,6 +99,56 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, flo
     return Transform;
 }
 
+float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out) {
+
+    //*out = *cloud; return(-1); //activate to bypass plane fitting and height estimation
+
+    std::vector<int> indices;
+    float threshold = 0.03;
+
+    std::cout << "starting ransac" << std::endl;
+    // Create SAC model
+    pcl::SampleConsensusModelParallelPlane<pcl::PointXYZRGB>::Ptr plane (new pcl::SampleConsensusModelParallelPlane<pcl::PointXYZRGB>(cloud));
+    plane->setAxis (Eigen::Vector3f(1,0,0));
+    plane->setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
+    std::cout << "created plane object" << std::endl;
+    // Create SAC method
+    pcl::SACSegmentation<pcl::PointXYZ> segplane;
+    //pcl::SampleConsensus<pcl::PointXYZRGB>::Ptr sac (new pcl::SampleConsensus<pcl::PointXYZRGB> (plane, threshold));
+    std::cout << "created ransac object" << std::endl;
+    segplane.setMaxIterations(10000);
+    segplane.setProbability(0.99);
+
+    // Fit model
+    //segplane.computeModel();
+
+    // Get inliers
+    std::vector<int> inliers;
+    //segplane.getInliers(inliers);
+
+    // Get the model coefficients
+    Eigen::VectorXf coeff;
+    //segplane.getModelCoefficients (coeff);
+    std::cout << "ransac complete" << std::endl;
+
+    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+    range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
+    //range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, (coeff[3]+0.01))));
+    *out = *cloud;
+    //filter out everything below plane
+    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+    condrem.setCondition (range_cond);
+    condrem.setInputCloud (out);
+    condrem.setKeepOrganized(true);
+
+    condrem.filter (*out);
+    (*out).is_dense = false;
+    pcl::removeNaNFromPointCloud(*out, *out, indices);
+
+    return(coeff[3]);
+
+}
+
 int
 main ()
 {
@@ -126,8 +188,8 @@ main ()
   seg.setMethodType (pcl::SAC_RANSAC);
   seg.setMaxIterations (1000);
   seg.setDistanceThreshold (0.01);
-  model.setAxis(Eigen::Vector3f(1,0,0));
-  model.setEpsAngle(30*0.0174532925); //*0.0174532925 to radians
+  model.setAxis (Eigen::Vector3f(1,0,0));
+  model.setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
 
   // Create the filtering object
   pcl::ExtractIndices<pcl::PointXYZ> extract;
@@ -165,4 +227,6 @@ main ()
   }
 
   return (0);
+
+
 }

From 618831cd9a25562582e4174524bf2df9443c36d2 Mon Sep 17 00:00:00 2001
From: Pepijn Hundepool <p.c.j.hundepool@student.tue.nl>
Date: Mon, 23 May 2022 18:03:45 +0200
Subject: [PATCH 027/136] Filter update

---
 ed_sensor_integration/src/kinect/code_v1.cpp | 132 ++++++++++++++++---
 1 file changed, 113 insertions(+), 19 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/code_v1.cpp b/ed_sensor_integration/src/kinect/code_v1.cpp
index a5398a7b..ac243602 100644
--- a/ed_sensor_integration/src/kinect/code_v1.cpp
+++ b/ed_sensor_integration/src/kinect/code_v1.cpp
@@ -9,18 +9,24 @@
 #include <pcl/sample_consensus/method_types.h>
 #include <pcl/sample_consensus/model_types.h>
 #include <pcl/sample_consensus/sac_model_parallel_plane.h>
+#include <pcl/sample_consensus/ransac.h>
 
 #include <pcl/segmentation/sac_segmentation.h>
+#include <pcl/segmentation/extract_clusters.h>
+
+#include <pcl/registration/transforms.h>
 
 #include <pcl/filters/voxel_grid.h>
 #include <pcl/filters/extract_indices.h>
 #include <pcl/filters/conditional_removal.h>
 #include <pcl/filters/filter.h>
+#include <pcl/filters/statistical_outlier_removal.h>
 
 #include <pcl/features/normal_3d.h>
 
 #include <ed/io/json_reader.h>
 #include <ed/serialization/serialization.h>
+//#include "ed_sensor_integration/sac_model_circle.h"
 
 #include <tue/config/read.h>
 #include <tue/config/reader.h>
@@ -31,7 +37,8 @@
 
 Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, float *zout) {
 
-    std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();
+    std::string json_filename = "2022-04-22-12-04-46.json";
+    //std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();
     // read json metadata
     tue::config::DataPointer meta_data;
 
@@ -99,7 +106,7 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, flo
     return Transform;
 }
 
-float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out) {
+float FilterPlane (pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, pcl::PointCloud<pcl::PointXYZ>::Ptr out) {
 
     //*out = *cloud; return(-1); //activate to bypass plane fitting and height estimation
 
@@ -108,35 +115,35 @@ float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud
 
     std::cout << "starting ransac" << std::endl;
     // Create SAC model
-    pcl::SampleConsensusModelParallelPlane<pcl::PointXYZRGB>::Ptr plane (new pcl::SampleConsensusModelParallelPlane<pcl::PointXYZRGB>(cloud));
+    pcl::SampleConsensusModelParallelPlane<pcl::PointXYZ>::Ptr plane (new pcl::SampleConsensusModelParallelPlane<pcl::PointXYZ>(cloud));
     plane->setAxis (Eigen::Vector3f(1,0,0));
     plane->setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
     std::cout << "created plane object" << std::endl;
     // Create SAC method
-    pcl::SACSegmentation<pcl::PointXYZ> segplane;
-    //pcl::SampleConsensus<pcl::PointXYZRGB>::Ptr sac (new pcl::SampleConsensus<pcl::PointXYZRGB> (plane, threshold));
+    //pcl::SACSegmentation<pcl::PointXYZ> segplane;
+    pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr segplane (new pcl::RandomSampleConsensus<pcl::PointXYZ> (plane, threshold));
     std::cout << "created ransac object" << std::endl;
-    segplane.setMaxIterations(10000);
-    segplane.setProbability(0.99);
+    segplane->setMaxIterations(10000);
+    segplane->setProbability(0.99);
 
     // Fit model
-    //segplane.computeModel();
+    segplane->computeModel();
 
     // Get inliers
     std::vector<int> inliers;
-    //segplane.getInliers(inliers);
+    segplane->getInliers(inliers);
 
     // Get the model coefficients
     Eigen::VectorXf coeff;
-    //segplane.getModelCoefficients (coeff);
+    segplane->getModelCoefficients (coeff);
     std::cout << "ransac complete" << std::endl;
 
-    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-    range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
+    pcl::ConditionAnd<pcl::PointXYZ>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZ> ());
+    range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZ>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZ> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
     //range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, (coeff[3]+0.01))));
     *out = *cloud;
     //filter out everything below plane
-    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+    pcl::ConditionalRemoval<pcl::PointXYZ> condrem;
     condrem.setCondition (range_cond);
     condrem.setInputCloud (out);
     condrem.setKeepOrganized(true);
@@ -150,18 +157,22 @@ float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud
 }
 
 int
-main ()
+main (int argc, char **argv)
 {
+  std::vector <pcl::PointCloud<pcl::PointXYZ>::Ptr, Eigen::aligned_allocator <pcl::PointCloud <pcl::PointXYZ>::Ptr > > inputs;
+//  float x, y, z;//used to store camera position
+//      pcl::transformPointCloud (*inputs[0], *inputs[0], ReadJson(argv[1], &x, &y, &z));
+
   pcl::PCLPointCloud2::Ptr cloud_blob (new pcl::PCLPointCloud2), cloud_filtered_blob (new pcl::PCLPointCloud2);
   pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>), cloud_p (new pcl::PointCloud<pcl::PointXYZ>), cloud_f (new pcl::PointCloud<pcl::PointXYZ>);
 
   // Fill in the cloud data
   pcl::PCDReader reader;
-  reader.read ("2022-04-05-13-28-28.pcd", *cloud_blob);
+  reader.read ("2022-04-22-12-04-46.pcd", *cloud_blob); //
 
   std::cerr << "PointCloud before filtering: " << cloud_blob->width * cloud_blob->height << " data points." << std::endl;
 
-  // Create the filtering object: downsample the dataset using a leaf size of 1cm
+  // Create the filtering object: downsample the dataset using a leaf size of 0.25cm
   pcl::VoxelGrid<pcl::PCLPointCloud2> sor;
   sor.setInputCloud (cloud_blob);
   sor.setLeafSize (0.0025f, 0.0025f, 0.0025f);
@@ -188,8 +199,8 @@ main ()
   seg.setMethodType (pcl::SAC_RANSAC);
   seg.setMaxIterations (1000);
   seg.setDistanceThreshold (0.01);
-  model.setAxis (Eigen::Vector3f(1,0,0));
-  model.setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
+  seg.setAxis (Eigen::Vector3f(1,0,0));
+  seg.setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
 
   // Create the filtering object
   pcl::ExtractIndices<pcl::PointXYZ> extract;
@@ -226,7 +237,90 @@ main ()
     i++;
   }
 
-  return (0);
+  // Creating the KdTree object for the search method of the extraction
+  pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
+  tree->setInputCloud (cloud_p);
+
+  std::vector<pcl::PointIndices> cluster_indices;
+  pcl::EuclideanClusterExtraction<pcl::PointXYZ> ec;
+  ec.setClusterTolerance (0.02); // 2cm
+  ec.setMinClusterSize (100);
+  ec.setMaxClusterSize (100000);
+  ec.setSearchMethod (tree);
+  ec.setInputCloud (cloud_p);
+  ec.extract (cluster_indices);
+
+  int j = 0;
+  for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it != cluster_indices.end (); ++it)
+  {
+      pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZ>);
+      for (const auto& idx : it->indices)
+      cloud_cluster->push_back ((*cloud_filtered)[idx]); //*
+      cloud_cluster->width = cloud_cluster->size ();
+      cloud_cluster->height = 1;
+      cloud_cluster->is_dense = true;
+
+      std::cout << "PointCloud representing the Cluster: " << cloud_cluster->size () << " data points." << std::endl;
+      std::stringstream ss;
+      ss << "cloud_cluster_" << j << ".pcd";
+      writer.write<pcl::PointXYZ> (ss.str (), *cloud_cluster, false); //*
+      j++;
+  }
+
+  //Removing outliers using a StatisticalOutlierRemoval filter
+  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud2 (new pcl::PointCloud<pcl::PointXYZ>);
+  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered2 (new pcl::PointCloud<pcl::PointXYZ>);
+
+  // Fill in the cloud data
+  pcl::PCDReader reader2;
+  // Replace the path below with the path where you saved your file
+  reader.read<pcl::PointXYZ> ("table_scene_lms400_plane_1.pcd", *cloud2);
+
+  std::cerr << "Cloud before filtering: " << std::endl;
+  std::cerr << *cloud2 << std::endl;
+
+  // Create the filtering object
+  pcl::StatisticalOutlierRemoval<pcl::PointXYZ> sor2;
+  sor2.setInputCloud (cloud2);
+  sor2.setMeanK (50);
+  sor2.setStddevMulThresh (1.0);
+  sor2.filter (*cloud_filtered2);
+
+  std::cerr << "Cloud after filtering: " << std::endl;
+  std::cerr << *cloud_filtered2 << std::endl;
 
+  pcl::PCDWriter writer2;
+  writer2.write<pcl::PointXYZ> ("table_scene_lms400_inliers.pcd", *cloud_filtered2, false);
+
+  sor2.setNegative (true);
+  sor2.filter (*cloud_filtered2);
+  writer2.write<pcl::PointXYZ> ("table_scene_lms400_outliers.pcd", *cloud_filtered2, false);
+
+  FilterPlane;
+
+//  pcl::SampleConsensusModelCircle<pcl::PointXYZ>::Ptr circle (new pcl::SampleConsensusModelCircle<pcl::PointXYZ>(cloud_ptr));
+
+//  // Create SAC method
+//  pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr saccirc (new pcl::RandomSampleConsensus<pcl::PointXYZ> (circle, threshold));
+//  saccirc->setMaxIterations(10000);
+//  saccirc->setProbability(1);
+
+//  // Fit model
+//  saccirc->computeModel();
+
+//  // Get inliers
+//  std::vector<int> inliers3;
+//  saccirc->getInliers(inliers3);
+
+//  // Get the model coefficients
+//  Eigen::VectorXf coeff3;
+//  saccirc->getModelCoefficients (coeff3);
+
+//  float min_inliers = 0.0;
+//  Eigen::VectorXf output;
+
+//  std::cout << "Circle model, " << static_cast<float>(inliers3.size())/static_cast<float>(cloud_p.size()) << std::endl;
+
+  return (0);
 
 }

From 52ef4df3312e939ce987314098b22e92a692ea94 Mon Sep 17 00:00:00 2001
From: Pepijn Hundepool <p.c.j.hundepool@student.tue.nl>
Date: Fri, 10 Jun 2022 13:04:48 +0200
Subject: [PATCH 028/136] Code before costmap

---
 ed_sensor_integration/CMakeLists.txt         |   1 +
 ed_sensor_integration/src/kinect/code_v1.cpp | 472 +++++++++++++++----
 2 files changed, 389 insertions(+), 84 deletions(-)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index d6e8bf22..511958d8 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -11,6 +11,7 @@ find_package(catkin REQUIRED COMPONENTS
  # rospy
  # roscpp
  # std_msgs
+  costmap_2d
   ed
   ed_sensor_integration_msgs
   geolib2
diff --git a/ed_sensor_integration/src/kinect/code_v1.cpp b/ed_sensor_integration/src/kinect/code_v1.cpp
index ac243602..11da239f 100644
--- a/ed_sensor_integration/src/kinect/code_v1.cpp
+++ b/ed_sensor_integration/src/kinect/code_v1.cpp
@@ -32,12 +32,70 @@
 #include <tue/config/reader.h>
 #include <tue/config/data_pointer.h>
 
+#include <tf/transform_listener.h>
+#include <costmap_2d/costmap_2d_ros.h>
+//#include <costmap_2d/plugins/obstale_layer.cpp>
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/highgui.hpp"
+#include "opencv2/imgproc.hpp"
+
+#include <pcl/range_image/range_image.h>
+#include <pcl/visualization/range_image_visualizer.h>
+#include <pcl/visualization/pcl_visualizer.h>
+#include <pcl/features/range_image_border_extractor.h>
+#include <pcl/keypoints/narf_keypoint.h>
+#include <pcl/features/narf_descriptor.h>
+#include <pcl/console/parse.h>
+#include <pcl/common/file_io.h> // for getFilenameWithoutExtension
+
 #include <fstream>
 #include <boost/filesystem/convenience.hpp>
 
+//typedef pcl::PointXYZ PointType;
+
+//// --------------------
+//// -----Parameters-----
+//// --------------------
+//float angular_resolution = 0.5f;
+//float support_size = 0.2f;
+//pcl::RangeImage::CoordinateFrame coordinate_frame = pcl::RangeImage::CAMERA_FRAME;
+//bool setUnseenToMaxRange = false;
+//bool rotation_invariant = true;
+
+//// --------------
+//// -----Help-----
+//// --------------
+//void
+//printUsage (const char* progName)
+//{
+//  std::cout << "\n\nUsage: "<<progName<<" [options] <scene.pcd>\n\n"
+//            << "Options:\n"
+//            << "-------------------------------------------\n"
+//            << "-r <float>   angular resolution in degrees (default "<<angular_resolution<<")\n"
+//            << "-c <int>     coordinate frame (default "<< (int)coordinate_frame<<")\n"
+//            << "-m           Treat all unseen points to max range\n"
+//            << "-s <float>   support size for the interest points (diameter of the used sphere - "
+//                                                                  "default "<<support_size<<")\n"
+//            << "-o <0/1>     switch rotational invariant version of the feature on/off"
+//            <<               " (default "<< (int)rotation_invariant<<")\n"
+//            << "-h           this help\n"
+//            << "\n\n";
+//}
+
+//void
+//setViewerPose (pcl::visualization::PCLVisualizer& viewer, const Eigen::Affine3f& viewer_pose)
+//{
+//  Eigen::Vector3f pos_vector = viewer_pose * Eigen::Vector3f (0, 0, 0);
+//  Eigen::Vector3f look_at_vector = viewer_pose.rotation () * Eigen::Vector3f (0, 0, 1) + pos_vector;
+//  Eigen::Vector3f up_vector = viewer_pose.rotation () * Eigen::Vector3f (0, -1, 0);
+//  viewer.setCameraPosition (pos_vector[0], pos_vector[1], pos_vector[2],
+//                            look_at_vector[0], look_at_vector[1], look_at_vector[2],
+//                            up_vector[0], up_vector[1], up_vector[2]);
+//}
+
 Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, float *zout) {
 
-    std::string json_filename = "2022-04-22-12-04-46.json";
+    std::string json_filename = "2022-04-22-11-44-48.json";
     //std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();
     // read json metadata
     tue::config::DataPointer meta_data;
@@ -106,55 +164,78 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, flo
     return Transform;
 }
 
-float FilterPlane (pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, pcl::PointCloud<pcl::PointXYZ>::Ptr out) {
-
-    //*out = *cloud; return(-1); //activate to bypass plane fitting and height estimation
-
-    std::vector<int> indices;
-    float threshold = 0.03;
-
-    std::cout << "starting ransac" << std::endl;
-    // Create SAC model
-    pcl::SampleConsensusModelParallelPlane<pcl::PointXYZ>::Ptr plane (new pcl::SampleConsensusModelParallelPlane<pcl::PointXYZ>(cloud));
-    plane->setAxis (Eigen::Vector3f(1,0,0));
-    plane->setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
-    std::cout << "created plane object" << std::endl;
-    // Create SAC method
-    //pcl::SACSegmentation<pcl::PointXYZ> segplane;
-    pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr segplane (new pcl::RandomSampleConsensus<pcl::PointXYZ> (plane, threshold));
-    std::cout << "created ransac object" << std::endl;
-    segplane->setMaxIterations(10000);
-    segplane->setProbability(0.99);
-
-    // Fit model
-    segplane->computeModel();
-
-    // Get inliers
-    std::vector<int> inliers;
-    segplane->getInliers(inliers);
-
-    // Get the model coefficients
-    Eigen::VectorXf coeff;
-    segplane->getModelCoefficients (coeff);
-    std::cout << "ransac complete" << std::endl;
-
-    pcl::ConditionAnd<pcl::PointXYZ>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZ> ());
-    range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZ>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZ> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
-    //range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, (coeff[3]+0.01))));
-    *out = *cloud;
-    //filter out everything below plane
-    pcl::ConditionalRemoval<pcl::PointXYZ> condrem;
-    condrem.setCondition (range_cond);
-    condrem.setInputCloud (out);
-    condrem.setKeepOrganized(true);
-
-    condrem.filter (*out);
-    (*out).is_dense = false;
-    pcl::removeNaNFromPointCloud(*out, *out, indices);
-
-    return(coeff[3]);
-
-}
+//float FilterPlane (pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, pcl::PointCloud<pcl::PointXYZ>::Ptr out) {
+
+//    //*out = *cloud; return(-1); //activate to bypass plane fitting and height estimation
+
+//    std::vector<int> indices;
+//    float threshold = 0.03;
+
+//    std::cout << "starting ransac" << std::endl;
+//    // Create SAC model
+//    pcl::SampleConsensusModelParallelPlane<pcl::PointXYZ>::Ptr plane (new pcl::SampleConsensusModelParallelPlane<pcl::PointXYZ>(cloud));
+//    plane->setAxis (Eigen::Vector3f(1,0,0));
+//    plane->setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
+//    std::cout << "created plane object" << std::endl;
+//    // Create SAC method
+//    //pcl::SACSegmentation<pcl::PointXYZ> segplane;
+//    pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr segplane (new pcl::RandomSampleConsensus<pcl::PointXYZ> (plane, threshold));
+//    std::cout << "created ransac object" << std::endl;
+//    segplane->setMaxIterations(10000);
+//    segplane->setProbability(0.99);
+
+//    // Fit model
+//    segplane->computeModel();
+
+//    // Get inliers
+//    std::vector<int> inliers;
+//    segplane->getInliers(inliers);
+
+//    // Get the model coefficients
+//    Eigen::VectorXf coeff;
+//    segplane->getModelCoefficients (coeff);
+//    std::cout << "ransac complete" << std::endl;
+
+//    pcl::ConditionAnd<pcl::PointXYZ>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZ> ());
+//    range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZ>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZ> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
+//    //range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, (coeff[3]+0.01))));
+//    *out = *cloud;
+//    //filter out everything below plane
+//    pcl::ConditionalRemoval<pcl::PointXYZ> condrem;
+//    condrem.setCondition (range_cond);
+//    condrem.setInputCloud (out);
+//    condrem.setKeepOrganized(true);
+
+//    condrem.filter (*out);
+//    (*out).is_dense = false;
+//    pcl::removeNaNFromPointCloud(*out, *out, indices);
+
+//    return(coeff[3]);
+
+//}
+
+//using namespace cv;
+//using namespace std;
+//int thresh = 100;
+//RNG rng(12345);
+//void thresh_callback(int, void* );
+
+//Mat src, src_gray;
+//Mat dst, detected_edges;
+
+//int lowThreshold = 0;
+//const int max_lowThreshold = 100;
+//const int ratio = 3;
+//const int kernel_size = 3;
+//const char* window_name = "Edge Map";
+//static void CannyThreshold(int, void*)
+//{
+//    blur( src_gray, detected_edges, Size(3,3) );
+//    Canny( detected_edges, detected_edges, lowThreshold, lowThreshold*ratio, kernel_size );
+//    dst = Scalar::all(0);
+//    src.copyTo( dst, detected_edges);
+//    imshow( window_name, dst );
+//}
 
 int
 main (int argc, char **argv)
@@ -168,7 +249,7 @@ main (int argc, char **argv)
 
   // Fill in the cloud data
   pcl::PCDReader reader;
-  reader.read ("2022-04-22-12-04-46.pcd", *cloud_blob); //
+  reader.read ("2022-04-22-11-44-48.pcd", *cloud_blob); //
 
   std::cerr << "PointCloud before filtering: " << cloud_blob->width * cloud_blob->height << " data points." << std::endl;
 
@@ -237,35 +318,35 @@ main (int argc, char **argv)
     i++;
   }
 
-  // Creating the KdTree object for the search method of the extraction
-  pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
-  tree->setInputCloud (cloud_p);
-
-  std::vector<pcl::PointIndices> cluster_indices;
-  pcl::EuclideanClusterExtraction<pcl::PointXYZ> ec;
-  ec.setClusterTolerance (0.02); // 2cm
-  ec.setMinClusterSize (100);
-  ec.setMaxClusterSize (100000);
-  ec.setSearchMethod (tree);
-  ec.setInputCloud (cloud_p);
-  ec.extract (cluster_indices);
-
-  int j = 0;
-  for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it != cluster_indices.end (); ++it)
-  {
-      pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZ>);
-      for (const auto& idx : it->indices)
-      cloud_cluster->push_back ((*cloud_filtered)[idx]); //*
-      cloud_cluster->width = cloud_cluster->size ();
-      cloud_cluster->height = 1;
-      cloud_cluster->is_dense = true;
-
-      std::cout << "PointCloud representing the Cluster: " << cloud_cluster->size () << " data points." << std::endl;
-      std::stringstream ss;
-      ss << "cloud_cluster_" << j << ".pcd";
-      writer.write<pcl::PointXYZ> (ss.str (), *cloud_cluster, false); //*
-      j++;
-  }
+//  // Creating the KdTree object for the search method of the extraction
+//  pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
+//  tree->setInputCloud (cloud_p);
+
+//  std::vector<pcl::PointIndices> cluster_indices;
+//  pcl::EuclideanClusterExtraction<pcl::PointXYZ> ec;
+//  ec.setClusterTolerance (0.02); // 2cm
+//  ec.setMinClusterSize (100);
+//  ec.setMaxClusterSize (100000);
+//  ec.setSearchMethod (tree);
+//  ec.setInputCloud (cloud_p);
+//  ec.extract (cluster_indices);
+
+//  int j = 0;
+//  for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it != cluster_indices.end (); ++it)
+//  {
+//      pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZ>);
+//      for (const auto& idx : it->indices)
+//      cloud_cluster->push_back ((*cloud_filtered)[idx]); //*
+//      cloud_cluster->width = cloud_cluster->size ();
+//      cloud_cluster->height = 1;
+//      cloud_cluster->is_dense = true;
+
+//      std::cout << "PointCloud representing the Cluster: " << cloud_cluster->size () << " data points." << std::endl;
+//      std::stringstream ss;
+//      ss << "cloud_cluster_" << j << ".pcd";
+//      writer.write<pcl::PointXYZ> (ss.str (), *cloud_cluster, false); //*
+//      j++;
+//  }
 
   //Removing outliers using a StatisticalOutlierRemoval filter
   pcl::PointCloud<pcl::PointXYZ>::Ptr cloud2 (new pcl::PointCloud<pcl::PointXYZ>);
@@ -282,8 +363,8 @@ main (int argc, char **argv)
   // Create the filtering object
   pcl::StatisticalOutlierRemoval<pcl::PointXYZ> sor2;
   sor2.setInputCloud (cloud2);
-  sor2.setMeanK (50);
-  sor2.setStddevMulThresh (1.0);
+  sor2.setMeanK (1);
+  sor2.setStddevMulThresh (0.001);
   sor2.filter (*cloud_filtered2);
 
   std::cerr << "Cloud after filtering: " << std::endl;
@@ -296,7 +377,72 @@ main (int argc, char **argv)
   sor2.filter (*cloud_filtered2);
   writer2.write<pcl::PointXYZ> ("table_scene_lms400_outliers.pcd", *cloud_filtered2, false);
 
-  FilterPlane;
+  //FilterPlane;
+
+  //Line detectors
+
+//  CommandLineParser parser( argc, argv, "{@input | cluster.png | input image}" );
+//  Mat src = imread( samples::findFile( parser.get<String>( "@input" ) ) );
+//  if( src.empty() )
+//  {
+//      cout << "Could not open or find the image!\n" << endl;
+//      cout << "usage: " << argv[0] << " <Input image>" << endl;
+//      return -1;
+//  }
+//  cvtColor( src, src_gray, COLOR_BGR2GRAY );
+//  blur( src_gray, src_gray, Size(3,3) );
+//  const char* source_window = "Source";
+//  namedWindow( source_window );
+//  imshow( source_window, src );
+//  const int max_thresh = 255;
+//  createTrackbar( "Canny thresh:", source_window, &thresh, max_thresh, thresh_callback );
+//  thresh_callback( 0, 0 );
+//  waitKey();
+//  return 0;
+//}
+
+//void thresh_callback(int, void* )
+//{
+//  Mat canny_output;
+//  Canny( src_gray, canny_output, thresh, thresh*2 );
+//  vector<vector<Point> > contours;
+//  findContours( canny_output, contours, RETR_TREE, CHAIN_APPROX_SIMPLE );
+//  vector<vector<Point> > contours_poly( contours.size() );
+//  vector<Rect> boundRect( contours.size() );
+//  vector<Point2f>centers( contours.size() );
+//  vector<float>radius( contours.size() );
+//  for( size_t i = 0; i < contours.size(); i++ )
+//  {
+//      approxPolyDP( contours[i], contours_poly[i], 3, false );
+//      boundRect[i] = boundingRect( contours_poly[i] );
+//      minEnclosingCircle( contours_poly[i], centers[i], radius[i] );
+//  }
+//  Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 );
+//  for( size_t i = 0; i< contours.size(); i++ )
+//  {
+//      Scalar color = Scalar( rng.uniform(0, 256), rng.uniform(0,256), rng.uniform(0,256) );
+//      drawContours( drawing, contours_poly, (int)i, color );
+//      //rectangle( drawing, boundRect[i].tl(), boundRect[i].br(), color, 2 );
+//      //circle( drawing, centers[i], (int)radius[i], color, 2 );
+//  }
+//  imshow( "Contours", drawing );
+//}
+
+  //Line detector
+//  CommandLineParser parser( argc, argv, "{@input | cluster.png | input image}" );
+//  src = imread( samples::findFile( parser.get<String>( "@input" ) ), IMREAD_COLOR ); // Load an image
+//  if( src.empty() )
+//  {
+//    std::cout << "Could not open or find the image!\n" << std::endl;
+//    std::cout << "Usage: " << argv[0] << " <Input image>" << std::endl;
+//    return -1;
+//  }
+//  dst.create( src.size(), src.type() );
+//  cvtColor( src, src_gray, COLOR_BGR2GRAY );
+//  namedWindow( window_name, WINDOW_AUTOSIZE );
+//  createTrackbar( "Min Threshold:", window_name, &lowThreshold, max_lowThreshold, CannyThreshold );
+//  CannyThreshold(0, 0);
+//  waitKey(0);
 
 //  pcl::SampleConsensusModelCircle<pcl::PointXYZ>::Ptr circle (new pcl::SampleConsensusModelCircle<pcl::PointXYZ>(cloud_ptr));
 
@@ -321,6 +467,164 @@ main (int argc, char **argv)
 
 //  std::cout << "Circle model, " << static_cast<float>(inliers3.size())/static_cast<float>(cloud_p.size()) << std::endl;
 
-  return (0);
+//Costmap
+
+//  if (pcl::console::find_argument (argc, argv, "-h") >= 0)
+//  {
+//    printUsage (argv[0]);
+//    return 0;
+//  }
+//  if (pcl::console::find_argument (argc, argv, "-m") >= 0)
+//  {
+//    setUnseenToMaxRange = true;
+//    std::cout << "Setting unseen values in range image to maximum range readings.\n";
+//  }
+//  if (pcl::console::parse (argc, argv, "-o", rotation_invariant) >= 0)
+//    std::cout << "Switching rotation invariant feature version "<< (rotation_invariant ? "on" : "off")<<".\n";
+//  int tmp_coordinate_frame;
+//  if (pcl::console::parse (argc, argv, "-c", tmp_coordinate_frame) >= 0)
+//  {
+//    coordinate_frame = pcl::RangeImage::CoordinateFrame (tmp_coordinate_frame);
+//    std::cout << "Using coordinate frame "<< (int)coordinate_frame<<".\n";
+//  }
+//  if (pcl::console::parse (argc, argv, "-s", support_size) >= 0)
+//    std::cout << "Setting support size to "<<support_size<<".\n";
+//  if (pcl::console::parse (argc, argv, "-r", angular_resolution) >= 0)
+//    std::cout << "Setting angular resolution to "<<angular_resolution<<"deg.\n";
+//  angular_resolution = pcl::deg2rad (angular_resolution);
+
+//  // ------------------------------------------------------------------
+//  // -----Read pcd file or create example point cloud if not given-----
+//  // ------------------------------------------------------------------
+//  pcl::PointCloud<PointType>::Ptr point_cloud_ptr (new pcl::PointCloud<PointType>);
+//  pcl::PointCloud<PointType>& point_cloud = *point_cloud_ptr;
+//  pcl::PointCloud<pcl::PointWithViewpoint> far_ranges;
+//  Eigen::Affine3f scene_sensor_pose (Eigen::Affine3f::Identity ());
+//  std::vector<int> pcd_filename_indices = pcl::console::parse_file_extension_argument (argc, argv, "pcd");
+//  if (!pcd_filename_indices.empty ())
+//  {
+//    std::string filename = argv[pcd_filename_indices[0]];
+//    if (pcl::io::loadPCDFile (filename, point_cloud) == -1)
+//    {
+//      std::cerr << "Was not able to open file \""<<filename<<"\".\n";
+//      printUsage (argv[0]);
+//      return 0;
+//    }
+//    scene_sensor_pose = Eigen::Affine3f (Eigen::Translation3f (point_cloud.sensor_origin_[0],
+//                                                               point_cloud.sensor_origin_[1],
+//                                                               point_cloud.sensor_origin_[2])) *
+//                        Eigen::Affine3f (point_cloud.sensor_orientation_);
+//    std::string far_ranges_filename = pcl::getFilenameWithoutExtension (filename)+"_far_ranges.pcd";
+//    if (pcl::io::loadPCDFile (far_ranges_filename.c_str (), far_ranges) == -1)
+//      std::cout << "Far ranges file \""<<far_ranges_filename<<"\" does not exists.\n";
+//  }
+//  else
+//  {
+//    setUnseenToMaxRange = true;
+//    std::cout << "\nNo *.pcd file given => Generating example point cloud.\n\n";
+//    for (float x=-0.5f; x<=0.5f; x+=0.01f)
+//    {
+//      for (float y=-0.5f; y<=0.5f; y+=0.01f)
+//      {
+//        PointType point;  point.x = x;  point.y = y;  point.z = 2.0f - y;
+//        point_cloud.push_back (point);
+//      }
+//    }
+//    point_cloud.width = point_cloud.size ();  point_cloud.height = 1;
+//  }
+
+//  // -----------------------------------------------
+//  // -----Create RangeImage from the PointCloud-----
+//  // -----------------------------------------------
+//  float noise_level = 0.0;
+//  float min_range = 0.0f;
+//  int border_size = 1;
+//  pcl::RangeImage::Ptr range_image_ptr (new pcl::RangeImage);
+//  pcl::RangeImage& range_image = *range_image_ptr;
+//  range_image.createFromPointCloud (point_cloud, angular_resolution, pcl::deg2rad (360.0f), pcl::deg2rad (180.0f),
+//                                   scene_sensor_pose, coordinate_frame, noise_level, min_range, border_size);
+//  range_image.integrateFarRanges (far_ranges);
+//  if (setUnseenToMaxRange)
+//    range_image.setUnseenToMaxRange ();
+
+//  // --------------------------------------------
+//  // -----Open 3D viewer and add point cloud-----
+//  // --------------------------------------------
+//  pcl::visualization::PCLVisualizer viewer ("3D Viewer");
+//  viewer.setBackgroundColor (1, 1, 1);
+//  pcl::visualization::PointCloudColorHandlerCustom<pcl::PointWithRange> range_image_color_handler (range_image_ptr, 0, 0, 0);
+//  viewer.addPointCloud (range_image_ptr, range_image_color_handler, "range image");
+//  viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 1, "range image");
+//  //viewer.addCoordinateSystem (1.0f, "global");
+//  //PointCloudColorHandlerCustom<PointType> point_cloud_color_handler (point_cloud_ptr, 150, 150, 150);
+//  //viewer.addPointCloud (point_cloud_ptr, point_cloud_color_handler, "original point cloud");
+//  viewer.initCameraParameters ();
+//  setViewerPose (viewer, range_image.getTransformationToWorldSystem ());
+
+//  // --------------------------
+//  // -----Show range image-----
+//  // --------------------------
+//  pcl::visualization::RangeImageVisualizer range_image_widget ("Range image");
+//  range_image_widget.showRangeImage (range_image);
+
+//  // --------------------------------
+//  // -----Extract NARF keypoints-----
+//  // --------------------------------
+//  pcl::RangeImageBorderExtractor range_image_border_extractor;
+//  pcl::NarfKeypoint narf_keypoint_detector;
+//  narf_keypoint_detector.setRangeImageBorderExtractor (&range_image_border_extractor);
+//  narf_keypoint_detector.setRangeImage (&range_image);
+//  narf_keypoint_detector.getParameters ().support_size = support_size;
+
+//  pcl::PointCloud<int> keypoint_indices;
+//  narf_keypoint_detector.compute (keypoint_indices);
+//  std::cout << "Found "<<keypoint_indices.size ()<<" key points.\n";
+
+//  // ----------------------------------------------
+//  // -----Show keypoints in range image widget-----
+//  // ----------------------------------------------
+// //for (std::size_t i=0; i<keypoint_indices.size (); ++i)
+//    //range_image_widget.markPoint (keypoint_indices[i]%range_image.width,
+//                                  //keypoint_indices[i]/range_image.width);
+
+//  // -------------------------------------
+//  // -----Show keypoints in 3D viewer-----
+//  // -------------------------------------
+//  pcl::PointCloud<pcl::PointXYZ>::Ptr keypoints_ptr (new pcl::PointCloud<pcl::PointXYZ>);
+//  pcl::PointCloud<pcl::PointXYZ>& keypoints = *keypoints_ptr;
+//  keypoints.resize (keypoint_indices.size ());
+//  for (std::size_t i=0; i<keypoint_indices.size (); ++i)
+//    keypoints[i].getVector3fMap () = range_image[keypoint_indices[i]].getVector3fMap ();
+//  pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> keypoints_color_handler (keypoints_ptr, 0, 255, 0);
+//  viewer.addPointCloud<pcl::PointXYZ> (keypoints_ptr, keypoints_color_handler, "keypoints");
+//  viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 7, "keypoints");
+
+//  // ------------------------------------------------------
+//  // -----Extract NARF descriptors for interest points-----
+//  // ------------------------------------------------------
+//  std::vector<int> keypoint_indices2;
+//  keypoint_indices2.resize (keypoint_indices.size ());
+//  for (unsigned int i=0; i<keypoint_indices.size (); ++i) // This step is necessary to get the right vector type
+//    keypoint_indices2[i]=keypoint_indices[i];
+//  pcl::NarfDescriptor narf_descriptor (&range_image, &keypoint_indices2);
+//  narf_descriptor.getParameters ().support_size = support_size;
+//  narf_descriptor.getParameters ().rotation_invariant = rotation_invariant;
+//  pcl::PointCloud<pcl::Narf36> narf_descriptors;
+//  narf_descriptor.compute (narf_descriptors);
+//  std::cout << "Extracted "<<narf_descriptors.size ()<<" descriptors for "
+//                      <<keypoint_indices.size ()<< " keypoints.\n";
+
+//  //--------------------
+//  // -----Main loop-----
+//  //--------------------
+//  while (!viewer.wasStopped ())
+//  {
+//    range_image_widget.spinOnce ();  // process GUI events
+//    viewer.spinOnce ();
+//    pcl_sleep(0.01);
+//  }
+//}
+
+  return 0;
 
 }

From e08696f67561808db641f7cb9bf033a51e13eec7 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Fri, 10 Jun 2022 14:52:14 +0200
Subject: [PATCH 029/136] added empty_spot_designator files

---
 ed_sensor_integration/CMakeLists.txt          |  3 +
 .../src/kinect/empty_spot_designator.cpp      | 86 +++++++++++++++++++
 2 files changed, 89 insertions(+)
 create mode 100644 ed_sensor_integration/src/kinect/empty_spot_designator.cpp

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index 511958d8..e3f423f3 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -130,6 +130,9 @@ target_link_libraries(ed_fitter ed_kinect)
 add_executable(ed_table_modeler src/kinect/code_v1.cpp)
 target_link_libraries(ed_table_modeler ${catkin_LIBRARIES})
 
+add_executable(ed_empty_spot_designator src/kinect/empty_spot_designator.cpp)
+target_link_libraries(ed_empty_spot_designator ${catkin_LIBRARIES})
+
 # ------------------------------------------------------------------------------------------------
 #                                           TESTS
 # ------------------------------------------------------------------------------------------------
diff --git a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
new file mode 100644
index 00000000..061ea346
--- /dev/null
+++ b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
@@ -0,0 +1,86 @@
+#include <iostream>
+#include <string>
+
+#include "opencv2/imgproc.hpp"
+#include <opencv2/highgui.hpp>
+
+//pcl library
+#include <pcl/io/pcd_io.h>
+
+
+double resolution = 0.005;
+cv::Point2d canvas_center;
+
+void readPCD(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, std::string filename)
+{
+    // Fill in the cloud data
+    pcl::PCDReader reader;
+    reader.read (filename, *cloud); //
+}
+
+cv::Point2d worldToCanvas(double x, double y)
+{
+    return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
+}
+
+void createCostmap(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, cv::Mat& canvas, cv::Scalar color)
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < cloud->points.size (); nIndex++)
+    {
+        double x = cloud->points[nIndex].z;
+        double y = -cloud->points[nIndex].x;
+        //double z = -cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+}
+
+
+void usage()
+{
+    std::cout << "USAGE: empty_spot_designator [pointcloud.pcd] [table_pointcloud.pcd]" << std::endl;
+}
+
+int main (int argc, char **argv)
+{
+    if (argc != 3)
+    {
+        usage();
+        return 0;
+    }
+
+    std::cout << "finding empty spot" << std::endl;
+
+    std::cout << "Loading pcd file" << std::endl;
+
+    std::string filename = argv[2];
+    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
+    readPCD(cloud, filename);
+
+    // read occupied data
+    std::string occupied_filename = argv[1];
+    pcl::PointCloud<pcl::PointXYZ>::Ptr occupied_cloud (new pcl::PointCloud<pcl::PointXYZ>);
+    readPCD(occupied_cloud, occupied_filename);
+
+    std::cout << "PointCloud representing the planar component: " << cloud->width * cloud->height << " data points." << std::endl;
+
+
+    std::cout << "creating costmap" << std::endl;
+    cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
+    cv::Scalar table_color(0, 255, 0);
+    cv::Scalar occupied_color(0, 0, 255);
+
+    createCostmap(occupied_cloud, canvas, occupied_color);
+    //createCostmap(cloud, canvas, table_color);
+
+    std::cout << "showing costmap" << std::endl;
+    cv::imshow("Laser Vizualization", canvas);
+    cv::waitKey();
+
+
+    return 0;
+}

From 6792251c0ed66b3107478f34f48dce756103dddb Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Fri, 10 Jun 2022 15:04:46 +0200
Subject: [PATCH 030/136] add dilation

---
 .../src/kinect/empty_spot_designator.cpp            | 13 +++++++++++--
 1 file changed, 11 insertions(+), 2 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
index 061ea346..4babf10b 100644
--- a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
+++ b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
@@ -39,6 +39,13 @@ void createCostmap(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, cv::Mat& canvas, c
     }
 }
 
+void dilateCostmap(cv::Mat& canvas)
+{
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_RECT,
+                                             cv::Size( 11, 11),
+                                             cv::Point(5, 5) );
+    cv::dilate(canvas, canvas, element );
+}
 
 void usage()
 {
@@ -74,8 +81,10 @@ int main (int argc, char **argv)
     cv::Scalar table_color(0, 255, 0);
     cv::Scalar occupied_color(0, 0, 255);
 
-    createCostmap(occupied_cloud, canvas, occupied_color);
-    //createCostmap(cloud, canvas, table_color);
+    //createCostmap(occupied_cloud, canvas, occupied_color);
+    createCostmap(cloud, canvas, table_color);
+
+    dilateCostmap(canvas);
 
     std::cout << "showing costmap" << std::endl;
     cv::imshow("Laser Vizualization", canvas);

From af5a212117742745e3124369f8a26046ad300bc1 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Mon, 15 Aug 2022 13:23:59 +0200
Subject: [PATCH 031/136] add docstrings for some functions

---
 ed_sensor_integration/tools/table_modeler.cpp | 24 +++++++++++++++++++
 1 file changed, 24 insertions(+)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 1bcb1d7d..aa8c2822 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -82,6 +82,12 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
     final_transform = targetToSource;
  }
 
+/**
+ * @brief FilterPlane fit a plane through a pointcloud, filter the points which lie in this plane and return the height of the plane #TODO separation of concerns.
+ * @param cloud: pointcloud to be filtered.
+ * @param out: pointcloud with all points that lie within the plane
+ * @return height (z coordinate) of the fitted plane.
+ */
 float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out) {
 	
 	//*out = *cloud; return(-1); //activate to bypass plane fitting and height estimation
@@ -129,6 +135,14 @@ float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud
 	
 }
 
+/**
+ * @brief Segment segment the pointcloud and return the cluster closest to the camera
+ * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
+ * @param x: coordinate of the camera
+ * @param y: coordinate of the camera
+ * @param z: coordinate of the camera
+ * @param [out] tableHeight[m]: estimated height of the table based on the cluster.
+ */
 void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z, std::vector<float> &tableHeight) {
 	
 	//return; //activate completely bypass segmentation and height estimation
@@ -194,6 +208,16 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
     *cloud = *cloud_out;
 }
 
+/**
+ * @brief ReadJson: Extract the pose of the camera corresponding to a pcd file.
+ *  Pose is expressed in map frame. (json filename is assumed to be the same as
+ *  the pcd file with a different extension.) #TODO strange interface
+ * @param pcd_filename: Filename of the pcd file
+ * @param xout: X Coordinate of the pose of the camera
+ * @param yout: Y Coordinate of the pose of the camera
+ * @param zout: Z Coordinate of the pose of the camera
+ * @return Eigen rotationmatrix
+ */
 Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, float *zout) {
 
     std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();

From 042bcacc7c1df70a89bd326843f15f93cac81668 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Mon, 15 Aug 2022 16:32:28 +0200
Subject: [PATCH 032/136] add remaining contracts

---
 ed_sensor_integration/tools/table_modeler.cpp | 19 +++++++++++++++++++
 1 file changed, 19 insertions(+)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index aa8c2822..5bb7b8bd 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -40,6 +40,12 @@
 #include "ed_sensor_integration/sac_model_circle.h"
 #include "ed_sensor_integration/sac_model_horizontal_plane.h"
 
+/**
+ * @brief pairAlign use iterative closest point to align two pointclouds with one another
+ * @param cloud_src: source cloud, will be transformed to be expressed in the same frame as the target cloud.
+ * @param cloud_tgt: target cloud to match to.
+ * @param final_transform: transform from target to source
+ */
 void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, Eigen::Matrix4f &final_transform)
 {
 	
@@ -296,6 +302,13 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, flo
     return Transform;
 }
 
+/**
+ * @brief Flatten: Remove z dimension from pointcloud.
+ * Also centers the pointcloud around x,y = (0,0)
+ * Also creates the convex hull of the flattened pointcloud. #TODO separation of concerns
+ * @param cloud: Input cloud
+ * @return Flattened point cloud.
+ */
 pcl::PointCloud<pcl::PointXYZ> Flatten(pcl::PointCloud<pcl::PointXYZRGB> cloud) {
     float totx = 0, toty = 0, avgx, avgy;
 
@@ -327,6 +340,12 @@ pcl::PointCloud<pcl::PointXYZ> Flatten(pcl::PointCloud<pcl::PointXYZRGB> cloud)
     return *flat;
 }
 
+/**
+ * @brief Fit: Estimate a geometric representation of the shape underlying the data in the pointcloud
+ * Will attempt a parallelogram model and a cirle model. #TODO add support for concave hull model.
+ * @param cloud: Point cloud specifiying a concave hull in 2D.
+ * @return Coefficients of the best model.
+ */
 Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
 	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_ptr (new pcl::PointCloud<pcl::PointXYZ>);
 	*cloud_ptr = cloud;

From 0cae81211862688e35cf3e0a42aea25798e45bcb Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Mon, 15 Aug 2022 16:36:04 +0200
Subject: [PATCH 033/136] indent tab to spaces

---
 ed_sensor_integration/tools/table_modeler.cpp | 318 +++++++++---------
 1 file changed, 159 insertions(+), 159 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 5bb7b8bd..0b2965df 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -48,9 +48,9 @@
  */
 void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, Eigen::Matrix4f &final_transform)
 {
-	
-	//final_transform = Eigen::Matrix4f::Identity(); return; //activate to bypass alignment
-	
+
+    //final_transform = Eigen::Matrix4f::Identity(); return; //activate to bypass alignment
+
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr src (new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr tgt (new pcl::PointCloud<pcl::PointXYZRGB>);
 
@@ -81,12 +81,12 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
     reg.align (*src);
 
 
-        //
+    //
     // Get the transformation from target to source
     targetToSource = reg.getFinalTransformation();//.inverse();
 
     final_transform = targetToSource;
- }
+}
 
 /**
  * @brief FilterPlane fit a plane through a pointcloud, filter the points which lie in this plane and return the height of the plane #TODO separation of concerns.
@@ -95,39 +95,39 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
  * @return height (z coordinate) of the fitted plane.
  */
 float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out) {
-	
-	//*out = *cloud; return(-1); //activate to bypass plane fitting and height estimation
-	
-	std::vector<int> indices;
-	float threshold = 0.03;
-	
-	std::cout << "starting ransac" << std::endl;
-	// Create SAC model
-	pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>::Ptr plane (new pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>(cloud));
-	std::cout << "created plane object" << std::endl;
-	// Create SAC method
-	pcl::RandomSampleConsensus<pcl::PointXYZRGB>::Ptr sac (new pcl::RandomSampleConsensus<pcl::PointXYZRGB> (plane, threshold));
-	std::cout << "created ransac object" << std::endl;
-	sac->setMaxIterations(10000);
-	sac->setProbability(0.99);
-	
-	// Fit model
-	sac->computeModel();
-
-	// Get inliers
-	std::vector<int> inliers;
-	sac->getInliers(inliers);
-
-	// Get the model coefficients
-	Eigen::VectorXf coeff;
-	sac->getModelCoefficients (coeff);
-	std::cout << "ransac complete" << std::endl;
-	
-	pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+
+    //*out = *cloud; return(-1); //activate to bypass plane fitting and height estimation
+
+    std::vector<int> indices;
+    float threshold = 0.03;
+
+    std::cout << "starting ransac" << std::endl;
+    // Create SAC model
+    pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>::Ptr plane (new pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>(cloud));
+    std::cout << "created plane object" << std::endl;
+    // Create SAC method
+    pcl::RandomSampleConsensus<pcl::PointXYZRGB>::Ptr sac (new pcl::RandomSampleConsensus<pcl::PointXYZRGB> (plane, threshold));
+    std::cout << "created ransac object" << std::endl;
+    sac->setMaxIterations(10000);
+    sac->setProbability(0.99);
+
+    // Fit model
+    sac->computeModel();
+
+    // Get inliers
+    std::vector<int> inliers;
+    sac->getInliers(inliers);
+
+    // Get the model coefficients
+    Eigen::VectorXf coeff;
+    sac->getModelCoefficients (coeff);
+    std::cout << "ransac complete" << std::endl;
+
+    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
     range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
     //range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, (coeff[3]+0.01))));
-	*out = *cloud;
-	//filter out everything below plane
+    *out = *cloud;
+    //filter out everything below plane
     pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
     condrem.setCondition (range_cond);
     condrem.setInputCloud (out);
@@ -136,9 +136,9 @@ float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud
     condrem.filter (*out);
     (*out).is_dense = false;
     pcl::removeNaNFromPointCloud(*out, *out, indices);
-	
-	return(coeff[3]);
-	
+
+    return(coeff[3]);
+
 }
 
 /**
@@ -150,9 +150,9 @@ float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud
  * @param [out] tableHeight[m]: estimated height of the table based on the cluster.
  */
 void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z, std::vector<float> &tableHeight) {
-	
-	//return; //activate completely bypass segmentation and height estimation
-	
+
+    //return; //activate completely bypass segmentation and height estimation
+
     std::cout << "starting segmentation" << std::endl;
     std::cout << "x = " << x << ", y = " << y << ", z = " << z << std::endl;
 
@@ -170,24 +170,24 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
     ec.extract (cluster_indices);
 
     std::cout << "obtained cluster indices" <<std::endl;
-	
-	//find closest cluster
+
+    //find closest cluster
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out;
     float mindist = INFINITY;
-	for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it != 
-	cluster_indices.end (); ++it) //iterate through all clusters
+    for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it !=
+         cluster_indices.end (); ++it) //iterate through all clusters
     {
-		//construct cluster
+        //construct cluster
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZRGB>);
         for (const auto& idx : it->indices)
-        cloud_cluster->push_back ((*cloud)[idx]); //*
+            cloud_cluster->push_back ((*cloud)[idx]); //*
         cloud_cluster->width = cloud_cluster->size ();
         cloud_cluster->height = 1;
         cloud_cluster->is_dense = true;
         float sumx = 0, sumy = 0, sumz = 0, dist = 0;
         for (uint j=0; j < (*cloud_cluster).width; ++j)
         {
-			//sum up all points
+            //sum up all points
             sumx += (*cloud_cluster)[j].x;
             sumy += (*cloud_cluster)[j].y;
             sumz += (*cloud_cluster)[j].z;
@@ -203,13 +203,13 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
             //currentTableHeight = maxz
         }
     }
-	
-	float height = FilterPlane(cloud_out, cloud_out);
-	if (height != -1)
-	{
-		tableHeight.push_back(height);
-	}
-	
+
+    float height = FilterPlane(cloud_out, cloud_out);
+    if (height != -1)
+    {
+        tableHeight.push_back(height);
+    }
+
     std::cout << "writing closest cluster" << std::endl;
     *cloud = *cloud_out;
 }
@@ -347,105 +347,105 @@ pcl::PointCloud<pcl::PointXYZ> Flatten(pcl::PointCloud<pcl::PointXYZRGB> cloud)
  * @return Coefficients of the best model.
  */
 Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
-	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_ptr (new pcl::PointCloud<pcl::PointXYZ>);
-	*cloud_ptr = cloud;
-	float threshold = 0.03;
-	// Create SAC model
-	pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>::Ptr line1 (new pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>(cloud_ptr));
-
-	// Create SAC method
-	pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr sac1 (new pcl::RandomSampleConsensus<pcl::PointXYZ> (line1, threshold));
-	sac1->setMaxIterations(10000);
-	sac1->setProbability(1);
-
-	// Fit model
-	sac1->computeModel();
-
-	// Get inliers
-	std::vector<int> inliers1;
-	sac1->getInliers(inliers1);
-
-	// Get the model coefficients
-	Eigen::VectorXf coeff1;
-	sac1->getModelCoefficients (coeff1);
-	
-	
-	//extract the inliers and fit second set of lines perpendicular
-	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud2 (new pcl::PointCloud<pcl::PointXYZ>);
-	pcl::PointIndices::Ptr line1_inliers (new pcl::PointIndices);
-	line1_inliers->indices = inliers1;
-	pcl::ExtractIndices<pcl::PointXYZ> extract;
-	extract.setInputCloud (cloud_ptr);
-	extract.setIndices (line1_inliers);
-	extract.setNegative (true);
-	extract.filter (*cloud2);
-	// Create second SAC model
-	pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>::Ptr line2 (new pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>(cloud2));
-	// Create SAC method
-	pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr sac2 (new pcl::RandomSampleConsensus<pcl::PointXYZ> (line2, threshold));
-	sac2->setMaxIterations(10000);
-	sac2->setProbability(1);
-	// Fit model
-	sac2->computeModel();
-	// Get inliers
-	std::vector<int> inliers2;
-	sac2->getInliers(inliers2);
-	// Get the model coefficients
-	Eigen::VectorXf coeff2;
-	sac2->getModelCoefficients (coeff2);
-
-	//pcl::io::savePCDFileASCII ("lines.pcd", *cloud2);
-	
-	pcl::PointIndices::Ptr line2_inliers (new pcl::PointIndices);
-	line2_inliers->indices = inliers2;
-	extract.setInputCloud (cloud2);
-	extract.setIndices (line2_inliers);
-	extract.filter (*cloud2);
-	//pcl::io::savePCDFileASCII ("outliers.pcd", *cloud2);
-	
-	
-	//repeat above steps for a circle
-	pcl::SampleConsensusModelCircle<pcl::PointXYZ>::Ptr circle (new pcl::SampleConsensusModelCircle<pcl::PointXYZ>(cloud_ptr));
-
-	// Create SAC method
-	pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr saccirc (new pcl::RandomSampleConsensus<pcl::PointXYZ> (circle, threshold));
-	saccirc->setMaxIterations(10000);
-	saccirc->setProbability(1);
-
-	// Fit model
-	saccirc->computeModel();
-
-	// Get inliers
-	std::vector<int> inliers3;
-	saccirc->getInliers(inliers3);
-
-	// Get the model coefficients
-	Eigen::VectorXf coeff3;
-	saccirc->getModelCoefficients (coeff3);
-	
-	float min_inliers = 0.0;
-	Eigen::VectorXf output;
-	
-	std::cout << "Parallelogram model, " << static_cast<float>(inliers1.size()+inliers2.size())/static_cast<float>(cloud.size()) << std::endl;
-	std::cout << "Circle model, " << static_cast<float>(inliers3.size())/static_cast<float>(cloud.size()) << std::endl;
-	
-	if ((inliers1.size()+inliers2.size() >= inliers3.size()) && (static_cast<float>(inliers1.size()+inliers2.size())/static_cast<float>(cloud.size()) > min_inliers))
-	{
-		float w = coeff1[2];
-		float l = coeff2[2];
-		float r = coeff1[3] - coeff2[3];//difference in angle: if not 90 degrees, model is a parallellogram	
-		
-		output.resize(3);
-		output[0] = l;
-		output[1] = w;
-		output[2] = r;
-	}
-	else if ((inliers1.size()+inliers2.size() < inliers3.size()) && (static_cast<float>(inliers3.size())/static_cast<float>(cloud.size()) > min_inliers))
-	{
-		output.resize(1);
-		output[0] = coeff3[2];
-	}
-	return (output);
+    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_ptr (new pcl::PointCloud<pcl::PointXYZ>);
+    *cloud_ptr = cloud;
+    float threshold = 0.03;
+    // Create SAC model
+    pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>::Ptr line1 (new pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>(cloud_ptr));
+
+    // Create SAC method
+    pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr sac1 (new pcl::RandomSampleConsensus<pcl::PointXYZ> (line1, threshold));
+    sac1->setMaxIterations(10000);
+    sac1->setProbability(1);
+
+    // Fit model
+    sac1->computeModel();
+
+    // Get inliers
+    std::vector<int> inliers1;
+    sac1->getInliers(inliers1);
+
+    // Get the model coefficients
+    Eigen::VectorXf coeff1;
+    sac1->getModelCoefficients (coeff1);
+
+
+    //extract the inliers and fit second set of lines perpendicular
+    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud2 (new pcl::PointCloud<pcl::PointXYZ>);
+    pcl::PointIndices::Ptr line1_inliers (new pcl::PointIndices);
+    line1_inliers->indices = inliers1;
+    pcl::ExtractIndices<pcl::PointXYZ> extract;
+    extract.setInputCloud (cloud_ptr);
+    extract.setIndices (line1_inliers);
+    extract.setNegative (true);
+    extract.filter (*cloud2);
+    // Create second SAC model
+    pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>::Ptr line2 (new pcl::SampleConsensusModelDoubleLine<pcl::PointXYZ>(cloud2));
+    // Create SAC method
+    pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr sac2 (new pcl::RandomSampleConsensus<pcl::PointXYZ> (line2, threshold));
+    sac2->setMaxIterations(10000);
+    sac2->setProbability(1);
+    // Fit model
+    sac2->computeModel();
+    // Get inliers
+    std::vector<int> inliers2;
+    sac2->getInliers(inliers2);
+    // Get the model coefficients
+    Eigen::VectorXf coeff2;
+    sac2->getModelCoefficients (coeff2);
+
+    //pcl::io::savePCDFileASCII ("lines.pcd", *cloud2);
+
+    pcl::PointIndices::Ptr line2_inliers (new pcl::PointIndices);
+    line2_inliers->indices = inliers2;
+    extract.setInputCloud (cloud2);
+    extract.setIndices (line2_inliers);
+    extract.filter (*cloud2);
+    //pcl::io::savePCDFileASCII ("outliers.pcd", *cloud2);
+
+
+    //repeat above steps for a circle
+    pcl::SampleConsensusModelCircle<pcl::PointXYZ>::Ptr circle (new pcl::SampleConsensusModelCircle<pcl::PointXYZ>(cloud_ptr));
+
+    // Create SAC method
+    pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr saccirc (new pcl::RandomSampleConsensus<pcl::PointXYZ> (circle, threshold));
+    saccirc->setMaxIterations(10000);
+    saccirc->setProbability(1);
+
+    // Fit model
+    saccirc->computeModel();
+
+    // Get inliers
+    std::vector<int> inliers3;
+    saccirc->getInliers(inliers3);
+
+    // Get the model coefficients
+    Eigen::VectorXf coeff3;
+    saccirc->getModelCoefficients (coeff3);
+
+    float min_inliers = 0.0;
+    Eigen::VectorXf output;
+
+    std::cout << "Parallelogram model, " << static_cast<float>(inliers1.size()+inliers2.size())/static_cast<float>(cloud.size()) << std::endl;
+    std::cout << "Circle model, " << static_cast<float>(inliers3.size())/static_cast<float>(cloud.size()) << std::endl;
+
+    if ((inliers1.size()+inliers2.size() >= inliers3.size()) && (static_cast<float>(inliers1.size()+inliers2.size())/static_cast<float>(cloud.size()) > min_inliers))
+    {
+        float w = coeff1[2];
+        float l = coeff2[2];
+        float r = coeff1[3] - coeff2[3];//difference in angle: if not 90 degrees, model is a parallellogram
+
+        output.resize(3);
+        output[0] = l;
+        output[1] = w;
+        output[2] = r;
+    }
+    else if ((inliers1.size()+inliers2.size() < inliers3.size()) && (static_cast<float>(inliers3.size())/static_cast<float>(cloud.size()) > min_inliers))
+    {
+        output.resize(1);
+        output[0] = coeff3[2];
+    }
+    return (output);
 }
 
 int main(int argc, char **argv) {
@@ -505,12 +505,12 @@ int main(int argc, char **argv) {
     Segment(inputs[0], x, y, z, tableHeight);
 
     *result = *inputs[0];
-	
-	pcl::io::savePCDFileASCII ("first.pcd", *inputs[0]);
-	
+
+    pcl::io::savePCDFileASCII ("first.pcd", *inputs[0]);
+
     for (int i = 1; i < argc-1; ++i)
     {
-        std::cout << "iteration " << i << std::endl;   
+        std::cout << "iteration " << i << std::endl;
 
         // align to world model coordinates
         pcl::transformPointCloud (*inputs[i], *inputs[i], ReadJson(argv[i+1], &x, &y, &z));

From 9c3cd45e5f528197d7390524e01802d08056ca53 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Mon, 15 Aug 2022 16:41:57 +0200
Subject: [PATCH 034/136] comments and formatting

---
 ed_sensor_integration/tools/table_modeler.cpp | 23 +------------------
 1 file changed, 1 insertion(+), 22 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 0b2965df..347519c9 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -57,31 +57,23 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
     *src = *cloud_src;
     *tgt = *cloud_tgt;
 
-
-    //
-    // Align
     pcl::IterativeClosestPointNonLinear<pcl::PointXYZRGB, pcl::PointXYZRGB> reg;
     reg.setTransformationEpsilon (1e-6);
     // Set the maximum distance between two correspondences (src<->tgt) to 10cm
     // Note: adjust this based on the size of your datasets
-    reg.setMaxCorrespondenceDistance (1);
+    reg.setMaxCorrespondenceDistance (1); // TODO Magic number
     // Set the point representation
     // reg.setPointRepresentation (pcl::make_shared<const MyPointRepresentation> (point_representation));
 
     reg.setInputSource (src);
     reg.setInputTarget (tgt);
 
-
-
-    //
     // Run the optimization
     Eigen::Matrix4f targetToSource;
     reg.setMaximumIterations (60);
 
     reg.align (*src);
 
-
-    //
     // Get the transformation from target to source
     targetToSource = reg.getFinalTransformation();//.inverse();
 
@@ -125,7 +117,6 @@ float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud
 
     pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
     range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
-    //range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, (coeff[3]+0.01))));
     *out = *cloud;
     //filter out everything below plane
     pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
@@ -138,7 +129,6 @@ float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud
     pcl::removeNaNFromPointCloud(*out, *out, indices);
 
     return(coeff[3]);
-
 }
 
 /**
@@ -319,7 +309,6 @@ pcl::PointCloud<pcl::PointXYZ> Flatten(pcl::PointCloud<pcl::PointXYZRGB> cloud)
     (*flat).resize((*flat).width);
     for (uint i=0; i < (cloud).width; ++i)
     {
-        //std::cout << "Writing point " << i << std::endl;
         (*flat)[i].x = cloud[i].x;
         (*flat)[i].y = cloud[i].y;
         (*flat)[i].z = 0;
@@ -369,7 +358,6 @@ Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
     Eigen::VectorXf coeff1;
     sac1->getModelCoefficients (coeff1);
 
-
     //extract the inliers and fit second set of lines perpendicular
     pcl::PointCloud<pcl::PointXYZ>::Ptr cloud2 (new pcl::PointCloud<pcl::PointXYZ>);
     pcl::PointIndices::Ptr line1_inliers (new pcl::PointIndices);
@@ -394,15 +382,11 @@ Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
     Eigen::VectorXf coeff2;
     sac2->getModelCoefficients (coeff2);
 
-    //pcl::io::savePCDFileASCII ("lines.pcd", *cloud2);
-
     pcl::PointIndices::Ptr line2_inliers (new pcl::PointIndices);
     line2_inliers->indices = inliers2;
     extract.setInputCloud (cloud2);
     extract.setIndices (line2_inliers);
     extract.filter (*cloud2);
-    //pcl::io::savePCDFileASCII ("outliers.pcd", *cloud2);
-
 
     //repeat above steps for a circle
     pcl::SampleConsensusModelCircle<pcl::PointXYZ>::Ptr circle (new pcl::SampleConsensusModelCircle<pcl::PointXYZ>(cloud_ptr));
@@ -458,7 +442,6 @@ int main(int argc, char **argv) {
         return 1;
     }
 
-    //pcl::PointCloud<pcl::PointXYZRGB>::Ptr inputs[argc-1]; //(new pcl::PointCloud<pcl::PointXYZRGB>);
     std::vector <pcl::PointCloud<pcl::PointXYZRGB>::Ptr, Eigen::aligned_allocator <pcl::PointCloud <pcl::PointXYZRGB>::Ptr > > inputs;
 
     std::vector<int> indices;
@@ -527,8 +510,6 @@ int main(int argc, char **argv) {
         // align to previous file
 
         source = inputs[i];
-        //target = inputs[i];
-
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr temp (new pcl::PointCloud<pcl::PointXYZRGB>);
 
         std::cout << "aligning cloud " << i << " to cloud " << i - 1 << std::endl;
@@ -555,7 +536,5 @@ int main(int argc, char **argv) {
     pcl::io::savePCDFileASCII ("flat.pcd", flat);
     std::cout << "The table is " << std::accumulate(tableHeight.begin(), tableHeight.end(), 0.0) / tableHeight.size() << "m tall" << std::endl;
     
-    
-
     return 0;
 }

From 9e66acd72e7fdd04f7c778629a44ae8e1d64c308 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Tue, 16 Aug 2022 18:49:42 +0200
Subject: [PATCH 035/136] remove unused rectangle model

---
 .../sac_model_rectangle.h                     | 333 ----------
 .../sac_model_rectangle.hpp                   | 586 ------------------
 ed_sensor_integration/tools/table_modeler.cpp |   1 -
 3 files changed, 920 deletions(-)
 delete mode 100644 ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.h
 delete mode 100644 ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.h
deleted file mode 100644
index f3a73dc4..00000000
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.h
+++ /dev/null
@@ -1,333 +0,0 @@
- /*
-  * Software License Agreement (BSD License)
-  *
-  *  Point Cloud Library (PCL) - www.pointclouds.org
-  *  Copyright (c) 2010-2011, Willow Garage, Inc.
-  *  Copyright (c) 2012-, Open Perception, Inc.
-  *
-  *  All rights reserved.
-  *
-  *  Redistribution and use in source and binary forms, with or without
-  *  modification, are permitted provided that the following conditions
-  *  are met:
-  *
-  *   * Redistributions of source code must retain the above copyright
-  *     notice, this list of conditions and the following disclaimer.
-  *   * Redistributions in binary form must reproduce the above
-  *     copyright notice, this list of conditions and the following
-  *     disclaimer in the documentation and/or other materials provided
-  *     with the distribution.
-  *   * Neither the name of the copyright holder(s) nor the names of its
-  *     contributors may be used to endorse or promote products derived
-  *     from this software without specific prior written permission.
-  *
-  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
-  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
-  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
-  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
-  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
-  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
-  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
-  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
-  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-  *  POSSIBILITY OF SUCH DAMAGE.
-  *
-  * $Id$
-  *
-  */
-  
- #pragma once
-  
- #include <pcl/sample_consensus/sac_model.h>
- #include <pcl/sample_consensus/model_types.h>
- #include <pcl/common/distances.h>
-  
- namespace pcl
- {
-   /** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
-     * The model coefficients are defined as:
-     *   - \b point_on_axis.x  : the X coordinate of a point located on the cylinder axis
-     *   - \b point_on_axis.y  : the Y coordinate of a point located on the cylinder axis
-     *   - \b point_on_axis.z  : the Z coordinate of a point located on the cylinder axis
-     *   - \b axis_direction.x : the X coordinate of the cylinder's axis direction
-     *   - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
-     *   - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
-     *   - \b radius           : the cylinder's radius
-     * 
-     * \author Radu Bogdan Rusu
-     * \ingroup sample_consensus
-     */
-   template <typename PointT>
-   class SampleConsensusModelRectangle : public SampleConsensusModel<PointT>
-   {
-     public:
-       using SampleConsensusModel<PointT>::model_name_;
-       using SampleConsensusModel<PointT>::input_;
-       using SampleConsensusModel<PointT>::indices_;
-       using SampleConsensusModel<PointT>::radius_min_;
-       using SampleConsensusModel<PointT>::radius_max_;
-       using SampleConsensusModel<PointT>::error_sqr_dists_;
-  
-       using PointCloud = typename SampleConsensusModel<PointT>::PointCloud;
-       using PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr;
-       using PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr;
-  
-       using Ptr = shared_ptr<SampleConsensusModelRectangle<PointT> >;
-       using ConstPtr = shared_ptr<const SampleConsensusModelRectangle<PointT>>;
-  
-       /** \brief Constructor for base SampleConsensusModelCylinder.
-         * \param[in] cloud the input point cloud dataset
-         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
-         */
-       SampleConsensusModelRectangle (const PointCloudConstPtr &cloud, bool random = false) 
-         : SampleConsensusModel<PointT> (cloud, random)
-         , axis_ (Eigen::Vector3f::Zero ())
-         , eps_angle_ (0)
-       {
-         model_name_ = "SampleConsensusModelRectangle";
-         sample_size_ = 3;
-         model_size_ = 5;
-       }
-  
-       /** \brief Constructor for base SampleConsensusModelCylinder.
-         * \param[in] cloud the input point cloud dataset
-         * \param[in] indices a vector of point indices to be used from \a cloud
-         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
-         */
-       SampleConsensusModelRectangle (const PointCloudConstPtr &cloud, 
-                                     const Indices &indices,
-                                     bool random = false) 
-         : SampleConsensusModel<PointT> (cloud, indices, random)
-         , axis_ (Eigen::Vector3f::Zero ())
-         , eps_angle_ (0)
-       {
-         model_name_ = "SampleConsensusModelRectangle";
-         sample_size_ = 3;
-         model_size_ = 5;
-       }
-  
-       /** \brief Copy constructor.
-         * \param[in] source the model to copy into this
-         */
-       SampleConsensusModelRectangle (const SampleConsensusModelRectangle &source) :
-         SampleConsensusModel<PointT> (),
-         axis_ (Eigen::Vector3f::Zero ()),
-         eps_angle_ (0)
-       {
-         *this = source;
-         model_name_ = "SampleConsensusModelRectangle";
-       }
-       
-       /** \brief Empty destructor */
-       ~SampleConsensusModelRectangle () {}
-  
-       /** \brief Copy constructor.
-         * \param[in] source the model to copy into this
-         */
-       inline SampleConsensusModelRectangle&
-       operator = (const SampleConsensusModelRectangle &source)
-       {
-         SampleConsensusModel<PointT>::operator=(source);
-         axis_ = source.axis_;
-         eps_angle_ = source.eps_angle_;
-         return (*this);
-       }
-  
-       /** \brief Set the angle epsilon (delta) threshold.
-         * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
-         */
-       inline void 
-       setEpsAngle (const double ea) { eps_angle_ = ea; }
-  
-       /** \brief Get the angle epsilon (delta) threshold. */
-       inline double 
-       getEpsAngle () const { return (eps_angle_); }
-  
-       /** \brief Set the axis along which we need to search for a cylinder direction.
-         * \param[in] ax the axis along which we need to search for a cylinder direction
-         */
-       inline void 
-       setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
-  
-       /** \brief Get the axis along which we need to search for a cylinder direction. */
-       inline Eigen::Vector3f 
-       getAxis () const { return (axis_); }
-  
-       /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
-         * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
-         * axis_direction, cylinder_radius_R
-         * \param[in] samples the point indices found as possible good candidates for creating a valid model
-         * \param[out] model_coefficients the resultant model coefficients
-         */
-       bool
-       computeModelCoefficients (const Indices &samples,
-                                 Eigen::VectorXf &model_coefficients) const override;
-  
-       /** \brief Compute all distances from the cloud data to a given cylinder model.
-         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
-         * \param[out] distances the resultant estimated distances
-         */
-       void
-       getDistancesToModel (const Eigen::VectorXf &model_coefficients,
-                            std::vector<double> &distances) const override;
-  
-       /** \brief Select all the points which respect the given model coefficients as inliers.
-         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
-         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
-         * \param[out] inliers the resultant model inliers
-         */
-       void 
-       selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
-                             const double threshold, 
-                             Indices &inliers) override;
-  
-       /** \brief Count all the points which respect the given model coefficients as inliers. 
-         * 
-         * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
-         * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
-         * \return the resultant number of inliers
-         */
-       std::size_t
-       countWithinDistance (const Eigen::VectorXf &model_coefficients,
-                            const double threshold) const override;
-  
-       /** \brief Recompute the cylinder coefficients using the given inlier set and return them to the user.
-         * @note: these are the coefficients of the cylinder model after refinement (e.g. after SVD)
-         * \param[in] inliers the data inliers found as supporting the model
-         * \param[in] model_coefficients the initial guess for the optimization
-         * \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization
-         */
-       void
-       optimizeModelCoefficients (const Indices &inliers,
-                                  const Eigen::VectorXf &model_coefficients,
-                                  Eigen::VectorXf &optimized_coefficients) const override;
-  
-  
-       /** \brief Create a new point cloud with inliers projected onto the cylinder model.
-         * \param[in] inliers the data inliers that we want to project on the cylinder model
-         * \param[in] model_coefficients the coefficients of a cylinder model
-         * \param[out] projected_points the resultant projected points
-         * \param[in] copy_data_fields set to true if we need to copy the other data fields
-         */
-       void
-       projectPoints (const Indices &inliers,
-                      const Eigen::VectorXf &model_coefficients,
-                      PointCloud &projected_points,
-                      bool copy_data_fields = true) const override;
-  
-       /** \brief Verify whether a subset of indices verifies the given cylinder model coefficients.
-         * \param[in] indices the data indices that need to be tested against the cylinder model
-         * \param[in] model_coefficients the cylinder model coefficients
-         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
-         */
-       bool
-       doSamplesVerifyModel (const std::set<int> &indices,
-                             const Eigen::VectorXf &model_coefficients,
-                             const double threshold) const override;
-  
-       /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
-       inline pcl::SacModel 
-       getModelType () const override { return (SACMODEL_CYLINDER); } //cannot add a unique identifier for rectangle
-  
-     protected:
-       using SampleConsensusModel<PointT>::sample_size_;
-       using SampleConsensusModel<PointT>::model_size_;
-  
-       /** \brief Get the distance from a point to a line (represented by a point and a direction)
-         * \param[in] pt a point
-         * \param[in] model_coefficients the line coefficients (a point on the line, line direction)
-         */
-       double
-       pointToLineDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const;
-  
-       /** \brief Project a point onto a line given by a point and a direction vector
-         * \param[in] pt the input point to project
-         * \param[in] line_pt the point on the line (make sure that line_pt[3] = 0 as there are no internal checks!)
-         * \param[in] line_dir the direction of the line (make sure that line_dir[3] = 0 as there are no internal checks!)
-         * \param[out] pt_proj the resultant projected point
-         */
-       inline void
-       projectPointToLine (const Eigen::Vector4f &pt,
-                           const Eigen::Vector4f &line_pt,
-                           const Eigen::Vector4f &line_dir,
-                           Eigen::Vector4f &pt_proj) const
-       {
-         float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
-         // Calculate the projection of the point on the line
-         pt_proj = line_pt + k * line_dir;
-       }
-  
-       /** \brief Project a point onto a cylinder given by its model coefficients (point_on_axis, axis_direction,
-         * cylinder_radius_R)
-         * \param[in] pt the input point to project
-         * \param[in] model_coefficients the coefficients of the cylinder (point_on_axis, axis_direction, cylinder_radius_R)
-         * \param[out] pt_proj the resultant projected point
-         */
-       void
-       projectPointToRectangle (const Eigen::Vector4f &pt,
-                               const Eigen::VectorXf &model_coefficients,
-                               Eigen::Vector4f &pt_proj) const;
-  
-       /** \brief Check whether a model is valid given the user constraints.
-         * \param[in] model_coefficients the set of model coefficients
-         */
-       bool
-       isModelValid (const Eigen::VectorXf &model_coefficients) const override;
-  
-       /** \brief Check if a sample of indices results in a good sample of points
-         * indices. Pure virtual.
-         * \param[in] samples the resultant index samples
-         */
-       bool
-       isSampleGood (const Indices &samples) const override;
-  
-     private:
-       /** \brief The axis along which we need to search for a cylinder direction. */
-       Eigen::Vector3f axis_;
-     
-       /** \brief The maximum allowed difference between the cylinder direction and the given axis. */
-       double eps_angle_;
-  
-       /** \brief Functor for the optimization function */
-       struct OptimizationFunctor : pcl::Functor<float>
-       {
-         /** Functor constructor
-           * \param[in] indices the indices of data points to evaluate
-           * \param[in] estimator pointer to the estimator object
-           */
-         OptimizationFunctor (const pcl::SampleConsensusModelRectangle<PointT> *model, const Indices& indices) :
-           pcl::Functor<float> (indices.size ()), model_ (model), indices_ (indices) {}
-  
-         /** Cost function to be minimized
-           * \param[in] x variables array
-           * \param[out] fvec resultant functions evaluations
-           * \return 0
-           */
-         int 
-         operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
-         {
-           Eigen::Vector4f line_pt  (x[0], x[1], x[2], 0);
-           Eigen::Vector4f line_dir (x[3], x[4], x[5], 0);
-           
-           for (int i = 0; i < values (); ++i)
-           {
-             // dist = f - r
-             Eigen::Vector4f pt = (*model_->input_)[indices_[i]].getVector4fMap();
-             pt[3] = 0;
-  
-             fvec[i] = static_cast<float> (pcl::sqrPointToLineDistance (pt, line_pt, line_dir) - x[6]*x[6]);
-           }
-           return (0);
-         }
-  
-         const pcl::SampleConsensusModelRectangle<PointT> *model_;
-         const Indices &indices_;
-       };
-   };
- }
-  
- //#ifdef PCL_NO_PRECOMPILE
- #include "ed_sensor_integration/sac_model_rectangle.hpp"
- //#endif
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp
deleted file mode 100644
index 00c740a3..00000000
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_rectangle.hpp
+++ /dev/null
@@ -1,586 +0,0 @@
- /*
-  * Software License Agreement (BSD License)
-  *
-  *  Point Cloud Library (PCL) - www.pointclouds.org
-  *  Copyright (c) 2009-2010, Willow Garage, Inc.
-  *  Copyright (c) 2012-, Open Perception, Inc.
-  *
-  *  All rights reserved.
-  *
-  *  Redistribution and use in source and binary forms, with or without
-  *  modification, are permitted provided that the following conditions
-  *  are met:
-  *
-  *   * Redistributions of source code must retain the above copyright
-  *     notice, this list of conditions and the following disclaimer.
-  *   * Redistributions in binary form must reproduce the above
-  *     copyright notice, this list of conditions and the following
-  *     disclaimer in the documentation and/or other materials provided
-  *     with the distribution.
-  *   * Neither the name of the copyright holder(s) nor the names of its
-  *     contributors may be used to endorse or promote products derived
-  *     from this software without specific prior written permission.
-  *
-  *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-  *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-  *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
-  *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
-  *  COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
-  *  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
-  *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
-  *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
-  *  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
-  *  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
-  *  ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-  *  POSSIBILITY OF SUCH DAMAGE.
-  *
-  * $Id$
-  *
-  */
-  
- #ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_RECTANGLE_H_
- #define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_RECTANGLE_H_
-  
- #include <unsupported/Eigen/NonLinearOptimization> // for LevenbergMarquardt
- #include "ed_sensor_integration/sac_model_rectangle.h"
- #include <pcl/common/common.h> // for getAngle3D
- #include <pcl/common/concatenate.h>
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool
- pcl::SampleConsensusModelRectangle<PointT>::isSampleGood (const Indices &samples) const
- {
-   if (samples.size () != sample_size_)
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelRectangle::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
-     return (false);
-   }
-   return (true);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool
- pcl::SampleConsensusModelRectangle<PointT>::computeModelCoefficients (
-       const Indices &samples, Eigen::VectorXf &model_coefficients) const
- {
-   // Need 3 samples
-   if (samples.size () != sample_size_)
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelRectangle::computeModelCoefficients] Invalid set of samples given (%lu)!\n", samples.size ());
-     return (false);
-   }
-  
-   if (std::abs ((*input_)[samples[0]].x - (*input_)[samples[1]].x) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].y - (*input_)[samples[1]].y) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].z - (*input_)[samples[1]].z) <= std::numeric_limits<float>::epsilon () ||
-       std::abs ((*input_)[samples[1]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[1]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[1]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon () ||
-       std::abs ((*input_)[samples[0]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon ()) 
-   {
-     return (false);
-   }
-   Eigen::Vector2f p1 ((*input_)[samples[0]].x, (*input_)[samples[0]].y);
-   Eigen::Vector2f p2 ((*input_)[samples[1]].x, (*input_)[samples[1]].y);
-   Eigen::Vector2f p3 ((*input_)[samples[2]].x, (*input_)[samples[2]].y);
-   
-   float x = p1(0), y = p1(1); //output: x and y values
-   
-   Eigen::Vector2f c1 = p2 - p1; //vector between point 1 and 2
-   
-   float l = sqrt(c1.dot(c1)); //output: initially define length as distance between point 1 and 2
-   
-   Eigen::Vector2f c2 = p1 - p3; //vector between point 3 and 1
-   
-   float w = (c1(0)*c2(1)-c2(0)*c1(1))/l; //output: width defined as distance between c1 and point 3, signed
-   
-   Eigen::Matrix2f transform = Eigen::Matrix2f::Identity().colwise().reverse().eval();
-   transform(1,0) = -1;
-   transform = transform*w/l;
-   Eigen::Vector2f c3 = transform * c1; //vector perpendicular to c1 with length w, pointing from c1 to point 3
-   
-   // determine rotation:
-   
-   float r = std::atan2(c1(1), c1(0)); //output: rotation of the rectangle
-   
-   //now check if p3 lies outside the described rectangle:
-   
-   Eigen::Vector2f t1 = p1+c3-p3, t2 = p2+c3-p3;
-   float d1 = sqrt(t1.dot(t1)), d2 = sqrt(t2.dot(t2));
-   if (d1 < l && d2 < d1)
-   {
-	   l = d1; //update only length
-   }
-   else if (d2 < l && d1 < d2)
-   {
-	   l = d2; //update both length and origin
-	   x = (p3-c3)(0);
-	   y = (p3-c3)(1);
-   }
-   
-   if (w < 0)
-   {
-	   x += c3(0);
-	   y += c3(1);
-	   w = std::abs(w);
-   }
-   
-   //save model coefficients
-   model_coefficients.resize (model_size_);
-   model_coefficients[0] = x;
-   model_coefficients[1] = y;
-   model_coefficients[2] = l;
-   model_coefficients[3] = w;
-   model_coefficients[4] = r;
-   
-   PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::computeModelCoefficients] Model is (%g,%g,%g,%g,%g).\n",
-              model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
-              model_coefficients[4]);
-   //std::cout << "P1: " << std::endl << p1 << std::endl << "P2: " << std::endl << p2 << std::endl << "P3: " << std::endl << p3 << std::endl << model_coefficients << std::endl;
-   return (true);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelRectangle<PointT>::getDistancesToModel (
-       const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
- {
-   // Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-   {
-     distances.clear ();
-     return;
-   }
-  
-   distances.resize (indices_->size ());
-   
-   float x = model_coefficients[0], y = model_coefficients[1], l = model_coefficients[2], w = model_coefficients[3], r = model_coefficients[4];
-   float d1, d2, d3, d4;
-
-   Eigen::Vector2f p1, p2, p3, p4, c1, c2;
-   
-   //define edge vectors
-   c1(0)=std::cos(r)*l;
-   c1(1)=std::sin(r)*l;
-
-   c2(0)= std::sin(r)*w;
-   c2(1)=-std::cos(r)*w;
-
-   //define corner vectors
-   p1(0)=x;
-   p1(1)=y;
-   p2 = p1 + c1;
-   p3 = p2 + c2;
-   p4 = p1 + c2;
-   
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-	   Eigen::Vector2f in ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y);
-	   
-	   //compute distances to lines
-		d1 = ( c1(0)*(p1(1)-in(1))-(p1(0)-in(0))* c1(1))/l; //Distance between line 1 and the point
-		d2 = ( c2(0)*(p2(1)-in(1))-(p2(0)-in(0))* c1(1))/w; //Distance between line 2 and the point
-		d3 = (-c1(0)*(p3(1)-in(1))-(p3(0)-in(0))*-c1(1))/l; //Distance between line 3 and the point
-		d4 = (-c1(0)*(p4(1)-in(1))-(p4(0)-in(0))*-c1(1))/w; //Distance between line 4 and the point
-		//note: these distances are signed, such that points lying inside the rectangle have positive distance to all lines
-
-		if (d1>0 && d2>0 && d3>0 && d4>0) //inside the rectangle
-		{
-			distances[i] = std::min(d1, std::min(d2, std::min(d3, d4))); //smallest of d1, d2, d3 and d4
-		}
-		else if (d1<=0 && d2>=0 && d4>=0) //closest to line 1
-		{
-			distances[i] = std::abs(d1);
-		}
-		else if (d2<=0 && d3>=0 && d1>=0) //closest to line 2
-		{
-			distances[i] = std::abs(d2);
-		}
-		else if (d3<=0 && d4>=0 && d2>=0) //closest to line 3
-		{
-			distances[i] = std::abs(d3);
-		}
-		else if (d4<=0 && d1>=0 && d3>=0) //closest to line 4
-		{
-			distances[i] = std::abs(d4);
-		}
-		else if (d1<0 && d4<0) //closest to corner 1
-		{
-			Eigen::Vector2f v = in - p1;
-			distances[i] = sqrt(v.dot(v)); //distance between corner 1 and the point
-		}
-		else if (d2<0 && d1<0) //closest to corner 2
-		{
-			Eigen::Vector2f v = in - p2;
-			distances[i] = sqrt(v.dot(v)); //distance between corner 2 and the point
-		}
-		else if (d3<0 && d2<0) //closest to corner 3
-		{
-			Eigen::Vector2f v = in - p3;
-			distances[i] = sqrt(v.dot(v)); //distance between corner 3 and the point
-		}
-		else if (d4<0 && d3<0) //closest to corner 4
-		{
-			Eigen::Vector2f v = in - p4;
-			distances[i] = sqrt(v.dot(v)); //distance between corner 4 and the point
-		}
-		//std::cout << distances[i] << std::endl;
-   }
-   //std::cout << std::accumulate(distances.begin(), distances.end(), 0.0) / distances.size() << ", ";
-  /*
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-   // Iterate through the 3d points and calculate the distances from them to the sphere
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     // @note need to revise this.
-     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
-  
-     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
-  
-     // Calculate the point's projection on the cylinder axis
-     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
-     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
-     Eigen::Vector4f dir = pt - pt_proj;
-     dir.normalize ();
-  
-     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
-     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
-     double d_normal = std::abs (getAngle3D (n, dir));
-     d_normal = (std::min) (d_normal, M_PI - d_normal);
-  
-     distances[i] = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);*/
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelRectangle<PointT>::selectWithinDistance (
-       const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
- {
-   /*
-   // Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-   {
-     inliers.clear ();
-     return;
-   }
-  
-   inliers.clear ();
-   error_sqr_dists_.clear ();
-   inliers.reserve (indices_->size ());
-   error_sqr_dists_.reserve (indices_->size ());
-  
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-   // Iterate through the 3d points and calculate the distances from them to the sphere
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
-     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
-     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
-       continue;
-  
-     // Calculate the point's projection on the cylinder axis
-     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
-     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
-     Eigen::Vector4f dir = pt - pt_proj;
-     dir.normalize ();
-  
-     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
-     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
-     double d_normal = std::abs (getAngle3D (n, dir));
-     d_normal = (std::min) (d_normal, M_PI - d_normal);
-  
-     double distance = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);
-     if (distance < threshold)
-     {
-       // Returns the indices of the points whose distances are smaller than the threshold
-       inliers.push_back ((*indices_)[i]);
-       error_sqr_dists_.push_back (distance);
-     }
-   }*/
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> std::size_t
- pcl::SampleConsensusModelRectangle<PointT>::countWithinDistance (
-       const Eigen::VectorXf &model_coefficients, const double threshold) const
- {
-   std::vector<double> distances;
-   getDistancesToModel (model_coefficients, distances);
-   int count = 0;
-   for (int i = 0; i < distances.size(); i++)
-   {
-	   if (distances[i] <= threshold) {count++;}
-   }
-   //std::cout << count << std::endl;
-   return (count);
-   /*// Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-     return (0);
-  
-   std::size_t nr_p = 0;
-  
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-   // Iterate through the 3d points and calculate the distances from them to the sphere
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
-     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
-     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
-       continue;
-  
-     // Calculate the point's projection on the cylinder axis
-     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
-     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
-     Eigen::Vector4f dir = pt - pt_proj;
-     dir.normalize ();
-  
-     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
-     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
-     double d_normal = std::abs (getAngle3D (n, dir));
-     d_normal = (std::min) (d_normal, M_PI - d_normal);
-  
-     if (std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist) < threshold)
-       nr_p++;
-   }
-   return (nr_p);*/
-   return (0);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelRectangle<PointT>::optimizeModelCoefficients (
-       const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
- {
-   optimized_coefficients = model_coefficients;
-  
-   // Needs a set of valid model coefficients
-   if (!isModelValid (model_coefficients))
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelRectangle::optimizeModelCoefficients] Given model is invalid!\n");
-     return;
-   }
-  
-   // Need more than the minimum sample size to make a difference
-   if (inliers.size () <= sample_size_)
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelRectangle:optimizeModelCoefficients] Not enough inliers found to optimize model coefficients (%lu)! Returning the same coefficients.\n", inliers.size ());
-     return;
-   }
-  
-   OptimizationFunctor functor (this, inliers);
-   Eigen::NumericalDiff<OptimizationFunctor > num_diff (functor);
-   Eigen::LevenbergMarquardt<Eigen::NumericalDiff<OptimizationFunctor>, float> lm (num_diff);
-   int info = lm.minimize (optimized_coefficients);
-   
-   // Compute the L2 norm of the residuals
-   PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::optimizeModelCoefficients] LM solver finished with exit code %i, having a residual norm of %g. \nInitial solution: %g %g %g %g %g %g %g \nFinal solution: %g %g %g %g %g %g %g\n",
-              info, lm.fvec.norm (), model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
-              model_coefficients[4], model_coefficients[5], model_coefficients[6], optimized_coefficients[0], optimized_coefficients[1], optimized_coefficients[2], optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5], optimized_coefficients[6]);
-     
-   Eigen::Vector3f line_dir (optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5]);
-   line_dir.normalize ();
-   optimized_coefficients[3] = line_dir[0];
-   optimized_coefficients[4] = line_dir[1];
-   optimized_coefficients[5] = line_dir[2];
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelRectangle<PointT>::projectPoints (
-       const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
- {
-   // Needs a valid set of model coefficients
-   if (!isModelValid (model_coefficients))
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelRectangle::projectPoints] Given model is invalid!\n");
-     return;
-   }
-  
-   projected_points.header = input_->header;
-   projected_points.is_dense = input_->is_dense;
-  
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-  
-   // Copy all the data fields from the input cloud to the projected one?
-   if (copy_data_fields)
-   {
-     // Allocate enough space and copy the basics
-     projected_points.resize (input_->size ());
-     projected_points.width    = input_->width;
-     projected_points.height   = input_->height;
-  
-     using FieldList = typename pcl::traits::fieldList<PointT>::type;
-     // Iterate over each point
-     for (std::size_t i = 0; i < projected_points.size (); ++i)
-       // Iterate over each dimension
-       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
-  
-     // Iterate through the 3d points and calculate the distances from them to the cylinder
-     for (const auto &inlier : inliers)
-     {
-       Eigen::Vector4f p ((*input_)[inlier].x,
-                          (*input_)[inlier].y,
-                          (*input_)[inlier].z,
-                          1);
-  
-       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
-  
-       pcl::Vector4fMap pp = projected_points[inlier].getVector4fMap ();
-       pp.matrix () = line_pt + k * line_dir;
-  
-       Eigen::Vector4f dir = p - pp;
-       dir[3] = 0.0f;
-       dir.normalize ();
-  
-       // Calculate the projection of the point onto the cylinder
-       pp += dir * model_coefficients[6];
-     }
-   }
-   else
-   {
-     // Allocate enough space and copy the basics
-     projected_points.resize (inliers.size ());
-     projected_points.width    = inliers.size ();
-     projected_points.height   = 1;
-  
-     using FieldList = typename pcl::traits::fieldList<PointT>::type;
-     // Iterate over each point
-     for (std::size_t i = 0; i < inliers.size (); ++i)
-       // Iterate over each dimension
-       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
-  
-     // Iterate through the 3d points and calculate the distances from them to the cylinder
-     for (std::size_t i = 0; i < inliers.size (); ++i)
-     {
-       pcl::Vector4fMap pp = projected_points[i].getVector4fMap ();
-       pcl::Vector4fMapConst p = (*input_)[inliers[i]].getVector4fMap ();
-  
-       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
-       // Calculate the projection of the point on the line
-       pp.matrix () = line_pt + k * line_dir;
-  
-       Eigen::Vector4f dir = p - pp;
-       dir[3] = 0.0f;
-       dir.normalize ();
-  
-       // Calculate the projection of the point onto the cylinder
-       pp += dir * model_coefficients[6];
-     }
-   }
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool
- pcl::SampleConsensusModelRectangle<PointT>::doSamplesVerifyModel (
-       const std::set<int> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
- {
-   // Needs a valid model coefficients
-   if (!isModelValid (model_coefficients))
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelRectangle::doSamplesVerifyModel] Given model is invalid!\n");
-     return (false);
-   }
-  
-   for (const auto &index : indices)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     // @note need to revise this.
-     Eigen::Vector4f pt ((*input_)[index].x, (*input_)[index].y, (*input_)[index].z, 0.0f);
-     if (std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]) > threshold)
-       return (false);
-   }
-  
-   return (true);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> double
- pcl::SampleConsensusModelRectangle<PointT>::pointToLineDistance (
-       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const
- {
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   return sqrt(pcl::sqrPointToLineDistance (pt, line_pt, line_dir));
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelRectangle<PointT>::projectPointToRectangle (
-       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients, Eigen::Vector4f &pt_proj) const
- {
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-  
-   float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) * line_dir.dot (line_dir);
-   pt_proj = line_pt + k * line_dir;
-  
-   Eigen::Vector4f dir = pt - pt_proj;
-   dir.normalize ();
-  
-   // Calculate the projection of the point onto the cylinder
-   pt_proj += dir * model_coefficients[6];
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool 
- pcl::SampleConsensusModelRectangle<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
- {
-   if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
-     return (false);
-  
-   // Check against template, if given
-   if (eps_angle_ > 0.0)
-   {
-     // Obtain the cylinder direction
-     const Eigen::Vector3f coeff(model_coefficients[3], model_coefficients[4], model_coefficients[5]);
-  
-     double angle_diff = std::abs (getAngle3D (axis_, coeff));
-     angle_diff = (std::min) (angle_diff, M_PI - angle_diff);
-     // Check whether the current cylinder model satisfies our angle threshold criterion with respect to the given axis
-     if (angle_diff > eps_angle_)
-     {
-       PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::isModelValid] Angle between cylinder direction and given axis is too large.\n");
-       return (false);
-     }
-   }
-  
-   if (radius_min_ != -std::numeric_limits<double>::max() && model_coefficients[6] < radius_min_)
-   {
-     PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::isModelValid] Radius is too small: should be larger than %g, but is %g.\n",
-                radius_min_, model_coefficients[6]);
-     return (false);
-   }
-   if (radius_max_ != std::numeric_limits<double>::max() && model_coefficients[6] > radius_max_)
-   {
-     PCL_DEBUG ("[pcl::SampleConsensusModelRectangle::isModelValid] Radius is too big: should be smaller than %g, but is %g.\n",
-                radius_max_, model_coefficients[6]);
-     return (false);
-   }
-  
-   return (true);
- }
-  
- #define PCL_INSTANTIATE_SampleConsensusModelRectangle(PointT) template class PCL_EXPORTS pcl::SampleConsensusModelRectangle<PointT>;
-  
- #endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_RECTANGLE_H_
diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 347519c9..54a7186f 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -35,7 +35,6 @@
 
 #include <fstream>
 
-//#include "ed_sensor_integration/sac_model_rectangle.h"
 #include "ed_sensor_integration/sac_model_double_line.h"
 #include "ed_sensor_integration/sac_model_circle.h"
 #include "ed_sensor_integration/sac_model_horizontal_plane.h"

From 950e8d9d1b3558e5208623236eb5d922079d9b07 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Tue, 16 Aug 2022 19:40:17 +0200
Subject: [PATCH 036/136] small cleanup of sac model

---
 .../sac_model_double_line.hpp                 | 57 ++++---------------
 1 file changed, 10 insertions(+), 47 deletions(-)

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
index e83dd718..25c0ed9d 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
@@ -92,20 +92,11 @@
    
    Eigen::Vector2f c1, c2;
    
-   if (/*eps_angle_ == INFINITY*/true) //if angle is given, only 2 points are required
-   {
-	   c1 = p2 - p1; //vector between point 1 and 2
-	   l = sqrt(c1.dot(c1)); //define length as distance between point 1 and 2
-	   // determine rotation:
-	   r = std::atan2(c1(1), c1(0)); //output: rotation of the double_line
-   }
-   else
-   {
-	   r = eps_angle_; //output: rotation of the double_line
-	   c1(0)=std::cos(r);
-	   c1(1)=std::sin(r);
-	   l = 1;
-   }
+   c1 = p2 - p1; //vector between point 1 and 2
+   l = sqrt(c1.dot(c1)); //define length as distance between point 1 and 2
+   // determine rotation:
+   r = std::atan2(c1(1), c1(0)); //output: orientation of the double_line
+
    c2 = p1 - p3; //vector between point 3 and 1
    w = (c1(0)*c2(1)-c2(0)*c1(1))/l; //output: width defined as distance between c1 and point 3, signed
 	   
@@ -138,19 +129,21 @@
   
    distances.resize (indices_->size ());
    
-   float x = model_coefficients[0], y = model_coefficients[1], w = model_coefficients[2], r = model_coefficients[3];
+   float x = model_coefficients[0]
+   float y = model_coefficients[1]
+   float w = model_coefficients[2]
+   float r = model_coefficients[3];
    float d1, d2;
 
    Eigen::Vector2f p1, p2, p3, p4, c1, c2;
    
+   // #TODO Calculation of distances without needing to define points
    //define edge vectors
    c1(0)=std::cos(r);
    c1(1)=std::sin(r);
 
    c2(0)= std::sin(r)*w;
    c2(1)=-std::cos(r)*w;
-   
-   //std::cout << "c2 = " << std::endl << c2 << std::endl;
 
    //define corner vectors
    p1(0)=x;
@@ -168,37 +161,7 @@
 		d2 = std::abs(c1(0)*(p3(1)-in(1))-(p3(0)-in(0))*c1(1)); //Distance between line 2 and the point
 
 		distances[i] = std::min(d1, d2); //smallest of d1 and d2
-		
-		//std::cout << distances[i] << std::endl;
    }
-   //std::cout << std::accumulate(distances.begin(), distances.end(), 0.0) / distances.size() << ", ";
-  /*
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-   // Iterate through the 3d points and calculate the distances from them to the sphere
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     // @note need to revise this.
-     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
-  
-     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
-  
-     // Calculate the point's projection on the cylinder axis
-     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
-     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
-     Eigen::Vector4f dir = pt - pt_proj;
-     dir.normalize ();
-  
-     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
-     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
-     double d_normal = std::abs (getAngle3D (n, dir));
-     d_normal = (std::min) (d_normal, M_PI - d_normal);
-  
-     distances[i] = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);*/
  }
   
  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////

From a3880586ff5660dd9b6ddd945b1f3e09b3a971b2 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Tue, 16 Aug 2022 20:04:08 +0200
Subject: [PATCH 037/136] fix indents

---
 .../ed_sensor_integration/sac_model_circle.h  | 578 +++++++-------
 .../sac_model_circle.hpp                      | 696 ++++++++---------
 .../sac_model_double_line.h                   | 576 +++++++-------
 .../sac_model_double_line.hpp                 | 732 +++++++++---------
 .../sac_model_horizontal_plane.h              | 298 +++----
 .../sac_model_horizontal_plane.hpp            | 162 ++--
 6 files changed, 1521 insertions(+), 1521 deletions(-)

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
index e0531b3d..0034cf9a 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
@@ -1,4 +1,4 @@
- /*
+/*
   * Software License Agreement (BSD License)
   *
   *  Point Cloud Library (PCL) - www.pointclouds.org
@@ -37,297 +37,297 @@
   * $Id$
   *
   */
-  
- #pragma once
-  
- #include <pcl/sample_consensus/sac_model.h>
- #include <pcl/sample_consensus/model_types.h>
- #include <pcl/common/distances.h>
-  
- namespace pcl
- {
-   /** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
-     * The model coefficients are defined as:
-     *   - \b point_on_axis.x  : the X coordinate of a point located on the cylinder axis
-     *   - \b point_on_axis.y  : the Y coordinate of a point located on the cylinder axis
-     *   - \b point_on_axis.z  : the Z coordinate of a point located on the cylinder axis
-     *   - \b axis_direction.x : the X coordinate of the cylinder's axis direction
-     *   - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
-     *   - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
-     *   - \b radius           : the cylinder's radius
-     * 
-     * \author Radu Bogdan Rusu
-     * \ingroup sample_consensus
+
+#pragma once
+
+#include <pcl/sample_consensus/sac_model.h>
+#include <pcl/sample_consensus/model_types.h>
+#include <pcl/common/distances.h>
+
+namespace pcl
+{
+/** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
+ * The model coefficients are defined as:
+ *   - \b point_on_axis.x  : the X coordinate of a point located on the cylinder axis
+ *   - \b point_on_axis.y  : the Y coordinate of a point located on the cylinder axis
+ *   - \b point_on_axis.z  : the Z coordinate of a point located on the cylinder axis
+ *   - \b axis_direction.x : the X coordinate of the cylinder's axis direction
+ *   - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
+ *   - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
+ *   - \b radius           : the cylinder's radius
+ *
+ * \author Radu Bogdan Rusu
+ * \ingroup sample_consensus
+ */
+template <typename PointT>
+class SampleConsensusModelCircle : public SampleConsensusModel<PointT>
+{
+public:
+    using SampleConsensusModel<PointT>::model_name_;
+    using SampleConsensusModel<PointT>::input_;
+    using SampleConsensusModel<PointT>::indices_;
+    using SampleConsensusModel<PointT>::radius_min_;
+    using SampleConsensusModel<PointT>::radius_max_;
+    using SampleConsensusModel<PointT>::error_sqr_dists_;
+
+    using PointCloud = typename SampleConsensusModel<PointT>::PointCloud;
+    using PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr;
+    using PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr;
+
+    using Ptr = shared_ptr<SampleConsensusModelCircle<PointT> >;
+    using ConstPtr = shared_ptr<const SampleConsensusModelCircle<PointT>>;
+
+    /** \brief Constructor for base SampleConsensusModelCylinder.
+     * \param[in] cloud the input point cloud dataset
+     * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
      */
-   template <typename PointT>
-   class SampleConsensusModelCircle : public SampleConsensusModel<PointT>
-   {
-     public:
-       using SampleConsensusModel<PointT>::model_name_;
-       using SampleConsensusModel<PointT>::input_;
-       using SampleConsensusModel<PointT>::indices_;
-       using SampleConsensusModel<PointT>::radius_min_;
-       using SampleConsensusModel<PointT>::radius_max_;
-       using SampleConsensusModel<PointT>::error_sqr_dists_;
-  
-       using PointCloud = typename SampleConsensusModel<PointT>::PointCloud;
-       using PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr;
-       using PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr;
-  
-       using Ptr = shared_ptr<SampleConsensusModelCircle<PointT> >;
-       using ConstPtr = shared_ptr<const SampleConsensusModelCircle<PointT>>;
-  
-       /** \brief Constructor for base SampleConsensusModelCylinder.
-         * \param[in] cloud the input point cloud dataset
-         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
-         */
-       SampleConsensusModelCircle (const PointCloudConstPtr &cloud, bool random = false) 
-         : SampleConsensusModel<PointT> (cloud, random)
-         , axis_ (Eigen::Vector3f::Zero ())
-         , eps_angle_ (INFINITY)
-       {
-         model_name_ = "SampleConsensusModelCircle";
-         sample_size_ = 3;
-         model_size_ = 3;
-       }
-  
-       /** \brief Constructor for base SampleConsensusModelCylinder.
-         * \param[in] cloud the input point cloud dataset
-         * \param[in] indices a vector of point indices to be used from \a cloud
-         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
-         */
-       SampleConsensusModelCircle (const PointCloudConstPtr &cloud, 
-                                     const Indices &indices,
-                                     bool random = false) 
-         : SampleConsensusModel<PointT> (cloud, indices, random)
-         , axis_ (Eigen::Vector3f::Zero ())
-         , eps_angle_ (0)
-       {
-         model_name_ = "SampleConsensusModelCircle";
-         sample_size_ = 3;
-         model_size_ = 3;
-       }
-  
-       /** \brief Copy constructor.
-         * \param[in] source the model to copy into this
-         */
-       SampleConsensusModelCircle (const SampleConsensusModelCircle &source) :
-         SampleConsensusModel<PointT> (),
-         axis_ (Eigen::Vector3f::Zero ()),
-         eps_angle_ (0)
-       {
-         *this = source;
-         model_name_ = "SampleConsensusModelCircle";
-       }
-       
-       /** \brief Empty destructor */
-       ~SampleConsensusModelCircle () {}
-  
-       /** \brief Copy constructor.
+    SampleConsensusModelCircle (const PointCloudConstPtr &cloud, bool random = false)
+        : SampleConsensusModel<PointT> (cloud, random)
+        , axis_ (Eigen::Vector3f::Zero ())
+        , eps_angle_ (INFINITY)
+    {
+        model_name_ = "SampleConsensusModelCircle";
+        sample_size_ = 3;
+        model_size_ = 3;
+    }
+
+    /** \brief Constructor for base SampleConsensusModelCylinder.
+     * \param[in] cloud the input point cloud dataset
+     * \param[in] indices a vector of point indices to be used from \a cloud
+     * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+     */
+    SampleConsensusModelCircle (const PointCloudConstPtr &cloud,
+                                const Indices &indices,
+                                bool random = false)
+        : SampleConsensusModel<PointT> (cloud, indices, random)
+        , axis_ (Eigen::Vector3f::Zero ())
+        , eps_angle_ (0)
+    {
+        model_name_ = "SampleConsensusModelCircle";
+        sample_size_ = 3;
+        model_size_ = 3;
+    }
+
+    /** \brief Copy constructor.
+     * \param[in] source the model to copy into this
+     */
+    SampleConsensusModelCircle (const SampleConsensusModelCircle &source) :
+        SampleConsensusModel<PointT> (),
+        axis_ (Eigen::Vector3f::Zero ()),
+        eps_angle_ (0)
+    {
+        *this = source;
+        model_name_ = "SampleConsensusModelCircle";
+    }
+
+    /** \brief Empty destructor */
+    ~SampleConsensusModelCircle () {}
+
+    /** \brief Copy constructor.
          * \param[in] source the model to copy into this
          */
-       inline SampleConsensusModelCircle&
-       operator = (const SampleConsensusModelCircle &source)
-       {
-         SampleConsensusModel<PointT>::operator=(source);
-         axis_ = source.axis_;
-         eps_angle_ = source.eps_angle_;
-         return (*this);
-       }
-  
-       /** \brief Set the angle epsilon (delta) threshold.
-         * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
-         */
-       inline void 
-       setEpsAngle (const double ea) { eps_angle_ = ea; }
-  
-       /** \brief Get the angle epsilon (delta) threshold. */
-       inline double 
-       getEpsAngle () const { return (eps_angle_); }
-  
-       /** \brief Set the axis along which we need to search for a cylinder direction.
-         * \param[in] ax the axis along which we need to search for a cylinder direction
-         */
-       inline void 
-       setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
-  
-       /** \brief Get the axis along which we need to search for a cylinder direction. */
-       inline Eigen::Vector3f 
-       getAxis () const { return (axis_); }
-  
-       /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
-         * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
-         * axis_direction, cylinder_radius_R
-         * \param[in] samples the point indices found as possible good candidates for creating a valid model
-         * \param[out] model_coefficients the resultant model coefficients
-         */
-       bool
-       computeModelCoefficients (const Indices &samples,
-                                 Eigen::VectorXf &model_coefficients) const override;
-  
-       /** \brief Compute all distances from the cloud data to a given cylinder model.
-         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
-         * \param[out] distances the resultant estimated distances
-         */
-       void
-       getDistancesToModel (const Eigen::VectorXf &model_coefficients,
-                            std::vector<double> &distances) const override;
-  
-       /** \brief Select all the points which respect the given model coefficients as inliers.
-         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
-         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
-         * \param[out] inliers the resultant model inliers
-         */
-       void 
-       selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
-                             const double threshold, 
-                             Indices &inliers) override;
-  
-       /** \brief Count all the points which respect the given model coefficients as inliers. 
-         * 
-         * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
-         * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
-         * \return the resultant number of inliers
-         */
-       std::size_t
-       countWithinDistance (const Eigen::VectorXf &model_coefficients,
-                            const double threshold) const override;
-  
-       /** \brief Recompute the cylinder coefficients using the given inlier set and return them to the user.
-         * @note: these are the coefficients of the cylinder model after refinement (e.g. after SVD)
-         * \param[in] inliers the data inliers found as supporting the model
-         * \param[in] model_coefficients the initial guess for the optimization
-         * \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization
-         */
-       void
-       optimizeModelCoefficients (const Indices &inliers,
-                                  const Eigen::VectorXf &model_coefficients,
-                                  Eigen::VectorXf &optimized_coefficients) const override;
-  
-  
-       /** \brief Create a new point cloud with inliers projected onto the cylinder model.
-         * \param[in] inliers the data inliers that we want to project on the cylinder model
-         * \param[in] model_coefficients the coefficients of a cylinder model
-         * \param[out] projected_points the resultant projected points
-         * \param[in] copy_data_fields set to true if we need to copy the other data fields
-         */
-       void
-       projectPoints (const Indices &inliers,
-                      const Eigen::VectorXf &model_coefficients,
-                      PointCloud &projected_points,
-                      bool copy_data_fields = true) const override;
-  
-       /** \brief Verify whether a subset of indices verifies the given cylinder model coefficients.
-         * \param[in] indices the data indices that need to be tested against the cylinder model
-         * \param[in] model_coefficients the cylinder model coefficients
-         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
-         */
-       bool
-       doSamplesVerifyModel (const std::set<int> &indices,
-                             const Eigen::VectorXf &model_coefficients,
-                             const double threshold) const override;
-  
-       /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
-       inline pcl::SacModel 
-       getModelType () const override { return (SACMODEL_CYLINDER); } //cannot add a unique identifier for double line
-  
-     protected:
-       using SampleConsensusModel<PointT>::sample_size_;
-       using SampleConsensusModel<PointT>::model_size_;
-  
-       /** \brief Get the distance from a point to a line (represented by a point and a direction)
-         * \param[in] pt a point
-         * \param[in] model_coefficients the line coefficients (a point on the line, line direction)
-         */
-       double
-       pointToLineDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const;
-  
-       /** \brief Project a point onto a line given by a point and a direction vector
-         * \param[in] pt the input point to project
-         * \param[in] line_pt the point on the line (make sure that line_pt[3] = 0 as there are no internal checks!)
-         * \param[in] line_dir the direction of the line (make sure that line_dir[3] = 0 as there are no internal checks!)
-         * \param[out] pt_proj the resultant projected point
-         */
-       inline void
-       projectPointToLine (const Eigen::Vector4f &pt,
-                           const Eigen::Vector4f &line_pt,
-                           const Eigen::Vector4f &line_dir,
-                           Eigen::Vector4f &pt_proj) const
-       {
-         float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
-         // Calculate the projection of the point on the line
-         pt_proj = line_pt + k * line_dir;
-       }
-  
-       /** \brief Project a point onto a cylinder given by its model coefficients (point_on_axis, axis_direction,
-         * cylinder_radius_R)
-         * \param[in] pt the input point to project
-         * \param[in] model_coefficients the coefficients of the cylinder (point_on_axis, axis_direction, cylinder_radius_R)
-         * \param[out] pt_proj the resultant projected point
-         */
-       void
-       projectPointToRectangle (const Eigen::Vector4f &pt,
+    inline SampleConsensusModelCircle&
+    operator = (const SampleConsensusModelCircle &source)
+    {
+        SampleConsensusModel<PointT>::operator=(source);
+        axis_ = source.axis_;
+        eps_angle_ = source.eps_angle_;
+        return (*this);
+    }
+
+    /** \brief Set the angle epsilon (delta) threshold.
+     * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
+     */
+    inline void
+    setEpsAngle (const double ea) { eps_angle_ = ea; }
+
+    /** \brief Get the angle epsilon (delta) threshold. */
+    inline double
+    getEpsAngle () const { return (eps_angle_); }
+
+    /** \brief Set the axis along which we need to search for a cylinder direction.
+     * \param[in] ax the axis along which we need to search for a cylinder direction
+     */
+    inline void
+    setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
+
+    /** \brief Get the axis along which we need to search for a cylinder direction. */
+    inline Eigen::Vector3f
+    getAxis () const { return (axis_); }
+
+    /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
+     * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
+     * axis_direction, cylinder_radius_R
+     * \param[in] samples the point indices found as possible good candidates for creating a valid model
+     * \param[out] model_coefficients the resultant model coefficients
+     */
+    bool
+    computeModelCoefficients (const Indices &samples,
+                              Eigen::VectorXf &model_coefficients) const override;
+
+    /** \brief Compute all distances from the cloud data to a given cylinder model.
+     * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
+     * \param[out] distances the resultant estimated distances
+     */
+    void
+    getDistancesToModel (const Eigen::VectorXf &model_coefficients,
+                         std::vector<double> &distances) const override;
+
+    /** \brief Select all the points which respect the given model coefficients as inliers.
+     * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
+     * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+     * \param[out] inliers the resultant model inliers
+     */
+    void
+    selectWithinDistance (const Eigen::VectorXf &model_coefficients,
+                          const double threshold,
+                          Indices &inliers) override;
+
+    /** \brief Count all the points which respect the given model coefficients as inliers.
+     *
+     * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
+     * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
+     * \return the resultant number of inliers
+     */
+    std::size_t
+    countWithinDistance (const Eigen::VectorXf &model_coefficients,
+                         const double threshold) const override;
+
+    /** \brief Recompute the cylinder coefficients using the given inlier set and return them to the user.
+     * @note: these are the coefficients of the cylinder model after refinement (e.g. after SVD)
+     * \param[in] inliers the data inliers found as supporting the model
+     * \param[in] model_coefficients the initial guess for the optimization
+     * \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization
+     */
+    void
+    optimizeModelCoefficients (const Indices &inliers,
                                const Eigen::VectorXf &model_coefficients,
-                               Eigen::Vector4f &pt_proj) const;
-  
-       /** \brief Check whether a model is valid given the user constraints.
-         * \param[in] model_coefficients the set of model coefficients
+                               Eigen::VectorXf &optimized_coefficients) const override;
+
+
+    /** \brief Create a new point cloud with inliers projected onto the cylinder model.
+     * \param[in] inliers the data inliers that we want to project on the cylinder model
+     * \param[in] model_coefficients the coefficients of a cylinder model
+     * \param[out] projected_points the resultant projected points
+     * \param[in] copy_data_fields set to true if we need to copy the other data fields
+     */
+    void
+    projectPoints (const Indices &inliers,
+                   const Eigen::VectorXf &model_coefficients,
+                   PointCloud &projected_points,
+                   bool copy_data_fields = true) const override;
+
+    /** \brief Verify whether a subset of indices verifies the given cylinder model coefficients.
+     * \param[in] indices the data indices that need to be tested against the cylinder model
+     * \param[in] model_coefficients the cylinder model coefficients
+     * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+     */
+    bool
+    doSamplesVerifyModel (const std::set<int> &indices,
+                          const Eigen::VectorXf &model_coefficients,
+                          const double threshold) const override;
+
+    /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
+    inline pcl::SacModel
+    getModelType () const override { return (SACMODEL_CYLINDER); } //cannot add a unique identifier for double line
+
+protected:
+    using SampleConsensusModel<PointT>::sample_size_;
+    using SampleConsensusModel<PointT>::model_size_;
+
+    /** \brief Get the distance from a point to a line (represented by a point and a direction)
+     * \param[in] pt a point
+     * \param[in] model_coefficients the line coefficients (a point on the line, line direction)
+     */
+    double
+    pointToLineDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const;
+
+    /** \brief Project a point onto a line given by a point and a direction vector
+     * \param[in] pt the input point to project
+     * \param[in] line_pt the point on the line (make sure that line_pt[3] = 0 as there are no internal checks!)
+     * \param[in] line_dir the direction of the line (make sure that line_dir[3] = 0 as there are no internal checks!)
+     * \param[out] pt_proj the resultant projected point
+     */
+    inline void
+    projectPointToLine (const Eigen::Vector4f &pt,
+                        const Eigen::Vector4f &line_pt,
+                        const Eigen::Vector4f &line_dir,
+                        Eigen::Vector4f &pt_proj) const
+    {
+        float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
+        // Calculate the projection of the point on the line
+        pt_proj = line_pt + k * line_dir;
+    }
+
+    /** \brief Project a point onto a cylinder given by its model coefficients (point_on_axis, axis_direction,
+     * cylinder_radius_R)
+     * \param[in] pt the input point to project
+     * \param[in] model_coefficients the coefficients of the cylinder (point_on_axis, axis_direction, cylinder_radius_R)
+     * \param[out] pt_proj the resultant projected point
+     */
+    void
+    projectPointToRectangle (const Eigen::Vector4f &pt,
+                             const Eigen::VectorXf &model_coefficients,
+                             Eigen::Vector4f &pt_proj) const;
+
+    /** \brief Check whether a model is valid given the user constraints.
+     * \param[in] model_coefficients the set of model coefficients
+     */
+    bool
+    isModelValid (const Eigen::VectorXf &model_coefficients) const override;
+
+    /** \brief Check if a sample of indices results in a good sample of points
+     * indices. Pure virtual.
+     * \param[in] samples the resultant index samples
+     */
+    bool
+    isSampleGood (const Indices &samples) const override;
+
+private:
+    /** \brief The axis along which we need to search for a cylinder direction. */
+    Eigen::Vector3f axis_;
+
+    /** \brief The maximum allowed difference between the cylinder direction and the given axis. */
+    double eps_angle_;
+
+    /** \brief Functor for the optimization function */
+    struct OptimizationFunctor : pcl::Functor<float>
+    {
+        /** Functor constructor
+         * \param[in] indices the indices of data points to evaluate
+         * \param[in] estimator pointer to the estimator object
          */
-       bool
-       isModelValid (const Eigen::VectorXf &model_coefficients) const override;
-  
-       /** \brief Check if a sample of indices results in a good sample of points
-         * indices. Pure virtual.
-         * \param[in] samples the resultant index samples
+        OptimizationFunctor (const pcl::SampleConsensusModelCircle<PointT> *model, const Indices& indices) :
+            pcl::Functor<float> (indices.size ()), model_ (model), indices_ (indices) {}
+
+        /** Cost function to be minimized
+         * \param[in] x variables array
+         * \param[out] fvec resultant functions evaluations
+         * \return 0
          */
-       bool
-       isSampleGood (const Indices &samples) const override;
-  
-     private:
-       /** \brief The axis along which we need to search for a cylinder direction. */
-       Eigen::Vector3f axis_;
-     
-       /** \brief The maximum allowed difference between the cylinder direction and the given axis. */
-       double eps_angle_;
-  
-       /** \brief Functor for the optimization function */
-       struct OptimizationFunctor : pcl::Functor<float>
-       {
-         /** Functor constructor
-           * \param[in] indices the indices of data points to evaluate
-           * \param[in] estimator pointer to the estimator object
-           */
-         OptimizationFunctor (const pcl::SampleConsensusModelCircle<PointT> *model, const Indices& indices) :
-           pcl::Functor<float> (indices.size ()), model_ (model), indices_ (indices) {}
-  
-         /** Cost function to be minimized
-           * \param[in] x variables array
-           * \param[out] fvec resultant functions evaluations
-           * \return 0
-           */
-         int 
-         operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
-         {
-           Eigen::Vector4f line_pt  (x[0], x[1], x[2], 0);
-           Eigen::Vector4f line_dir (x[3], x[4], x[5], 0);
-           
-           for (int i = 0; i < values (); ++i)
-           {
-             // dist = f - r
-             Eigen::Vector4f pt = (*model_->input_)[indices_[i]].getVector4fMap();
-             pt[3] = 0;
-  
-             fvec[i] = static_cast<float> (pcl::sqrPointToLineDistance (pt, line_pt, line_dir) - x[6]*x[6]);
-           }
-           return (0);
-         }
-  
-         const pcl::SampleConsensusModelCircle<PointT> *model_;
-         const Indices &indices_;
-       };
-   };
- }
-  
- //#ifdef PCL_NO_PRECOMPILE
- #include "ed_sensor_integration/sac_model_circle.hpp"
- //#endif
+        int
+        operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
+        {
+            Eigen::Vector4f line_pt  (x[0], x[1], x[2], 0);
+            Eigen::Vector4f line_dir (x[3], x[4], x[5], 0);
+
+            for (int i = 0; i < values (); ++i)
+            {
+                // dist = f - r
+                Eigen::Vector4f pt = (*model_->input_)[indices_[i]].getVector4fMap();
+                pt[3] = 0;
+
+                fvec[i] = static_cast<float> (pcl::sqrPointToLineDistance (pt, line_pt, line_dir) - x[6]*x[6]);
+            }
+            return (0);
+        }
+
+        const pcl::SampleConsensusModelCircle<PointT> *model_;
+        const Indices &indices_;
+    };
+};
+}
+
+//#ifdef PCL_NO_PRECOMPILE
+#include "ed_sensor_integration/sac_model_circle.hpp"
+//#endif
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp
index 968cb988..54028d16 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp
@@ -1,4 +1,4 @@
- /*
+/*
   * Software License Agreement (BSD License)
   *
   *  Point Cloud Library (PCL) - www.pointclouds.org
@@ -37,108 +37,108 @@
   * $Id$
   *
   */
-  
- #ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_CIRCLE_H_
- #define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_CIRCLE_H_
-  
- #include <unsupported/Eigen/NonLinearOptimization> // for LevenbergMarquardt
- #include "ed_sensor_integration/sac_model_circle.h"
- #include <pcl/common/common.h> // for getAngle3D
- #include <pcl/common/concatenate.h>
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool
- pcl::SampleConsensusModelCircle<PointT>::isSampleGood (const Indices &samples) const
- {
-   if (samples.size () != sample_size_)
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelCircle::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
-     return (false);
-   }
-   return (true);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool
- pcl::SampleConsensusModelCircle<PointT>::computeModelCoefficients (
-       const Indices &samples, Eigen::VectorXf &model_coefficients) const
- {
-   // Need 3 samples
-   if (samples.size () != sample_size_)
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelCircle::computeModelCoefficients] Invalid set of samples given (%lu)!\n", samples.size ());
-     return (false);
-   }
-  
-   if (std::abs ((*input_)[samples[0]].x - (*input_)[samples[1]].x) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].y - (*input_)[samples[1]].y) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].z - (*input_)[samples[1]].z) <= std::numeric_limits<float>::epsilon () ||
-       std::abs ((*input_)[samples[1]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[1]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[1]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon () ||
-       std::abs ((*input_)[samples[0]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon ()) 
-   {
-     return (false);
-   }
-   Eigen::Vector2f p1 ((*input_)[samples[0]].x, (*input_)[samples[0]].y);
-   Eigen::Vector2f p2 ((*input_)[samples[1]].x, (*input_)[samples[1]].y);
-   Eigen::Vector2f p3 ((*input_)[samples[2]].x, (*input_)[samples[2]].y);
-   
-   float x, y, l, r;
-   
-   float denominator = 2*(p1(0)*(p2(1)-p3(1)) - p1(1)*(p2(0)-p3(0)) + p2(0)*p3(1) - p3(0)*p2(1));
-   x = (p1.dot(p1)*(p2(1)-p3(1)) + p2.dot(p2)*(p3(1)-p1(1)) + p3.dot(p3)*(p1(1)-p2(1))) / denominator;
-   y = (p1.dot(p1)*(p2(0)-p3(0)) + p2.dot(p2)*(p3(0)-p1(0)) + p3.dot(p3)*(p1(0)-p2(0))) / denominator;
-   
-   Eigen::Vector2f d;
-   d(0) = x-p1(0);
-   d(1) = y-p1(1);
-   r = sqrt(d.dot(d));
-	   
-   //save model coefficients
-   model_coefficients.resize (model_size_);
-   model_coefficients[0] = x;
-   model_coefficients[1] = y;
-   model_coefficients[2] = r;
-   
-   PCL_DEBUG ("[pcl::SampleConsensusModelCircle::computeModelCoefficients] Model is (%g,%g,%g).\n",
-              model_coefficients[0], model_coefficients[1], model_coefficients[2]);
-   //std::cout << "P1: " << std::endl << p1 << std::endl << "P2: " << std::endl << p2 << std::endl << "P3: " << std::endl << p3 << std::endl << model_coefficients << std::endl;
-   return (true);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelCircle<PointT>::getDistancesToModel (
-       const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
- {
-   // Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-   {
-     distances.clear ();
-     return;
-   }
-  
-   distances.resize (indices_->size ());
-   
-   float x = model_coefficients[0], y = model_coefficients[1], r = model_coefficients[2];
-
-   Eigen::Vector2f p1, c1;
-   p1(0) = x;
-   p1(1) = y;
-   
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-	   Eigen::Vector2f in ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y);
-	   c1 = p1 - in;
-	   distances[i] = std::abs(sqrt(c1.dot(c1))-r);
-		
-		//std::cout << distances[i] << std::endl;
-   }
-   //std::cout << std::accumulate(distances.begin(), distances.end(), 0.0) / distances.size() << ", ";
-  /*
+
+#ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_CIRCLE_H_
+#define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_CIRCLE_H_
+
+#include <unsupported/Eigen/NonLinearOptimization> // for LevenbergMarquardt
+#include "ed_sensor_integration/sac_model_circle.h"
+#include <pcl/common/common.h> // for getAngle3D
+#include <pcl/common/concatenate.h>
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> bool
+pcl::SampleConsensusModelCircle<PointT>::isSampleGood (const Indices &samples) const
+{
+    if (samples.size () != sample_size_)
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelCircle::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
+        return (false);
+    }
+    return (true);
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> bool
+pcl::SampleConsensusModelCircle<PointT>::computeModelCoefficients (
+        const Indices &samples, Eigen::VectorXf &model_coefficients) const
+{
+    // Need 3 samples
+    if (samples.size () != sample_size_)
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelCircle::computeModelCoefficients] Invalid set of samples given (%lu)!\n", samples.size ());
+        return (false);
+    }
+
+    if (std::abs ((*input_)[samples[0]].x - (*input_)[samples[1]].x) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[0]].y - (*input_)[samples[1]].y) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[0]].z - (*input_)[samples[1]].z) <= std::numeric_limits<float>::epsilon () ||
+            std::abs ((*input_)[samples[1]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[1]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[1]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon () ||
+            std::abs ((*input_)[samples[0]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[0]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[0]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon ())
+    {
+        return (false);
+    }
+    Eigen::Vector2f p1 ((*input_)[samples[0]].x, (*input_)[samples[0]].y);
+    Eigen::Vector2f p2 ((*input_)[samples[1]].x, (*input_)[samples[1]].y);
+    Eigen::Vector2f p3 ((*input_)[samples[2]].x, (*input_)[samples[2]].y);
+
+    float x, y, l, r;
+
+    float denominator = 2*(p1(0)*(p2(1)-p3(1)) - p1(1)*(p2(0)-p3(0)) + p2(0)*p3(1) - p3(0)*p2(1));
+    x = (p1.dot(p1)*(p2(1)-p3(1)) + p2.dot(p2)*(p3(1)-p1(1)) + p3.dot(p3)*(p1(1)-p2(1))) / denominator;
+    y = (p1.dot(p1)*(p2(0)-p3(0)) + p2.dot(p2)*(p3(0)-p1(0)) + p3.dot(p3)*(p1(0)-p2(0))) / denominator;
+
+    Eigen::Vector2f d;
+    d(0) = x-p1(0);
+    d(1) = y-p1(1);
+    r = sqrt(d.dot(d));
+
+    //save model coefficients
+    model_coefficients.resize (model_size_);
+    model_coefficients[0] = x;
+    model_coefficients[1] = y;
+    model_coefficients[2] = r;
+
+    PCL_DEBUG ("[pcl::SampleConsensusModelCircle::computeModelCoefficients] Model is (%g,%g,%g).\n",
+               model_coefficients[0], model_coefficients[1], model_coefficients[2]);
+    //std::cout << "P1: " << std::endl << p1 << std::endl << "P2: " << std::endl << p2 << std::endl << "P3: " << std::endl << p3 << std::endl << model_coefficients << std::endl;
+    return (true);
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelCircle<PointT>::getDistancesToModel (
+        const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
+{
+    // Check if the model is valid given the user constraints
+    if (!isModelValid (model_coefficients))
+    {
+        distances.clear ();
+        return;
+    }
+
+    distances.resize (indices_->size ());
+
+    float x = model_coefficients[0], y = model_coefficients[1], r = model_coefficients[2];
+
+    Eigen::Vector2f p1, c1;
+    p1(0) = x;
+    p1(1) = y;
+
+    for (std::size_t i = 0; i < indices_->size (); ++i)
+    {
+        Eigen::Vector2f in ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y);
+        c1 = p1 - in;
+        distances[i] = std::abs(sqrt(c1.dot(c1))-r);
+
+        //std::cout << distances[i] << std::endl;
+    }
+    //std::cout << std::accumulate(distances.begin(), distances.end(), 0.0) / distances.size() << ", ";
+    /*
    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
    float ptdotdir = line_pt.dot (line_dir);
@@ -150,49 +150,49 @@
      // dist(point,cylinder_axis) and cylinder radius
      // @note need to revise this.
      Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
-  
+
      const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
-  
+
      // Calculate the point's projection on the cylinder axis
      float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
      Eigen::Vector4f pt_proj = line_pt + k * line_dir;
      Eigen::Vector4f dir = pt - pt_proj;
      dir.normalize ();
-  
+
      // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
      Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
      double d_normal = std::abs (getAngle3D (n, dir));
      d_normal = (std::min) (d_normal, M_PI - d_normal);
-  
+
      distances[i] = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);*/
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelCircle<PointT>::selectWithinDistance (
-       const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
- {
-   std::vector<double> distances;
-   getDistancesToModel (model_coefficients, distances);
-   for (int i = 0; i < distances.size(); i++)
-   {
-	   if (distances[i] < threshold) {inliers.push_back ((*indices_)[i]);}
-   }
-   
-   //std::cout << model_coefficients[2] << std::endl;
-   /*
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelCircle<PointT>::selectWithinDistance (
+        const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
+{
+    std::vector<double> distances;
+    getDistancesToModel (model_coefficients, distances);
+    for (int i = 0; i < distances.size(); i++)
+    {
+        if (distances[i] < threshold) {inliers.push_back ((*indices_)[i]);}
+    }
+
+    //std::cout << model_coefficients[2] << std::endl;
+    /*
    // Check if the model is valid given the user constraints
    if (!isModelValid (model_coefficients))
    {
      inliers.clear ();
      return;
    }
-  
+
    inliers.clear ();
    error_sqr_dists_.clear ();
    inliers.reserve (indices_->size ());
    error_sqr_dists_.reserve (indices_->size ());
-  
+
    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
    float ptdotdir = line_pt.dot (line_dir);
@@ -206,18 +206,18 @@
      const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
      if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
        continue;
-  
+
      // Calculate the point's projection on the cylinder axis
      float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
      Eigen::Vector4f pt_proj = line_pt + k * line_dir;
      Eigen::Vector4f dir = pt - pt_proj;
      dir.normalize ();
-  
+
      // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
      Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
      double d_normal = std::abs (getAngle3D (n, dir));
      d_normal = (std::min) (d_normal, M_PI - d_normal);
-  
+
      double distance = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);
      if (distance < threshold)
      {
@@ -226,28 +226,28 @@
        error_sqr_dists_.push_back (distance);
      }
    }*/
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> std::size_t
- pcl::SampleConsensusModelCircle<PointT>::countWithinDistance (
-       const Eigen::VectorXf &model_coefficients, const double threshold) const
- {
-   std::vector<double> distances;
-   getDistancesToModel (model_coefficients, distances);
-   int count = 0;
-   for (int i = 0; i < distances.size(); i++)
-   {
-	   if (distances[i] <= threshold) {count++;}
-   }
-   //std::cout << count << std::endl;
-   return (count);
-   /*// Check if the model is valid given the user constraints
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> std::size_t
+pcl::SampleConsensusModelCircle<PointT>::countWithinDistance (
+        const Eigen::VectorXf &model_coefficients, const double threshold) const
+{
+    std::vector<double> distances;
+    getDistancesToModel (model_coefficients, distances);
+    int count = 0;
+    for (int i = 0; i < distances.size(); i++)
+    {
+        if (distances[i] <= threshold) {count++;}
+    }
+    //std::cout << count << std::endl;
+    return (count);
+    /*// Check if the model is valid given the user constraints
    if (!isModelValid (model_coefficients))
      return (0);
-  
+
    std::size_t nr_p = 0;
-  
+
    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);
    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
    float ptdotdir = line_pt.dot (line_dir);
@@ -261,217 +261,217 @@
      const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
      if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
        continue;
-  
+
      // Calculate the point's projection on the cylinder axis
      float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
      Eigen::Vector4f pt_proj = line_pt + k * line_dir;
      Eigen::Vector4f dir = pt - pt_proj;
      dir.normalize ();
-  
+
      // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
      Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
      double d_normal = std::abs (getAngle3D (n, dir));
      d_normal = (std::min) (d_normal, M_PI - d_normal);
-  
+
      if (std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist) < threshold)
        nr_p++;
    }
    return (nr_p);*/
-   return (0);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelCircle<PointT>::optimizeModelCoefficients (
-       const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
- {
-   optimized_coefficients = model_coefficients;
-  
-   // Needs a set of valid model coefficients
-   if (!isModelValid (model_coefficients))
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelCircle::optimizeModelCoefficients] Given model is invalid!\n");
-     return;
-   }
-  
-   // Need more than the minimum sample size to make a difference
-   if (inliers.size () <= sample_size_)
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelCircle:optimizeModelCoefficients] Not enough inliers found to optimize model coefficients (%lu)! Returning the same coefficients.\n", inliers.size ());
-     return;
-   }
-  
-   OptimizationFunctor functor (this, inliers);
-   Eigen::NumericalDiff<OptimizationFunctor > num_diff (functor);
-   Eigen::LevenbergMarquardt<Eigen::NumericalDiff<OptimizationFunctor>, float> lm (num_diff);
-   int info = lm.minimize (optimized_coefficients);
-   
-   // Compute the L2 norm of the residuals
-   PCL_DEBUG ("[pcl::SampleConsensusModelCircle::optimizeModelCoefficients] LM solver finished with exit code %i, having a residual norm of %g. \nInitial solution: %g %g %g %g %g %g %g \nFinal solution: %g %g %g %g %g %g %g\n",
-              info, lm.fvec.norm (), model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
-              model_coefficients[4], model_coefficients[5], model_coefficients[6], optimized_coefficients[0], optimized_coefficients[1], optimized_coefficients[2], optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5], optimized_coefficients[6]);
-     
-   Eigen::Vector3f line_dir (optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5]);
-   line_dir.normalize ();
-   optimized_coefficients[3] = line_dir[0];
-   optimized_coefficients[4] = line_dir[1];
-   optimized_coefficients[5] = line_dir[2];
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelCircle<PointT>::projectPoints (
-       const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
- {
-   // Needs a valid set of model coefficients
-   if (!isModelValid (model_coefficients))
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelCircle::projectPoints] Given model is invalid!\n");
-     return;
-   }
-  
-   projected_points.header = input_->header;
-   projected_points.is_dense = input_->is_dense;
-  
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-  
-   // Copy all the data fields from the input cloud to the projected one?
-   if (copy_data_fields)
-   {
-     // Allocate enough space and copy the basics
-     projected_points.resize (input_->size ());
-     projected_points.width    = input_->width;
-     projected_points.height   = input_->height;
-  
-     using FieldList = typename pcl::traits::fieldList<PointT>::type;
-     // Iterate over each point
-     for (std::size_t i = 0; i < projected_points.size (); ++i)
-       // Iterate over each dimension
-       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
-  
-     // Iterate through the 3d points and calculate the distances from them to the cylinder
-     for (const auto &inlier : inliers)
-     {
-       Eigen::Vector4f p ((*input_)[inlier].x,
-                          (*input_)[inlier].y,
-                          (*input_)[inlier].z,
-                          1);
-  
-       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
-  
-       pcl::Vector4fMap pp = projected_points[inlier].getVector4fMap ();
-       pp.matrix () = line_pt + k * line_dir;
-  
-       Eigen::Vector4f dir = p - pp;
-       dir[3] = 0.0f;
-       dir.normalize ();
-  
-       // Calculate the projection of the point onto the cylinder
-       pp += dir * model_coefficients[6];
-     }
-   }
-   else
-   {
-     // Allocate enough space and copy the basics
-     projected_points.resize (inliers.size ());
-     projected_points.width    = inliers.size ();
-     projected_points.height   = 1;
-  
-     using FieldList = typename pcl::traits::fieldList<PointT>::type;
-     // Iterate over each point
-     for (std::size_t i = 0; i < inliers.size (); ++i)
-       // Iterate over each dimension
-       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
-  
-     // Iterate through the 3d points and calculate the distances from them to the cylinder
-     for (std::size_t i = 0; i < inliers.size (); ++i)
-     {
-       pcl::Vector4fMap pp = projected_points[i].getVector4fMap ();
-       pcl::Vector4fMapConst p = (*input_)[inliers[i]].getVector4fMap ();
-  
-       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
-       // Calculate the projection of the point on the line
-       pp.matrix () = line_pt + k * line_dir;
-  
-       Eigen::Vector4f dir = p - pp;
-       dir[3] = 0.0f;
-       dir.normalize ();
-  
-       // Calculate the projection of the point onto the cylinder
-       pp += dir * model_coefficients[6];
-     }
-   }
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool
- pcl::SampleConsensusModelCircle<PointT>::doSamplesVerifyModel (
-       const std::set<int> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
- {
-   // Needs a valid model coefficients
-   if (!isModelValid (model_coefficients))
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelCircle::doSamplesVerifyModel] Given model is invalid!\n");
-     return (false);
-   }
-  
-   for (const auto &index : indices)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     // @note need to revise this.
-     Eigen::Vector4f pt ((*input_)[index].x, (*input_)[index].y, (*input_)[index].z, 0.0f);
-     if (std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]) > threshold)
-       return (false);
-   }
-  
-   return (true);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> double
- pcl::SampleConsensusModelCircle<PointT>::pointToLineDistance (
-       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const
- {
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   return sqrt(pcl::sqrPointToLineDistance (pt, line_pt, line_dir));
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelCircle<PointT>::projectPointToRectangle (
-       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients, Eigen::Vector4f &pt_proj) const
- {
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-  
-   float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) * line_dir.dot (line_dir);
-   pt_proj = line_pt + k * line_dir;
-  
-   Eigen::Vector4f dir = pt - pt_proj;
-   dir.normalize ();
-  
-   // Calculate the projection of the point onto the cylinder
-   pt_proj += dir * model_coefficients[6];
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool 
- pcl::SampleConsensusModelCircle<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
- {
-   if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
-     return (false);
-  /*
+    return (0);
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelCircle<PointT>::optimizeModelCoefficients (
+        const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
+{
+    optimized_coefficients = model_coefficients;
+
+    // Needs a set of valid model coefficients
+    if (!isModelValid (model_coefficients))
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelCircle::optimizeModelCoefficients] Given model is invalid!\n");
+        return;
+    }
+
+    // Need more than the minimum sample size to make a difference
+    if (inliers.size () <= sample_size_)
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelCircle:optimizeModelCoefficients] Not enough inliers found to optimize model coefficients (%lu)! Returning the same coefficients.\n", inliers.size ());
+        return;
+    }
+
+    OptimizationFunctor functor (this, inliers);
+    Eigen::NumericalDiff<OptimizationFunctor > num_diff (functor);
+    Eigen::LevenbergMarquardt<Eigen::NumericalDiff<OptimizationFunctor>, float> lm (num_diff);
+    int info = lm.minimize (optimized_coefficients);
+
+    // Compute the L2 norm of the residuals
+    PCL_DEBUG ("[pcl::SampleConsensusModelCircle::optimizeModelCoefficients] LM solver finished with exit code %i, having a residual norm of %g. \nInitial solution: %g %g %g %g %g %g %g \nFinal solution: %g %g %g %g %g %g %g\n",
+               info, lm.fvec.norm (), model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
+            model_coefficients[4], model_coefficients[5], model_coefficients[6], optimized_coefficients[0], optimized_coefficients[1], optimized_coefficients[2], optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5], optimized_coefficients[6]);
+
+    Eigen::Vector3f line_dir (optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5]);
+    line_dir.normalize ();
+    optimized_coefficients[3] = line_dir[0];
+    optimized_coefficients[4] = line_dir[1];
+    optimized_coefficients[5] = line_dir[2];
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelCircle<PointT>::projectPoints (
+        const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
+{
+    // Needs a valid set of model coefficients
+    if (!isModelValid (model_coefficients))
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelCircle::projectPoints] Given model is invalid!\n");
+        return;
+    }
+
+    projected_points.header = input_->header;
+    projected_points.is_dense = input_->is_dense;
+
+    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+    float ptdotdir = line_pt.dot (line_dir);
+    float dirdotdir = 1.0f / line_dir.dot (line_dir);
+
+    // Copy all the data fields from the input cloud to the projected one?
+    if (copy_data_fields)
+    {
+        // Allocate enough space and copy the basics
+        projected_points.resize (input_->size ());
+        projected_points.width    = input_->width;
+        projected_points.height   = input_->height;
+
+        using FieldList = typename pcl::traits::fieldList<PointT>::type;
+        // Iterate over each point
+        for (std::size_t i = 0; i < projected_points.size (); ++i)
+            // Iterate over each dimension
+            pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
+
+        // Iterate through the 3d points and calculate the distances from them to the cylinder
+        for (const auto &inlier : inliers)
+        {
+            Eigen::Vector4f p ((*input_)[inlier].x,
+                               (*input_)[inlier].y,
+                               (*input_)[inlier].z,
+                               1);
+
+            float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
+
+            pcl::Vector4fMap pp = projected_points[inlier].getVector4fMap ();
+            pp.matrix () = line_pt + k * line_dir;
+
+            Eigen::Vector4f dir = p - pp;
+            dir[3] = 0.0f;
+            dir.normalize ();
+
+            // Calculate the projection of the point onto the cylinder
+            pp += dir * model_coefficients[6];
+        }
+    }
+    else
+    {
+        // Allocate enough space and copy the basics
+        projected_points.resize (inliers.size ());
+        projected_points.width    = inliers.size ();
+        projected_points.height   = 1;
+
+        using FieldList = typename pcl::traits::fieldList<PointT>::type;
+        // Iterate over each point
+        for (std::size_t i = 0; i < inliers.size (); ++i)
+            // Iterate over each dimension
+            pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
+
+        // Iterate through the 3d points and calculate the distances from them to the cylinder
+        for (std::size_t i = 0; i < inliers.size (); ++i)
+        {
+            pcl::Vector4fMap pp = projected_points[i].getVector4fMap ();
+            pcl::Vector4fMapConst p = (*input_)[inliers[i]].getVector4fMap ();
+
+            float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
+            // Calculate the projection of the point on the line
+            pp.matrix () = line_pt + k * line_dir;
+
+            Eigen::Vector4f dir = p - pp;
+            dir[3] = 0.0f;
+            dir.normalize ();
+
+            // Calculate the projection of the point onto the cylinder
+            pp += dir * model_coefficients[6];
+        }
+    }
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> bool
+pcl::SampleConsensusModelCircle<PointT>::doSamplesVerifyModel (
+        const std::set<int> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
+{
+    // Needs a valid model coefficients
+    if (!isModelValid (model_coefficients))
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelCircle::doSamplesVerifyModel] Given model is invalid!\n");
+        return (false);
+    }
+
+    for (const auto &index : indices)
+    {
+        // Approximate the distance from the point to the cylinder as the difference between
+        // dist(point,cylinder_axis) and cylinder radius
+        // @note need to revise this.
+        Eigen::Vector4f pt ((*input_)[index].x, (*input_)[index].y, (*input_)[index].z, 0.0f);
+        if (std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]) > threshold)
+            return (false);
+    }
+
+    return (true);
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> double
+pcl::SampleConsensusModelCircle<PointT>::pointToLineDistance (
+        const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const
+{
+    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+    return sqrt(pcl::sqrPointToLineDistance (pt, line_pt, line_dir));
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelCircle<PointT>::projectPointToRectangle (
+        const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients, Eigen::Vector4f &pt_proj) const
+{
+    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+
+    float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) * line_dir.dot (line_dir);
+    pt_proj = line_pt + k * line_dir;
+
+    Eigen::Vector4f dir = pt - pt_proj;
+    dir.normalize ();
+
+    // Calculate the projection of the point onto the cylinder
+    pt_proj += dir * model_coefficients[6];
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> bool
+pcl::SampleConsensusModelCircle<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
+{
+    if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
+        return (false);
+    /*
    // Check against template, if given
    if (eps_angle_ > 0.0)
    {
      // Obtain the cylinder direction
      const Eigen::Vector3f coeff(model_coefficients[3], model_coefficients[4], model_coefficients[5]);
-  
+
      double angle_diff = std::abs (getAngle3D (axis_, coeff));
      angle_diff = (std::min) (angle_diff, M_PI - angle_diff);
      // Check whether the current cylinder model satisfies our angle threshold criterion with respect to the given axis
@@ -481,7 +481,7 @@
        return (false);
      }
    }
-  
+
    if (radius_min_ != -std::numeric_limits<double>::max() && model_coefficients[6] < radius_min_)
    {
      PCL_DEBUG ("[pcl::SampleConsensusModelCircle::isModelValid] Radius is too small: should be larger than %g, but is %g.\n",
@@ -494,10 +494,10 @@
                 radius_max_, model_coefficients[6]);
      return (false);
    }*/
-  
-   return (true);
- }
-  
- #define PCL_INSTANTIATE_SampleConsensusModelCircle(PointT) template class PCL_EXPORTS pcl::SampleConsensusModelCircle<PointT>;
-  
- #endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_CIRCLE_H_
+
+    return (true);
+}
+
+#define PCL_INSTANTIATE_SampleConsensusModelCircle(PointT) template class PCL_EXPORTS pcl::SampleConsensusModelCircle<PointT>;
+
+#endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_CIRCLE_H_
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
index 42d46dcc..2b0a8804 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
@@ -1,4 +1,4 @@
- /*
+/*
   * Software License Agreement (BSD License)
   *
   *  Point Cloud Library (PCL) - www.pointclouds.org
@@ -37,297 +37,297 @@
   * $Id$
   *
   */
-  
- #pragma once
-  
- #include <pcl/sample_consensus/sac_model.h>
- #include <pcl/sample_consensus/model_types.h>
- #include <pcl/common/distances.h>
-  
- namespace pcl
- {
-   /** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
-     * The model coefficients are defined as:
-     *   - \b point_on_axis.x  : the X coordinate of a point located on the cylinder axis
-     *   - \b point_on_axis.y  : the Y coordinate of a point located on the cylinder axis
-     *   - \b point_on_axis.z  : the Z coordinate of a point located on the cylinder axis
-     *   - \b axis_direction.x : the X coordinate of the cylinder's axis direction
-     *   - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
-     *   - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
-     *   - \b radius           : the cylinder's radius
-     * 
-     * \author Radu Bogdan Rusu
-     * \ingroup sample_consensus
+
+#pragma once
+
+#include <pcl/sample_consensus/sac_model.h>
+#include <pcl/sample_consensus/model_types.h>
+#include <pcl/common/distances.h>
+
+namespace pcl
+{
+/** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
+ * The model coefficients are defined as:
+ *   - \b point_on_axis.x  : the X coordinate of a point located on the cylinder axis
+ *   - \b point_on_axis.y  : the Y coordinate of a point located on the cylinder axis
+ *   - \b point_on_axis.z  : the Z coordinate of a point located on the cylinder axis
+ *   - \b axis_direction.x : the X coordinate of the cylinder's axis direction
+ *   - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
+ *   - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
+ *   - \b radius           : the cylinder's radius
+ *
+ * \author Radu Bogdan Rusu
+ * \ingroup sample_consensus
+ */
+template <typename PointT>
+class SampleConsensusModelDoubleLine : public SampleConsensusModel<PointT>
+{
+public:
+    using SampleConsensusModel<PointT>::model_name_;
+    using SampleConsensusModel<PointT>::input_;
+    using SampleConsensusModel<PointT>::indices_;
+    using SampleConsensusModel<PointT>::radius_min_;
+    using SampleConsensusModel<PointT>::radius_max_;
+    using SampleConsensusModel<PointT>::error_sqr_dists_;
+
+    using PointCloud = typename SampleConsensusModel<PointT>::PointCloud;
+    using PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr;
+    using PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr;
+
+    using Ptr = shared_ptr<SampleConsensusModelDoubleLine<PointT> >;
+    using ConstPtr = shared_ptr<const SampleConsensusModelDoubleLine<PointT>>;
+
+    /** \brief Constructor for base SampleConsensusModelCylinder.
+     * \param[in] cloud the input point cloud dataset
+     * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
      */
-   template <typename PointT>
-   class SampleConsensusModelDoubleLine : public SampleConsensusModel<PointT>
-   {
-     public:
-       using SampleConsensusModel<PointT>::model_name_;
-       using SampleConsensusModel<PointT>::input_;
-       using SampleConsensusModel<PointT>::indices_;
-       using SampleConsensusModel<PointT>::radius_min_;
-       using SampleConsensusModel<PointT>::radius_max_;
-       using SampleConsensusModel<PointT>::error_sqr_dists_;
-  
-       using PointCloud = typename SampleConsensusModel<PointT>::PointCloud;
-       using PointCloudPtr = typename SampleConsensusModel<PointT>::PointCloudPtr;
-       using PointCloudConstPtr = typename SampleConsensusModel<PointT>::PointCloudConstPtr;
-  
-       using Ptr = shared_ptr<SampleConsensusModelDoubleLine<PointT> >;
-       using ConstPtr = shared_ptr<const SampleConsensusModelDoubleLine<PointT>>;
-  
-       /** \brief Constructor for base SampleConsensusModelCylinder.
-         * \param[in] cloud the input point cloud dataset
-         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
-         */
-       SampleConsensusModelDoubleLine (const PointCloudConstPtr &cloud, bool random = false) 
-         : SampleConsensusModel<PointT> (cloud, random)
-         , axis_ (Eigen::Vector3f::Zero ())
-         , eps_angle_ (INFINITY)
-       {
-         model_name_ = "SampleConsensusModelDoubleLine";
-         sample_size_ = 3;
-         model_size_ = 4;
-       }
-  
-       /** \brief Constructor for base SampleConsensusModelCylinder.
-         * \param[in] cloud the input point cloud dataset
-         * \param[in] indices a vector of point indices to be used from \a cloud
-         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
-         */
-       SampleConsensusModelDoubleLine (const PointCloudConstPtr &cloud, 
-                                     const Indices &indices,
-                                     bool random = false) 
-         : SampleConsensusModel<PointT> (cloud, indices, random)
-         , axis_ (Eigen::Vector3f::Zero ())
-         , eps_angle_ (0)
-       {
-         model_name_ = "SampleConsensusModelDoubleLine";
-         sample_size_ = 3;
-         model_size_ = 4;
-       }
-  
-       /** \brief Copy constructor.
-         * \param[in] source the model to copy into this
-         */
-       SampleConsensusModelDoubleLine (const SampleConsensusModelDoubleLine &source) :
-         SampleConsensusModel<PointT> (),
-         axis_ (Eigen::Vector3f::Zero ()),
-         eps_angle_ (0)
-       {
-         *this = source;
-         model_name_ = "SampleConsensusModelDoubleLine";
-       }
-       
-       /** \brief Empty destructor */
-       ~SampleConsensusModelDoubleLine () {}
-  
-       /** \brief Copy constructor.
-         * \param[in] source the model to copy into this
-         */
-       inline SampleConsensusModelDoubleLine&
-       operator = (const SampleConsensusModelDoubleLine &source)
-       {
-         SampleConsensusModel<PointT>::operator=(source);
-         axis_ = source.axis_;
-         eps_angle_ = source.eps_angle_;
-         return (*this);
-       }
-  
-       /** \brief Set the angle epsilon (delta) threshold.
-         * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
-         */
-       inline void 
-       setEpsAngle (const double ea) { eps_angle_ = ea; }
-  
-       /** \brief Get the angle epsilon (delta) threshold. */
-       inline double 
-       getEpsAngle () const { return (eps_angle_); }
-  
-       /** \brief Set the axis along which we need to search for a cylinder direction.
-         * \param[in] ax the axis along which we need to search for a cylinder direction
-         */
-       inline void 
-       setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
-  
-       /** \brief Get the axis along which we need to search for a cylinder direction. */
-       inline Eigen::Vector3f 
-       getAxis () const { return (axis_); }
-  
-       /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
-         * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
-         * axis_direction, cylinder_radius_R
-         * \param[in] samples the point indices found as possible good candidates for creating a valid model
-         * \param[out] model_coefficients the resultant model coefficients
-         */
-       bool
-       computeModelCoefficients (const Indices &samples,
-                                 Eigen::VectorXf &model_coefficients) const override;
-  
-       /** \brief Compute all distances from the cloud data to a given cylinder model.
+    SampleConsensusModelDoubleLine (const PointCloudConstPtr &cloud, bool random = false)
+        : SampleConsensusModel<PointT> (cloud, random)
+        , axis_ (Eigen::Vector3f::Zero ())
+        , eps_angle_ (INFINITY)
+    {
+        model_name_ = "SampleConsensusModelDoubleLine";
+        sample_size_ = 3;
+        model_size_ = 4;
+    }
+
+    /** \brief Constructor for base SampleConsensusModelCylinder.
+     * \param[in] cloud the input point cloud dataset
+     * \param[in] indices a vector of point indices to be used from \a cloud
+     * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+     */
+    SampleConsensusModelDoubleLine (const PointCloudConstPtr &cloud,
+                                    const Indices &indices,
+                                    bool random = false)
+        : SampleConsensusModel<PointT> (cloud, indices, random)
+        , axis_ (Eigen::Vector3f::Zero ())
+        , eps_angle_ (0)
+    {
+        model_name_ = "SampleConsensusModelDoubleLine";
+        sample_size_ = 3;
+        model_size_ = 4;
+    }
+
+    /** \brief Copy constructor.
+     * \param[in] source the model to copy into this
+     */
+    SampleConsensusModelDoubleLine (const SampleConsensusModelDoubleLine &source) :
+        SampleConsensusModel<PointT> (),
+        axis_ (Eigen::Vector3f::Zero ()),
+        eps_angle_ (0)
+    {
+        *this = source;
+        model_name_ = "SampleConsensusModelDoubleLine";
+    }
+
+    /** \brief Empty destructor */
+    ~SampleConsensusModelDoubleLine () {}
+
+    /** \brief Copy constructor.
+     * \param[in] source the model to copy into this
+     */
+    inline SampleConsensusModelDoubleLine&
+    operator = (const SampleConsensusModelDoubleLine &source)
+    {
+        SampleConsensusModel<PointT>::operator=(source);
+        axis_ = source.axis_;
+        eps_angle_ = source.eps_angle_;
+        return (*this);
+    }
+
+    /** \brief Set the angle epsilon (delta) threshold.
+     * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
+     */
+    inline void
+    setEpsAngle (const double ea) { eps_angle_ = ea; }
+
+    /** \brief Get the angle epsilon (delta) threshold. */
+    inline double
+    getEpsAngle () const { return (eps_angle_); }
+
+    /** \brief Set the axis along which we need to search for a cylinder direction.
+     * \param[in] ax the axis along which we need to search for a cylinder direction
+     */
+    inline void
+    setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
+
+    /** \brief Get the axis along which we need to search for a cylinder direction. */
+    inline Eigen::Vector3f
+    getAxis () const { return (axis_); }
+
+    /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
+     * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
+     * axis_direction, cylinder_radius_R
+     * \param[in] samples the point indices found as possible good candidates for creating a valid model
+     * \param[out] model_coefficients the resultant model coefficients
+     */
+    bool
+    computeModelCoefficients (const Indices &samples,
+                              Eigen::VectorXf &model_coefficients) const override;
+
+    /** \brief Compute all distances from the cloud data to a given cylinder model.
          * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
          * \param[out] distances the resultant estimated distances
          */
-       void
-       getDistancesToModel (const Eigen::VectorXf &model_coefficients,
-                            std::vector<double> &distances) const override;
-  
-       /** \brief Select all the points which respect the given model coefficients as inliers.
-         * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
-         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
-         * \param[out] inliers the resultant model inliers
-         */
-       void 
-       selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
-                             const double threshold, 
-                             Indices &inliers) override;
-  
-       /** \brief Count all the points which respect the given model coefficients as inliers. 
-         * 
-         * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
-         * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
-         * \return the resultant number of inliers
-         */
-       std::size_t
-       countWithinDistance (const Eigen::VectorXf &model_coefficients,
-                            const double threshold) const override;
-  
-       /** \brief Recompute the cylinder coefficients using the given inlier set and return them to the user.
-         * @note: these are the coefficients of the cylinder model after refinement (e.g. after SVD)
-         * \param[in] inliers the data inliers found as supporting the model
-         * \param[in] model_coefficients the initial guess for the optimization
-         * \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization
-         */
-       void
-       optimizeModelCoefficients (const Indices &inliers,
-                                  const Eigen::VectorXf &model_coefficients,
-                                  Eigen::VectorXf &optimized_coefficients) const override;
-  
-  
-       /** \brief Create a new point cloud with inliers projected onto the cylinder model.
-         * \param[in] inliers the data inliers that we want to project on the cylinder model
-         * \param[in] model_coefficients the coefficients of a cylinder model
-         * \param[out] projected_points the resultant projected points
-         * \param[in] copy_data_fields set to true if we need to copy the other data fields
-         */
-       void
-       projectPoints (const Indices &inliers,
-                      const Eigen::VectorXf &model_coefficients,
-                      PointCloud &projected_points,
-                      bool copy_data_fields = true) const override;
-  
-       /** \brief Verify whether a subset of indices verifies the given cylinder model coefficients.
-         * \param[in] indices the data indices that need to be tested against the cylinder model
-         * \param[in] model_coefficients the cylinder model coefficients
-         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
-         */
-       bool
-       doSamplesVerifyModel (const std::set<int> &indices,
-                             const Eigen::VectorXf &model_coefficients,
-                             const double threshold) const override;
-  
-       /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
-       inline pcl::SacModel 
-       getModelType () const override { return (SACMODEL_CYLINDER); } //cannot add a unique identifier for double line
-  
-     protected:
-       using SampleConsensusModel<PointT>::sample_size_;
-       using SampleConsensusModel<PointT>::model_size_;
-  
-       /** \brief Get the distance from a point to a line (represented by a point and a direction)
-         * \param[in] pt a point
-         * \param[in] model_coefficients the line coefficients (a point on the line, line direction)
-         */
-       double
-       pointToLineDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const;
-  
-       /** \brief Project a point onto a line given by a point and a direction vector
-         * \param[in] pt the input point to project
-         * \param[in] line_pt the point on the line (make sure that line_pt[3] = 0 as there are no internal checks!)
-         * \param[in] line_dir the direction of the line (make sure that line_dir[3] = 0 as there are no internal checks!)
-         * \param[out] pt_proj the resultant projected point
-         */
-       inline void
-       projectPointToLine (const Eigen::Vector4f &pt,
-                           const Eigen::Vector4f &line_pt,
-                           const Eigen::Vector4f &line_dir,
-                           Eigen::Vector4f &pt_proj) const
-       {
-         float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
-         // Calculate the projection of the point on the line
-         pt_proj = line_pt + k * line_dir;
-       }
-  
-       /** \brief Project a point onto a cylinder given by its model coefficients (point_on_axis, axis_direction,
-         * cylinder_radius_R)
-         * \param[in] pt the input point to project
-         * \param[in] model_coefficients the coefficients of the cylinder (point_on_axis, axis_direction, cylinder_radius_R)
-         * \param[out] pt_proj the resultant projected point
-         */
-       void
-       projectPointToRectangle (const Eigen::Vector4f &pt,
+    void
+    getDistancesToModel (const Eigen::VectorXf &model_coefficients,
+                         std::vector<double> &distances) const override;
+
+    /** \brief Select all the points which respect the given model coefficients as inliers.
+     * \param[in] model_coefficients the coefficients of a cylinder model that we need to compute distances to
+     * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+     * \param[out] inliers the resultant model inliers
+     */
+    void
+    selectWithinDistance (const Eigen::VectorXf &model_coefficients,
+                          const double threshold,
+                          Indices &inliers) override;
+
+    /** \brief Count all the points which respect the given model coefficients as inliers.
+     *
+     * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
+     * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
+     * \return the resultant number of inliers
+     */
+    std::size_t
+    countWithinDistance (const Eigen::VectorXf &model_coefficients,
+                         const double threshold) const override;
+
+    /** \brief Recompute the cylinder coefficients using the given inlier set and return them to the user.
+     * @note: these are the coefficients of the cylinder model after refinement (e.g. after SVD)
+     * \param[in] inliers the data inliers found as supporting the model
+     * \param[in] model_coefficients the initial guess for the optimization
+     * \param[out] optimized_coefficients the resultant recomputed coefficients after non-linear optimization
+     */
+    void
+    optimizeModelCoefficients (const Indices &inliers,
                                const Eigen::VectorXf &model_coefficients,
-                               Eigen::Vector4f &pt_proj) const;
-  
-       /** \brief Check whether a model is valid given the user constraints.
-         * \param[in] model_coefficients the set of model coefficients
+                               Eigen::VectorXf &optimized_coefficients) const override;
+
+
+    /** \brief Create a new point cloud with inliers projected onto the cylinder model.
+     * \param[in] inliers the data inliers that we want to project on the cylinder model
+     * \param[in] model_coefficients the coefficients of a cylinder model
+     * \param[out] projected_points the resultant projected points
+     * \param[in] copy_data_fields set to true if we need to copy the other data fields
+     */
+    void
+    projectPoints (const Indices &inliers,
+                   const Eigen::VectorXf &model_coefficients,
+                   PointCloud &projected_points,
+                   bool copy_data_fields = true) const override;
+
+    /** \brief Verify whether a subset of indices verifies the given cylinder model coefficients.
+     * \param[in] indices the data indices that need to be tested against the cylinder model
+     * \param[in] model_coefficients the cylinder model coefficients
+     * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+     */
+    bool
+    doSamplesVerifyModel (const std::set<int> &indices,
+                          const Eigen::VectorXf &model_coefficients,
+                          const double threshold) const override;
+
+    /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
+    inline pcl::SacModel
+    getModelType () const override { return (SACMODEL_CYLINDER); } //cannot add a unique identifier for double line
+
+protected:
+    using SampleConsensusModel<PointT>::sample_size_;
+    using SampleConsensusModel<PointT>::model_size_;
+
+    /** \brief Get the distance from a point to a line (represented by a point and a direction)
+     * \param[in] pt a point
+     * \param[in] model_coefficients the line coefficients (a point on the line, line direction)
+     */
+    double
+    pointToLineDistance (const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const;
+
+    /** \brief Project a point onto a line given by a point and a direction vector
+     * \param[in] pt the input point to project
+     * \param[in] line_pt the point on the line (make sure that line_pt[3] = 0 as there are no internal checks!)
+     * \param[in] line_dir the direction of the line (make sure that line_dir[3] = 0 as there are no internal checks!)
+     * \param[out] pt_proj the resultant projected point
+     */
+    inline void
+    projectPointToLine (const Eigen::Vector4f &pt,
+                        const Eigen::Vector4f &line_pt,
+                        const Eigen::Vector4f &line_dir,
+                        Eigen::Vector4f &pt_proj) const
+    {
+        float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);
+        // Calculate the projection of the point on the line
+        pt_proj = line_pt + k * line_dir;
+    }
+
+    /** \brief Project a point onto a cylinder given by its model coefficients (point_on_axis, axis_direction,
+     * cylinder_radius_R)
+     * \param[in] pt the input point to project
+     * \param[in] model_coefficients the coefficients of the cylinder (point_on_axis, axis_direction, cylinder_radius_R)
+     * \param[out] pt_proj the resultant projected point
+     */
+    void
+    projectPointToRectangle (const Eigen::Vector4f &pt,
+                             const Eigen::VectorXf &model_coefficients,
+                             Eigen::Vector4f &pt_proj) const;
+
+    /** \brief Check whether a model is valid given the user constraints.
+     * \param[in] model_coefficients the set of model coefficients
+     */
+    bool
+    isModelValid (const Eigen::VectorXf &model_coefficients) const override;
+
+    /** \brief Check if a sample of indices results in a good sample of points
+     * indices. Pure virtual.
+     * \param[in] samples the resultant index samples
+     */
+    bool
+    isSampleGood (const Indices &samples) const override;
+
+private:
+    /** \brief The axis along which we need to search for a cylinder direction. */
+    Eigen::Vector3f axis_;
+
+    /** \brief The maximum allowed difference between the cylinder direction and the given axis. */
+    double eps_angle_;
+
+    /** \brief Functor for the optimization function */
+    struct OptimizationFunctor : pcl::Functor<float>
+    {
+        /** Functor constructor
+         * \param[in] indices the indices of data points to evaluate
+         * \param[in] estimator pointer to the estimator object
          */
-       bool
-       isModelValid (const Eigen::VectorXf &model_coefficients) const override;
-  
-       /** \brief Check if a sample of indices results in a good sample of points
-         * indices. Pure virtual.
-         * \param[in] samples the resultant index samples
+        OptimizationFunctor (const pcl::SampleConsensusModelDoubleLine<PointT> *model, const Indices& indices) :
+            pcl::Functor<float> (indices.size ()), model_ (model), indices_ (indices) {}
+
+        /** Cost function to be minimized
+         * \param[in] x variables array
+         * \param[out] fvec resultant functions evaluations
+         * \return 0
          */
-       bool
-       isSampleGood (const Indices &samples) const override;
-  
-     private:
-       /** \brief The axis along which we need to search for a cylinder direction. */
-       Eigen::Vector3f axis_;
-     
-       /** \brief The maximum allowed difference between the cylinder direction and the given axis. */
-       double eps_angle_;
-  
-       /** \brief Functor for the optimization function */
-       struct OptimizationFunctor : pcl::Functor<float>
-       {
-         /** Functor constructor
-           * \param[in] indices the indices of data points to evaluate
-           * \param[in] estimator pointer to the estimator object
-           */
-         OptimizationFunctor (const pcl::SampleConsensusModelDoubleLine<PointT> *model, const Indices& indices) :
-           pcl::Functor<float> (indices.size ()), model_ (model), indices_ (indices) {}
-  
-         /** Cost function to be minimized
-           * \param[in] x variables array
-           * \param[out] fvec resultant functions evaluations
-           * \return 0
-           */
-         int 
-         operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
-         {
-           Eigen::Vector4f line_pt  (x[0], x[1], x[2], 0);
-           Eigen::Vector4f line_dir (x[3], x[4], x[5], 0);
-           
-           for (int i = 0; i < values (); ++i)
-           {
-             // dist = f - r
-             Eigen::Vector4f pt = (*model_->input_)[indices_[i]].getVector4fMap();
-             pt[3] = 0;
-  
-             fvec[i] = static_cast<float> (pcl::sqrPointToLineDistance (pt, line_pt, line_dir) - x[6]*x[6]);
-           }
-           return (0);
-         }
-  
-         const pcl::SampleConsensusModelDoubleLine<PointT> *model_;
-         const Indices &indices_;
-       };
-   };
- }
-  
- //#ifdef PCL_NO_PRECOMPILE
- #include "ed_sensor_integration/sac_model_double_line.hpp"
- //#endif
+        int
+        operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
+        {
+            Eigen::Vector4f line_pt  (x[0], x[1], x[2], 0);
+            Eigen::Vector4f line_dir (x[3], x[4], x[5], 0);
+
+            for (int i = 0; i < values (); ++i)
+            {
+                // dist = f - r
+                Eigen::Vector4f pt = (*model_->input_)[indices_[i]].getVector4fMap();
+                pt[3] = 0;
+
+                fvec[i] = static_cast<float> (pcl::sqrPointToLineDistance (pt, line_pt, line_dir) - x[6]*x[6]);
+            }
+            return (0);
+        }
+
+        const pcl::SampleConsensusModelDoubleLine<PointT> *model_;
+        const Indices &indices_;
+    };
+};
+}
+
+//#ifdef PCL_NO_PRECOMPILE
+#include "ed_sensor_integration/sac_model_double_line.hpp"
+//#endif
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
index 25c0ed9d..526c8cec 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
@@ -1,4 +1,4 @@
- /*
+/*
   * Software License Agreement (BSD License)
   *
   *  Point Cloud Library (PCL) - www.pointclouds.org
@@ -37,159 +37,159 @@
   * $Id$
   *
   */
-  
- #ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_DOUBLE_LINE_H_
- #define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_DOUBLE_LINE_H_
-  
- #include <unsupported/Eigen/NonLinearOptimization> // for LevenbergMarquardt
- #include "ed_sensor_integration/sac_model_double_line.h"
- #include <pcl/common/common.h> // for getAngle3D
- #include <pcl/common/concatenate.h>
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool
- pcl::SampleConsensusModelDoubleLine<PointT>::isSampleGood (const Indices &samples) const
- {
-   if (samples.size () != sample_size_)
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
-     return (false);
-   }
-   return (true);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool
- pcl::SampleConsensusModelDoubleLine<PointT>::computeModelCoefficients (
-       const Indices &samples, Eigen::VectorXf &model_coefficients) const
- {
-   // Need 3 samples
-   if (samples.size () != sample_size_)
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::computeModelCoefficients] Invalid set of samples given (%lu)!\n", samples.size ());
-     return (false);
-   }
-  
-   if (std::abs ((*input_)[samples[0]].x - (*input_)[samples[1]].x) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].y - (*input_)[samples[1]].y) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].z - (*input_)[samples[1]].z) <= std::numeric_limits<float>::epsilon () ||
-       std::abs ((*input_)[samples[1]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[1]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[1]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon () ||
-       std::abs ((*input_)[samples[0]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () && 
-       std::abs ((*input_)[samples[0]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon ()) 
-   {
-     return (false);
-   }
-   Eigen::Vector2f p1 ((*input_)[samples[0]].x, (*input_)[samples[0]].y);
-   Eigen::Vector2f p2 ((*input_)[samples[1]].x, (*input_)[samples[1]].y);
-   Eigen::Vector2f p3 ((*input_)[samples[2]].x, (*input_)[samples[2]].y);
-   
-   float x, y, l, w, r;
-   
-   x = p1(0), y = p1(1); //output: x and y values
-   
-   Eigen::Vector2f c1, c2;
-   
-   c1 = p2 - p1; //vector between point 1 and 2
-   l = sqrt(c1.dot(c1)); //define length as distance between point 1 and 2
-   // determine rotation:
-   r = std::atan2(c1(1), c1(0)); //output: orientation of the double_line
-
-   c2 = p1 - p3; //vector between point 3 and 1
-   w = (c1(0)*c2(1)-c2(0)*c1(1))/l; //output: width defined as distance between c1 and point 3, signed
-	   
-   //save model coefficients
-   model_coefficients.resize (model_size_);
-   model_coefficients[0] = x;
-   model_coefficients[1] = y;
-   model_coefficients[2] = w;
-   model_coefficients[3] = r;
-   
-   //std::cout << w << std::endl;
-   
-   PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::computeModelCoefficients] Model is (%g,%g,%g,%g,%g).\n",
-              model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3]);
-   //std::cout << "P1: " << std::endl << p1 << std::endl << "P2: " << std::endl << p2 << std::endl << "P3: " << std::endl << p3 << std::endl << model_coefficients << std::endl;
-   return (true);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelDoubleLine<PointT>::getDistancesToModel (
-       const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
- {
-   // Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-   {
-     distances.clear ();
-     return;
-   }
-  
-   distances.resize (indices_->size ());
-   
-   float x = model_coefficients[0]
-   float y = model_coefficients[1]
-   float w = model_coefficients[2]
-   float r = model_coefficients[3];
-   float d1, d2;
-
-   Eigen::Vector2f p1, p2, p3, p4, c1, c2;
-   
-   // #TODO Calculation of distances without needing to define points
-   //define edge vectors
-   c1(0)=std::cos(r);
-   c1(1)=std::sin(r);
-
-   c2(0)= std::sin(r)*w;
-   c2(1)=-std::cos(r)*w;
-
-   //define corner vectors
-   p1(0)=x;
-   p1(1)=y;
-   p2 = p1 + c1;
-   p3 = p2 + c2;
-   p4 = p1 + c2;
-   
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-	   Eigen::Vector2f in ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y);
-	   
-	   //compute distances to lines
-		d1 = std::abs(c1(0)*(p1(1)-in(1))-(p1(0)-in(0))*c1(1)); //Distance between line 1 and the point
-		d2 = std::abs(c1(0)*(p3(1)-in(1))-(p3(0)-in(0))*c1(1)); //Distance between line 2 and the point
 
-		distances[i] = std::min(d1, d2); //smallest of d1 and d2
-   }
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelDoubleLine<PointT>::selectWithinDistance (
-       const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
- {
-   std::vector<double> distances;
-   getDistancesToModel (model_coefficients, distances);
-   for (int i = 0; i < distances.size(); i++)
-   {
-	   if (distances[i] < threshold) {inliers.push_back ((*indices_)[i]);}
-   }
-   
-   //std::cout << model_coefficients[2] << std::endl;
-   /*
+#ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_DOUBLE_LINE_H_
+#define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_DOUBLE_LINE_H_
+
+#include <unsupported/Eigen/NonLinearOptimization> // for LevenbergMarquardt
+#include "ed_sensor_integration/sac_model_double_line.h"
+#include <pcl/common/common.h> // for getAngle3D
+#include <pcl/common/concatenate.h>
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> bool
+pcl::SampleConsensusModelDoubleLine<PointT>::isSampleGood (const Indices &samples) const
+{
+    if (samples.size () != sample_size_)
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::isSampleGood] Wrong number of samples (is %lu, should be %lu)!\n", samples.size (), sample_size_);
+        return (false);
+    }
+    return (true);
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> bool
+pcl::SampleConsensusModelDoubleLine<PointT>::computeModelCoefficients (
+        const Indices &samples, Eigen::VectorXf &model_coefficients) const
+{
+    // Need 3 samples
+    if (samples.size () != sample_size_)
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::computeModelCoefficients] Invalid set of samples given (%lu)!\n", samples.size ());
+        return (false);
+    }
+
+    if (std::abs ((*input_)[samples[0]].x - (*input_)[samples[1]].x) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[0]].y - (*input_)[samples[1]].y) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[0]].z - (*input_)[samples[1]].z) <= std::numeric_limits<float>::epsilon () ||
+            std::abs ((*input_)[samples[1]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[1]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[1]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon () ||
+            std::abs ((*input_)[samples[0]].x - (*input_)[samples[2]].x) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[0]].y - (*input_)[samples[2]].y) <= std::numeric_limits<float>::epsilon () &&
+            std::abs ((*input_)[samples[0]].z - (*input_)[samples[2]].z) <= std::numeric_limits<float>::epsilon ())
+    {
+        return (false);
+    }
+    Eigen::Vector2f p1 ((*input_)[samples[0]].x, (*input_)[samples[0]].y);
+    Eigen::Vector2f p2 ((*input_)[samples[1]].x, (*input_)[samples[1]].y);
+    Eigen::Vector2f p3 ((*input_)[samples[2]].x, (*input_)[samples[2]].y);
+
+    float x, y, l, w, r;
+
+    x = p1(0), y = p1(1); //output: x and y values
+
+    Eigen::Vector2f c1, c2;
+
+    c1 = p2 - p1; //vector between point 1 and 2
+    l = sqrt(c1.dot(c1)); //define length as distance between point 1 and 2
+    // determine rotation:
+    r = std::atan2(c1(1), c1(0)); //output: orientation of the double_line
+
+    c2 = p1 - p3; //vector between point 3 and 1
+    w = (c1(0)*c2(1)-c2(0)*c1(1))/l; //output: width defined as distance between c1 and point 3, signed
+
+    //save model coefficients
+    model_coefficients.resize (model_size_);
+    model_coefficients[0] = x;
+    model_coefficients[1] = y;
+    model_coefficients[2] = w;
+    model_coefficients[3] = r;
+
+    //std::cout << w << std::endl;
+
+    PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::computeModelCoefficients] Model is (%g,%g,%g,%g,%g).\n",
+               model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3]);
+    //std::cout << "P1: " << std::endl << p1 << std::endl << "P2: " << std::endl << p2 << std::endl << "P3: " << std::endl << p3 << std::endl << model_coefficients << std::endl;
+    return (true);
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelDoubleLine<PointT>::getDistancesToModel (
+        const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
+{
+    // Check if the model is valid given the user constraints
+    if (!isModelValid (model_coefficients))
+    {
+        distances.clear ();
+        return;
+    }
+
+    distances.resize (indices_->size ());
+
+    float x = model_coefficients[0]
+            float y = model_coefficients[1]
+            float w = model_coefficients[2]
+            float r = model_coefficients[3];
+    float d1, d2;
+
+    Eigen::Vector2f p1, p2, p3, p4, c1, c2;
+
+    // #TODO Calculation of distances without needing to define points
+    //define edge vectors
+    c1(0)=std::cos(r);
+    c1(1)=std::sin(r);
+
+    c2(0)= std::sin(r)*w;
+    c2(1)=-std::cos(r)*w;
+
+    //define corner vectors
+    p1(0)=x;
+    p1(1)=y;
+    p2 = p1 + c1;
+    p3 = p2 + c2;
+    p4 = p1 + c2;
+
+    for (std::size_t i = 0; i < indices_->size (); ++i)
+    {
+        Eigen::Vector2f in ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y);
+
+        //compute distances to lines
+        d1 = std::abs(c1(0)*(p1(1)-in(1))-(p1(0)-in(0))*c1(1)); //Distance between line 1 and the point
+        d2 = std::abs(c1(0)*(p3(1)-in(1))-(p3(0)-in(0))*c1(1)); //Distance between line 2 and the point
+
+        distances[i] = std::min(d1, d2); //smallest of d1 and d2
+    }
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelDoubleLine<PointT>::selectWithinDistance (
+        const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
+{
+    std::vector<double> distances;
+    getDistancesToModel (model_coefficients, distances);
+    for (int i = 0; i < distances.size(); i++)
+    {
+        if (distances[i] < threshold) {inliers.push_back ((*indices_)[i]);}
+    }
+
+    //std::cout << model_coefficients[2] << std::endl;
+    /*
    // Check if the model is valid given the user constraints
    if (!isModelValid (model_coefficients))
    {
      inliers.clear ();
      return;
    }
-  
+
    inliers.clear ();
    error_sqr_dists_.clear ();
    inliers.reserve (indices_->size ());
    error_sqr_dists_.reserve (indices_->size ());
-  
+
    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
    float ptdotdir = line_pt.dot (line_dir);
@@ -203,18 +203,18 @@
      const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
      if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
        continue;
-  
+
      // Calculate the point's projection on the cylinder axis
      float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
      Eigen::Vector4f pt_proj = line_pt + k * line_dir;
      Eigen::Vector4f dir = pt - pt_proj;
      dir.normalize ();
-  
+
      // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
      Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
      double d_normal = std::abs (getAngle3D (n, dir));
      d_normal = (std::min) (d_normal, M_PI - d_normal);
-  
+
      double distance = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);
      if (distance < threshold)
      {
@@ -223,28 +223,28 @@
        error_sqr_dists_.push_back (distance);
      }
    }*/
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> std::size_t
- pcl::SampleConsensusModelDoubleLine<PointT>::countWithinDistance (
-       const Eigen::VectorXf &model_coefficients, const double threshold) const
- {
-   std::vector<double> distances;
-   getDistancesToModel (model_coefficients, distances);
-   int count = 0;
-   for (int i = 0; i < distances.size(); i++)
-   {
-	   if (distances[i] <= threshold) {count++;}
-   }
-   //std::cout << count << std::endl;
-   return (count);
-   /*// Check if the model is valid given the user constraints
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> std::size_t
+pcl::SampleConsensusModelDoubleLine<PointT>::countWithinDistance (
+        const Eigen::VectorXf &model_coefficients, const double threshold) const
+{
+    std::vector<double> distances;
+    getDistancesToModel (model_coefficients, distances);
+    int count = 0;
+    for (int i = 0; i < distances.size(); i++)
+    {
+        if (distances[i] <= threshold) {count++;}
+    }
+    //std::cout << count << std::endl;
+    return (count);
+    /*// Check if the model is valid given the user constraints
    if (!isModelValid (model_coefficients))
      return (0);
-  
+
    std::size_t nr_p = 0;
-  
+
    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);
    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
    float ptdotdir = line_pt.dot (line_dir);
@@ -258,217 +258,217 @@
      const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
      if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
        continue;
-  
+
      // Calculate the point's projection on the cylinder axis
      float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
      Eigen::Vector4f pt_proj = line_pt + k * line_dir;
      Eigen::Vector4f dir = pt - pt_proj;
      dir.normalize ();
-  
+
      // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
      Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
      double d_normal = std::abs (getAngle3D (n, dir));
      d_normal = (std::min) (d_normal, M_PI - d_normal);
-  
+
      if (std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist) < threshold)
        nr_p++;
    }
    return (nr_p);*/
-   return (0);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelDoubleLine<PointT>::optimizeModelCoefficients (
-       const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
- {
-   optimized_coefficients = model_coefficients;
-  
-   // Needs a set of valid model coefficients
-   if (!isModelValid (model_coefficients))
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::optimizeModelCoefficients] Given model is invalid!\n");
-     return;
-   }
-  
-   // Need more than the minimum sample size to make a difference
-   if (inliers.size () <= sample_size_)
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine:optimizeModelCoefficients] Not enough inliers found to optimize model coefficients (%lu)! Returning the same coefficients.\n", inliers.size ());
-     return;
-   }
-  
-   OptimizationFunctor functor (this, inliers);
-   Eigen::NumericalDiff<OptimizationFunctor > num_diff (functor);
-   Eigen::LevenbergMarquardt<Eigen::NumericalDiff<OptimizationFunctor>, float> lm (num_diff);
-   int info = lm.minimize (optimized_coefficients);
-   
-   // Compute the L2 norm of the residuals
-   PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::optimizeModelCoefficients] LM solver finished with exit code %i, having a residual norm of %g. \nInitial solution: %g %g %g %g %g %g %g \nFinal solution: %g %g %g %g %g %g %g\n",
-              info, lm.fvec.norm (), model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
-              model_coefficients[4], model_coefficients[5], model_coefficients[6], optimized_coefficients[0], optimized_coefficients[1], optimized_coefficients[2], optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5], optimized_coefficients[6]);
-     
-   Eigen::Vector3f line_dir (optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5]);
-   line_dir.normalize ();
-   optimized_coefficients[3] = line_dir[0];
-   optimized_coefficients[4] = line_dir[1];
-   optimized_coefficients[5] = line_dir[2];
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelDoubleLine<PointT>::projectPoints (
-       const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
- {
-   // Needs a valid set of model coefficients
-   if (!isModelValid (model_coefficients))
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::projectPoints] Given model is invalid!\n");
-     return;
-   }
-  
-   projected_points.header = input_->header;
-   projected_points.is_dense = input_->is_dense;
-  
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-  
-   // Copy all the data fields from the input cloud to the projected one?
-   if (copy_data_fields)
-   {
-     // Allocate enough space and copy the basics
-     projected_points.resize (input_->size ());
-     projected_points.width    = input_->width;
-     projected_points.height   = input_->height;
-  
-     using FieldList = typename pcl::traits::fieldList<PointT>::type;
-     // Iterate over each point
-     for (std::size_t i = 0; i < projected_points.size (); ++i)
-       // Iterate over each dimension
-       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
-  
-     // Iterate through the 3d points and calculate the distances from them to the cylinder
-     for (const auto &inlier : inliers)
-     {
-       Eigen::Vector4f p ((*input_)[inlier].x,
-                          (*input_)[inlier].y,
-                          (*input_)[inlier].z,
-                          1);
-  
-       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
-  
-       pcl::Vector4fMap pp = projected_points[inlier].getVector4fMap ();
-       pp.matrix () = line_pt + k * line_dir;
-  
-       Eigen::Vector4f dir = p - pp;
-       dir[3] = 0.0f;
-       dir.normalize ();
-  
-       // Calculate the projection of the point onto the cylinder
-       pp += dir * model_coefficients[6];
-     }
-   }
-   else
-   {
-     // Allocate enough space and copy the basics
-     projected_points.resize (inliers.size ());
-     projected_points.width    = inliers.size ();
-     projected_points.height   = 1;
-  
-     using FieldList = typename pcl::traits::fieldList<PointT>::type;
-     // Iterate over each point
-     for (std::size_t i = 0; i < inliers.size (); ++i)
-       // Iterate over each dimension
-       pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
-  
-     // Iterate through the 3d points and calculate the distances from them to the cylinder
-     for (std::size_t i = 0; i < inliers.size (); ++i)
-     {
-       pcl::Vector4fMap pp = projected_points[i].getVector4fMap ();
-       pcl::Vector4fMapConst p = (*input_)[inliers[i]].getVector4fMap ();
-  
-       float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
-       // Calculate the projection of the point on the line
-       pp.matrix () = line_pt + k * line_dir;
-  
-       Eigen::Vector4f dir = p - pp;
-       dir[3] = 0.0f;
-       dir.normalize ();
-  
-       // Calculate the projection of the point onto the cylinder
-       pp += dir * model_coefficients[6];
-     }
-   }
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool
- pcl::SampleConsensusModelDoubleLine<PointT>::doSamplesVerifyModel (
-       const std::set<int> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
- {
-   // Needs a valid model coefficients
-   if (!isModelValid (model_coefficients))
-   {
-     PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::doSamplesVerifyModel] Given model is invalid!\n");
-     return (false);
-   }
-  
-   for (const auto &index : indices)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     // @note need to revise this.
-     Eigen::Vector4f pt ((*input_)[index].x, (*input_)[index].y, (*input_)[index].z, 0.0f);
-     if (std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]) > threshold)
-       return (false);
-   }
-  
-   return (true);
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> double
- pcl::SampleConsensusModelDoubleLine<PointT>::pointToLineDistance (
-       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const
- {
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   return sqrt(pcl::sqrPointToLineDistance (pt, line_pt, line_dir));
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelDoubleLine<PointT>::projectPointToRectangle (
-       const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients, Eigen::Vector4f &pt_proj) const
- {
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-  
-   float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) * line_dir.dot (line_dir);
-   pt_proj = line_pt + k * line_dir;
-  
-   Eigen::Vector4f dir = pt - pt_proj;
-   dir.normalize ();
-  
-   // Calculate the projection of the point onto the cylinder
-   pt_proj += dir * model_coefficients[6];
- }
-  
- //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool 
- pcl::SampleConsensusModelDoubleLine<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
- {
-   if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
-     return (false);
-  /*
+    return (0);
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelDoubleLine<PointT>::optimizeModelCoefficients (
+        const Indices &inliers, const Eigen::VectorXf &model_coefficients, Eigen::VectorXf &optimized_coefficients) const
+{
+    optimized_coefficients = model_coefficients;
+
+    // Needs a set of valid model coefficients
+    if (!isModelValid (model_coefficients))
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::optimizeModelCoefficients] Given model is invalid!\n");
+        return;
+    }
+
+    // Need more than the minimum sample size to make a difference
+    if (inliers.size () <= sample_size_)
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine:optimizeModelCoefficients] Not enough inliers found to optimize model coefficients (%lu)! Returning the same coefficients.\n", inliers.size ());
+        return;
+    }
+
+    OptimizationFunctor functor (this, inliers);
+    Eigen::NumericalDiff<OptimizationFunctor > num_diff (functor);
+    Eigen::LevenbergMarquardt<Eigen::NumericalDiff<OptimizationFunctor>, float> lm (num_diff);
+    int info = lm.minimize (optimized_coefficients);
+
+    // Compute the L2 norm of the residuals
+    PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::optimizeModelCoefficients] LM solver finished with exit code %i, having a residual norm of %g. \nInitial solution: %g %g %g %g %g %g %g \nFinal solution: %g %g %g %g %g %g %g\n",
+               info, lm.fvec.norm (), model_coefficients[0], model_coefficients[1], model_coefficients[2], model_coefficients[3],
+            model_coefficients[4], model_coefficients[5], model_coefficients[6], optimized_coefficients[0], optimized_coefficients[1], optimized_coefficients[2], optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5], optimized_coefficients[6]);
+
+    Eigen::Vector3f line_dir (optimized_coefficients[3], optimized_coefficients[4], optimized_coefficients[5]);
+    line_dir.normalize ();
+    optimized_coefficients[3] = line_dir[0];
+    optimized_coefficients[4] = line_dir[1];
+    optimized_coefficients[5] = line_dir[2];
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelDoubleLine<PointT>::projectPoints (
+        const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields) const
+{
+    // Needs a valid set of model coefficients
+    if (!isModelValid (model_coefficients))
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::projectPoints] Given model is invalid!\n");
+        return;
+    }
+
+    projected_points.header = input_->header;
+    projected_points.is_dense = input_->is_dense;
+
+    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+    float ptdotdir = line_pt.dot (line_dir);
+    float dirdotdir = 1.0f / line_dir.dot (line_dir);
+
+    // Copy all the data fields from the input cloud to the projected one?
+    if (copy_data_fields)
+    {
+        // Allocate enough space and copy the basics
+        projected_points.resize (input_->size ());
+        projected_points.width    = input_->width;
+        projected_points.height   = input_->height;
+
+        using FieldList = typename pcl::traits::fieldList<PointT>::type;
+        // Iterate over each point
+        for (std::size_t i = 0; i < projected_points.size (); ++i)
+            // Iterate over each dimension
+            pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[i], projected_points[i]));
+
+        // Iterate through the 3d points and calculate the distances from them to the cylinder
+        for (const auto &inlier : inliers)
+        {
+            Eigen::Vector4f p ((*input_)[inlier].x,
+                               (*input_)[inlier].y,
+                               (*input_)[inlier].z,
+                               1);
+
+            float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
+
+            pcl::Vector4fMap pp = projected_points[inlier].getVector4fMap ();
+            pp.matrix () = line_pt + k * line_dir;
+
+            Eigen::Vector4f dir = p - pp;
+            dir[3] = 0.0f;
+            dir.normalize ();
+
+            // Calculate the projection of the point onto the cylinder
+            pp += dir * model_coefficients[6];
+        }
+    }
+    else
+    {
+        // Allocate enough space and copy the basics
+        projected_points.resize (inliers.size ());
+        projected_points.width    = inliers.size ();
+        projected_points.height   = 1;
+
+        using FieldList = typename pcl::traits::fieldList<PointT>::type;
+        // Iterate over each point
+        for (std::size_t i = 0; i < inliers.size (); ++i)
+            // Iterate over each dimension
+            pcl::for_each_type <FieldList> (NdConcatenateFunctor <PointT, PointT> ((*input_)[inliers[i]], projected_points[i]));
+
+        // Iterate through the 3d points and calculate the distances from them to the cylinder
+        for (std::size_t i = 0; i < inliers.size (); ++i)
+        {
+            pcl::Vector4fMap pp = projected_points[i].getVector4fMap ();
+            pcl::Vector4fMapConst p = (*input_)[inliers[i]].getVector4fMap ();
+
+            float k = (p.dot (line_dir) - ptdotdir) * dirdotdir;
+            // Calculate the projection of the point on the line
+            pp.matrix () = line_pt + k * line_dir;
+
+            Eigen::Vector4f dir = p - pp;
+            dir[3] = 0.0f;
+            dir.normalize ();
+
+            // Calculate the projection of the point onto the cylinder
+            pp += dir * model_coefficients[6];
+        }
+    }
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> bool
+pcl::SampleConsensusModelDoubleLine<PointT>::doSamplesVerifyModel (
+        const std::set<int> &indices, const Eigen::VectorXf &model_coefficients, const double threshold) const
+{
+    // Needs a valid model coefficients
+    if (!isModelValid (model_coefficients))
+    {
+        PCL_ERROR ("[pcl::SampleConsensusModelDoubleLine::doSamplesVerifyModel] Given model is invalid!\n");
+        return (false);
+    }
+
+    for (const auto &index : indices)
+    {
+        // Approximate the distance from the point to the cylinder as the difference between
+        // dist(point,cylinder_axis) and cylinder radius
+        // @note need to revise this.
+        Eigen::Vector4f pt ((*input_)[index].x, (*input_)[index].y, (*input_)[index].z, 0.0f);
+        if (std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]) > threshold)
+            return (false);
+    }
+
+    return (true);
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> double
+pcl::SampleConsensusModelDoubleLine<PointT>::pointToLineDistance (
+        const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients) const
+{
+    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+    return sqrt(pcl::sqrPointToLineDistance (pt, line_pt, line_dir));
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelDoubleLine<PointT>::projectPointToRectangle (
+        const Eigen::Vector4f &pt, const Eigen::VectorXf &model_coefficients, Eigen::Vector4f &pt_proj) const
+{
+    Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
+    Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
+
+    float k = (pt.dot (line_dir) - line_pt.dot (line_dir)) * line_dir.dot (line_dir);
+    pt_proj = line_pt + k * line_dir;
+
+    Eigen::Vector4f dir = pt - pt_proj;
+    dir.normalize ();
+
+    // Calculate the projection of the point onto the cylinder
+    pt_proj += dir * model_coefficients[6];
+}
+
+//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+template <typename PointT> bool
+pcl::SampleConsensusModelDoubleLine<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
+{
+    if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
+        return (false);
+    /*
    // Check against template, if given
    if (eps_angle_ > 0.0)
    {
      // Obtain the cylinder direction
      const Eigen::Vector3f coeff(model_coefficients[3], model_coefficients[4], model_coefficients[5]);
-  
+
      double angle_diff = std::abs (getAngle3D (axis_, coeff));
      angle_diff = (std::min) (angle_diff, M_PI - angle_diff);
      // Check whether the current cylinder model satisfies our angle threshold criterion with respect to the given axis
@@ -478,7 +478,7 @@
        return (false);
      }
    }
-  
+
    if (radius_min_ != -std::numeric_limits<double>::max() && model_coefficients[6] < radius_min_)
    {
      PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::isModelValid] Radius is too small: should be larger than %g, but is %g.\n",
@@ -491,10 +491,10 @@
                 radius_max_, model_coefficients[6]);
      return (false);
    }*/
-  
-   return (true);
- }
-  
- #define PCL_INSTANTIATE_SampleConsensusModelDoubleLine(PointT) template class PCL_EXPORTS pcl::SampleConsensusModelDoubleLine<PointT>;
-  
- #endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_DOUBLE_LINE_H_
+
+    return (true);
+}
+
+#define PCL_INSTANTIATE_SampleConsensusModelDoubleLine(PointT) template class PCL_EXPORTS pcl::SampleConsensusModelDoubleLine<PointT>;
+
+#endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_DOUBLE_LINE_H_
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.h
index 11a7ddd1..b59e34df 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.h
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.h
@@ -37,158 +37,158 @@
   * $Id$
   *
   */
-  
- #pragma once
-  
- #include <pcl/sample_consensus/sac_model_plane.h>
-  
- namespace pcl
- {
-   /** \brief @b SampleConsensusModelParallelPlane defines a model for 3D plane segmentation using additional
-     * angular constraints. The plane must be parallel to a user-specified axis
-     * (\ref setAxis) within a user-specified angle threshold (\ref setEpsAngle).
-     * In other words, the plane <b>normal</b> must be (nearly) <b>perpendicular</b> to the specified axis.
-     *
-     * Code example for a plane model, parallel (within a 15 degrees tolerance) with the Z axis:
-     * \code
-     * SampleConsensusModelParallelPlane<pcl::PointXYZ> model (cloud);
-     * model.setAxis (Eigen::Vector3f (0.0, 0.0, 1.0));
-     * model.setEpsAngle (pcl::deg2rad (15));
-     * \endcode
-     *
-     * \note Please remember that you need to specify an angle > 0 in order to activate the axis-angle constraint!
-     *
-     * \author Radu B. Rusu, Nico Blodow
-     * \ingroup sample_consensus
+
+#pragma once
+
+#include <pcl/sample_consensus/sac_model_plane.h>
+
+namespace pcl
+{
+/** \brief @b SampleConsensusModelParallelPlane defines a model for 3D plane segmentation using additional
+ * angular constraints. The plane must be parallel to a user-specified axis
+ * (\ref setAxis) within a user-specified angle threshold (\ref setEpsAngle).
+ * In other words, the plane <b>normal</b> must be (nearly) <b>perpendicular</b> to the specified axis.
+ *
+ * Code example for a plane model, parallel (within a 15 degrees tolerance) with the Z axis:
+ * \code
+ * SampleConsensusModelParallelPlane<pcl::PointXYZ> model (cloud);
+ * model.setAxis (Eigen::Vector3f (0.0, 0.0, 1.0));
+ * model.setEpsAngle (pcl::deg2rad (15));
+ * \endcode
+ *
+ * \note Please remember that you need to specify an angle > 0 in order to activate the axis-angle constraint!
+ *
+ * \author Radu B. Rusu, Nico Blodow
+ * \ingroup sample_consensus
+ */
+template <typename PointT>
+class SampleConsensusModelHorizontalPlane : public SampleConsensusModelPlane<PointT>
+{
+public:
+    using SampleConsensusModel<PointT>::model_name_;
+    using SampleConsensusModel<PointT>::indices_;
+    using SampleConsensusModel<PointT>::input_;
+
+    using PointCloud = typename SampleConsensusModelPlane<PointT>::PointCloud;
+    using PointCloudPtr = typename SampleConsensusModelPlane<PointT>::PointCloudPtr;
+    using PointCloudConstPtr = typename SampleConsensusModelPlane<PointT>::PointCloudConstPtr;
+
+    using Ptr = shared_ptr<SampleConsensusModelHorizontalPlane<PointT> >;
+    using ConstPtr = shared_ptr<const SampleConsensusModelHorizontalPlane<PointT>>;
+
+    /** \brief Constructor for base SampleConsensusModelHorizontalPlane.
+     * \param[in] cloud the input point cloud dataset
+     * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
      */
-   template <typename PointT>
-   class SampleConsensusModelHorizontalPlane : public SampleConsensusModelPlane<PointT>
-   {
-     public:
-       using SampleConsensusModel<PointT>::model_name_;
-       using SampleConsensusModel<PointT>::indices_;
-	   using SampleConsensusModel<PointT>::input_;
-	   
-       using PointCloud = typename SampleConsensusModelPlane<PointT>::PointCloud;
-       using PointCloudPtr = typename SampleConsensusModelPlane<PointT>::PointCloudPtr;
-       using PointCloudConstPtr = typename SampleConsensusModelPlane<PointT>::PointCloudConstPtr;
-  
-       using Ptr = shared_ptr<SampleConsensusModelHorizontalPlane<PointT> >;
-       using ConstPtr = shared_ptr<const SampleConsensusModelHorizontalPlane<PointT>>;
-  
-       /** \brief Constructor for base SampleConsensusModelHorizontalPlane.
-         * \param[in] cloud the input point cloud dataset
-         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
-         */
-       SampleConsensusModelHorizontalPlane (const PointCloudConstPtr &cloud,
-                                          bool random = false) 
-         : SampleConsensusModelPlane<PointT> (cloud, random)
-         , axis_ (Eigen::Vector3f::Zero ())
-         , eps_angle_ (0.0)
-         , sin_angle_ (-1.0)
-       {
-         model_name_ = "SampleConsensusModelHorizontalPlane";
-         sample_size_ = 3;
-         model_size_ = 4;
-       }
-  
-       /** \brief Constructor for base SampleConsensusModelHorizontalPlane.
-         * \param[in] cloud the input point cloud dataset
-         * \param[in] indices a vector of point indices to be used from \a cloud
-         * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
-         */
-       SampleConsensusModelHorizontalPlane (const PointCloudConstPtr &cloud, 
-                                          const Indices &indices,
-                                          bool random = false) 
-         : SampleConsensusModelPlane<PointT> (cloud, indices, random)
-         , axis_ (Eigen::Vector3f::Zero ())
-         , eps_angle_ (0.0)
-         , sin_angle_ (-1.0)
-       {
-         model_name_ = "SampleConsensusModelHorizontalPlane";
-         sample_size_ = 3;
-         model_size_ = 4;
-       }
-       
-       /** \brief Empty destructor */
-       ~SampleConsensusModelHorizontalPlane () {}
-  
-       /** \brief Set the axis along which we need to search for a plane perpendicular to.
-         * \param[in] ax the axis along which we need to search for a plane perpendicular to
-         */
-       inline void
-       setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
-  
-       /** \brief Get the axis along which we need to search for a plane perpendicular to. */
-       inline Eigen::Vector3f
-       getAxis () const { return (axis_); }
-  
-       /** \brief Set the angle epsilon (delta) threshold.
-         * \param[in] ea the maximum allowed difference between the plane normal and the given axis.
-         * \note You need to specify an angle > 0 in order to activate the axis-angle constraint!
-         */
-       inline void
-       setEpsAngle (const double ea) { eps_angle_ = ea; sin_angle_ = std::abs (sin (ea));}
-  
-       /** \brief Get the angle epsilon (delta) threshold. */
-       inline double
-       getEpsAngle () const { return (eps_angle_); }
-       
-       bool
-       computeModelCoefficients (const Indices &samples,
-                                 Eigen::VectorXf &model_coefficients) const override;
-  
-       /** \brief Select all the points which respect the given model coefficients as inliers.
-         * \param[in] model_coefficients the coefficients of a plane model that we need to compute distances to
-         * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
-         * \param[out] inliers the resultant model inliers
-         */
-       void
-       selectWithinDistance (const Eigen::VectorXf &model_coefficients,
-                             const double threshold,
-                             Indices &inliers) override;
-  
-       /** \brief Count all the points which respect the given model coefficients as inliers.
+    SampleConsensusModelHorizontalPlane (const PointCloudConstPtr &cloud,
+                                         bool random = false)
+        : SampleConsensusModelPlane<PointT> (cloud, random)
+        , axis_ (Eigen::Vector3f::Zero ())
+        , eps_angle_ (0.0)
+        , sin_angle_ (-1.0)
+    {
+        model_name_ = "SampleConsensusModelHorizontalPlane";
+        sample_size_ = 3;
+        model_size_ = 4;
+    }
+
+    /** \brief Constructor for base SampleConsensusModelHorizontalPlane.
+     * \param[in] cloud the input point cloud dataset
+     * \param[in] indices a vector of point indices to be used from \a cloud
+     * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false)
+     */
+    SampleConsensusModelHorizontalPlane (const PointCloudConstPtr &cloud,
+                                         const Indices &indices,
+                                         bool random = false)
+        : SampleConsensusModelPlane<PointT> (cloud, indices, random)
+        , axis_ (Eigen::Vector3f::Zero ())
+        , eps_angle_ (0.0)
+        , sin_angle_ (-1.0)
+    {
+        model_name_ = "SampleConsensusModelHorizontalPlane";
+        sample_size_ = 3;
+        model_size_ = 4;
+    }
+
+    /** \brief Empty destructor */
+    ~SampleConsensusModelHorizontalPlane () {}
+
+    /** \brief Set the axis along which we need to search for a plane perpendicular to.
+     * \param[in] ax the axis along which we need to search for a plane perpendicular to
+     */
+    inline void
+    setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
+
+    /** \brief Get the axis along which we need to search for a plane perpendicular to. */
+    inline Eigen::Vector3f
+    getAxis () const { return (axis_); }
+
+    /** \brief Set the angle epsilon (delta) threshold.
+     * \param[in] ea the maximum allowed difference between the plane normal and the given axis.
+     * \note You need to specify an angle > 0 in order to activate the axis-angle constraint!
+     */
+    inline void
+    setEpsAngle (const double ea) { eps_angle_ = ea; sin_angle_ = std::abs (sin (ea));}
+
+    /** \brief Get the angle epsilon (delta) threshold. */
+    inline double
+    getEpsAngle () const { return (eps_angle_); }
+
+    bool
+    computeModelCoefficients (const Indices &samples,
+                              Eigen::VectorXf &model_coefficients) const override;
+
+    /** \brief Select all the points which respect the given model coefficients as inliers.
+     * \param[in] model_coefficients the coefficients of a plane model that we need to compute distances to
+     * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers
+     * \param[out] inliers the resultant model inliers
+     */
+    void
+    selectWithinDistance (const Eigen::VectorXf &model_coefficients,
+                          const double threshold,
+                          Indices &inliers) override;
+
+    /** \brief Count all the points which respect the given model coefficients as inliers.
          *
          * \param[in] model_coefficients the coefficients of a model that we need to compute distances to
          * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers
          * \return the resultant number of inliers
          */
-       std::size_t
-       countWithinDistance (const Eigen::VectorXf &model_coefficients,
-                            const double threshold) const override;
-  
-       /** \brief Compute all distances from the cloud data to a given plane model.
-         * \param[in] model_coefficients the coefficients of a plane model that we need to compute distances to
-         * \param[out] distances the resultant estimated distances
-         */
-       void
-       getDistancesToModel (const Eigen::VectorXf &model_coefficients,
-                            std::vector<double> &distances) const override;
-  
-       /** \brief Return a unique id for this model (SACMODEL_HORIZONTAL_PLANE). */
-       inline pcl::SacModel
-       getModelType () const override { return (SACMODEL_PARALLEL_PLANE); }//cannot add unique identifier
-  
-     protected:
-       using SampleConsensusModel<PointT>::sample_size_;
-       using SampleConsensusModel<PointT>::model_size_;
-  
-       /** \brief Check whether a model is valid given the user constraints.
-         * \param[in] model_coefficients the set of model coefficients
-         */
-       bool
-       isModelValid (const Eigen::VectorXf &model_coefficients) const override;
-  
-       /** \brief The axis along which we need to search for a plane perpendicular to. */
-       Eigen::Vector3f axis_;
-  
-       /** \brief The maximum allowed difference between the plane and the given axis. */
-       double eps_angle_;
-  
-       /** \brief The sine of the angle*/
-       double sin_angle_;
-   };
- }
-  
- #include "ed_sensor_integration/sac_model_horizontal_plane.hpp"
+    std::size_t
+    countWithinDistance (const Eigen::VectorXf &model_coefficients,
+                         const double threshold) const override;
+
+    /** \brief Compute all distances from the cloud data to a given plane model.
+     * \param[in] model_coefficients the coefficients of a plane model that we need to compute distances to
+     * \param[out] distances the resultant estimated distances
+     */
+    void
+    getDistancesToModel (const Eigen::VectorXf &model_coefficients,
+                         std::vector<double> &distances) const override;
+
+    /** \brief Return a unique id for this model (SACMODEL_HORIZONTAL_PLANE). */
+    inline pcl::SacModel
+    getModelType () const override { return (SACMODEL_PARALLEL_PLANE); }//cannot add unique identifier
+
+protected:
+    using SampleConsensusModel<PointT>::sample_size_;
+    using SampleConsensusModel<PointT>::model_size_;
+
+    /** \brief Check whether a model is valid given the user constraints.
+     * \param[in] model_coefficients the set of model coefficients
+     */
+    bool
+    isModelValid (const Eigen::VectorXf &model_coefficients) const override;
+
+    /** \brief The axis along which we need to search for a plane perpendicular to. */
+    Eigen::Vector3f axis_;
+
+    /** \brief The maximum allowed difference between the plane and the given axis. */
+    double eps_angle_;
+
+    /** \brief The sine of the angle*/
+    double sin_angle_;
+};
+}
+
+#include "ed_sensor_integration/sac_model_horizontal_plane.hpp"
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.hpp
index ecbb95ff..989e5bb2 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.hpp
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_horizontal_plane.hpp
@@ -37,80 +37,80 @@
   * $Id$
   a
   */
-  
- #ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_HORIZONTAL_PLANE_H_
- #define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_HORIZONTAL_PLANE_H_
-  
- #include "ed_sensor_integration/sac_model_horizontal_plane.h"
-  
- //////////////////////////////////////////////////////////////////////////
- 
- template <typename PointT> bool
- pcl::SampleConsensusModelHorizontalPlane<PointT>::computeModelCoefficients (
-       const Indices &samples, Eigen::VectorXf &model_coefficients) const
- {
-	 model_coefficients.resize (model_size_);
-	 model_coefficients[0] = 0;
-	 model_coefficients[1] = 0;
-	 model_coefficients[2] = -1;
-	 model_coefficients[3] = (*input_)[samples[0]].z;
-	 //std::cout <<model_coefficients << std::endl;
-	 return (true);
- }
- 
- template <typename PointT> void
- pcl::SampleConsensusModelHorizontalPlane<PointT>::selectWithinDistance (
-       const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
- {
-   // Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-   {
-     inliers.clear ();
-     return;
-   }
-  
-   SampleConsensusModelPlane<PointT>::selectWithinDistance (model_coefficients, threshold, inliers);
- }
-  
- //////////////////////////////////////////////////////////////////////////
- template <typename PointT> std::size_t
- pcl::SampleConsensusModelHorizontalPlane<PointT>::countWithinDistance (
-       const Eigen::VectorXf &model_coefficients, const double threshold) const
- {
-   // Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-   {
-     return (0);
-   }
-   //std::cout << model_coefficients << std::endl;
-  //std::cout << SampleConsensusModelPlane<PointT>::countWithinDistance (model_coefficients, threshold) << std::endl;
-   return (SampleConsensusModelPlane<PointT>::countWithinDistance (model_coefficients, threshold));
- }
-  
- //////////////////////////////////////////////////////////////////////////
- template <typename PointT> void
- pcl::SampleConsensusModelHorizontalPlane<PointT>::getDistancesToModel (
-       const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
- {
-   // Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-   {
-     distances.clear ();
-     return;
-   }
-  
-   SampleConsensusModelPlane<PointT>::getDistancesToModel (model_coefficients, distances);
- }
-  
- //////////////////////////////////////////////////////////////////////////
- template <typename PointT> bool
- pcl::SampleConsensusModelHorizontalPlane<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
- {
-   if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
-   {
-     return (false);
-   }
-  /*
+
+#ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_HORIZONTAL_PLANE_H_
+#define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_HORIZONTAL_PLANE_H_
+
+#include "ed_sensor_integration/sac_model_horizontal_plane.h"
+
+//////////////////////////////////////////////////////////////////////////
+
+template <typename PointT> bool
+pcl::SampleConsensusModelHorizontalPlane<PointT>::computeModelCoefficients (
+        const Indices &samples, Eigen::VectorXf &model_coefficients) const
+{
+    model_coefficients.resize (model_size_);
+    model_coefficients[0] = 0;
+    model_coefficients[1] = 0;
+    model_coefficients[2] = -1;
+    model_coefficients[3] = (*input_)[samples[0]].z;
+    //std::cout <<model_coefficients << std::endl;
+    return (true);
+}
+
+template <typename PointT> void
+pcl::SampleConsensusModelHorizontalPlane<PointT>::selectWithinDistance (
+        const Eigen::VectorXf &model_coefficients, const double threshold, Indices &inliers)
+{
+    // Check if the model is valid given the user constraints
+    if (!isModelValid (model_coefficients))
+    {
+        inliers.clear ();
+        return;
+    }
+
+    SampleConsensusModelPlane<PointT>::selectWithinDistance (model_coefficients, threshold, inliers);
+}
+
+//////////////////////////////////////////////////////////////////////////
+template <typename PointT> std::size_t
+pcl::SampleConsensusModelHorizontalPlane<PointT>::countWithinDistance (
+        const Eigen::VectorXf &model_coefficients, const double threshold) const
+{
+    // Check if the model is valid given the user constraints
+    if (!isModelValid (model_coefficients))
+    {
+        return (0);
+    }
+    //std::cout << model_coefficients << std::endl;
+    //std::cout << SampleConsensusModelPlane<PointT>::countWithinDistance (model_coefficients, threshold) << std::endl;
+    return (SampleConsensusModelPlane<PointT>::countWithinDistance (model_coefficients, threshold));
+}
+
+//////////////////////////////////////////////////////////////////////////
+template <typename PointT> void
+pcl::SampleConsensusModelHorizontalPlane<PointT>::getDistancesToModel (
+        const Eigen::VectorXf &model_coefficients, std::vector<double> &distances) const
+{
+    // Check if the model is valid given the user constraints
+    if (!isModelValid (model_coefficients))
+    {
+        distances.clear ();
+        return;
+    }
+
+    SampleConsensusModelPlane<PointT>::getDistancesToModel (model_coefficients, distances);
+}
+
+//////////////////////////////////////////////////////////////////////////
+template <typename PointT> bool
+pcl::SampleConsensusModelHorizontalPlane<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
+{
+    if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
+    {
+        return (false);
+    }
+    /*
    // Check against template, if given
    if (eps_angle_ > 0.0)
    {
@@ -118,7 +118,7 @@
      Eigen::Vector4f coeff = model_coefficients;
      coeff[3] = 0.0f;
      coeff.normalize ();
-  
+
      Eigen::Vector4f axis (axis_[0], axis_[1], axis_[2], 0.0f);
      if (std::abs (axis.dot (coeff)) > sin_angle_)
      {
@@ -127,9 +127,9 @@
      }
    }
   */
-   return (true);
- }
-  
- #define PCL_INSTANTIATE_SampleConsensusModelHorizontalPlane(T) template class PCL_EXPORTS pcl::SampleConsensusModelHorizontalPlane<T>;
-  
- #endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_HORIZONTAL_PLANE_H_
+    return (true);
+}
+
+#define PCL_INSTANTIATE_SampleConsensusModelHorizontalPlane(T) template class PCL_EXPORTS pcl::SampleConsensusModelHorizontalPlane<T>;
+
+#endif    // PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_HORIZONTAL_PLANE_H_

From 50eb12a2f0be40a4a3093787b58d96aa84271a90 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Tue, 16 Aug 2022 20:20:24 +0200
Subject: [PATCH 038/136] updat docstring of sac models

---
 .../ed_sensor_integration/sac_model_circle.h      | 14 +++++---------
 .../ed_sensor_integration/sac_model_double_line.h | 15 ++++++---------
 2 files changed, 11 insertions(+), 18 deletions(-)

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
index 0034cf9a..ffc794d0 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
@@ -46,17 +46,13 @@
 
 namespace pcl
 {
-/** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
+/** \brief @b SampleConsensusModelCircle defines a model for 2D circle from 3D samples (ignoring the third dimension).
  * The model coefficients are defined as:
- *   - \b point_on_axis.x  : the X coordinate of a point located on the cylinder axis
- *   - \b point_on_axis.y  : the Y coordinate of a point located on the cylinder axis
- *   - \b point_on_axis.z  : the Z coordinate of a point located on the cylinder axis
- *   - \b axis_direction.x : the X coordinate of the cylinder's axis direction
- *   - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
- *   - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
- *   - \b radius           : the cylinder's radius
+ *   - \b point_on_axis.x  : the X coordinate of the circle's center point
+ *   - \b point_on_axis.y  : the Y coordinate of the circle's center point
+ *   - \b radius           : the circle's radius
  *
- * \author Radu Bogdan Rusu
+ * \author Thijs Beurskens
  * \ingroup sample_consensus
  */
 template <typename PointT>
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
index 2b0a8804..681536a6 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
@@ -46,17 +46,14 @@
 
 namespace pcl
 {
-/** \brief @b SampleConsensusModelCylinder defines a model for 3D cylinder segmentation.
+/** \brief @b SampleConsensusModelDoubleLine defines a model for two parallel lines segmentation.
  * The model coefficients are defined as:
- *   - \b point_on_axis.x  : the X coordinate of a point located on the cylinder axis
- *   - \b point_on_axis.y  : the Y coordinate of a point located on the cylinder axis
- *   - \b point_on_axis.z  : the Z coordinate of a point located on the cylinder axis
- *   - \b axis_direction.x : the X coordinate of the cylinder's axis direction
- *   - \b axis_direction.y : the Y coordinate of the cylinder's axis direction
- *   - \b axis_direction.z : the Z coordinate of the cylinder's axis direction
- *   - \b radius           : the cylinder's radius
+ *   - \b point_on_axis.x  : the X coordinate of a point located on one of the lines
+ *   - \b point_on_axis.y  : the Y coordinate of a point located on one of the lines
+ *   - \b distance         : distance between the two lines, signed
+ *   - \b axis_direction.r : the angle between the lines and the x axis
  *
- * \author Radu Bogdan Rusu
+ * \author Thijs Beurskens
  * \ingroup sample_consensus
  */
 template <typename PointT>

From 81aaf5c8735942a1919a5abebafb91ff6682899d Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Tue, 16 Aug 2022 20:28:17 +0200
Subject: [PATCH 039/136] cleanup commented code

---
 ed_sensor_integration/tools/table_modeler.cpp | 66 ++++++-------------
 1 file changed, 19 insertions(+), 47 deletions(-)

diff --git a/ed_sensor_integration/tools/table_modeler.cpp b/ed_sensor_integration/tools/table_modeler.cpp
index 54a7186f..a6fbe275 100644
--- a/ed_sensor_integration/tools/table_modeler.cpp
+++ b/ed_sensor_integration/tools/table_modeler.cpp
@@ -16,7 +16,6 @@
 
 #include <pcl/sample_consensus/method_types.h>
 #include <pcl/sample_consensus/model_types.h>
-//#include <pcl/sample_consensus/ransac.h>
 
 #include <pcl/segmentation/extract_clusters.h>
 #include <pcl/segmentation/sac_segmentation.h>
@@ -47,9 +46,6 @@
  */
 void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_tgt, Eigen::Matrix4f &final_transform)
 {
-
-    //final_transform = Eigen::Matrix4f::Identity(); return; //activate to bypass alignment
-
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr src (new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr tgt (new pcl::PointCloud<pcl::PointXYZRGB>);
 
@@ -61,8 +57,6 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
     // Set the maximum distance between two correspondences (src<->tgt) to 10cm
     // Note: adjust this based on the size of your datasets
     reg.setMaxCorrespondenceDistance (1); // TODO Magic number
-    // Set the point representation
-    // reg.setPointRepresentation (pcl::make_shared<const MyPointRepresentation> (point_representation));
 
     reg.setInputSource (src);
     reg.setInputTarget (tgt);
@@ -85,10 +79,8 @@ void pairAlign (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_src, const pc
  * @param out: pointcloud with all points that lie within the plane
  * @return height (z coordinate) of the fitted plane.
  */
-float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out) {
-
-    //*out = *cloud; return(-1); //activate to bypass plane fitting and height estimation
-
+float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out)
+{
     std::vector<int> indices;
     float threshold = 0.03;
 
@@ -138,10 +130,8 @@ float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud
  * @param z: coordinate of the camera
  * @param [out] tableHeight[m]: estimated height of the table based on the cluster.
  */
-void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z, std::vector<float> &tableHeight) {
-
-    //return; //activate completely bypass segmentation and height estimation
-
+void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z, std::vector<float> &tableHeight)
+{
     std::cout << "starting segmentation" << std::endl;
     std::cout << "x = " << x << ", y = " << y << ", z = " << z << std::endl;
 
@@ -189,7 +179,6 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
             std::cout << "updating closest cluster" << std::endl;
             mindist = dist;
             cloud_out = cloud_cluster;
-            //currentTableHeight = maxz
         }
     }
 
@@ -226,7 +215,7 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, flo
     catch (tue::config::ParseException& e)
     {
         std::cerr << "Could not open '" << json_filename << "'.\n\n" << e.what() << std::endl;
-        //return 0;
+        //return 0; #TODO proper behaviour for not finding files.
     }
 
     tue::config::Reader r(meta_data);
@@ -235,7 +224,7 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, flo
     if (!ed::deserialize(r, "sensor_pose", sensor_pose))
     {
         std::cerr << "No field 'sensor_pose' specified." << std::endl;
-        //return 0;
+        //return 0; #TODO proper behaviour for not finding data.
     }
     // convert from geolib coordinates to ros coordinates #TODO remove geolib coordinates for camera pose
     sensor_pose.R = sensor_pose.R * geo::Mat3(1, 0, 0, 0, -1, 0, 0, 0, -1);
@@ -257,36 +246,21 @@ Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, flo
     *yout = y;
     *zout = z;
 
-    //float qx, qy, qz, qw;
-
-    //const float n = 2.0f/(qx*qx+qy*qy+qz*qz+qw*qw);
-    Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();/* {
-        {1.0f - n*qy*qy - n*qz*qz, n*qx*qy - n*qz*qw, n*qx*qz + n*qy*qw, x},
-        {n*qx*qy + n*qz*qw, 1.0f - n*qx*qx - n*qz*qz, n*qy*qz - n*qx*qw, y},
-        {n*qx*qz - n*qy*qw, n*qy*qz + n*qx*qw, 1.0f - n*qx*qx - n*qy*qy, z},
-        {0.0f, 0.0f, 0.0f, 1.0f}}; */
+    Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();
 
-    Transform(0,0) = xx;//1.0f - n*qy*qy - n*qz*qz;
-    Transform(0,1) = xy;//n*qx*qy - n*qz*qw;
-    Transform(0,2) = xz;//n*qx*qz + n*qy*qw;
+    Transform(0,0) = xx;
+    Transform(0,1) = xy;
+    Transform(0,2) = xz;
     Transform(0,3) = x;
-    Transform(1,0) = yx;//n*qx*qy + n*qz*qw;
-    Transform(1,1) = yy;//1.0f - n*qx*qx - n*qz*qz;
-    Transform(1,2) = yz;//n*qy*qz - n*qx*qw;
+    Transform(1,0) = yx;
+    Transform(1,1) = yy;
+    Transform(1,2) = yz;
     Transform(1,3) = y;
-    Transform(2,0) = zx;//n*qx*qz - n*qy*qw;
-    Transform(2,1) = zy;//n*qy*qz + n*qx*qw;
-    Transform(2,2) = zz;//1.0f - n*qx*qx - n*qy*qy;
+    Transform(2,0) = zx;
+    Transform(2,1) = zy;
+    Transform(2,2) = zz;
     Transform(2,3) = z;
 
-    /*
-    //Temporary fix for wrong rotational matrix
-    Eigen::Matrix4f Correction = Eigen::Matrix4f::Identity();
-    Correction(1,1) = -1;
-    Correction(2,2) = -1;
-    Transform = Transform * Correction.inverse();
-    */
-
     std::cout << Transform << std::endl;
     return Transform;
 }
@@ -431,10 +405,8 @@ Eigen::VectorXf Fit(pcl::PointCloud<pcl::PointXYZ> cloud) {
     return (output);
 }
 
-int main(int argc, char **argv) {
-
-    // open pcd files
-
+int main(int argc, char **argv)
+{
     if (argc < 2)
     {
         std::cout << "Usage:\n\n   table_modeler FILENAME1 FILENAME2 ...\n\n";
@@ -454,7 +426,7 @@ int main(int argc, char **argv) {
         std::cout << "attempting to open " << name << std::endl;
         if (pcl::io::loadPCDFile<pcl::PointXYZRGB> (name, *m) == -1) //* load the file
         {
-            //PCL_ERROR ("Couldn't read file" + name + "\n");
+            std::cout << "Couldn't read file" << name << std::endl;
             return -1;
         }
         std::cout << "opened " << name << std::endl;

From ce99405214337f4b8874e77187b5c18449e74080 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Tue, 16 Aug 2022 20:55:41 +0200
Subject: [PATCH 040/136] fix semicolon

---
 .../ed_sensor_integration/sac_model_double_line.hpp       | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
index 526c8cec..ba09ab6b 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
@@ -129,10 +129,10 @@ pcl::SampleConsensusModelDoubleLine<PointT>::getDistancesToModel (
 
     distances.resize (indices_->size ());
 
-    float x = model_coefficients[0]
-            float y = model_coefficients[1]
-            float w = model_coefficients[2]
-            float r = model_coefficients[3];
+    float x = model_coefficients[0];
+    float y = model_coefficients[1];
+    float w = model_coefficients[2];
+    float r = model_coefficients[3];
     float d1, d2;
 
     Eigen::Vector2f p1, p2, p3, p4, c1, c2;

From e6bf91d4f568be0300f180b09b0432f5ec15136b Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Tue, 16 Aug 2022 21:35:28 +0200
Subject: [PATCH 041/136] cleanup sac models

---
 .../ed_sensor_integration/sac_model_circle.h  |  38 +----
 .../sac_model_circle.hpp                      | 148 +-----------------
 .../sac_model_double_line.h                   |  38 +----
 .../sac_model_double_line.hpp                 | 115 --------------
 4 files changed, 5 insertions(+), 334 deletions(-)

diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
index ffc794d0..c895fb47 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.h
@@ -79,8 +79,6 @@ class SampleConsensusModelCircle : public SampleConsensusModel<PointT>
      */
     SampleConsensusModelCircle (const PointCloudConstPtr &cloud, bool random = false)
         : SampleConsensusModel<PointT> (cloud, random)
-        , axis_ (Eigen::Vector3f::Zero ())
-        , eps_angle_ (INFINITY)
     {
         model_name_ = "SampleConsensusModelCircle";
         sample_size_ = 3;
@@ -96,8 +94,6 @@ class SampleConsensusModelCircle : public SampleConsensusModel<PointT>
                                 const Indices &indices,
                                 bool random = false)
         : SampleConsensusModel<PointT> (cloud, indices, random)
-        , axis_ (Eigen::Vector3f::Zero ())
-        , eps_angle_ (0)
     {
         model_name_ = "SampleConsensusModelCircle";
         sample_size_ = 3;
@@ -108,9 +104,7 @@ class SampleConsensusModelCircle : public SampleConsensusModel<PointT>
      * \param[in] source the model to copy into this
      */
     SampleConsensusModelCircle (const SampleConsensusModelCircle &source) :
-        SampleConsensusModel<PointT> (),
-        axis_ (Eigen::Vector3f::Zero ()),
-        eps_angle_ (0)
+        SampleConsensusModel<PointT> ()
     {
         *this = source;
         model_name_ = "SampleConsensusModelCircle";
@@ -126,31 +120,9 @@ class SampleConsensusModelCircle : public SampleConsensusModel<PointT>
     operator = (const SampleConsensusModelCircle &source)
     {
         SampleConsensusModel<PointT>::operator=(source);
-        axis_ = source.axis_;
-        eps_angle_ = source.eps_angle_;
         return (*this);
     }
 
-    /** \brief Set the angle epsilon (delta) threshold.
-     * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
-     */
-    inline void
-    setEpsAngle (const double ea) { eps_angle_ = ea; }
-
-    /** \brief Get the angle epsilon (delta) threshold. */
-    inline double
-    getEpsAngle () const { return (eps_angle_); }
-
-    /** \brief Set the axis along which we need to search for a cylinder direction.
-     * \param[in] ax the axis along which we need to search for a cylinder direction
-     */
-    inline void
-    setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
-
-    /** \brief Get the axis along which we need to search for a cylinder direction. */
-    inline Eigen::Vector3f
-    getAxis () const { return (axis_); }
-
     /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
      * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
      * axis_direction, cylinder_radius_R
@@ -225,7 +197,7 @@ class SampleConsensusModelCircle : public SampleConsensusModel<PointT>
 
     /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
     inline pcl::SacModel
-    getModelType () const override { return (SACMODEL_CYLINDER); } //cannot add a unique identifier for double line
+    getModelType () const override { return (SACMODEL_CYLINDER); } // #TODO cannot add a unique identifier
 
 protected:
     using SampleConsensusModel<PointT>::sample_size_;
@@ -280,12 +252,6 @@ class SampleConsensusModelCircle : public SampleConsensusModel<PointT>
     isSampleGood (const Indices &samples) const override;
 
 private:
-    /** \brief The axis along which we need to search for a cylinder direction. */
-    Eigen::Vector3f axis_;
-
-    /** \brief The maximum allowed difference between the cylinder direction and the given axis. */
-    double eps_angle_;
-
     /** \brief Functor for the optimization function */
     struct OptimizationFunctor : pcl::Functor<float>
     {
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp
index 54028d16..8c395a25 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_circle.hpp
@@ -105,7 +105,6 @@ pcl::SampleConsensusModelCircle<PointT>::computeModelCoefficients (
 
     PCL_DEBUG ("[pcl::SampleConsensusModelCircle::computeModelCoefficients] Model is (%g,%g,%g).\n",
                model_coefficients[0], model_coefficients[1], model_coefficients[2]);
-    //std::cout << "P1: " << std::endl << p1 << std::endl << "P2: " << std::endl << p2 << std::endl << "P3: " << std::endl << p3 << std::endl << model_coefficients << std::endl;
     return (true);
 }
 
@@ -134,37 +133,7 @@ pcl::SampleConsensusModelCircle<PointT>::getDistancesToModel (
         Eigen::Vector2f in ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y);
         c1 = p1 - in;
         distances[i] = std::abs(sqrt(c1.dot(c1))-r);
-
-        //std::cout << distances[i] << std::endl;
     }
-    //std::cout << std::accumulate(distances.begin(), distances.end(), 0.0) / distances.size() << ", ";
-    /*
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-   // Iterate through the 3d points and calculate the distances from them to the sphere
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     // @note need to revise this.
-     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
-
-     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
-
-     // Calculate the point's projection on the cylinder axis
-     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
-     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
-     Eigen::Vector4f dir = pt - pt_proj;
-     dir.normalize ();
-
-     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
-     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
-     double d_normal = std::abs (getAngle3D (n, dir));
-     d_normal = (std::min) (d_normal, M_PI - d_normal);
-
-     distances[i] = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);*/
 }
 
 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -178,54 +147,6 @@ pcl::SampleConsensusModelCircle<PointT>::selectWithinDistance (
     {
         if (distances[i] < threshold) {inliers.push_back ((*indices_)[i]);}
     }
-
-    //std::cout << model_coefficients[2] << std::endl;
-    /*
-   // Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-   {
-     inliers.clear ();
-     return;
-   }
-
-   inliers.clear ();
-   error_sqr_dists_.clear ();
-   inliers.reserve (indices_->size ());
-   error_sqr_dists_.reserve (indices_->size ());
-
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-   // Iterate through the 3d points and calculate the distances from them to the sphere
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
-     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
-     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
-       continue;
-
-     // Calculate the point's projection on the cylinder axis
-     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
-     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
-     Eigen::Vector4f dir = pt - pt_proj;
-     dir.normalize ();
-
-     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
-     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
-     double d_normal = std::abs (getAngle3D (n, dir));
-     d_normal = (std::min) (d_normal, M_PI - d_normal);
-
-     double distance = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);
-     if (distance < threshold)
-     {
-       // Returns the indices of the points whose distances are smaller than the threshold
-       inliers.push_back ((*indices_)[i]);
-       error_sqr_dists_.push_back (distance);
-     }
-   }*/
 }
 
 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -240,44 +161,7 @@ pcl::SampleConsensusModelCircle<PointT>::countWithinDistance (
     {
         if (distances[i] <= threshold) {count++;}
     }
-    //std::cout << count << std::endl;
     return (count);
-    /*// Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-     return (0);
-
-   std::size_t nr_p = 0;
-
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-   // Iterate through the 3d points and calculate the distances from them to the sphere
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
-     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
-     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
-       continue;
-
-     // Calculate the point's projection on the cylinder axis
-     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
-     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
-     Eigen::Vector4f dir = pt - pt_proj;
-     dir.normalize ();
-
-     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
-     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
-     double d_normal = std::abs (getAngle3D (n, dir));
-     d_normal = (std::min) (d_normal, M_PI - d_normal);
-
-     if (std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist) < threshold)
-       nr_p++;
-   }
-   return (nr_p);*/
-    return (0);
 }
 
 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -427,7 +311,6 @@ pcl::SampleConsensusModelCircle<PointT>::doSamplesVerifyModel (
         if (std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]) > threshold)
             return (false);
     }
-
     return (true);
 }
 
@@ -460,41 +343,12 @@ pcl::SampleConsensusModelCircle<PointT>::projectPointToRectangle (
 }
 
 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
+// TODO do not overwrite we dont change it.
 template <typename PointT> bool
 pcl::SampleConsensusModelCircle<PointT>::isModelValid (const Eigen::VectorXf &model_coefficients) const
 {
     if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
         return (false);
-    /*
-   // Check against template, if given
-   if (eps_angle_ > 0.0)
-   {
-     // Obtain the cylinder direction
-     const Eigen::Vector3f coeff(model_coefficients[3], model_coefficients[4], model_coefficients[5]);
-
-     double angle_diff = std::abs (getAngle3D (axis_, coeff));
-     angle_diff = (std::min) (angle_diff, M_PI - angle_diff);
-     // Check whether the current cylinder model satisfies our angle threshold criterion with respect to the given axis
-     if (angle_diff > eps_angle_)
-     {
-       PCL_DEBUG ("[pcl::SampleConsensusModelCircle::isModelValid] Angle between cylinder direction and given axis is too large.\n");
-       return (false);
-     }
-   }
-
-   if (radius_min_ != -std::numeric_limits<double>::max() && model_coefficients[6] < radius_min_)
-   {
-     PCL_DEBUG ("[pcl::SampleConsensusModelCircle::isModelValid] Radius is too small: should be larger than %g, but is %g.\n",
-                radius_min_, model_coefficients[6]);
-     return (false);
-   }
-   if (radius_max_ != std::numeric_limits<double>::max() && model_coefficients[6] > radius_max_)
-   {
-     PCL_DEBUG ("[pcl::SampleConsensusModelCircle::isModelValid] Radius is too big: should be smaller than %g, but is %g.\n",
-                radius_max_, model_coefficients[6]);
-     return (false);
-   }*/
-
     return (true);
 }
 
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
index 681536a6..6a60559b 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.h
@@ -80,8 +80,6 @@ class SampleConsensusModelDoubleLine : public SampleConsensusModel<PointT>
      */
     SampleConsensusModelDoubleLine (const PointCloudConstPtr &cloud, bool random = false)
         : SampleConsensusModel<PointT> (cloud, random)
-        , axis_ (Eigen::Vector3f::Zero ())
-        , eps_angle_ (INFINITY)
     {
         model_name_ = "SampleConsensusModelDoubleLine";
         sample_size_ = 3;
@@ -97,8 +95,6 @@ class SampleConsensusModelDoubleLine : public SampleConsensusModel<PointT>
                                     const Indices &indices,
                                     bool random = false)
         : SampleConsensusModel<PointT> (cloud, indices, random)
-        , axis_ (Eigen::Vector3f::Zero ())
-        , eps_angle_ (0)
     {
         model_name_ = "SampleConsensusModelDoubleLine";
         sample_size_ = 3;
@@ -109,9 +105,7 @@ class SampleConsensusModelDoubleLine : public SampleConsensusModel<PointT>
      * \param[in] source the model to copy into this
      */
     SampleConsensusModelDoubleLine (const SampleConsensusModelDoubleLine &source) :
-        SampleConsensusModel<PointT> (),
-        axis_ (Eigen::Vector3f::Zero ()),
-        eps_angle_ (0)
+        SampleConsensusModel<PointT> ()
     {
         *this = source;
         model_name_ = "SampleConsensusModelDoubleLine";
@@ -127,31 +121,9 @@ class SampleConsensusModelDoubleLine : public SampleConsensusModel<PointT>
     operator = (const SampleConsensusModelDoubleLine &source)
     {
         SampleConsensusModel<PointT>::operator=(source);
-        axis_ = source.axis_;
-        eps_angle_ = source.eps_angle_;
         return (*this);
     }
 
-    /** \brief Set the angle epsilon (delta) threshold.
-     * \param[in] ea the maximum allowed difference between the cylinder axis and the given axis.
-     */
-    inline void
-    setEpsAngle (const double ea) { eps_angle_ = ea; }
-
-    /** \brief Get the angle epsilon (delta) threshold. */
-    inline double
-    getEpsAngle () const { return (eps_angle_); }
-
-    /** \brief Set the axis along which we need to search for a cylinder direction.
-     * \param[in] ax the axis along which we need to search for a cylinder direction
-     */
-    inline void
-    setAxis (const Eigen::Vector3f &ax) { axis_ = ax; }
-
-    /** \brief Get the axis along which we need to search for a cylinder direction. */
-    inline Eigen::Vector3f
-    getAxis () const { return (axis_); }
-
     /** \brief Check whether the given index samples can form a valid cylinder model, compute the model coefficients
      * from these samples and store them in model_coefficients. The cylinder coefficients are: point_on_axis,
      * axis_direction, cylinder_radius_R
@@ -226,7 +198,7 @@ class SampleConsensusModelDoubleLine : public SampleConsensusModel<PointT>
 
     /** \brief Return a unique id for this model (SACMODEL_CYLINDER). */
     inline pcl::SacModel
-    getModelType () const override { return (SACMODEL_CYLINDER); } //cannot add a unique identifier for double line
+    getModelType () const override { return (SACMODEL_CYLINDER); } // #TODO cannot add a unique identifier for double line
 
 protected:
     using SampleConsensusModel<PointT>::sample_size_;
@@ -281,12 +253,6 @@ class SampleConsensusModelDoubleLine : public SampleConsensusModel<PointT>
     isSampleGood (const Indices &samples) const override;
 
 private:
-    /** \brief The axis along which we need to search for a cylinder direction. */
-    Eigen::Vector3f axis_;
-
-    /** \brief The maximum allowed difference between the cylinder direction and the given axis. */
-    double eps_angle_;
-
     /** \brief Functor for the optimization function */
     struct OptimizationFunctor : pcl::Functor<float>
     {
diff --git a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
index ba09ab6b..e7b64bac 100644
--- a/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
+++ b/ed_sensor_integration/include/ed_sensor_integration/sac_model_double_line.hpp
@@ -175,54 +175,6 @@ pcl::SampleConsensusModelDoubleLine<PointT>::selectWithinDistance (
     {
         if (distances[i] < threshold) {inliers.push_back ((*indices_)[i]);}
     }
-
-    //std::cout << model_coefficients[2] << std::endl;
-    /*
-   // Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-   {
-     inliers.clear ();
-     return;
-   }
-
-   inliers.clear ();
-   error_sqr_dists_.clear ();
-   inliers.reserve (indices_->size ());
-   error_sqr_dists_.reserve (indices_->size ());
-
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0.0f);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0.0f);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-   // Iterate through the 3d points and calculate the distances from them to the sphere
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
-     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
-     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
-       continue;
-
-     // Calculate the point's projection on the cylinder axis
-     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
-     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
-     Eigen::Vector4f dir = pt - pt_proj;
-     dir.normalize ();
-
-     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
-     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
-     double d_normal = std::abs (getAngle3D (n, dir));
-     d_normal = (std::min) (d_normal, M_PI - d_normal);
-
-     double distance = std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist);
-     if (distance < threshold)
-     {
-       // Returns the indices of the points whose distances are smaller than the threshold
-       inliers.push_back ((*indices_)[i]);
-       error_sqr_dists_.push_back (distance);
-     }
-   }*/
 }
 
 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -237,44 +189,7 @@ pcl::SampleConsensusModelDoubleLine<PointT>::countWithinDistance (
     {
         if (distances[i] <= threshold) {count++;}
     }
-    //std::cout << count << std::endl;
     return (count);
-    /*// Check if the model is valid given the user constraints
-   if (!isModelValid (model_coefficients))
-     return (0);
-
-   std::size_t nr_p = 0;
-
-   Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);
-   Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);
-   float ptdotdir = line_pt.dot (line_dir);
-   float dirdotdir = 1.0f / line_dir.dot (line_dir);
-   // Iterate through the 3d points and calculate the distances from them to the sphere
-   for (std::size_t i = 0; i < indices_->size (); ++i)
-   {
-     // Approximate the distance from the point to the cylinder as the difference between
-     // dist(point,cylinder_axis) and cylinder radius
-     Eigen::Vector4f pt ((*input_)[(*indices_)[i]].x, (*input_)[(*indices_)[i]].y, (*input_)[(*indices_)[i]].z, 0.0f);
-     const double weighted_euclid_dist = (1.0 - normal_distance_weight_) * std::abs (pointToLineDistance (pt, model_coefficients) - model_coefficients[6]);
-     if (weighted_euclid_dist > threshold) // Early termination: cannot be an inlier
-       continue;
-
-     // Calculate the point's projection on the cylinder axis
-     float k = (pt.dot (line_dir) - ptdotdir) * dirdotdir;
-     Eigen::Vector4f pt_proj = line_pt + k * line_dir;
-     Eigen::Vector4f dir = pt - pt_proj;
-     dir.normalize ();
-
-     // Calculate the angular distance between the point normal and the (dir=pt_proj->pt) vector
-     Eigen::Vector4f n  ((*normals_)[(*indices_)[i]].normal[0], (*normals_)[(*indices_)[i]].normal[1], (*normals_)[(*indices_)[i]].normal[2], 0.0f);
-     double d_normal = std::abs (getAngle3D (n, dir));
-     d_normal = (std::min) (d_normal, M_PI - d_normal);
-
-     if (std::abs (normal_distance_weight_ * d_normal + weighted_euclid_dist) < threshold)
-       nr_p++;
-   }
-   return (nr_p);*/
-    return (0);
 }
 
 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
@@ -462,36 +377,6 @@ pcl::SampleConsensusModelDoubleLine<PointT>::isModelValid (const Eigen::VectorXf
 {
     if (!SampleConsensusModel<PointT>::isModelValid (model_coefficients))
         return (false);
-    /*
-   // Check against template, if given
-   if (eps_angle_ > 0.0)
-   {
-     // Obtain the cylinder direction
-     const Eigen::Vector3f coeff(model_coefficients[3], model_coefficients[4], model_coefficients[5]);
-
-     double angle_diff = std::abs (getAngle3D (axis_, coeff));
-     angle_diff = (std::min) (angle_diff, M_PI - angle_diff);
-     // Check whether the current cylinder model satisfies our angle threshold criterion with respect to the given axis
-     if (angle_diff > eps_angle_)
-     {
-       PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::isModelValid] Angle between cylinder direction and given axis is too large.\n");
-       return (false);
-     }
-   }
-
-   if (radius_min_ != -std::numeric_limits<double>::max() && model_coefficients[6] < radius_min_)
-   {
-     PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::isModelValid] Radius is too small: should be larger than %g, but is %g.\n",
-                radius_min_, model_coefficients[6]);
-     return (false);
-   }
-   if (radius_max_ != std::numeric_limits<double>::max() && model_coefficients[6] > radius_max_)
-   {
-     PCL_DEBUG ("[pcl::SampleConsensusModelDoubleLine::isModelValid] Radius is too big: should be smaller than %g, but is %g.\n",
-                radius_max_, model_coefficients[6]);
-     return (false);
-   }*/
-
     return (true);
 }
 

From a5e9c3f0eb2bbd73fb91f7409ce00f226ae78803 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Thu, 18 Aug 2022 17:04:10 +0200
Subject: [PATCH 042/136] made empty_spot_visualizer live

---
 ed_sensor_integration/CMakeLists.txt          |   2 +-
 .../src/kinect/empty_spot_designator.cpp      | 115 +++++++++++++-----
 2 files changed, 83 insertions(+), 34 deletions(-)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index 2b6375af..bcd53e97 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -125,7 +125,7 @@ add_executable(ed_table_modeler tools/table_modeler.cpp)
 target_link_libraries (ed_table_modeler ${catkin_LIBRARIES})
 
 add_executable(ed_empty_spot_designator src/kinect/empty_spot_designator.cpp)
-target_link_libraries(ed_empty_spot_designator ${catkin_LIBRARIES})
+target_link_libraries(ed_empty_spot_designator ed_kinect ${catkin_LIBRARIES})
 # ------------------------------------------------------------------------------------------------
 #                                           TESTS
 # ------------------------------------------------------------------------------------------------
diff --git a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
index 4babf10b..9009ddd7 100644
--- a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
+++ b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
@@ -1,9 +1,14 @@
 #include <iostream>
 #include <string>
 
+#include <ed/kinect/image_buffer.h>
+
 #include "opencv2/imgproc.hpp"
 #include <opencv2/highgui.hpp>
 
+#include <ros/ros.h>
+#include <rgbd/image.h>
+
 //pcl library
 #include <pcl/io/pcd_io.h>
 
@@ -11,11 +16,31 @@
 double resolution = 0.005;
 cv::Point2d canvas_center;
 
-void readPCD(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, std::string filename)
+void imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZ>::Ptr cloud)
 {
     // Fill in the cloud data
-    pcl::PCDReader reader;
-    reader.read (filename, *cloud); //
+    cloud->width = image.getDepthImage().cols;
+    cloud->height = image.getDepthImage().rows;
+    cloud->is_dense = false;
+    cloud->resize (cloud->width * cloud->height);
+
+    double fx = image.getCameraModel().fx();
+    double fy = image.getCameraModel().fy();
+
+    double half_height = 0.5 * cloud->height;
+    double half_width = 0.5 * cloud->width;
+
+    for (uint i=0; i < cloud->height; ++i)
+    {
+        for (uint j=0; j < cloud->width; ++j)
+        {
+            double d = image.getDepthImage().at<float>(i,j);
+
+            cloud->at(j,i).x = (-half_width+j) * d / fx;
+            cloud->at(j,i).y = (-half_height+i) * d / fy;
+            cloud->at(j,i).z = d;
+        }
+    }
 }
 
 cv::Point2d worldToCanvas(double x, double y)
@@ -47,49 +72,73 @@ void dilateCostmap(cv::Mat& canvas)
     cv::dilate(canvas, canvas, element );
 }
 
+/**
+ * @brief usage, print how the executable should be used and explain the input
+ */
 void usage()
 {
-    std::cout << "USAGE: empty_spot_designator [pointcloud.pcd] [table_pointcloud.pcd]" << std::endl;
+    std::cout << "Usage: ed_empty_spot_designator RGBD_TOPIC" << std::endl
+              << "RGBD_TOPIC topic on which the rgbd image is published, example /hero/head_rgbd_sensor/rgbd" << std::endl;
 }
 
+
+/**
+ * @brief main executable to visualise the empty spot finder of live images.
+ * @param argc:
+ * @return
+ */
 int main (int argc, char **argv)
 {
-    if (argc != 3)
+    if (argc != 2)
     {
         usage();
         return 0;
     }
 
-    std::cout << "finding empty spot" << std::endl;
-
-    std::cout << "Loading pcd file" << std::endl;
+    ros::init(argc, argv, "empty_spot_visualizer");
 
-    std::string filename = argv[2];
-    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
-    readPCD(cloud, filename);
-
-    // read occupied data
-    std::string occupied_filename = argv[1];
-    pcl::PointCloud<pcl::PointXYZ>::Ptr occupied_cloud (new pcl::PointCloud<pcl::PointXYZ>);
-    readPCD(occupied_cloud, occupied_filename);
-
-    std::cout << "PointCloud representing the planar component: " << cloud->width * cloud->height << " data points." << std::endl;
-
-
-    std::cout << "creating costmap" << std::endl;
-    cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
-    cv::Scalar table_color(0, 255, 0);
-    cv::Scalar occupied_color(0, 0, 255);
-
-    //createCostmap(occupied_cloud, canvas, occupied_color);
-    createCostmap(cloud, canvas, table_color);
-
-    dilateCostmap(canvas);
-
-    std::cout << "showing costmap" << std::endl;
-    cv::imshow("Laser Vizualization", canvas);
-    cv::waitKey();
+    std::string topic = argv[1];
+    std::cout << "Using topic: " << topic << std::endl;
 
+    ImageBuffer image_buffer;
+    image_buffer.initialize(topic, "base_link");
 
+    while(ros::ok())
+    {
+        rgbd::ImageConstPtr image;
+        geo::Pose3D sensor_pose;
+
+        if (!image_buffer.waitForRecentImage(image, sensor_pose, 2.0))
+        {
+            std::cerr << "No image received, will try again." << std::endl;
+            continue;
+        }
+        std::cout << "converting image to cloud" << std::endl;
+        pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
+        imageToCloud(*image, cloud);
+
+        std::cout << "creating costmap" << std::endl;
+        cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
+        cv::Scalar table_color(0, 255, 0);
+        cv::Scalar occupied_color(0, 0, 255);
+
+        //createCostmap(occupied_cloud, canvas, occupied_color);
+        createCostmap(cloud, canvas, table_color);
+
+        std::cout << "showing costmap" << std::endl;
+        cv::imshow("Laser Vizualization", canvas);
+
+        // show snapshot
+        cv::Mat rgbcanvas = image->getRGBImage();
+        cv::imshow("RGB", rgbcanvas);
+
+        char key = cv::waitKey(30);
+
+        if (key == 'q')
+        {
+            break;
+        }
+    }
+    cv::destroyAllWindows();
     return 0;
 }

From 4ee5226abb23f7c3b1331f80628afeeee57f133a Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 20 Aug 2022 16:44:06 +0200
Subject: [PATCH 043/136] added segmentation

---
 .../src/kinect/empty_spot_designator.cpp      | 207 +++++++++++++++++-
 1 file changed, 202 insertions(+), 5 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
index 9009ddd7..b43a9e99 100644
--- a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
+++ b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
@@ -9,14 +9,37 @@
 #include <ros/ros.h>
 #include <rgbd/image.h>
 
-//pcl library
+//pcl library # TODO remove the unused ones #TODO find out which ones are unused
+#include <pcl/point_cloud.h>
+#include <pcl/point_representation.h>
+
 #include <pcl/io/pcd_io.h>
 
+#include <pcl/filters/filter.h>
+#include <pcl/filters/extract_indices.h>
+#include <pcl/filters/conditional_removal.h>
+
+#include <pcl/features/normal_3d.h>
+
+#include <pcl/registration/icp.h>
+#include <pcl/registration/icp_nl.h>
+#include <pcl/registration/transforms.h>
+
+#include <pcl/sample_consensus/method_types.h>
+#include <pcl/sample_consensus/model_types.h>
+
+#include <pcl/segmentation/extract_clusters.h>
+#include <pcl/segmentation/sac_segmentation.h>
+
+#include <pcl/surface/convex_hull.h>
+
+#include "ed_sensor_integration/sac_model_horizontal_plane.h"
+
 
 double resolution = 0.005;
 cv::Point2d canvas_center;
 
-void imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZ>::Ptr cloud)
+void imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
 {
     // Fill in the cloud data
     cloud->width = image.getDepthImage().cols;
@@ -43,12 +66,164 @@ void imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZ>::Ptr
     }
 }
 
+Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
+{
+    // convert from geolib coordinates to ros coordinates #TODO remove geolib coordinates for camera pose
+    pose.R = pose.R * geo::Mat3(1, 0, 0, 0, -1, 0, 0, 0, -1);
+
+    float x = pose.t.x;
+    float y = pose.t.y;
+    float z = pose.t.z;
+    float xx = pose.R.xx;
+    float xy = pose.R.xy;
+    float xz = pose.R.xz;
+    float yx = pose.R.yx;
+    float yy = pose.R.yy;
+    float yz = pose.R.yz;
+    float zx = pose.R.zx;
+    float zy = pose.R.zy;
+    float zz = pose.R.zz;
+
+    Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();
+
+    Transform(0,0) = xx;
+    Transform(0,1) = xy;
+    Transform(0,2) = xz;
+    Transform(0,3) = x;
+    Transform(1,0) = yx;
+    Transform(1,1) = yy;
+    Transform(1,2) = yz;
+    Transform(1,3) = y;
+    Transform(2,0) = zx;
+    Transform(2,1) = zy;
+    Transform(2,2) = zz;
+    Transform(2,3) = z;
+
+    std::cout << Transform << std::endl;
+    return Transform;
+}
+
+/**
+ * @brief FilterPlane fit a plane through a pointcloud, filter the points which lie in this plane and return the height of the plane #TODO separation of concerns.
+ * @param cloud: pointcloud to be filtered.
+ * @param out: pointcloud with all points that lie within the plane
+ * @return height (z coordinate) of the fitted plane.
+ */
+float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out)
+{
+    std::vector<int> indices;
+    float threshold = 0.03;
+
+    std::cout << "starting ransac" << std::endl;
+    // Create SAC model
+    pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>::Ptr plane (new pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>(cloud));
+    std::cout << "created plane object" << std::endl;
+    // Create SAC method
+    pcl::RandomSampleConsensus<pcl::PointXYZRGB>::Ptr sac (new pcl::RandomSampleConsensus<pcl::PointXYZRGB> (plane, threshold));
+    std::cout << "created ransac object" << std::endl;
+    sac->setMaxIterations(10000);
+    sac->setProbability(0.99);
+
+    // Fit model
+    sac->computeModel();
+
+    // Get inliers
+    std::vector<int> inliers;
+    sac->getInliers(inliers);
+
+    // Get the model coefficients
+    Eigen::VectorXf coeff;
+    sac->getModelCoefficients (coeff);
+    std::cout << "ransac complete" << std::endl;
+
+    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+    range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
+    *out = *cloud;
+    //filter out everything below plane
+    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+    condrem.setCondition (range_cond);
+    condrem.setInputCloud (out);
+    condrem.setKeepOrganized(true);
+
+    condrem.filter (*out);
+    (*out).is_dense = false;
+    pcl::removeNaNFromPointCloud(*out, *out, indices);
+
+    return(coeff[3]);
+}
+
+/**
+ * @brief Segment segment the pointcloud and return the cluster closest to the camera
+ * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
+ * @param x: coordinate of the camera
+ * @param y: coordinate of the camera
+ * @param z: coordinate of the camera
+ * @param [out] tableHeight[m]: estimated height of the table based on the cluster.
+ */
+void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z)
+{
+    std::cout << "starting segmentation" << std::endl;
+    std::cout << "x = " << x << ", y = " << y << ", z = " << z << std::endl;
+
+    // Creating the KdTree object for the search method of the extraction
+    pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZRGB>);
+    tree->setInputCloud (cloud);
+
+    std::vector<pcl::PointIndices> cluster_indices;
+    pcl::EuclideanClusterExtraction<pcl::PointXYZRGB> ec; //using euclidian cluster extraction
+    ec.setClusterTolerance (0.1);
+    ec.setMinClusterSize ((*cloud).size()/100); //#TODO magic number
+    ec.setMaxClusterSize ((*cloud).size());
+    ec.setSearchMethod (tree);
+    ec.setInputCloud (cloud);
+    ec.extract (cluster_indices);
+
+    std::cout << "obtained cluster indices" <<std::endl;
+
+    //find closest cluster
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out;
+    float mindist = INFINITY;
+    for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it !=
+         cluster_indices.end (); ++it) //iterate through all clusters
+    {
+        //construct cluster
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZRGB>);
+        for (const auto& idx : it->indices)
+            cloud_cluster->push_back ((*cloud)[idx]); //*
+        cloud_cluster->width = cloud_cluster->size ();
+        cloud_cluster->height = 1;
+        cloud_cluster->is_dense = true;
+        float sumx = 0, sumy = 0, sumz = 0, dist = 0;
+        for (uint j=0; j < (*cloud_cluster).width; ++j)
+        {
+            //sum up all points
+            sumx += (*cloud_cluster)[j].x;
+            sumy += (*cloud_cluster)[j].y;
+            sumz += (*cloud_cluster)[j].z;
+        }
+        //find distance from camera to the middle of the cluster
+        dist = pow((sumx/(*cloud_cluster).width-x),2) + pow((sumy/(*cloud_cluster).width-y),2) + pow((sumz/(*cloud_cluster).width-z),2);
+        std::cout << "distance is " << sqrt(dist) << std::endl;
+        if (dist < mindist) //check if closest so far
+        {
+            std::cout << "updating closest cluster" << std::endl;
+            mindist = dist;
+            cloud_out = cloud_cluster;
+        }
+    }
+
+    float height = FilterPlane(cloud_out, cloud_out);
+
+    std::cout << "writing closest cluster" << std::endl;
+    *cloud = *cloud_out;
+}
+
 cv::Point2d worldToCanvas(double x, double y)
 {
     return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
 }
 
-void createCostmap(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, cv::Mat& canvas, cv::Scalar color)
+void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Mat& canvas, cv::Scalar color)
 {
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
@@ -114,9 +289,31 @@ int main (int argc, char **argv)
             continue;
         }
         std::cout << "converting image to cloud" << std::endl;
-        pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
         imageToCloud(*image, cloud);
 
+        // transform to base link frame
+        Eigen::Matrix4f transform = geolibToEigen(sensor_pose);
+        pcl::transformPointCloud(*cloud, *cloud, transform);
+
+        // keep track of the indices in the original image
+        std::vector<int> indices;
+
+        // Filter out floor
+        pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+        range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, 0.1)));
+        // build the filter
+        pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+        condrem.setCondition (range_cond);
+        condrem.setInputCloud (cloud);
+        condrem.setKeepOrganized(true);
+        // apply filter
+        condrem.filter (*cloud);
+        (*cloud).is_dense = false;
+        pcl::removeNaNFromPointCloud(*cloud, *cloud, indices);
+
+        Segment(cloud, 0.0, 0.0, 0.0);
+
         std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
         cv::Scalar table_color(0, 255, 0);
@@ -126,7 +323,7 @@ int main (int argc, char **argv)
         createCostmap(cloud, canvas, table_color);
 
         std::cout << "showing costmap" << std::endl;
-        cv::imshow("Laser Vizualization", canvas);
+        cv::imshow("Costmap topview", canvas);
 
         // show snapshot
         cv::Mat rgbcanvas = image->getRGBImage();

From 68732a5df5f08b8c755a632a3d3d64e0c8398ace Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Mon, 22 Aug 2022 13:53:48 +0200
Subject: [PATCH 044/136] add_saving of costmap

---
 .../src/kinect/empty_spot_designator.cpp          | 15 ++++++++++++++-
 1 file changed, 14 insertions(+), 1 deletion(-)

diff --git a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
index b43a9e99..b407d55d 100644
--- a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
+++ b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
@@ -57,11 +57,16 @@ void imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::P
     {
         for (uint j=0; j < cloud->width; ++j)
         {
+
+            cv::Vec3b bgr = image.getRGBImage().at<cv::Vec3b>(i,j);
             double d = image.getDepthImage().at<float>(i,j);
 
             cloud->at(j,i).x = (-half_width+j) * d / fx;
             cloud->at(j,i).y = (-half_height+i) * d / fy;
             cloud->at(j,i).z = d;
+            cloud->at(j,i).r = bgr[2];
+            cloud->at(j,i).g = bgr[1];
+            cloud->at(j,i).b = bgr[0];
         }
     }
 }
@@ -278,6 +283,8 @@ int main (int argc, char **argv)
     ImageBuffer image_buffer;
     image_buffer.initialize(topic, "base_link");
 
+    pcl::PCDWriter writer;
+
     while(ros::ok())
     {
         rgbd::ImageConstPtr image;
@@ -331,10 +338,16 @@ int main (int argc, char **argv)
 
         char key = cv::waitKey(30);
 
-        if (key == 'q')
+        if (key == 32)
+        {
+            writer.write<pcl::PointXYZRGB> ("segmented_cloud.pcd", *cloud, false);
+            std::cout << "wrote current cloud to 'segmented_cloud.pcd'." << std::endl;
+        }
+        else if (key == 'q')
         {
             break;
         }
+
     }
     cv::destroyAllWindows();
     return 0;

From ad9e90198c2596dbc48fa171ec9cc03d8ed4798e Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Mon, 22 Aug 2022 13:54:54 +0200
Subject: [PATCH 045/136] fix coordinate system of costmap creation

---
 ed_sensor_integration/src/kinect/empty_spot_designator.cpp | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
index b407d55d..30b3865c 100644
--- a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
+++ b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
@@ -234,9 +234,8 @@ void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Mat& canvas
 
     for (int nIndex = 0; nIndex < cloud->points.size (); nIndex++)
     {
-        double x = cloud->points[nIndex].z;
-        double y = -cloud->points[nIndex].x;
-        //double z = -cloud->points[nIndex].y;
+        double x = cloud->points[nIndex].x;
+        double y = -cloud->points[nIndex].y;
 
         cv::Point2d p = worldToCanvas(x, y);
         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)

From 22413af32196ac3f9d5b72bf036f40b7637f58e7 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Mon, 22 Aug 2022 14:10:36 +0200
Subject: [PATCH 046/136] optimise cluster selection

---
 .../src/kinect/empty_spot_designator.cpp      | 39 ++++++++++---------
 1 file changed, 20 insertions(+), 19 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
index 30b3865c..ee3c2fd9 100644
--- a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
+++ b/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
@@ -183,40 +183,41 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
     ec.setInputCloud (cloud);
     ec.extract (cluster_indices);
 
-    std::cout << "obtained cluster indices" <<std::endl;
+    std::cout << "obtained " << cluster_indices.size() << " cluster indices" <<std::endl;
 
     //find closest cluster
-    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out;
-    float mindist = INFINITY;
+    pcl::PointIndices closest_cluster;
+    float mindist_sq = INFINITY;
     for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it !=
          cluster_indices.end (); ++it) //iterate through all clusters
     {
         //construct cluster
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZRGB>);
+        float sumx = 0, sumy = 0, sumz = 0, dist_sq = 0;
+        int n = 0;
         for (const auto& idx : it->indices)
-            cloud_cluster->push_back ((*cloud)[idx]); //*
-        cloud_cluster->width = cloud_cluster->size ();
-        cloud_cluster->height = 1;
-        cloud_cluster->is_dense = true;
-        float sumx = 0, sumy = 0, sumz = 0, dist = 0;
-        for (uint j=0; j < (*cloud_cluster).width; ++j)
         {
-            //sum up all points
-            sumx += (*cloud_cluster)[j].x;
-            sumy += (*cloud_cluster)[j].y;
-            sumz += (*cloud_cluster)[j].z;
+            sumx += (*cloud)[idx].x;
+            sumy += (*cloud)[idx].y;
+            sumz += (*cloud)[idx].z;
+            n++;
         }
+
         //find distance from camera to the middle of the cluster
-        dist = pow((sumx/(*cloud_cluster).width-x),2) + pow((sumy/(*cloud_cluster).width-y),2) + pow((sumz/(*cloud_cluster).width-z),2);
-        std::cout << "distance is " << sqrt(dist) << std::endl;
-        if (dist < mindist) //check if closest so far
+        dist_sq = pow((sumx/n-x),2) + pow((sumy/n-y),2) + pow((sumz/n-z),2);
+        std::cout << "distance is " << sqrt(dist_sq) << std::endl;
+        if (dist_sq < mindist_sq) //check if closest so far
         {
             std::cout << "updating closest cluster" << std::endl;
-            mindist = dist;
-            cloud_out = cloud_cluster;
+            mindist_sq = dist_sq;
+            closest_cluster = *it;
         }
     }
 
+    //construct cluster
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out (new pcl::PointCloud<pcl::PointXYZRGB>);
+    for (uint i : closest_cluster.indices)
+        cloud_out->push_back( (*cloud)[i] ); //*
+
     float height = FilterPlane(cloud_out, cloud_out);
 
     std::cout << "writing closest cluster" << std::endl;

From 3ed3ad419b42a8b318c2cc7336a36db29e4a2f5b Mon Sep 17 00:00:00 2001
From: Peter van Dooren <p.v.dooren@tue.nl>
Date: Mon, 12 Sep 2022 15:23:04 +0200
Subject: [PATCH 047/136] move esd to tools

---
 ed_sensor_integration/CMakeLists.txt                            | 2 +-
 .../{src/kinect => tools}/empty_spot_designator.cpp             | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)
 rename ed_sensor_integration/{src/kinect => tools}/empty_spot_designator.cpp (99%)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index bcd53e97..b3aaebf4 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -124,7 +124,7 @@ target_link_libraries(ed_fitter_live ed_kinect)
 add_executable(ed_table_modeler tools/table_modeler.cpp)
 target_link_libraries (ed_table_modeler ${catkin_LIBRARIES})
 
-add_executable(ed_empty_spot_designator src/kinect/empty_spot_designator.cpp)
+add_executable(ed_empty_spot_designator tools/empty_spot_designator.cpp)
 target_link_libraries(ed_empty_spot_designator ed_kinect ${catkin_LIBRARIES})
 # ------------------------------------------------------------------------------------------------
 #                                           TESTS
diff --git a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
similarity index 99%
rename from ed_sensor_integration/src/kinect/empty_spot_designator.cpp
rename to ed_sensor_integration/tools/empty_spot_designator.cpp
index ee3c2fd9..d27dccb9 100644
--- a/ed_sensor_integration/src/kinect/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -1,7 +1,7 @@
 #include <iostream>
 #include <string>
 
-#include <ed/kinect/image_buffer.h>
+#include "ed/kinect/image_buffer.h"
 
 #include "opencv2/imgproc.hpp"
 #include <opencv2/highgui.hpp>

From 905237eaa9d6b4506cee841aea6a71a406d12a03 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <p.v.dooren@tue.nl>
Date: Mon, 12 Sep 2022 17:03:57 +0200
Subject: [PATCH 048/136] fix world to map y

---
 ed_sensor_integration/tools/empty_spot_designator.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index d27dccb9..ed904bb3 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -236,7 +236,7 @@ void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Mat& canvas
     for (int nIndex = 0; nIndex < cloud->points.size (); nIndex++)
     {
         double x = cloud->points[nIndex].x;
-        double y = -cloud->points[nIndex].y;
+        double y = cloud->points[nIndex].y;
 
         cv::Point2d p = worldToCanvas(x, y);
         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)

From 9ca1cf2db59febd9d08e70aef0e93501f3b02d3f Mon Sep 17 00:00:00 2001
From: Peter van Dooren <p.v.dooren@tue.nl>
Date: Mon, 12 Sep 2022 17:04:22 +0200
Subject: [PATCH 049/136] add pure plane segmentation

---
 .../tools/empty_spot_designator.cpp           | 57 ++++++++++++++++++-
 1 file changed, 56 insertions(+), 1 deletion(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index ed904bb3..e524d131 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -27,6 +27,7 @@
 
 #include <pcl/sample_consensus/method_types.h>
 #include <pcl/sample_consensus/model_types.h>
+#include <pcl/sample_consensus/sac_model_parallel_plane.h>
 
 #include <pcl/segmentation/extract_clusters.h>
 #include <pcl/segmentation/sac_segmentation.h>
@@ -224,6 +225,60 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
     *cloud = *cloud_out;
 }
 
+/**
+ * @brief SegmentPlane segment the pointcloud and return the cluster closest to the camera
+ * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
+ * @param x: coordinate of the camera
+ * @param y: coordinate of the camera
+ * @param z: coordinate of the camera
+ */
+void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z)
+{
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_p (new pcl::PointCloud<pcl::PointXYZRGB>), cloud_f (new pcl::PointCloud<pcl::PointXYZRGB>);
+
+    pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
+    pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
+    // Create the segmentation object
+    pcl::SACSegmentation<pcl::PointXYZRGB> seg;
+    pcl::SampleConsensusModelParallelPlane<pcl::PointXYZRGB> model (cloud);
+    // Optional
+    seg.setOptimizeCoefficients (true);
+    // Mandatory
+    seg.setModelType (pcl::SACMODEL_PARALLEL_PLANE);
+    seg.setMethodType (pcl::SAC_RANSAC);
+    seg.setMaxIterations (1000);
+    seg.setDistanceThreshold (0.01);
+    seg.setAxis (Eigen::Vector3f(1,0,0));
+    seg.setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
+
+    // Create the filtering object
+    pcl::ExtractIndices<pcl::PointXYZRGB> extract;
+
+    int i = 0, nr_points = (int) cloud->size ();
+
+    // Segment the largest planar component from the remaining cloud
+    seg.setInputCloud(cloud);
+    seg.segment(*inliers, *coefficients);
+
+    if (inliers->indices.size() == 0) {
+        std::cerr << "Could not estimate a planar model for the given dataset." << std::endl;
+        return;
+    }
+
+    // Extract the inliers
+    extract.setInputCloud(cloud);
+    extract.setIndices(inliers);
+    extract.setNegative(false);
+    extract.filter(*cloud_p);
+    std::cerr << "PointCloud representing the planar component: " << cloud_p->width * cloud_p->height << " data points."
+              << std::endl;
+
+    // Create the filtering object
+    extract.setNegative(true);
+    extract.filter(*cloud_f);
+    cloud.swap(cloud_f);
+}
+
 cv::Point2d worldToCanvas(double x, double y)
 {
     return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
@@ -319,7 +374,7 @@ int main (int argc, char **argv)
         (*cloud).is_dense = false;
         pcl::removeNaNFromPointCloud(*cloud, *cloud, indices);
 
-        Segment(cloud, 0.0, 0.0, 0.0);
+        SegmentPlane(cloud, 0.0, 0.0, 0.0);
 
         std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));

From 58a24cdba9b79e71d1b855e29c55c96a10f87cf7 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Mon, 3 Oct 2022 11:49:56 +0200
Subject: [PATCH 050/136] remove deprecated code

---
 ed_sensor_integration/src/kinect/code_v1.cpp | 630 -------------------
 ed_sensor_integration/tools/image_saver.cpp  |   1 -
 2 files changed, 631 deletions(-)
 delete mode 100644 ed_sensor_integration/src/kinect/code_v1.cpp

diff --git a/ed_sensor_integration/src/kinect/code_v1.cpp b/ed_sensor_integration/src/kinect/code_v1.cpp
deleted file mode 100644
index 11da239f..00000000
--- a/ed_sensor_integration/src/kinect/code_v1.cpp
+++ /dev/null
@@ -1,630 +0,0 @@
-#include <iostream>
-#include <pcl/ModelCoefficients.h>
-#include <pcl/io/pcd_io.h>
-
-#include <pcl/point_types.h>
-#include <pcl/point_cloud.h>
-#include <pcl/point_representation.h>
-
-#include <pcl/sample_consensus/method_types.h>
-#include <pcl/sample_consensus/model_types.h>
-#include <pcl/sample_consensus/sac_model_parallel_plane.h>
-#include <pcl/sample_consensus/ransac.h>
-
-#include <pcl/segmentation/sac_segmentation.h>
-#include <pcl/segmentation/extract_clusters.h>
-
-#include <pcl/registration/transforms.h>
-
-#include <pcl/filters/voxel_grid.h>
-#include <pcl/filters/extract_indices.h>
-#include <pcl/filters/conditional_removal.h>
-#include <pcl/filters/filter.h>
-#include <pcl/filters/statistical_outlier_removal.h>
-
-#include <pcl/features/normal_3d.h>
-
-#include <ed/io/json_reader.h>
-#include <ed/serialization/serialization.h>
-//#include "ed_sensor_integration/sac_model_circle.h"
-
-#include <tue/config/read.h>
-#include <tue/config/reader.h>
-#include <tue/config/data_pointer.h>
-
-#include <tf/transform_listener.h>
-#include <costmap_2d/costmap_2d_ros.h>
-//#include <costmap_2d/plugins/obstale_layer.cpp>
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/highgui.hpp"
-#include "opencv2/imgproc.hpp"
-
-#include <pcl/range_image/range_image.h>
-#include <pcl/visualization/range_image_visualizer.h>
-#include <pcl/visualization/pcl_visualizer.h>
-#include <pcl/features/range_image_border_extractor.h>
-#include <pcl/keypoints/narf_keypoint.h>
-#include <pcl/features/narf_descriptor.h>
-#include <pcl/console/parse.h>
-#include <pcl/common/file_io.h> // for getFilenameWithoutExtension
-
-#include <fstream>
-#include <boost/filesystem/convenience.hpp>
-
-//typedef pcl::PointXYZ PointType;
-
-//// --------------------
-//// -----Parameters-----
-//// --------------------
-//float angular_resolution = 0.5f;
-//float support_size = 0.2f;
-//pcl::RangeImage::CoordinateFrame coordinate_frame = pcl::RangeImage::CAMERA_FRAME;
-//bool setUnseenToMaxRange = false;
-//bool rotation_invariant = true;
-
-//// --------------
-//// -----Help-----
-//// --------------
-//void
-//printUsage (const char* progName)
-//{
-//  std::cout << "\n\nUsage: "<<progName<<" [options] <scene.pcd>\n\n"
-//            << "Options:\n"
-//            << "-------------------------------------------\n"
-//            << "-r <float>   angular resolution in degrees (default "<<angular_resolution<<")\n"
-//            << "-c <int>     coordinate frame (default "<< (int)coordinate_frame<<")\n"
-//            << "-m           Treat all unseen points to max range\n"
-//            << "-s <float>   support size for the interest points (diameter of the used sphere - "
-//                                                                  "default "<<support_size<<")\n"
-//            << "-o <0/1>     switch rotational invariant version of the feature on/off"
-//            <<               " (default "<< (int)rotation_invariant<<")\n"
-//            << "-h           this help\n"
-//            << "\n\n";
-//}
-
-//void
-//setViewerPose (pcl::visualization::PCLVisualizer& viewer, const Eigen::Affine3f& viewer_pose)
-//{
-//  Eigen::Vector3f pos_vector = viewer_pose * Eigen::Vector3f (0, 0, 0);
-//  Eigen::Vector3f look_at_vector = viewer_pose.rotation () * Eigen::Vector3f (0, 0, 1) + pos_vector;
-//  Eigen::Vector3f up_vector = viewer_pose.rotation () * Eigen::Vector3f (0, -1, 0);
-//  viewer.setCameraPosition (pos_vector[0], pos_vector[1], pos_vector[2],
-//                            look_at_vector[0], look_at_vector[1], look_at_vector[2],
-//                            up_vector[0], up_vector[1], up_vector[2]);
-//}
-
-Eigen::Matrix4f ReadJson(std::string pcd_filename, float *xout, float *yout, float *zout) {
-
-    std::string json_filename = "2022-04-22-11-44-48.json";
-    //std::string json_filename = boost::filesystem::change_extension(pcd_filename, ".json").string();
-    // read json metadata
-    tue::config::DataPointer meta_data;
-
-    try
-    {
-        meta_data = tue::config::fromFile(json_filename);
-    }
-    catch (tue::config::ParseException& e)
-    {
-        std::cerr << "Could not open '" << json_filename << "'.\n\n" << e.what() << std::endl;
-        //return 0;
-    }
-
-    tue::config::Reader r(meta_data);
-    // Read sensor pose
-    geo::Pose3D sensor_pose;
-    if (!ed::deserialize(r, "sensor_pose", sensor_pose))
-    {
-        std::cerr << "No field 'sensor_pose' specified." << std::endl;
-        //return 0;
-    }
-    // convert from geolib coordinates to ros coordinates #TODO remove geolib coordinates for camera pose
-    sensor_pose.R = sensor_pose.R * geo::Mat3(1, 0, 0, 0, -1, 0, 0, 0, -1);
-
-    float x = sensor_pose.t.x;
-    float y = sensor_pose.t.y;
-    float z = sensor_pose.t.z;
-    float xx = sensor_pose.R.xx;
-    float xy = sensor_pose.R.xy;
-    float xz = sensor_pose.R.xz;
-    float yx = sensor_pose.R.yx;
-    float yy = sensor_pose.R.yy;
-    float yz = sensor_pose.R.yz;
-    float zx = sensor_pose.R.zx;
-    float zy = sensor_pose.R.zy;
-    float zz = sensor_pose.R.zz;
-
-    *xout = x;
-    *yout = y;
-    *zout = z;
-
-    //float qx, qy, qz, qw;
-
-    //const float n = 2.0f/(qx*qx+qy*qy+qz*qz+qw*qw);
-    Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();/* {
-        {1.0f - n*qy*qy - n*qz*qz, n*qx*qy - n*qz*qw, n*qx*qz + n*qy*qw, x},
-        {n*qx*qy + n*qz*qw, 1.0f - n*qx*qx - n*qz*qz, n*qy*qz - n*qx*qw, y},
-        {n*qx*qz - n*qy*qw, n*qy*qz + n*qx*qw, 1.0f - n*qx*qx - n*qy*qy, z},
-        {0.0f, 0.0f, 0.0f, 1.0f}}; */
-
-    Transform(0,0) = xx;//1.0f - n*qy*qy - n*qz*qz;
-    Transform(0,1) = xy;//n*qx*qy - n*qz*qw;
-    Transform(0,2) = xz;//n*qx*qz + n*qy*qw;
-    Transform(0,3) = x;
-    Transform(1,0) = yx;//n*qx*qy + n*qz*qw;
-    Transform(1,1) = yy;//1.0f - n*qx*qx - n*qz*qz;
-    Transform(1,2) = yz;//n*qy*qz - n*qx*qw;
-    Transform(1,3) = y;
-    Transform(2,0) = zx;//n*qx*qz - n*qy*qw;
-    Transform(2,1) = zy;//n*qy*qz + n*qx*qw;
-    Transform(2,2) = zz;//1.0f - n*qx*qx - n*qy*qy;
-    Transform(2,3) = z;
-
-    std::cout << Transform << std::endl;
-    return Transform;
-}
-
-//float FilterPlane (pcl::PointCloud<pcl::PointXYZ>::Ptr cloud, pcl::PointCloud<pcl::PointXYZ>::Ptr out) {
-
-//    //*out = *cloud; return(-1); //activate to bypass plane fitting and height estimation
-
-//    std::vector<int> indices;
-//    float threshold = 0.03;
-
-//    std::cout << "starting ransac" << std::endl;
-//    // Create SAC model
-//    pcl::SampleConsensusModelParallelPlane<pcl::PointXYZ>::Ptr plane (new pcl::SampleConsensusModelParallelPlane<pcl::PointXYZ>(cloud));
-//    plane->setAxis (Eigen::Vector3f(1,0,0));
-//    plane->setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
-//    std::cout << "created plane object" << std::endl;
-//    // Create SAC method
-//    //pcl::SACSegmentation<pcl::PointXYZ> segplane;
-//    pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr segplane (new pcl::RandomSampleConsensus<pcl::PointXYZ> (plane, threshold));
-//    std::cout << "created ransac object" << std::endl;
-//    segplane->setMaxIterations(10000);
-//    segplane->setProbability(0.99);
-
-//    // Fit model
-//    segplane->computeModel();
-
-//    // Get inliers
-//    std::vector<int> inliers;
-//    segplane->getInliers(inliers);
-
-//    // Get the model coefficients
-//    Eigen::VectorXf coeff;
-//    segplane->getModelCoefficients (coeff);
-//    std::cout << "ransac complete" << std::endl;
-
-//    pcl::ConditionAnd<pcl::PointXYZ>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZ> ());
-//    range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZ>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZ> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
-//    //range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, (coeff[3]+0.01))));
-//    *out = *cloud;
-//    //filter out everything below plane
-//    pcl::ConditionalRemoval<pcl::PointXYZ> condrem;
-//    condrem.setCondition (range_cond);
-//    condrem.setInputCloud (out);
-//    condrem.setKeepOrganized(true);
-
-//    condrem.filter (*out);
-//    (*out).is_dense = false;
-//    pcl::removeNaNFromPointCloud(*out, *out, indices);
-
-//    return(coeff[3]);
-
-//}
-
-//using namespace cv;
-//using namespace std;
-//int thresh = 100;
-//RNG rng(12345);
-//void thresh_callback(int, void* );
-
-//Mat src, src_gray;
-//Mat dst, detected_edges;
-
-//int lowThreshold = 0;
-//const int max_lowThreshold = 100;
-//const int ratio = 3;
-//const int kernel_size = 3;
-//const char* window_name = "Edge Map";
-//static void CannyThreshold(int, void*)
-//{
-//    blur( src_gray, detected_edges, Size(3,3) );
-//    Canny( detected_edges, detected_edges, lowThreshold, lowThreshold*ratio, kernel_size );
-//    dst = Scalar::all(0);
-//    src.copyTo( dst, detected_edges);
-//    imshow( window_name, dst );
-//}
-
-int
-main (int argc, char **argv)
-{
-  std::vector <pcl::PointCloud<pcl::PointXYZ>::Ptr, Eigen::aligned_allocator <pcl::PointCloud <pcl::PointXYZ>::Ptr > > inputs;
-//  float x, y, z;//used to store camera position
-//      pcl::transformPointCloud (*inputs[0], *inputs[0], ReadJson(argv[1], &x, &y, &z));
-
-  pcl::PCLPointCloud2::Ptr cloud_blob (new pcl::PCLPointCloud2), cloud_filtered_blob (new pcl::PCLPointCloud2);
-  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>), cloud_p (new pcl::PointCloud<pcl::PointXYZ>), cloud_f (new pcl::PointCloud<pcl::PointXYZ>);
-
-  // Fill in the cloud data
-  pcl::PCDReader reader;
-  reader.read ("2022-04-22-11-44-48.pcd", *cloud_blob); //
-
-  std::cerr << "PointCloud before filtering: " << cloud_blob->width * cloud_blob->height << " data points." << std::endl;
-
-  // Create the filtering object: downsample the dataset using a leaf size of 0.25cm
-  pcl::VoxelGrid<pcl::PCLPointCloud2> sor;
-  sor.setInputCloud (cloud_blob);
-  sor.setLeafSize (0.0025f, 0.0025f, 0.0025f);
-  sor.filter (*cloud_filtered_blob);
-
-  // Convert to the templated PointCloud
-  pcl::fromPCLPointCloud2 (*cloud_filtered_blob, *cloud_filtered);
-
-  std::cerr << "PointCloud after filtering: " << cloud_filtered->width * cloud_filtered->height << " data points." << std::endl;
-
-  // Write the downsampled version to disk
-  pcl::PCDWriter writer;
-  writer.write<pcl::PointXYZ> ("table_scene_lms400_downsampled.pcd", *cloud_filtered, false);
-
-  pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
-  pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
-  // Create the segmentation object
-  pcl::SACSegmentation<pcl::PointXYZ> seg;
-  pcl::SampleConsensusModelParallelPlane<pcl::PointXYZ> model (cloud_filtered);
-  // Optional
-  seg.setOptimizeCoefficients (true);
-  // Mandatory
-  seg.setModelType (pcl::SACMODEL_PARALLEL_PLANE);
-  seg.setMethodType (pcl::SAC_RANSAC);
-  seg.setMaxIterations (1000);
-  seg.setDistanceThreshold (0.01);
-  seg.setAxis (Eigen::Vector3f(1,0,0));
-  seg.setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
-
-  // Create the filtering object
-  pcl::ExtractIndices<pcl::PointXYZ> extract;
-
-  int i = 0, nr_points = (int) cloud_filtered->size ();
-  // While 30% of the original cloud is still there
-  while (cloud_filtered->size () > 0.3 * nr_points)
-  {
-    // Segment the largest planar component from the remaining cloud
-    seg.setInputCloud (cloud_filtered);
-    seg.segment (*inliers, *coefficients);
-
-    if (inliers->indices.size () == 0)
-    {
-      std::cerr << "Could not estimate a planar model for the given dataset." << std::endl;
-      break;
-    }
-
-    // Extract the inliers
-    extract.setInputCloud (cloud_filtered);
-    extract.setIndices (inliers);
-    extract.setNegative (false);
-    extract.filter (*cloud_p);
-    std::cerr << "PointCloud representing the planar component: " << cloud_p->width * cloud_p->height << " data points." << std::endl;
-
-    std::stringstream ss;
-    ss << "table_scene_lms400_plane_" << i << ".pcd";
-    writer.write<pcl::PointXYZ> (ss.str (), *cloud_p, false);
-
-    // Create the filtering object
-    extract.setNegative (true);
-    extract.filter (*cloud_f);
-    cloud_filtered.swap (cloud_f);
-    i++;
-  }
-
-//  // Creating the KdTree object for the search method of the extraction
-//  pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
-//  tree->setInputCloud (cloud_p);
-
-//  std::vector<pcl::PointIndices> cluster_indices;
-//  pcl::EuclideanClusterExtraction<pcl::PointXYZ> ec;
-//  ec.setClusterTolerance (0.02); // 2cm
-//  ec.setMinClusterSize (100);
-//  ec.setMaxClusterSize (100000);
-//  ec.setSearchMethod (tree);
-//  ec.setInputCloud (cloud_p);
-//  ec.extract (cluster_indices);
-
-//  int j = 0;
-//  for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it != cluster_indices.end (); ++it)
-//  {
-//      pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_cluster (new pcl::PointCloud<pcl::PointXYZ>);
-//      for (const auto& idx : it->indices)
-//      cloud_cluster->push_back ((*cloud_filtered)[idx]); //*
-//      cloud_cluster->width = cloud_cluster->size ();
-//      cloud_cluster->height = 1;
-//      cloud_cluster->is_dense = true;
-
-//      std::cout << "PointCloud representing the Cluster: " << cloud_cluster->size () << " data points." << std::endl;
-//      std::stringstream ss;
-//      ss << "cloud_cluster_" << j << ".pcd";
-//      writer.write<pcl::PointXYZ> (ss.str (), *cloud_cluster, false); //*
-//      j++;
-//  }
-
-  //Removing outliers using a StatisticalOutlierRemoval filter
-  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud2 (new pcl::PointCloud<pcl::PointXYZ>);
-  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered2 (new pcl::PointCloud<pcl::PointXYZ>);
-
-  // Fill in the cloud data
-  pcl::PCDReader reader2;
-  // Replace the path below with the path where you saved your file
-  reader.read<pcl::PointXYZ> ("table_scene_lms400_plane_1.pcd", *cloud2);
-
-  std::cerr << "Cloud before filtering: " << std::endl;
-  std::cerr << *cloud2 << std::endl;
-
-  // Create the filtering object
-  pcl::StatisticalOutlierRemoval<pcl::PointXYZ> sor2;
-  sor2.setInputCloud (cloud2);
-  sor2.setMeanK (1);
-  sor2.setStddevMulThresh (0.001);
-  sor2.filter (*cloud_filtered2);
-
-  std::cerr << "Cloud after filtering: " << std::endl;
-  std::cerr << *cloud_filtered2 << std::endl;
-
-  pcl::PCDWriter writer2;
-  writer2.write<pcl::PointXYZ> ("table_scene_lms400_inliers.pcd", *cloud_filtered2, false);
-
-  sor2.setNegative (true);
-  sor2.filter (*cloud_filtered2);
-  writer2.write<pcl::PointXYZ> ("table_scene_lms400_outliers.pcd", *cloud_filtered2, false);
-
-  //FilterPlane;
-
-  //Line detectors
-
-//  CommandLineParser parser( argc, argv, "{@input | cluster.png | input image}" );
-//  Mat src = imread( samples::findFile( parser.get<String>( "@input" ) ) );
-//  if( src.empty() )
-//  {
-//      cout << "Could not open or find the image!\n" << endl;
-//      cout << "usage: " << argv[0] << " <Input image>" << endl;
-//      return -1;
-//  }
-//  cvtColor( src, src_gray, COLOR_BGR2GRAY );
-//  blur( src_gray, src_gray, Size(3,3) );
-//  const char* source_window = "Source";
-//  namedWindow( source_window );
-//  imshow( source_window, src );
-//  const int max_thresh = 255;
-//  createTrackbar( "Canny thresh:", source_window, &thresh, max_thresh, thresh_callback );
-//  thresh_callback( 0, 0 );
-//  waitKey();
-//  return 0;
-//}
-
-//void thresh_callback(int, void* )
-//{
-//  Mat canny_output;
-//  Canny( src_gray, canny_output, thresh, thresh*2 );
-//  vector<vector<Point> > contours;
-//  findContours( canny_output, contours, RETR_TREE, CHAIN_APPROX_SIMPLE );
-//  vector<vector<Point> > contours_poly( contours.size() );
-//  vector<Rect> boundRect( contours.size() );
-//  vector<Point2f>centers( contours.size() );
-//  vector<float>radius( contours.size() );
-//  for( size_t i = 0; i < contours.size(); i++ )
-//  {
-//      approxPolyDP( contours[i], contours_poly[i], 3, false );
-//      boundRect[i] = boundingRect( contours_poly[i] );
-//      minEnclosingCircle( contours_poly[i], centers[i], radius[i] );
-//  }
-//  Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 );
-//  for( size_t i = 0; i< contours.size(); i++ )
-//  {
-//      Scalar color = Scalar( rng.uniform(0, 256), rng.uniform(0,256), rng.uniform(0,256) );
-//      drawContours( drawing, contours_poly, (int)i, color );
-//      //rectangle( drawing, boundRect[i].tl(), boundRect[i].br(), color, 2 );
-//      //circle( drawing, centers[i], (int)radius[i], color, 2 );
-//  }
-//  imshow( "Contours", drawing );
-//}
-
-  //Line detector
-//  CommandLineParser parser( argc, argv, "{@input | cluster.png | input image}" );
-//  src = imread( samples::findFile( parser.get<String>( "@input" ) ), IMREAD_COLOR ); // Load an image
-//  if( src.empty() )
-//  {
-//    std::cout << "Could not open or find the image!\n" << std::endl;
-//    std::cout << "Usage: " << argv[0] << " <Input image>" << std::endl;
-//    return -1;
-//  }
-//  dst.create( src.size(), src.type() );
-//  cvtColor( src, src_gray, COLOR_BGR2GRAY );
-//  namedWindow( window_name, WINDOW_AUTOSIZE );
-//  createTrackbar( "Min Threshold:", window_name, &lowThreshold, max_lowThreshold, CannyThreshold );
-//  CannyThreshold(0, 0);
-//  waitKey(0);
-
-//  pcl::SampleConsensusModelCircle<pcl::PointXYZ>::Ptr circle (new pcl::SampleConsensusModelCircle<pcl::PointXYZ>(cloud_ptr));
-
-//  // Create SAC method
-//  pcl::RandomSampleConsensus<pcl::PointXYZ>::Ptr saccirc (new pcl::RandomSampleConsensus<pcl::PointXYZ> (circle, threshold));
-//  saccirc->setMaxIterations(10000);
-//  saccirc->setProbability(1);
-
-//  // Fit model
-//  saccirc->computeModel();
-
-//  // Get inliers
-//  std::vector<int> inliers3;
-//  saccirc->getInliers(inliers3);
-
-//  // Get the model coefficients
-//  Eigen::VectorXf coeff3;
-//  saccirc->getModelCoefficients (coeff3);
-
-//  float min_inliers = 0.0;
-//  Eigen::VectorXf output;
-
-//  std::cout << "Circle model, " << static_cast<float>(inliers3.size())/static_cast<float>(cloud_p.size()) << std::endl;
-
-//Costmap
-
-//  if (pcl::console::find_argument (argc, argv, "-h") >= 0)
-//  {
-//    printUsage (argv[0]);
-//    return 0;
-//  }
-//  if (pcl::console::find_argument (argc, argv, "-m") >= 0)
-//  {
-//    setUnseenToMaxRange = true;
-//    std::cout << "Setting unseen values in range image to maximum range readings.\n";
-//  }
-//  if (pcl::console::parse (argc, argv, "-o", rotation_invariant) >= 0)
-//    std::cout << "Switching rotation invariant feature version "<< (rotation_invariant ? "on" : "off")<<".\n";
-//  int tmp_coordinate_frame;
-//  if (pcl::console::parse (argc, argv, "-c", tmp_coordinate_frame) >= 0)
-//  {
-//    coordinate_frame = pcl::RangeImage::CoordinateFrame (tmp_coordinate_frame);
-//    std::cout << "Using coordinate frame "<< (int)coordinate_frame<<".\n";
-//  }
-//  if (pcl::console::parse (argc, argv, "-s", support_size) >= 0)
-//    std::cout << "Setting support size to "<<support_size<<".\n";
-//  if (pcl::console::parse (argc, argv, "-r", angular_resolution) >= 0)
-//    std::cout << "Setting angular resolution to "<<angular_resolution<<"deg.\n";
-//  angular_resolution = pcl::deg2rad (angular_resolution);
-
-//  // ------------------------------------------------------------------
-//  // -----Read pcd file or create example point cloud if not given-----
-//  // ------------------------------------------------------------------
-//  pcl::PointCloud<PointType>::Ptr point_cloud_ptr (new pcl::PointCloud<PointType>);
-//  pcl::PointCloud<PointType>& point_cloud = *point_cloud_ptr;
-//  pcl::PointCloud<pcl::PointWithViewpoint> far_ranges;
-//  Eigen::Affine3f scene_sensor_pose (Eigen::Affine3f::Identity ());
-//  std::vector<int> pcd_filename_indices = pcl::console::parse_file_extension_argument (argc, argv, "pcd");
-//  if (!pcd_filename_indices.empty ())
-//  {
-//    std::string filename = argv[pcd_filename_indices[0]];
-//    if (pcl::io::loadPCDFile (filename, point_cloud) == -1)
-//    {
-//      std::cerr << "Was not able to open file \""<<filename<<"\".\n";
-//      printUsage (argv[0]);
-//      return 0;
-//    }
-//    scene_sensor_pose = Eigen::Affine3f (Eigen::Translation3f (point_cloud.sensor_origin_[0],
-//                                                               point_cloud.sensor_origin_[1],
-//                                                               point_cloud.sensor_origin_[2])) *
-//                        Eigen::Affine3f (point_cloud.sensor_orientation_);
-//    std::string far_ranges_filename = pcl::getFilenameWithoutExtension (filename)+"_far_ranges.pcd";
-//    if (pcl::io::loadPCDFile (far_ranges_filename.c_str (), far_ranges) == -1)
-//      std::cout << "Far ranges file \""<<far_ranges_filename<<"\" does not exists.\n";
-//  }
-//  else
-//  {
-//    setUnseenToMaxRange = true;
-//    std::cout << "\nNo *.pcd file given => Generating example point cloud.\n\n";
-//    for (float x=-0.5f; x<=0.5f; x+=0.01f)
-//    {
-//      for (float y=-0.5f; y<=0.5f; y+=0.01f)
-//      {
-//        PointType point;  point.x = x;  point.y = y;  point.z = 2.0f - y;
-//        point_cloud.push_back (point);
-//      }
-//    }
-//    point_cloud.width = point_cloud.size ();  point_cloud.height = 1;
-//  }
-
-//  // -----------------------------------------------
-//  // -----Create RangeImage from the PointCloud-----
-//  // -----------------------------------------------
-//  float noise_level = 0.0;
-//  float min_range = 0.0f;
-//  int border_size = 1;
-//  pcl::RangeImage::Ptr range_image_ptr (new pcl::RangeImage);
-//  pcl::RangeImage& range_image = *range_image_ptr;
-//  range_image.createFromPointCloud (point_cloud, angular_resolution, pcl::deg2rad (360.0f), pcl::deg2rad (180.0f),
-//                                   scene_sensor_pose, coordinate_frame, noise_level, min_range, border_size);
-//  range_image.integrateFarRanges (far_ranges);
-//  if (setUnseenToMaxRange)
-//    range_image.setUnseenToMaxRange ();
-
-//  // --------------------------------------------
-//  // -----Open 3D viewer and add point cloud-----
-//  // --------------------------------------------
-//  pcl::visualization::PCLVisualizer viewer ("3D Viewer");
-//  viewer.setBackgroundColor (1, 1, 1);
-//  pcl::visualization::PointCloudColorHandlerCustom<pcl::PointWithRange> range_image_color_handler (range_image_ptr, 0, 0, 0);
-//  viewer.addPointCloud (range_image_ptr, range_image_color_handler, "range image");
-//  viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 1, "range image");
-//  //viewer.addCoordinateSystem (1.0f, "global");
-//  //PointCloudColorHandlerCustom<PointType> point_cloud_color_handler (point_cloud_ptr, 150, 150, 150);
-//  //viewer.addPointCloud (point_cloud_ptr, point_cloud_color_handler, "original point cloud");
-//  viewer.initCameraParameters ();
-//  setViewerPose (viewer, range_image.getTransformationToWorldSystem ());
-
-//  // --------------------------
-//  // -----Show range image-----
-//  // --------------------------
-//  pcl::visualization::RangeImageVisualizer range_image_widget ("Range image");
-//  range_image_widget.showRangeImage (range_image);
-
-//  // --------------------------------
-//  // -----Extract NARF keypoints-----
-//  // --------------------------------
-//  pcl::RangeImageBorderExtractor range_image_border_extractor;
-//  pcl::NarfKeypoint narf_keypoint_detector;
-//  narf_keypoint_detector.setRangeImageBorderExtractor (&range_image_border_extractor);
-//  narf_keypoint_detector.setRangeImage (&range_image);
-//  narf_keypoint_detector.getParameters ().support_size = support_size;
-
-//  pcl::PointCloud<int> keypoint_indices;
-//  narf_keypoint_detector.compute (keypoint_indices);
-//  std::cout << "Found "<<keypoint_indices.size ()<<" key points.\n";
-
-//  // ----------------------------------------------
-//  // -----Show keypoints in range image widget-----
-//  // ----------------------------------------------
-// //for (std::size_t i=0; i<keypoint_indices.size (); ++i)
-//    //range_image_widget.markPoint (keypoint_indices[i]%range_image.width,
-//                                  //keypoint_indices[i]/range_image.width);
-
-//  // -------------------------------------
-//  // -----Show keypoints in 3D viewer-----
-//  // -------------------------------------
-//  pcl::PointCloud<pcl::PointXYZ>::Ptr keypoints_ptr (new pcl::PointCloud<pcl::PointXYZ>);
-//  pcl::PointCloud<pcl::PointXYZ>& keypoints = *keypoints_ptr;
-//  keypoints.resize (keypoint_indices.size ());
-//  for (std::size_t i=0; i<keypoint_indices.size (); ++i)
-//    keypoints[i].getVector3fMap () = range_image[keypoint_indices[i]].getVector3fMap ();
-//  pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> keypoints_color_handler (keypoints_ptr, 0, 255, 0);
-//  viewer.addPointCloud<pcl::PointXYZ> (keypoints_ptr, keypoints_color_handler, "keypoints");
-//  viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 7, "keypoints");
-
-//  // ------------------------------------------------------
-//  // -----Extract NARF descriptors for interest points-----
-//  // ------------------------------------------------------
-//  std::vector<int> keypoint_indices2;
-//  keypoint_indices2.resize (keypoint_indices.size ());
-//  for (unsigned int i=0; i<keypoint_indices.size (); ++i) // This step is necessary to get the right vector type
-//    keypoint_indices2[i]=keypoint_indices[i];
-//  pcl::NarfDescriptor narf_descriptor (&range_image, &keypoint_indices2);
-//  narf_descriptor.getParameters ().support_size = support_size;
-//  narf_descriptor.getParameters ().rotation_invariant = rotation_invariant;
-//  pcl::PointCloud<pcl::Narf36> narf_descriptors;
-//  narf_descriptor.compute (narf_descriptors);
-//  std::cout << "Extracted "<<narf_descriptors.size ()<<" descriptors for "
-//                      <<keypoint_indices.size ()<< " keypoints.\n";
-
-//  //--------------------
-//  // -----Main loop-----
-//  //--------------------
-//  while (!viewer.wasStopped ())
-//  {
-//    range_image_widget.spinOnce ();  // process GUI events
-//    viewer.spinOnce ();
-//    pcl_sleep(0.01);
-//  }
-//}
-
-  return 0;
-
-}
diff --git a/ed_sensor_integration/tools/image_saver.cpp b/ed_sensor_integration/tools/image_saver.cpp
index 54920754..96d36ae1 100644
--- a/ed_sensor_integration/tools/image_saver.cpp
+++ b/ed_sensor_integration/tools/image_saver.cpp
@@ -58,7 +58,6 @@ int main(int argc, char **argv)
     ros::init(argc, argv, "ed_image_saver");
     ros::NodeHandle nh;
     ros::ServiceClient cl_get_image = nh.serviceClient<ed_sensor_integration_msgs::GetImage>("ed/kinect/get_image");
-    //ros::Subscriber laser_sub = nh.subscribe("base_laser/measurements", 1, LaserCallback);
 
     double fps = 1;
 

From deb1cf51fbb712425ac566b7052553fc211775b0 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Fri, 7 Oct 2022 16:00:44 +0200
Subject: [PATCH 051/136] fix pointer bug

---
 .../tools/empty_spot_designator.cpp                | 14 +++++---------
 1 file changed, 5 insertions(+), 9 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index e524d131..a632722d 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -234,13 +234,12 @@ void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, fl
  */
 void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z)
 {
-    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_p (new pcl::PointCloud<pcl::PointXYZRGB>), cloud_f (new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_p (new pcl::PointCloud<pcl::PointXYZRGB>);
 
     pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
     pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
     // Create the segmentation object
     pcl::SACSegmentation<pcl::PointXYZRGB> seg;
-    pcl::SampleConsensusModelParallelPlane<pcl::PointXYZRGB> model (cloud);
     // Optional
     seg.setOptimizeCoefficients (true);
     // Mandatory
@@ -249,7 +248,7 @@ void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float
     seg.setMaxIterations (1000);
     seg.setDistanceThreshold (0.01);
     seg.setAxis (Eigen::Vector3f(1,0,0));
-    seg.setEpsAngle(15*0.0174532925); //*0.0174532925 to radians
+    seg.setEpsAngle(5*0.0174532925); //*0.0174532925 to radians
 
     // Create the filtering object
     pcl::ExtractIndices<pcl::PointXYZRGB> extract;
@@ -270,13 +269,10 @@ void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float
     extract.setIndices(inliers);
     extract.setNegative(false);
     extract.filter(*cloud_p);
-    std::cerr << "PointCloud representing the planar component: " << cloud_p->width * cloud_p->height << " data points."
-              << std::endl;
+    std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
+     << "Plane with coefficients: " << *coefficients << std::endl;
 
-    // Create the filtering object
-    extract.setNegative(true);
-    extract.filter(*cloud_f);
-    cloud.swap(cloud_f);
+    cloud->swap(*cloud_p);
 }
 
 cv::Point2d worldToCanvas(double x, double y)

From 419bb7eaec1e2eb49bd2d45357d6a84e15d3942f Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Mon, 14 Nov 2022 19:46:25 +0100
Subject: [PATCH 052/136] test

---
 ed_sensor_integration/tools/empty_spot_designator.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index a632722d..26d9c05d 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -374,7 +374,7 @@ int main (int argc, char **argv)
 
         std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
-        cv::Scalar table_color(0, 255, 0);
+        cv::Scalar table_color(0, 0, 255);
         cv::Scalar occupied_color(0, 0, 255);
 
         //createCostmap(occupied_cloud, canvas, occupied_color);

From 6a5fcacebfe90d44b6b4589b7716290dbe5ba992 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <113358406+MaxVroonhoven@users.noreply.github.com>
Date: Tue, 15 Nov 2022 15:58:36 +0100
Subject: [PATCH 053/136] test2

---
 ed_sensor_integration/tools/empty_spot_designator.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 26d9c05d..2192fb6d 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -372,7 +372,7 @@ int main (int argc, char **argv)
 
         SegmentPlane(cloud, 0.0, 0.0, 0.0);
 
-        std::cout << "creating costmap" << std::endl;
+        std::cout << "creating costmap test2" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
         cv::Scalar table_color(0, 0, 255);
         cv::Scalar occupied_color(0, 0, 255);
@@ -380,7 +380,7 @@ int main (int argc, char **argv)
         //createCostmap(occupied_cloud, canvas, occupied_color);
         createCostmap(cloud, canvas, table_color);
 
-        std::cout << "showing costmap" << std::endl;
+        std::cout << "showing costmap test2" << std::endl;
         cv::imshow("Costmap topview", canvas);
 
         // show snapshot

From 6a97cd6ff19f59cdc514f6a39a7e2c987293a462 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <113358406+MaxVroonhoven@users.noreply.github.com>
Date: Tue, 15 Nov 2022 22:11:25 +0100
Subject: [PATCH 054/136] reverting tests

---
 ed_sensor_integration/tools/empty_spot_designator.cpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 2192fb6d..a632722d 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -372,15 +372,15 @@ int main (int argc, char **argv)
 
         SegmentPlane(cloud, 0.0, 0.0, 0.0);
 
-        std::cout << "creating costmap test2" << std::endl;
+        std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
-        cv::Scalar table_color(0, 0, 255);
+        cv::Scalar table_color(0, 255, 0);
         cv::Scalar occupied_color(0, 0, 255);
 
         //createCostmap(occupied_cloud, canvas, occupied_color);
         createCostmap(cloud, canvas, table_color);
 
-        std::cout << "showing costmap test2" << std::endl;
+        std::cout << "showing costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
 
         // show snapshot

From 2d7b3b49b1d60169b1ce6469c15530445256a015 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Tue, 15 Nov 2022 23:06:20 +0100
Subject: [PATCH 055/136] local test

---
 ed_sensor_integration/tools/empty_spot_designator.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index a632722d..932e6f59 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -372,7 +372,7 @@ int main (int argc, char **argv)
 
         SegmentPlane(cloud, 0.0, 0.0, 0.0);
 
-        std::cout << "creating costmap" << std::endl;
+        std::cout << "creating costmap test" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
         cv::Scalar table_color(0, 255, 0);
         cv::Scalar occupied_color(0, 0, 255);
@@ -380,7 +380,7 @@ int main (int argc, char **argv)
         //createCostmap(occupied_cloud, canvas, occupied_color);
         createCostmap(cloud, canvas, table_color);
 
-        std::cout << "showing costmap" << std::endl;
+        std::cout << "showing costmap test" << std::endl;
         cv::imshow("Costmap topview", canvas);
 
         // show snapshot

From dc696366107f2beb6c8e2f9ae569ebd93d44be2c Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Tue, 15 Nov 2022 17:23:59 +0100
Subject: [PATCH 056/136] remove table modeler

---
 ed_sensor_integration/CMakeLists.txt | 2 --
 1 file changed, 2 deletions(-)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index b3aaebf4..a35f398f 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -121,8 +121,6 @@ target_link_libraries(ed_fitter_data ed_kinect)
 add_executable(ed_fitter_live tools/fitter_viz_live.cpp)
 target_link_libraries(ed_fitter_live ed_kinect)
 
-add_executable(ed_table_modeler tools/table_modeler.cpp)
-target_link_libraries (ed_table_modeler ${catkin_LIBRARIES})
 
 add_executable(ed_empty_spot_designator tools/empty_spot_designator.cpp)
 target_link_libraries(ed_empty_spot_designator ed_kinect ${catkin_LIBRARIES})

From 8a248b2951fd0633efa6c9a23bcd75bfaacc4ef7 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Thu, 17 Nov 2022 20:04:58 +0100
Subject: [PATCH 057/136] Added objects to bitmap

---
 .../tools/empty_spot_designator.cpp           | 341 +++++++++++-------
 1 file changed, 218 insertions(+), 123 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 932e6f59..176abdaf 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -109,121 +109,143 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
     return Transform;
 }
 
-/**
- * @brief FilterPlane fit a plane through a pointcloud, filter the points which lie in this plane and return the height of the plane #TODO separation of concerns.
- * @param cloud: pointcloud to be filtered.
- * @param out: pointcloud with all points that lie within the plane
- * @return height (z coordinate) of the fitted plane.
- */
-float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out)
-{
-    std::vector<int> indices;
-    float threshold = 0.03;
-
-    std::cout << "starting ransac" << std::endl;
-    // Create SAC model
-    pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>::Ptr plane (new pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>(cloud));
-    std::cout << "created plane object" << std::endl;
-    // Create SAC method
-    pcl::RandomSampleConsensus<pcl::PointXYZRGB>::Ptr sac (new pcl::RandomSampleConsensus<pcl::PointXYZRGB> (plane, threshold));
-    std::cout << "created ransac object" << std::endl;
-    sac->setMaxIterations(10000);
-    sac->setProbability(0.99);
-
-    // Fit model
-    sac->computeModel();
-
-    // Get inliers
-    std::vector<int> inliers;
-    sac->getInliers(inliers);
-
-    // Get the model coefficients
-    Eigen::VectorXf coeff;
-    sac->getModelCoefficients (coeff);
-    std::cout << "ransac complete" << std::endl;
-
-    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-    range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
-    *out = *cloud;
-    //filter out everything below plane
-    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
-    condrem.setCondition (range_cond);
-    condrem.setInputCloud (out);
-    condrem.setKeepOrganized(true);
-
-    condrem.filter (*out);
-    (*out).is_dense = false;
-    pcl::removeNaNFromPointCloud(*out, *out, indices);
-
-    return(coeff[3]);
-}
-
-/**
- * @brief Segment segment the pointcloud and return the cluster closest to the camera
- * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
- * @param x: coordinate of the camera
- * @param y: coordinate of the camera
- * @param z: coordinate of the camera
- * @param [out] tableHeight[m]: estimated height of the table based on the cluster.
- */
-void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z)
-{
-    std::cout << "starting segmentation" << std::endl;
-    std::cout << "x = " << x << ", y = " << y << ", z = " << z << std::endl;
-
-    // Creating the KdTree object for the search method of the extraction
-    pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZRGB>);
-    tree->setInputCloud (cloud);
-
-    std::vector<pcl::PointIndices> cluster_indices;
-    pcl::EuclideanClusterExtraction<pcl::PointXYZRGB> ec; //using euclidian cluster extraction
-    ec.setClusterTolerance (0.1);
-    ec.setMinClusterSize ((*cloud).size()/100); //#TODO magic number
-    ec.setMaxClusterSize ((*cloud).size());
-    ec.setSearchMethod (tree);
-    ec.setInputCloud (cloud);
-    ec.extract (cluster_indices);
-
-    std::cout << "obtained " << cluster_indices.size() << " cluster indices" <<std::endl;
-
-    //find closest cluster
-    pcl::PointIndices closest_cluster;
-    float mindist_sq = INFINITY;
-    for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it !=
-         cluster_indices.end (); ++it) //iterate through all clusters
-    {
-        //construct cluster
-        float sumx = 0, sumy = 0, sumz = 0, dist_sq = 0;
-        int n = 0;
-        for (const auto& idx : it->indices)
-        {
-            sumx += (*cloud)[idx].x;
-            sumy += (*cloud)[idx].y;
-            sumz += (*cloud)[idx].z;
-            n++;
-        }
-
-        //find distance from camera to the middle of the cluster
-        dist_sq = pow((sumx/n-x),2) + pow((sumy/n-y),2) + pow((sumz/n-z),2);
-        std::cout << "distance is " << sqrt(dist_sq) << std::endl;
-        if (dist_sq < mindist_sq) //check if closest so far
-        {
-            std::cout << "updating closest cluster" << std::endl;
-            mindist_sq = dist_sq;
-            closest_cluster = *it;
-        }
-    }
-
-    //construct cluster
-    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out (new pcl::PointCloud<pcl::PointXYZRGB>);
-    for (uint i : closest_cluster.indices)
-        cloud_out->push_back( (*cloud)[i] ); //*
-
-    float height = FilterPlane(cloud_out, cloud_out);
+// /**
+//  * @brief FilterPlane fit a plane through a pointcloud, filter the points which lie in this plane and return the height of the plane #TODO separation of concerns.
+//  * @param cloud_backup: pointcloud to be filtered.
+//  * @param out: pointcloud with all points that lie within the plane
+//  * @return height (z coordinate) of the fitted plane.
+//  */
+// float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_backup, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out)
+// {
+//     std::vector<int> indices;
+//     float threshold = 0.03;
+
+//     std::cout << "starting ransac" << std::endl;
+//     // Create SAC model
+//     pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>::Ptr plane (new pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>(cloud_backup));
+//     std::cout << "created plane object" << std::endl;
+//     // Create SAC method
+//     pcl::RandomSampleConsensus<pcl::PointXYZRGB>::Ptr sac (new pcl::RandomSampleConsensus<pcl::PointXYZRGB> (plane, threshold));
+//     std::cout << "created ransac object" << std::endl;
+//     sac->setMaxIterations(10000);
+//     sac->setProbability(0.99);
+
+//     // Fit model
+//     sac->computeModel();
+
+//     // Get inliers
+//     std::vector<int> inliers;
+//     sac->getInliers(inliers);
+
+//     // Get the model coefficients
+//     Eigen::VectorXf coeff;
+//     sac->getModelCoefficients (coeff);
+//     std::cout << "ransac complete" << std::endl;
+
+//     pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+//     range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
+//     *out = *cloud_backup;
+
+//     //filter out everything below plane
+//     pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+//     condrem.setCondition (range_cond);
+//     condrem.setInputCloud (out);
+//     condrem.setKeepOrganized(true);
+
+//     condrem.filter (*out);
+//     (*out).is_dense = false;
+//     pcl::removeNaNFromPointCloud(*out, *out, indices);
+
+//     return(coeff[3]);
+    
+
+//  }
+
+// /**
+//  * @brief Segment the pointcloud and return the cluster closest to the camera
+//  * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
+//  * @param x: coordinate of the camera
+//  * @param y: coordinate of the camera
+//  * @param z: coordinate of the camera
+//  * @param [out] height [m]: estimated height of the table based on the cluster.
+//  */
+// void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z,pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud)
+// {
+//     std::cout << "starting segmentation" << std::endl;
+//     std::cout << "x = " << x << ", y = " << y << ", z = " << z << std::endl;
+
+//     // Creating the KdTree object for the search method of the extraction
+//     pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZRGB>);
+//     tree->setInputCloud (cloud);
+
+//     std::vector<pcl::PointIndices> cluster_indices;
+//     pcl::EuclideanClusterExtraction<pcl::PointXYZRGB> ec; //using euclidian cluster extraction
+//     ec.setClusterTolerance (0.1);
+//     ec.setMinClusterSize ((*cloud).size()/100); //#TODO magic number
+//     ec.setMaxClusterSize ((*cloud).size());
+//     ec.setSearchMethod (tree);
+//     ec.setInputCloud (cloud);
+//     ec.extract (cluster_indices);
+
+//     std::cout << "obtained " << cluster_indices.size() << " cluster indices" <<std::endl;
+
+//     //find closest cluster
+//     pcl::PointIndices closest_cluster;
+//     float mindist_sq = INFINITY;
+//     for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it !=
+//          cluster_indices.end (); ++it) //iterate through all clusters
+//     {
+//         //construct cluster
+//         float sumx = 0, sumy = 0, sumz = 0, dist_sq = 0;
+//         int n = 0;
+//         for (const auto& idx : it->indices)
+//         {
+//             sumx += (*cloud)[idx].x;
+//             sumy += (*cloud)[idx].y;
+//             sumz += (*cloud)[idx].z;
+//             n++;
+//         }
+
+//         //find distance from camera to the middle of the cluster
+//         dist_sq = pow((sumx/n-x),2) + pow((sumy/n-y),2) + pow((sumz/n-z),2);
+//         std::cout << "distance is " << sqrt(dist_sq) << std::endl;
+//         if (dist_sq < mindist_sq) //check if closest so far
+//         {
+//             std::cout << "updating closest cluster" << std::endl;
+//             mindist_sq = dist_sq;
+//             closest_cluster = *it;
+//         }
+//     }
+
+    // //construct cluster
+    // pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out (new pcl::PointCloud<pcl::PointXYZRGB>);
+    // // pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
+    // for (uint i : closest_cluster.indices)
+    //     cloud_out->push_back( (*cloud)[i] ); //*
+
+    // // float height = FilterPlane(cloud_out, cloud_out);
+
+    // std::cout << "writing closest cluster" << std::endl;
+
+    // // Filter out objects and put them in seperate cloud
+    // pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+    // range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
+    // pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.02)));
+    // range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
+    // pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.30)));
+    // // build the filter
+    // pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+    // condrem.setCondition (range_cond);
+    // condrem.setInputCloud (cloud);
+    // condrem.setKeepOrganized(true);
+    // // apply filter
+    // condrem.filter (*object_cloud);
+    
+    // Update cloud
+    // *cloud = *cloud_out;
+
+// }
 
-    std::cout << "writing closest cluster" << std::endl;
-    *cloud = *cloud_out;
-}
 
 /**
  * @brief SegmentPlane segment the pointcloud and return the cluster closest to the camera
@@ -275,12 +297,14 @@ void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float
     cloud->swap(*cloud_p);
 }
 
+
 cv::Point2d worldToCanvas(double x, double y)
 {
     return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
 }
 
 void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Mat& canvas, cv::Scalar color)
+
 {
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
@@ -293,16 +317,35 @@ void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Mat& canvas
         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
     }
+
+    
 }
+void createObjectCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, cv::Mat& canvas, cv::Scalar color)
 
-void dilateCostmap(cv::Mat& canvas)
 {
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_RECT,
-                                             cv::Size( 11, 11),
-                                             cv::Point(5, 5) );
-    cv::dilate(canvas, canvas, element );
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < object_cloud->points.size (); nIndex++)
+    {
+        double x = object_cloud->points[nIndex].x;
+        double y = object_cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+
+    
 }
 
+// void dilateCostmap(cv::Mat& canvas)
+// {
+//     cv::Mat element = cv::getStructuringElement( cv::MORPH_RECT,
+//                                              cv::Size( 11, 11),
+//                                              cv::Point(5, 5) );
+//     cv::dilate(canvas, canvas, element );
+// }
+
 /**
  * @brief usage, print how the executable should be used and explain the input
  */
@@ -370,17 +413,69 @@ int main (int argc, char **argv)
         (*cloud).is_dense = false;
         pcl::removeNaNFromPointCloud(*cloud, *cloud, indices);
 
+        // Filter out objects and put them in seperate cloud
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out (new pcl::PointCloud<pcl::PointXYZRGB>);
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_backup(new pcl::PointCloud<pcl::PointXYZRGB>);
+        cloud_backup = cloud;  // back-up cloud used for FilterPlane to get the height of the table    
+
+        // Get the height of the table for the object detection
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_p (new pcl::PointCloud<pcl::PointXYZRGB>);
+
+        pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
+        pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
+        // Create the segmentation object
+        pcl::SACSegmentation<pcl::PointXYZRGB> seg;
+        // Optional
+        seg.setOptimizeCoefficients (true);
+        // Mandatory
+        seg.setModelType (pcl::SACMODEL_PARALLEL_PLANE);
+        seg.setMethodType (pcl::SAC_RANSAC);
+        seg.setMaxIterations (1000);
+        seg.setDistanceThreshold (0.01);
+        seg.setAxis (Eigen::Vector3f(1,0,0));
+        seg.setEpsAngle(5*0.0174532925); //*0.0174532925 to radians
+
+        // Create the filtering object
+        pcl::ExtractIndices<pcl::PointXYZRGB> extract;
+
+        int i = 0, nr_points = (int) cloud->size ();
+
+        // Segment the largest planar component from the remaining cloud
+        seg.setInputCloud(cloud);
+        seg.segment(*inliers, *coefficients);
+
+        float height = abs(coefficients->values[3]);
+
+        pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+        range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
+        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.02)));
+        range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
+        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.25)));
+        // build the filter
+        pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem2;
+        condrem2.setCondition (range_cond2);
+        condrem2.setInputCloud (cloud);
+        condrem2.setKeepOrganized(true);
+        // apply filter
+        condrem2.filter (*object_cloud);
+
         SegmentPlane(cloud, 0.0, 0.0, 0.0);
 
-        std::cout << "creating costmap test" << std::endl;
+
+
+        std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
         cv::Scalar table_color(0, 255, 0);
         cv::Scalar occupied_color(0, 0, 255);
-
-        //createCostmap(occupied_cloud, canvas, occupied_color);
+        
+        //createCostmap(occupied_cloud, canvas, table_color);
         createCostmap(cloud, canvas, table_color);
 
-        std::cout << "showing costmap test" << std::endl;
+        //prints on top of costmap(object_cloud, canvas, occupied_color)
+        createObjectCostmap(object_cloud, canvas, occupied_color);
+
+        std::cout << "showing costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
 
         // show snapshot

From 4700bcaec30dc1b455b7e263cd8064fba9c5d1e8 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Fri, 18 Nov 2022 23:40:43 +0100
Subject: [PATCH 058/136] Occluded space added to bitmap

---
 .../tools/empty_spot_designator.cpp           | 82 +++++++++++++++++++
 1 file changed, 82 insertions(+)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 176abdaf..4ad63145 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -31,6 +31,8 @@
 
 #include <pcl/segmentation/extract_clusters.h>
 #include <pcl/segmentation/sac_segmentation.h>
+#include <pcl/point_types.h>
+#include <pcl/io/pcd_io.h>
 
 #include <pcl/surface/convex_hull.h>
 
@@ -297,6 +299,39 @@ void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float
     cloud->swap(*cloud_p);
 }
 
+/**
+ * @brief Filter the occluded space and return cloud (occluded_cloud) with these point
+ * @param object_cloud: pointcloud used to 
+ * @param x: coordinate of the camera
+ * @param y: coordinate of the camera
+ * @param z: coordinate of the camera
+ * @param height: z coordinate of the table
+ */
+void OccludedSpace (pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, float x, float y, float z, float height)
+{
+pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
+    occluded_cloud->width=object_cloud->width;
+    occluded_cloud->height=object_cloud->height;
+    occluded_cloud->is_dense = false;
+    occluded_cloud->points.resize(occluded_cloud->width*occluded_cloud->height);
+
+
+    for (int nIndex = 0; nIndex < object_cloud->points.size (); nIndex++)
+    {
+        double lower = object_cloud->points[nIndex].z - z;
+        double upper = height - object_cloud->points[nIndex].y;
+        double lambda = upper / lower;
+        double dx = object_cloud->points[nIndex].x - x;
+        double dy = object_cloud->points[nIndex].y- y;
+
+        
+        occluded_cloud->points[nIndex].z =  height;
+        occluded_cloud->points[nIndex].x = object_cloud->points[nIndex].x + lambda * dx;
+        occluded_cloud->points[nIndex].y = object_cloud->points[nIndex].y + lambda * dy;
+        
+    }
+
+}
 
 cv::Point2d worldToCanvas(double x, double y)
 {
@@ -337,6 +372,25 @@ void createObjectCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, cv
 
     
 }
+void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud, cv::Mat& canvas, cv::Scalar color)
+
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < occluded_cloud->points.size (); nIndex++)
+    {
+        double x = occluded_cloud->points[nIndex].x;
+        double y = occluded_cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+
+    
+}
+
+
 
 // void dilateCostmap(cv::Mat& canvas)
 // {
@@ -459,6 +513,30 @@ int main (int argc, char **argv)
         condrem2.setKeepOrganized(true);
         // apply filter
         condrem2.filter (*object_cloud);
+        pcl::removeNaNFromPointCloud(*object_cloud, *object_cloud, indices);
+
+        // Create pointcloud with occluded space
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
+        occluded_cloud->width=object_cloud->width;
+        occluded_cloud->height=object_cloud->height;
+        occluded_cloud->is_dense = false;
+        occluded_cloud->points.resize(occluded_cloud->width*occluded_cloud->height);
+        float x = transform(0,3);
+        float y = transform(1,3);
+        float z = transform(2,3);
+        for (int nIndex = 0; nIndex < object_cloud->points.size (); nIndex++)
+        {
+        auto lower = object_cloud->points[nIndex].z - z;
+        auto upper = height - object_cloud->points[nIndex].z;
+        auto lambda = upper / lower;
+        auto dx = object_cloud->points[nIndex].x - x;
+        auto dy = object_cloud->points[nIndex].y- y;
+
+        
+        occluded_cloud->points[nIndex].z =  height;
+        occluded_cloud->points[nIndex].x = object_cloud->points[nIndex].x + lambda * dx;
+        occluded_cloud->points[nIndex].y = object_cloud->points[nIndex].y + lambda * dy;
+        }
 
         SegmentPlane(cloud, 0.0, 0.0, 0.0);
 
@@ -468,10 +546,14 @@ int main (int argc, char **argv)
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
         cv::Scalar table_color(0, 255, 0);
         cv::Scalar occupied_color(0, 0, 255);
+        cv::Scalar occluded_color(255,0,0);
         
         //createCostmap(occupied_cloud, canvas, table_color);
         createCostmap(cloud, canvas, table_color);
 
+        //prints on top of costmap(object_cloud, canvas, occupied_color)
+        createOccludedCostmap(occluded_cloud, canvas, occluded_color);       
+
         //prints on top of costmap(object_cloud, canvas, occupied_color)
         createObjectCostmap(object_cloud, canvas, occupied_color);
 

From 21c2033379050b1e4124cb3fb7c4c00120d824e2 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Thu, 24 Nov 2022 16:44:41 +0100
Subject: [PATCH 059/136] Added FOV and not table to bitmap

---
 .../tools/empty_spot_designator.cpp           | 213 ++++++++++++------
 1 file changed, 145 insertions(+), 68 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 4ad63145..088a66c9 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -12,7 +12,7 @@
 //pcl library # TODO remove the unused ones #TODO find out which ones are unused
 #include <pcl/point_cloud.h>
 #include <pcl/point_representation.h>
-
+#include <pcl/common/common.h>
 #include <pcl/io/pcd_io.h>
 
 #include <pcl/filters/filter.h>
@@ -45,8 +45,11 @@ cv::Point2d canvas_center;
 void imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
 {
     // Fill in the cloud data
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL (new pcl::PointCloud<pcl::PointXYZRGB>);
     cloud->width = image.getDepthImage().cols;
     cloud->height = image.getDepthImage().rows;
+    // FOVL->width = image.getDepthImage(0).col;
+    // FOVL->height = image.getDepthImage().rows;
     cloud->is_dense = false;
     cloud->resize (cloud->width * cloud->height);
 
@@ -252,9 +255,9 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
 /**
  * @brief SegmentPlane segment the pointcloud and return the cluster closest to the camera
  * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
- * @param x: coordinate of the camera
- * @param y: coordinate of the camera
- * @param z: coordinate of the camera
+ * @param x: coordinate of the camera ! unused
+ * @param y: coordinate of the camera ! unused
+ * @param z: coordinate of the camera ! unused
  */
 void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z)
 {
@@ -299,39 +302,6 @@ void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float
     cloud->swap(*cloud_p);
 }
 
-/**
- * @brief Filter the occluded space and return cloud (occluded_cloud) with these point
- * @param object_cloud: pointcloud used to 
- * @param x: coordinate of the camera
- * @param y: coordinate of the camera
- * @param z: coordinate of the camera
- * @param height: z coordinate of the table
- */
-void OccludedSpace (pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, float x, float y, float z, float height)
-{
-pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
-    occluded_cloud->width=object_cloud->width;
-    occluded_cloud->height=object_cloud->height;
-    occluded_cloud->is_dense = false;
-    occluded_cloud->points.resize(occluded_cloud->width*occluded_cloud->height);
-
-
-    for (int nIndex = 0; nIndex < object_cloud->points.size (); nIndex++)
-    {
-        double lower = object_cloud->points[nIndex].z - z;
-        double upper = height - object_cloud->points[nIndex].y;
-        double lambda = upper / lower;
-        double dx = object_cloud->points[nIndex].x - x;
-        double dy = object_cloud->points[nIndex].y- y;
-
-        
-        occluded_cloud->points[nIndex].z =  height;
-        occluded_cloud->points[nIndex].x = object_cloud->points[nIndex].x + lambda * dx;
-        occluded_cloud->points[nIndex].y = object_cloud->points[nIndex].y + lambda * dy;
-        
-    }
-
-}
 
 cv::Point2d worldToCanvas(double x, double y)
 {
@@ -355,6 +325,7 @@ void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Mat& canvas
 
     
 }
+
 void createObjectCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, cv::Mat& canvas, cv::Scalar color)
 
 {
@@ -370,8 +341,8 @@ void createObjectCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, cv
             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
     }
 
-    
 }
+
 void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud, cv::Mat& canvas, cv::Scalar color)
 
 {
@@ -382,23 +353,74 @@ void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud
         double x = occluded_cloud->points[nIndex].x;
         double y = occluded_cloud->points[nIndex].y;
 
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }   
+}
+
+void createNotTableCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud, cv::Mat& canvas, cv::Scalar color)
+
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < notTable_cloud->points.size (); nIndex++)
+    {
+        double x = notTable_cloud->points[nIndex].x;
+        double y = notTable_cloud->points[nIndex].y;
+
         cv::Point2d p = worldToCanvas(x, y);
         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
     }
+}
 
-    
+void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
+
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
+        {
+        float initial_x = x;
+        float initial_y = y;
+        double y = initial_y + 0.001*nIndex;
+        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+        }
 }
 
+void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
 
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
+        {
+        float initial_x = x;
+        float initial_y = y;
+        double y = initial_y - 0.001*nIndex;
+        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
 
-// void dilateCostmap(cv::Mat& canvas)
-// {
-//     cv::Mat element = cv::getStructuringElement( cv::MORPH_RECT,
-//                                              cv::Size( 11, 11),
-//                                              cv::Point(5, 5) );
-//     cv::dilate(canvas, canvas, element );
-// }
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+        }
+}
+
+void dilateCostmap(cv::Mat& canvas)
+{
+    float resolution = 0.005;
+    float radius = 0.10;
+    float margin = 0.01;
+    float length = radius + margin;
+    float Pixelsize = length / resolution;
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::dilate(canvas, canvas, element );
+}
 
 /**
  * @brief usage, print how the executable should be used and explain the input
@@ -454,28 +476,13 @@ int main (int argc, char **argv)
         // keep track of the indices in the original image
         std::vector<int> indices;
 
-        // Filter out floor
-        pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-        range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, 0.1)));
-        // build the filter
-        pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
-        condrem.setCondition (range_cond);
-        condrem.setInputCloud (cloud);
-        condrem.setKeepOrganized(true);
-        // apply filter
-        condrem.filter (*cloud);
-        (*cloud).is_dense = false;
-        pcl::removeNaNFromPointCloud(*cloud, *cloud, indices);
 
         // Filter out objects and put them in seperate cloud
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out (new pcl::PointCloud<pcl::PointXYZRGB>);
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_backup(new pcl::PointCloud<pcl::PointXYZRGB>);
-        cloud_backup = cloud;  // back-up cloud used for FilterPlane to get the height of the table    
-
+   
         // Get the height of the table for the object detection
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_p (new pcl::PointCloud<pcl::PointXYZRGB>);
-
         pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
         pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
         // Create the segmentation object
@@ -503,9 +510,9 @@ int main (int argc, char **argv)
 
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.02)));
+        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.03)));
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.25)));
+        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.80)));
         // build the filter
         pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem2;
         condrem2.setCondition (range_cond2);
@@ -515,6 +522,10 @@ int main (int argc, char **argv)
         condrem2.filter (*object_cloud);
         pcl::removeNaNFromPointCloud(*object_cloud, *object_cloud, indices);
 
+
+
+
+
         // Create pointcloud with occluded space
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
         occluded_cloud->width=object_cloud->width;
@@ -538,25 +549,91 @@ int main (int argc, char **argv)
         occluded_cloud->points[nIndex].y = object_cloud->points[nIndex].y + lambda * dy;
         }
 
-        SegmentPlane(cloud, 0.0, 0.0, 0.0);
+        // Filter out items above table
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr backup_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
+        pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond3 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+        range_cond3->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height)));
+        // build the filter
+        pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem3;
+        condrem3.setCondition (range_cond3);
+        condrem3.setInputCloud (cloud);
+        condrem3.setKeepOrganized(true);
+        // apply filter
+        condrem3.filter (*backup_cloud);
+        (*backup_cloud).is_dense = false;
+        pcl::removeNaNFromPointCloud(*backup_cloud, *backup_cloud, indices);
+
+        // Not table cloud
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
+        notTable_cloud->width       = backup_cloud->width;
+        notTable_cloud->height      = backup_cloud->height;
+        notTable_cloud->is_dense    = false;
+        notTable_cloud->points.resize(notTable_cloud->width*notTable_cloud->height);
+        for (int nIndex = 0; nIndex < backup_cloud->points.size (); nIndex++)
+        {
+        auto lower  = z - backup_cloud->points[nIndex].z;
+        auto upper  = height - backup_cloud->points[nIndex].z;
+        auto lambda = upper / lower;
+        auto dx     = x - backup_cloud->points[nIndex].x;
+        auto dy     = y - backup_cloud->points[nIndex].y;       
+        notTable_cloud->points[nIndex].z = height;
+        notTable_cloud->points[nIndex].x = backup_cloud->points[nIndex].x + lambda * dx;
+        notTable_cloud->points[nIndex].y = backup_cloud->points[nIndex].y + lambda * dy;
+        }
+
+        float min_x = cloud->points[0].x; 
+        float min_y = cloud->points[0].y; 
+        float max_x = cloud->points[0].x; 
+        float max_y = cloud->points[0].y;
+
+        // Filter out floor
+        pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+        range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, 0.1)));
+        // build the filter
+        pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+        condrem.setCondition (range_cond);
+        condrem.setInputCloud (cloud);
+        condrem.setKeepOrganized(true);
+        // apply filter
+        condrem.filter (*cloud);
+        (*cloud).is_dense = false;
+        pcl::removeNaNFromPointCloud(*cloud, *cloud, indices);
 
 
+        SegmentPlane(cloud, 0.0, 0.0, 0.0);
+  
 
+        
         std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
         cv::Scalar table_color(0, 255, 0);
         cv::Scalar occupied_color(0, 0, 255);
         cv::Scalar occluded_color(255,0,0);
+        cv::Scalar test_color(0, 255, 255);
         
-        //createCostmap(occupied_cloud, canvas, table_color);
+
+
+        // Add not table to costmap
+        createNotTableCostmap(notTable_cloud, canvas, occupied_color); 
+
+        // Add table plane to costmap
         createCostmap(cloud, canvas, table_color);
 
-        //prints on top of costmap(object_cloud, canvas, occupied_color)
+        // prints on top of costmap(object_cloud, canvas, occupied_color)
         createOccludedCostmap(occluded_cloud, canvas, occluded_color);       
 
-        //prints on top of costmap(object_cloud, canvas, occupied_color)
+        // prints on top of costmap(object_cloud, canvas, occupied_color)
         createObjectCostmap(object_cloud, canvas, occupied_color);
 
+        // FOV left
+        createFOVLCostmap(canvas, occupied_color, transform(0,3), transform(1,3));
+
+        // FOV right
+        createFOVRCostmap(canvas, occupied_color, transform(0,3), transform(1,3));
+
+        // Dilate the costmap
+        dilateCostmap(canvas);
+
         std::cout << "showing costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
 

From 39d81f9384c9539523e040926fee6f21ccedac4e Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Mon, 5 Dec 2022 23:08:12 +0100
Subject: [PATCH 060/136] Added preferred distance + Point extraction

---
 .../tools/empty_spot_designator.cpp           | 125 +++++++++++++++---
 1 file changed, 103 insertions(+), 22 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 088a66c9..8939d1a4 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -3,8 +3,10 @@
 
 #include "ed/kinect/image_buffer.h"
 
-#include "opencv2/imgproc.hpp"
+#include <opencv2/imgproc/imgproc.hpp>
 #include <opencv2/highgui.hpp>
+#include <opencv2/core/core.hpp>
+#include <vector>
 
 #include <ros/ros.h>
 #include <rgbd/image.h>
@@ -110,7 +112,7 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
     Transform(2,2) = zz;
     Transform(2,3) = z;
 
-    std::cout << Transform << std::endl;
+    // std::cout << Transform << std::endl;
     return Transform;
 }
 
@@ -255,11 +257,8 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
 /**
  * @brief SegmentPlane segment the pointcloud and return the cluster closest to the camera
  * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
- * @param x: coordinate of the camera ! unused
- * @param y: coordinate of the camera ! unused
- * @param z: coordinate of the camera ! unused
  */
-void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z)
+void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
 {
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_p (new pcl::PointCloud<pcl::PointXYZRGB>);
 
@@ -296,18 +295,18 @@ void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float
     extract.setIndices(inliers);
     extract.setNegative(false);
     extract.filter(*cloud_p);
-    std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
-     << "Plane with coefficients: " << *coefficients << std::endl;
+    // std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
+    //  << "Plane with coefficients: " << *coefficients << std::endl;
 
     cloud->swap(*cloud_p);
 }
-
+// cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
 
 cv::Point2d worldToCanvas(double x, double y)
 {
     return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
 }
-
+ 
 void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Mat& canvas, cv::Scalar color)
 
 {
@@ -409,12 +408,48 @@ void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
         }
 }
 
+void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height)
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int i = 0; i < 8; i++)
+        {
+            for (int nIndex = 0; nIndex < 4000; nIndex++)
+            {
+            float initial_x = x;
+            float initial_y = y;
+            double y = initial_y + -2+ 0.001*nIndex;
+            double x = initial_x + (z-height)*tan(67.5/(180/M_PI)); // 0.125*i*
+
+            cv::Point2d p = worldToCanvas(x, y);
+            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+            }
+        }
+}
+
+void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color)
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        float radius = 0.70;
+            for (float phi = 0; phi < 360; phi++)
+            {
+
+            double y = radius * sin(phi/(180/M_PI));
+            double x = radius * cos(phi/(180/M_PI));
+
+            cv::Point2d p = worldToCanvas(x, y);
+            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+            }
+        
+}
+
 void dilateCostmap(cv::Mat& canvas)
 {
     float resolution = 0.005;
     float radius = 0.10;
     float margin = 0.01;
-    float length = radius + margin;
+    float length = radius + margin; 
     float Pixelsize = length / resolution;
     cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
                                              cv::Size( Pixelsize, Pixelsize),
@@ -422,6 +457,46 @@ void dilateCostmap(cv::Mat& canvas)
     cv::dilate(canvas, canvas, element );
 }
 
+double ExtractPlacementOption(cv::Mat& canvas, cv::Scalar targetColor)
+{
+
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    std::vector<cv::Point> identicalPoints;
+
+    for(int row = canvas.rows; row > 0; --row)
+    {
+        for(int col = canvas.rows; col > 0; --col)
+        {
+            cv::Vec3b currPixel = canvas.at<cv::Vec3b>(row, col);
+            if(currPixel.val[0] == targetColor.val[0] &&
+               currPixel.val[1] == targetColor.val[1] &&
+               currPixel.val[2] == targetColor.val[2])
+            {
+                identicalPoints.push_back(cv::Point(col, row));
+            }
+        }
+    }
+    
+
+    cv::Point Point = identicalPoints[0];
+    double x = (Point.x-canvas_center.x)*-resolution;
+    double y = (Point.y-canvas_center.y)*-resolution;
+
+
+
+    std::cout << "The point on the canvas that is closest to HERO is:" << std::endl;
+    std::cout << Point << std::endl;
+    std::cout << "With X-coordinate:" << std::endl;
+    std::cout << x << std::endl;
+    std::cout << "And Y-coordinate:" << std::endl;
+    std::cout << y << std::endl;  
+
+
+    return x;
+    return y;
+}
+
 /**
  * @brief usage, print how the executable should be used and explain the input
  */
@@ -465,7 +540,7 @@ int main (int argc, char **argv)
             std::cerr << "No image received, will try again." << std::endl;
             continue;
         }
-        std::cout << "converting image to cloud" << std::endl;
+        // std::cout << "converting image to cloud" << std::endl;
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
         imageToCloud(*image, cloud);
 
@@ -512,7 +587,7 @@ int main (int argc, char **argv)
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
         pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.03)));
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.80)));
+        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.30)));
         // build the filter
         pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem2;
         condrem2.setCondition (range_cond2);
@@ -552,7 +627,7 @@ int main (int argc, char **argv)
         // Filter out items above table
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr backup_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond3 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-        range_cond3->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height)));
+        range_cond3->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height-0.05)));
         // build the filter
         pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem3;
         condrem3.setCondition (range_cond3);
@@ -581,10 +656,6 @@ int main (int argc, char **argv)
         notTable_cloud->points[nIndex].y = backup_cloud->points[nIndex].y + lambda * dy;
         }
 
-        float min_x = cloud->points[0].x; 
-        float min_y = cloud->points[0].y; 
-        float max_x = cloud->points[0].x; 
-        float max_y = cloud->points[0].y;
 
         // Filter out floor
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
@@ -600,16 +671,17 @@ int main (int argc, char **argv)
         pcl::removeNaNFromPointCloud(*cloud, *cloud, indices);
 
 
-        SegmentPlane(cloud, 0.0, 0.0, 0.0);
+        SegmentPlane(cloud);
   
 
         
-        std::cout << "creating costmap" << std::endl;
+        // std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
         cv::Scalar table_color(0, 255, 0);
         cv::Scalar occupied_color(0, 0, 255);
         cv::Scalar occluded_color(255,0,0);
-        cv::Scalar test_color(0, 255, 255);
+        cv::Scalar radius_color(100,0,100);
+        cv::Scalar placement_color(100, 255, 100);
         
 
 
@@ -631,10 +703,19 @@ int main (int argc, char **argv)
         // FOV right
         createFOVRCostmap(canvas, occupied_color, transform(0,3), transform(1,3));
 
+        // FOV down
+        createFOVHCostmap(canvas, occupied_color, transform(0,3), transform(1,3), transform(2,3), height);
+
+        // HERO preferred radius
+        createRadiusCostmap(canvas, radius_color);
+
         // Dilate the costmap
         dilateCostmap(canvas);
 
-        std::cout << "showing costmap" << std::endl;
+        ExtractPlacementOption(canvas, placement_color);
+    
+
+        // std::cout << "showing costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
 
         // show snapshot

From 8d1f004f8ecc34254c2f44428af65b7969a5a295 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Wed, 7 Dec 2022 16:15:58 +0100
Subject: [PATCH 061/136] Placement point costmap

---
 .../tools/empty_spot_designator.cpp           | 54 ++++++++++---------
 1 file changed, 29 insertions(+), 25 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 8939d1a4..baa5f962 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -457,16 +457,16 @@ void dilateCostmap(cv::Mat& canvas)
     cv::dilate(canvas, canvas, element );
 }
 
-double ExtractPlacementOption(cv::Mat& canvas, cv::Scalar targetColor)
+cv::Point2d ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor, cv::Scalar color)
 {
 
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
     std::vector<cv::Point> identicalPoints;
 
-    for(int row = canvas.rows; row > 0; --row)
+    for(int row = 0; row < canvas.rows; ++row)
     {
-        for(int col = canvas.rows; col > 0; --col)
+        for(int col = 0; col < canvas.rows; ++col)
         {
             cv::Vec3b currPixel = canvas.at<cv::Vec3b>(row, col);
             if(currPixel.val[0] == targetColor.val[0] &&
@@ -477,24 +477,24 @@ double ExtractPlacementOption(cv::Mat& canvas, cv::Scalar targetColor)
             }
         }
     }
-    
-
-    cv::Point Point = identicalPoints[0];
-    double x = (Point.x-canvas_center.x)*-resolution;
-    double y = (Point.y-canvas_center.y)*-resolution;
-
+       
+    for(int i = 0; i < identicalPoints.size(); i++)
+    {   
+        cv::Point2d p = identicalPoints[i];
+        if (p.x >= 0 && p.y >= 0 && p.x < placement_canvas.cols && p.y < placement_canvas.rows)
+            placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(targetColor[0], targetColor[1], targetColor[2]); 
 
+    }
+    cv::Point2d Point = identicalPoints[0];
+    double y = (Point.x-canvas_center.x)*-resolution;
+    double x = (Point.y-canvas_center.y)*-resolution;
 
-    std::cout << "The point on the canvas that is closest to HERO is:" << std::endl;
     std::cout << Point << std::endl;
-    std::cout << "With X-coordinate:" << std::endl;
-    std::cout << x << std::endl;
-    std::cout << "And Y-coordinate:" << std::endl;
-    std::cout << y << std::endl;  
-
-
-    return x;
-    return y;
+    std::cout <<  x << std::endl;
+    std::cout <<  y << std::endl;
+    cv::Point2d p = cv::Point2d(y, x);
+    placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]); 
+    return Point;
 }
 
 /**
@@ -677,20 +677,20 @@ int main (int argc, char **argv)
         
         // std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
+        cv::Mat placement_canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
         cv::Scalar table_color(0, 255, 0);
         cv::Scalar occupied_color(0, 0, 255);
         cv::Scalar occluded_color(255,0,0);
         cv::Scalar radius_color(100,0,100);
         cv::Scalar placement_color(100, 255, 100);
+        cv::Scalar point_color(255,0,0);
         
-
+        // Add table plane to costmap
+        createCostmap(cloud, canvas, table_color);
 
         // Add not table to costmap
         createNotTableCostmap(notTable_cloud, canvas, occupied_color); 
 
-        // Add table plane to costmap
-        createCostmap(cloud, canvas, table_color);
-
         // prints on top of costmap(object_cloud, canvas, occupied_color)
         createOccludedCostmap(occluded_cloud, canvas, occluded_color);       
 
@@ -706,18 +706,22 @@ int main (int argc, char **argv)
         // FOV down
         createFOVHCostmap(canvas, occupied_color, transform(0,3), transform(1,3), transform(2,3), height);
 
-        // HERO preferred radius
-        createRadiusCostmap(canvas, radius_color);
+        // // HERO preferred radius
+        // createRadiusCostmap(canvas, radius_color);
 
         // Dilate the costmap
         dilateCostmap(canvas);
 
-        ExtractPlacementOption(canvas, placement_color);
+
+        ExtractPlacementOptions(canvas, placement_canvas, table_color, point_color);
     
 
         // std::cout << "showing costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
 
+        // // std::cout << "showing costmap" << std::endl;
+        cv::imshow("Placement options costmap topview", placement_canvas);
+
         // show snapshot
         cv::Mat rgbcanvas = image->getRGBImage();
         cv::imshow("RGB", rgbcanvas);

From ce480ad5fe5406a951c1605519bee8ea1d6b4ac7 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Thu, 8 Dec 2022 17:50:31 +0100
Subject: [PATCH 062/136] Initial test on HERO

---
 .../tools/empty_spot_designator.cpp           | 28 +++++++++++--------
 1 file changed, 16 insertions(+), 12 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index baa5f962..0d609688 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -457,7 +457,7 @@ void dilateCostmap(cv::Mat& canvas)
     cv::dilate(canvas, canvas, element );
 }
 
-cv::Point2d ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor, cv::Scalar color)
+void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor, cv::Scalar point_color, double height)
 {
 
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
@@ -477,6 +477,7 @@ cv::Point2d ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas,
             }
         }
     }
+
        
     for(int i = 0; i < identicalPoints.size(); i++)
     {   
@@ -485,16 +486,17 @@ cv::Point2d ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas,
             placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(targetColor[0], targetColor[1], targetColor[2]); 
 
     }
-    cv::Point2d Point = identicalPoints[0];
-    double y = (Point.x-canvas_center.x)*-resolution;
-    double x = (Point.y-canvas_center.y)*-resolution;
-
-    std::cout << Point << std::endl;
-    std::cout <<  x << std::endl;
-    std::cout <<  y << std::endl;
-    cv::Point2d p = cv::Point2d(y, x);
-    placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]); 
-    return Point;
+    cv::Point2d PlacementPoint = identicalPoints[0];
+    double y = (PlacementPoint.x-canvas_center.x)*-resolution;
+    double x = (PlacementPoint.y-canvas_center.y)*-resolution;
+
+    double margin = 0.02;
+
+    std::cout << "The selected point for placement in (x,y,z) coordinates is:" << std::endl;
+    std::cout << "(" << x << ", " << y << ", " << height+margin << ")" << std::endl;
+    std::cout << "Which is " << sqrt(pow(x,2)+pow(y,2)) << " cm away from HERO" << std::endl;
+    placement_canvas.at<cv::Vec3b>(PlacementPoint) = cv::Vec3b(point_color[0], point_color[1], point_color[2]); 
+
 }
 
 /**
@@ -685,6 +687,7 @@ int main (int argc, char **argv)
         cv::Scalar placement_color(100, 255, 100);
         cv::Scalar point_color(255,0,0);
         
+        
         // Add table plane to costmap
         createCostmap(cloud, canvas, table_color);
 
@@ -712,8 +715,9 @@ int main (int argc, char **argv)
         // Dilate the costmap
         dilateCostmap(canvas);
 
+        ExtractPlacementOptions(canvas, placement_canvas, table_color, point_color, height);
 
-        ExtractPlacementOptions(canvas, placement_canvas, table_color, point_color);
+        // VisualizePlacementPoint(PlacementPoint, placement_canvas, point_color);
     
 
         // std::cout << "showing costmap" << std::endl;

From e510f154758debb03565a9d75771c7bd7e9de3b1 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Fri, 9 Dec 2022 15:13:51 +0100
Subject: [PATCH 063/136] refactor segmentplane

---
 .../tools/empty_spot_designator.cpp           | 88 +++++++++----------
 1 file changed, 44 insertions(+), 44 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 0d609688..9255723c 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -257,11 +257,10 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
 /**
  * @brief SegmentPlane segment the pointcloud and return the cluster closest to the camera
  * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
+ * @return height of the segmented plane
  */
-void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
+float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out)
 {
-    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_p (new pcl::PointCloud<pcl::PointXYZRGB>);
-
     pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
     pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
     // Create the segmentation object
@@ -279,26 +278,26 @@ void SegmentPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
     // Create the filtering object
     pcl::ExtractIndices<pcl::PointXYZRGB> extract;
 
-    int i = 0, nr_points = (int) cloud->size ();
+    int i = 0, nr_points = (int) cloud_in->size ();
 
     // Segment the largest planar component from the remaining cloud
-    seg.setInputCloud(cloud);
+    seg.setInputCloud(cloud_in);
     seg.segment(*inliers, *coefficients);
 
     if (inliers->indices.size() == 0) {
         std::cerr << "Could not estimate a planar model for the given dataset." << std::endl;
-        return;
+        return -1.0;
     }
 
     // Extract the inliers
-    extract.setInputCloud(cloud);
+    extract.setInputCloud(cloud_in);
     extract.setIndices(inliers);
     extract.setNegative(false);
-    extract.filter(*cloud_p);
-    // std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
-    //  << "Plane with coefficients: " << *coefficients << std::endl;
+    extract.filter(*cloud_out);
+    std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
+      << "Plane with coefficients: " << *coefficients << std::endl;
 
-    cloud->swap(*cloud_p);
+    return abs(coefficients->values[3]);
 }
 // cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
 
@@ -463,6 +462,8 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
     std::vector<cv::Point> identicalPoints;
+    cv::Point2d PlacementPoint;
+    bool found = false;
 
     for(int row = 0; row < canvas.rows; ++row)
     {
@@ -473,20 +474,18 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
                currPixel.val[1] == targetColor.val[1] &&
                currPixel.val[2] == targetColor.val[2])
             {
-                identicalPoints.push_back(cv::Point(col, row));
+                cv::Point2d p = cv::Point(col, row);
+                PlacementPoint = p;
+                found = true;
+                if (p.x >= 0 && p.y >= 0 && p.x < placement_canvas.cols && p.y < placement_canvas.rows)
+                    placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(targetColor[0], targetColor[1], targetColor[2]);
             }
         }
     }
 
-       
-    for(int i = 0; i < identicalPoints.size(); i++)
-    {   
-        cv::Point2d p = identicalPoints[i];
-        if (p.x >= 0 && p.y >= 0 && p.x < placement_canvas.cols && p.y < placement_canvas.rows)
-            placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(targetColor[0], targetColor[1], targetColor[2]); 
+    if (!found)
+        return;
 
-    }
-    cv::Point2d PlacementPoint = identicalPoints[0];
     double y = (PlacementPoint.x-canvas_center.x)*-resolution;
     double x = (PlacementPoint.y-canvas_center.y)*-resolution;
 
@@ -542,7 +541,7 @@ int main (int argc, char **argv)
             std::cerr << "No image received, will try again." << std::endl;
             continue;
         }
-        // std::cout << "converting image to cloud" << std::endl;
+        std::cout << "converting image to cloud" << std::endl;
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
         imageToCloud(*image, cloud);
 
@@ -554,6 +553,26 @@ int main (int argc, char **argv)
         std::vector<int> indices;
 
 
+        // Filter out floor
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr floorless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+
+        pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
+        range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, 0.1)));
+        // build the filter
+        pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+        condrem.setCondition (range_cond);
+        condrem.setInputCloud (cloud);
+        condrem.setKeepOrganized(true);
+        // apply filter
+        condrem.filter (*floorless_cloud);
+        (*floorless_cloud).is_dense = false;
+        pcl::removeNaNFromPointCloud(*floorless_cloud, *floorless_cloud, indices);
+
+        std::cout << "segmentPlane" << std::endl;
+        float height = SegmentPlane(floorless_cloud, floorless_cloud);
+        std::cout << "found height " << height << std::endl;
+
+
         // Filter out objects and put them in seperate cloud
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out (new pcl::PointCloud<pcl::PointXYZRGB>);
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
@@ -583,8 +602,6 @@ int main (int argc, char **argv)
         seg.setInputCloud(cloud);
         seg.segment(*inliers, *coefficients);
 
-        float height = abs(coefficients->values[3]);
-
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
         pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.03)));
@@ -658,24 +675,6 @@ int main (int argc, char **argv)
         notTable_cloud->points[nIndex].y = backup_cloud->points[nIndex].y + lambda * dy;
         }
 
-
-        // Filter out floor
-        pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-        range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, 0.1)));
-        // build the filter
-        pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
-        condrem.setCondition (range_cond);
-        condrem.setInputCloud (cloud);
-        condrem.setKeepOrganized(true);
-        // apply filter
-        condrem.filter (*cloud);
-        (*cloud).is_dense = false;
-        pcl::removeNaNFromPointCloud(*cloud, *cloud, indices);
-
-
-        SegmentPlane(cloud);
-  
-
         
         // std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
@@ -687,9 +686,9 @@ int main (int argc, char **argv)
         cv::Scalar placement_color(100, 255, 100);
         cv::Scalar point_color(255,0,0);
         
-        
+        std::cout << "creating costmap" << std::endl;
         // Add table plane to costmap
-        createCostmap(cloud, canvas, table_color);
+        createCostmap(floorless_cloud, canvas, table_color);
 
         // Add not table to costmap
         createNotTableCostmap(notTable_cloud, canvas, occupied_color); 
@@ -713,8 +712,9 @@ int main (int argc, char **argv)
         // createRadiusCostmap(canvas, radius_color);
 
         // Dilate the costmap
-        dilateCostmap(canvas);
+        //dilateCostmap(canvas);
 
+        std::cout << "extract placement options" << std::endl;
         ExtractPlacementOptions(canvas, placement_canvas, table_color, point_color, height);
 
         // VisualizePlacementPoint(PlacementPoint, placement_canvas, point_color);

From c46b68db80a992ba9a2384959907dcdedbef31dc Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Thu, 15 Dec 2022 16:05:39 +0100
Subject: [PATCH 064/136] Fixed Bug + Added placement radius

---
 .../tools/empty_spot_designator.cpp           | 74 +++++++------------
 1 file changed, 28 insertions(+), 46 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 9255723c..b4f8fea3 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -429,16 +429,29 @@ void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, floa
 void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color)
 {
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        float radius = 0.70;
+        float upper_radius = 0.805;
+        float lower_radius = 0.545;
             for (float phi = 0; phi < 360; phi++)
             {
+                for (int i = 0; i < 100; i++)
+                {
+                double y = upper_radius * sin(phi/(180/M_PI)) + 0.03 * i * sin(phi/(180/M_PI));
+                double x = upper_radius * cos(phi/(180/M_PI)) + 0.03 * i * cos(phi/(180/M_PI));
 
-            double y = radius * sin(phi/(180/M_PI));
-            double x = radius * cos(phi/(180/M_PI));
+                cv::Point2d p = worldToCanvas(x, y);
+                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+                }
 
-            cv::Point2d p = worldToCanvas(x, y);
-            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                for (int i = 0; i < 100; i++)
+                {
+                double y = lower_radius * sin(phi/(180/M_PI)) - lower_radius/100 * i * sin(phi/(180/M_PI));
+                double x = lower_radius * cos(phi/(180/M_PI)) - lower_radius/100 * i * cos(phi/(180/M_PI));
+
+                cv::Point2d p = worldToCanvas(x, y);
+                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
                 canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+                }
             }
         
 }
@@ -465,9 +478,9 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
     cv::Point2d PlacementPoint;
     bool found = false;
 
-    for(int row = 0; row < canvas.rows; ++row)
+    for(int row = canvas.rows; row > 0; --row)
     {
-        for(int col = 0; col < canvas.rows; ++col)
+        for(int col = canvas.cols; col > 0; --col)
         {
             cv::Vec3b currPixel = canvas.at<cv::Vec3b>(row, col);
             if(currPixel.val[0] == targetColor.val[0] &&
@@ -568,43 +581,16 @@ int main (int argc, char **argv)
         (*floorless_cloud).is_dense = false;
         pcl::removeNaNFromPointCloud(*floorless_cloud, *floorless_cloud, indices);
 
-        std::cout << "segmentPlane" << std::endl;
+        std::cout << "SegmentPlane" << std::endl;
         float height = SegmentPlane(floorless_cloud, floorless_cloud);
-        std::cout << "found height " << height << std::endl;
+        std::cout << "Found plane height " << height << std::endl;
 
 
         // Filter out objects and put them in seperate cloud
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out (new pcl::PointCloud<pcl::PointXYZRGB>);
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-   
-        // Get the height of the table for the object detection
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_p (new pcl::PointCloud<pcl::PointXYZRGB>);
-        pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
-        pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
-        // Create the segmentation object
-        pcl::SACSegmentation<pcl::PointXYZRGB> seg;
-        // Optional
-        seg.setOptimizeCoefficients (true);
-        // Mandatory
-        seg.setModelType (pcl::SACMODEL_PARALLEL_PLANE);
-        seg.setMethodType (pcl::SAC_RANSAC);
-        seg.setMaxIterations (1000);
-        seg.setDistanceThreshold (0.01);
-        seg.setAxis (Eigen::Vector3f(1,0,0));
-        seg.setEpsAngle(5*0.0174532925); //*0.0174532925 to radians
-
-        // Create the filtering object
-        pcl::ExtractIndices<pcl::PointXYZRGB> extract;
-
-        int i = 0, nr_points = (int) cloud->size ();
-
-        // Segment the largest planar component from the remaining cloud
-        seg.setInputCloud(cloud);
-        seg.segment(*inliers, *coefficients);
-
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.03)));
+        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.05)));
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
         pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.30)));
         // build the filter
@@ -616,10 +602,6 @@ int main (int argc, char **argv)
         condrem2.filter (*object_cloud);
         pcl::removeNaNFromPointCloud(*object_cloud, *object_cloud, indices);
 
-
-
-
-
         // Create pointcloud with occluded space
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
         occluded_cloud->width=object_cloud->width;
@@ -643,7 +625,7 @@ int main (int argc, char **argv)
         occluded_cloud->points[nIndex].y = object_cloud->points[nIndex].y + lambda * dy;
         }
 
-        // Filter out items above table
+        // Filter out items above table to create not table cloud
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr backup_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond3 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
         range_cond3->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height-0.05)));
@@ -677,7 +659,7 @@ int main (int argc, char **argv)
 
         
         // std::cout << "creating costmap" << std::endl;
-        cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
+        cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
         cv::Mat placement_canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
         cv::Scalar table_color(0, 255, 0);
         cv::Scalar occupied_color(0, 0, 255);
@@ -708,11 +690,11 @@ int main (int argc, char **argv)
         // FOV down
         createFOVHCostmap(canvas, occupied_color, transform(0,3), transform(1,3), transform(2,3), height);
 
-        // // HERO preferred radius
-        // createRadiusCostmap(canvas, radius_color);
+        // HERO preferred radius
+        createRadiusCostmap(canvas, radius_color);
 
         // Dilate the costmap
-        //dilateCostmap(canvas);
+        dilateCostmap(canvas);
 
         std::cout << "extract placement options" << std::endl;
         ExtractPlacementOptions(canvas, placement_canvas, table_color, point_color, height);

From c13e09b251451dbcabd604932ecfb80ec28b1188 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Thu, 12 Jan 2023 16:16:39 +0100
Subject: [PATCH 065/136] Placement costmap improved

---
 .../tools/empty_spot_designator.cpp           | 88 ++++++++++++-------
 1 file changed, 54 insertions(+), 34 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index b4f8fea3..dc805588 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -44,7 +44,7 @@
 double resolution = 0.005;
 cv::Point2d canvas_center;
 
-void imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
+double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
 {
     // Fill in the cloud data
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL (new pcl::PointCloud<pcl::PointXYZRGB>);
@@ -77,6 +77,7 @@ void imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::P
             cloud->at(j,i).b = bgr[0];
         }
     }
+return image.getCameraModel().fx();
 }
 
 Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
@@ -294,8 +295,8 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::
     extract.setIndices(inliers);
     extract.setNegative(false);
     extract.filter(*cloud_out);
-    std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
-      << "Plane with coefficients: " << *coefficients << std::endl;
+    // std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
+    //   << "Plane with coefficients: " << *coefficients << std::endl;
 
     return abs(coefficients->values[3]);
 }
@@ -373,21 +374,39 @@ void createNotTableCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud
     }
 }
 
-void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
+void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, double fx)
 
 {
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
         for (int nIndex = 0; nIndex < 3000 ; nIndex++)
         {
+        // double d = image.getDepthImage().at<float>(i,j);
+        // double fx = image.getCameraModel().fx();
+        float dpix = canvas.cols;
         float initial_x = x;
         float initial_y = y;
-        double y = initial_y + 0.001*nIndex;
+        double y = initial_y + (0.001)*nIndex;
         double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
+        // double x = y * (1/fx) *dpix;
+        // std::cout << x << std::endl;
 
         cv::Point2d p = worldToCanvas(x, y);
         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
         }
+
+
+        // for (int nIndex = 0; nIndex < 500 ; nIndex++)
+        // {
+        // float dpix = nIndex/2;
+        // double y = 0.005*nIndex;
+        // double x = y * (1/fx) * dpix;
+        // std::cout << x << std::endl;
+        // cv::Point2d p = worldToCanvas(x, y);
+        // if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+        //     canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+
+        // }
 }
 
 void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
@@ -410,14 +429,14 @@ void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
 void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height)
 {
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int i = 0; i < 8; i++)
+        for (int i = 0; i < 100; i++)
         {
             for (int nIndex = 0; nIndex < 4000; nIndex++)
             {
             float initial_x = x;
             float initial_y = y;
             double y = initial_y + -2+ 0.001*nIndex;
-            double x = initial_x + (z-height)*tan(67.5/(180/M_PI)); // 0.125*i*
+            double x = 0.01*i*(initial_x + (z-height)*tan(67.0/(180/M_PI))); // 67.5 deg
 
             cv::Point2d p = worldToCanvas(x, y);
             if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
@@ -426,11 +445,11 @@ void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, floa
         }
 }
 
-void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color)
+void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
 {
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        float upper_radius = 0.805;
-        float lower_radius = 0.545;
+        float upper_radius = 0.75 + placement_margin/2;
+        float lower_radius = 0.60 - placement_margin/2;
             for (float phi = 0; phi < 360; phi++)
             {
                 for (int i = 0; i < 100; i++)
@@ -456,17 +475,14 @@ void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color)
         
 }
 
-void dilateCostmap(cv::Mat& canvas)
+void dilateCostmap(cv::Mat& canvas, float placement_margin)
 {
-    float resolution = 0.005;
-    float radius = 0.10;
-    float margin = 0.01;
-    float length = radius + margin; 
-    float Pixelsize = length / resolution;
+    float Pixelsize = placement_margin / resolution;
     cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
                                              cv::Size( Pixelsize, Pixelsize),
                                              cv::Point(-1, -1) );
     cv::dilate(canvas, canvas, element );
+
 }
 
 void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor, cv::Scalar point_color, double height)
@@ -504,9 +520,9 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
 
     double margin = 0.02;
 
-    std::cout << "The selected point for placement in (x,y,z) coordinates is:" << std::endl;
-    std::cout << "(" << x << ", " << y << ", " << height+margin << ")" << std::endl;
-    std::cout << "Which is " << sqrt(pow(x,2)+pow(y,2)) << " cm away from HERO" << std::endl;
+    // std::cout << "The selected point for placement in (x,y,z) coordinates is:" << std::endl;
+    // std::cout << "(" << x << ", " << y << ", " << height+margin << ")" << std::endl;
+    // std::cout << "Which is " << sqrt(pow(x,2)+pow(y,2)) << " cm away from HERO" << std::endl;
     placement_canvas.at<cv::Vec3b>(PlacementPoint) = cv::Vec3b(point_color[0], point_color[1], point_color[2]); 
 
 }
@@ -554,9 +570,9 @@ int main (int argc, char **argv)
             std::cerr << "No image received, will try again." << std::endl;
             continue;
         }
-        std::cout << "converting image to cloud" << std::endl;
+        // std::cout << "converting image to cloud" << std::endl;
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-        imageToCloud(*image, cloud);
+        double fx = imageToCloud(*image, cloud);
 
         // transform to base link frame
         Eigen::Matrix4f transform = geolibToEigen(sensor_pose);
@@ -581,16 +597,16 @@ int main (int argc, char **argv)
         (*floorless_cloud).is_dense = false;
         pcl::removeNaNFromPointCloud(*floorless_cloud, *floorless_cloud, indices);
 
-        std::cout << "SegmentPlane" << std::endl;
+        // std::cout << "SegmentPlane" << std::endl;
         float height = SegmentPlane(floorless_cloud, floorless_cloud);
-        std::cout << "Found plane height " << height << std::endl;
+        // std::cout << "Found plane height " << height << std::endl;
 
 
         // Filter out objects and put them in seperate cloud
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.05)));
+        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.02)));
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
         pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.30)));
         // build the filter
@@ -667,8 +683,14 @@ int main (int argc, char **argv)
         cv::Scalar radius_color(100,0,100);
         cv::Scalar placement_color(100, 255, 100);
         cv::Scalar point_color(255,0,0);
+
+        // Object placement margins
+        float object_diameter = 0.10;
+        float error_margin = 0.02;
+        float length = object_diameter + error_margin; 
+        float placement_margin = 2*0.02 + length;
         
-        std::cout << "creating costmap" << std::endl;
+        // std::cout << "creating costmap" << std::endl;
         // Add table plane to costmap
         createCostmap(floorless_cloud, canvas, table_color);
 
@@ -682,30 +704,28 @@ int main (int argc, char **argv)
         createObjectCostmap(object_cloud, canvas, occupied_color);
 
         // FOV left
-        createFOVLCostmap(canvas, occupied_color, transform(0,3), transform(1,3));
+        createFOVLCostmap(canvas, occluded_color, transform(0,3), transform(1,3), fx);
 
         // FOV right
-        createFOVRCostmap(canvas, occupied_color, transform(0,3), transform(1,3));
+        createFOVRCostmap(canvas, occluded_color, transform(0,3), transform(1,3));
 
         // FOV down
-        createFOVHCostmap(canvas, occupied_color, transform(0,3), transform(1,3), transform(2,3), height);
+        createFOVHCostmap(canvas, occluded_color, transform(0,3), transform(1,3), transform(2,3), height);
 
         // HERO preferred radius
-        createRadiusCostmap(canvas, radius_color);
+        createRadiusCostmap(canvas, radius_color, placement_margin);
 
         // Dilate the costmap
-        dilateCostmap(canvas);
+        dilateCostmap(canvas, placement_margin);
 
         std::cout << "extract placement options" << std::endl;
-        ExtractPlacementOptions(canvas, placement_canvas, table_color, point_color, height);
 
-        // VisualizePlacementPoint(PlacementPoint, placement_canvas, point_color);
-    
+        ExtractPlacementOptions(canvas, placement_canvas, table_color, point_color, height);
 
         // std::cout << "showing costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
 
-        // // std::cout << "showing costmap" << std::endl;
+        // std::cout << "showing costmap" << std::endl;
         cv::imshow("Placement options costmap topview", placement_canvas);
 
         // show snapshot

From 89792a0d0a7ce1a3f49bc1a458832f04fed90df0 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Thu, 12 Jan 2023 17:08:47 +0100
Subject: [PATCH 066/136] Experiment

---
 ed_sensor_integration/tools/empty_spot_designator.cpp | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index dc805588..6fd66fa1 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -597,9 +597,9 @@ int main (int argc, char **argv)
         (*floorless_cloud).is_dense = false;
         pcl::removeNaNFromPointCloud(*floorless_cloud, *floorless_cloud, indices);
 
-        // std::cout << "SegmentPlane" << std::endl;
+        std::cout << "SegmentPlane" << std::endl;
         float height = SegmentPlane(floorless_cloud, floorless_cloud);
-        // std::cout << "Found plane height " << height << std::endl;
+        std::cout << "Found plane height " << height << std::endl;
 
 
         // Filter out objects and put them in seperate cloud
@@ -690,7 +690,7 @@ int main (int argc, char **argv)
         float length = object_diameter + error_margin; 
         float placement_margin = 2*0.02 + length;
         
-        // std::cout << "creating costmap" << std::endl;
+        std::cout << "creating costmap" << std::endl;
         // Add table plane to costmap
         createCostmap(floorless_cloud, canvas, table_color);
 
@@ -722,10 +722,10 @@ int main (int argc, char **argv)
 
         ExtractPlacementOptions(canvas, placement_canvas, table_color, point_color, height);
 
-        // std::cout << "showing costmap" << std::endl;
+        std::cout << "showing costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
 
-        // std::cout << "showing costmap" << std::endl;
+        std::cout << "showing placement costmap" << std::endl;
         cv::imshow("Placement options costmap topview", placement_canvas);
 
         // show snapshot

From 8b538df1ceb5911d0b19b4bab721d5bf772a2be4 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Tue, 17 Jan 2023 14:25:38 +0100
Subject: [PATCH 067/136] Latest Experiment

---
 .../tools/empty_spot_designator.cpp           | 30 +++++++++++--------
 1 file changed, 17 insertions(+), 13 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 6fd66fa1..9d9c3725 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -436,7 +436,7 @@ void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, floa
             float initial_x = x;
             float initial_y = y;
             double y = initial_y + -2+ 0.001*nIndex;
-            double x = 0.01*i*(initial_x + (z-height)*tan(67.0/(180/M_PI))); // 67.5 deg
+            double x = (initial_x + (z-height)*tan(67.0/(180/M_PI))); // 67.5 deg
 
             cv::Point2d p = worldToCanvas(x, y);
             if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
@@ -475,13 +475,13 @@ void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_marg
         
 }
 
-void dilateCostmap(cv::Mat& canvas, float placement_margin)
+void dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin)
 {
     float Pixelsize = placement_margin / resolution;
     cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
                                              cv::Size( Pixelsize, Pixelsize),
                                              cv::Point(-1, -1) );
-    cv::dilate(canvas, canvas, element );
+    cv::dilate(canvas, dilated_canvas, element );
 
 }
 
@@ -520,9 +520,9 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
 
     double margin = 0.02;
 
-    // std::cout << "The selected point for placement in (x,y,z) coordinates is:" << std::endl;
-    // std::cout << "(" << x << ", " << y << ", " << height+margin << ")" << std::endl;
-    // std::cout << "Which is " << sqrt(pow(x,2)+pow(y,2)) << " cm away from HERO" << std::endl;
+    std::cout << "The selected point for placement in (x,y,z) coordinates is:" << std::endl;
+    std::cout << "(" << x << ", " << y << ", " << height+margin << ")" << std::endl;
+    std::cout << "Which is " << sqrt(pow(x,2)+pow(y,2)) << " cm away from HERO" << std::endl;
     placement_canvas.at<cv::Vec3b>(PlacementPoint) = cv::Vec3b(point_color[0], point_color[1], point_color[2]); 
 
 }
@@ -606,7 +606,7 @@ int main (int argc, char **argv)
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.02)));
+        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.05)));
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
         pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.30)));
         // build the filter
@@ -617,7 +617,7 @@ int main (int argc, char **argv)
         // apply filter
         condrem2.filter (*object_cloud);
         pcl::removeNaNFromPointCloud(*object_cloud, *object_cloud, indices);
-
+        
         // Create pointcloud with occluded space
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
         occluded_cloud->width=object_cloud->width;
@@ -676,7 +676,8 @@ int main (int argc, char **argv)
         
         // std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-        cv::Mat placement_canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
+        cv::Mat dilated_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+        cv::Mat placement_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
         cv::Scalar table_color(0, 255, 0);
         cv::Scalar occupied_color(0, 0, 255);
         cv::Scalar occluded_color(255,0,0);
@@ -697,10 +698,10 @@ int main (int argc, char **argv)
         // Add not table to costmap
         createNotTableCostmap(notTable_cloud, canvas, occupied_color); 
 
-        // prints on top of costmap(object_cloud, canvas, occupied_color)
+        // Add occluded space to costmap
         createOccludedCostmap(occluded_cloud, canvas, occluded_color);       
 
-        // prints on top of costmap(object_cloud, canvas, occupied_color)
+        // Add objects to costmap
         createObjectCostmap(object_cloud, canvas, occupied_color);
 
         // FOV left
@@ -716,11 +717,11 @@ int main (int argc, char **argv)
         createRadiusCostmap(canvas, radius_color, placement_margin);
 
         // Dilate the costmap
-        dilateCostmap(canvas, placement_margin);
+        dilateCostmap(canvas, dilated_canvas, placement_margin);
 
         std::cout << "extract placement options" << std::endl;
 
-        ExtractPlacementOptions(canvas, placement_canvas, table_color, point_color, height);
+        ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
 
         std::cout << "showing costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
@@ -728,6 +729,9 @@ int main (int argc, char **argv)
         std::cout << "showing placement costmap" << std::endl;
         cv::imshow("Placement options costmap topview", placement_canvas);
 
+        std::cout << "showing dilated costmap" << std::endl;
+        cv::imshow("Dilated costmap topview", dilated_canvas);
+
         // show snapshot
         cv::Mat rgbcanvas = image->getRGBImage();
         cv::imshow("RGB", rgbcanvas);

From 87bce740428f27f33cd4c39bc47e06d9b2ea352d Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Tue, 7 Mar 2023 20:02:24 +0100
Subject: [PATCH 068/136] Improved object filtering

---
 .../tools/empty_spot_designator.cpp           | 89 ++++++++++++-------
 1 file changed, 58 insertions(+), 31 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 9d9c3725..225f7fcb 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -44,17 +44,19 @@
 double resolution = 0.005;
 cv::Point2d canvas_center;
 
-double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
+double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL)
 {
     // Fill in the cloud data
-    pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL (new pcl::PointCloud<pcl::PointXYZRGB>);
     cloud->width = image.getDepthImage().cols;
     cloud->height = image.getDepthImage().rows;
-    // FOVL->width = image.getDepthImage(0).col;
-    // FOVL->height = image.getDepthImage().rows;
     cloud->is_dense = false;
     cloud->resize (cloud->width * cloud->height);
 
+    FOVL->width = cloud->width;
+    FOVL->height = image.getDepthImage().rows;
+    FOVL->is_dense = false;
+    FOVL->resize (FOVL->width * FOVL->height);
+
     double fx = image.getCameraModel().fx();
     double fy = image.getCameraModel().fy();
 
@@ -75,8 +77,13 @@ double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>:
             cloud->at(j,i).r = bgr[2];
             cloud->at(j,i).g = bgr[1];
             cloud->at(j,i).b = bgr[0];
+
+            // FOVL->at(j,0).y = cloud->at(j,0).y;
+            // FOVL->at(j,0).x = cloud->at(j,0).x;
+
         }
     }
+
 return image.getCameraModel().fx();
 }
 
@@ -260,7 +267,7 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
  * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
  * @return height of the segmented plane
  */
-float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out)
+float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in2, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_no_plane)
 {
     pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
     pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
@@ -278,7 +285,7 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::
 
     // Create the filtering object
     pcl::ExtractIndices<pcl::PointXYZRGB> extract;
-
+    pcl::ExtractIndices<pcl::PointXYZRGB> extract2;
     int i = 0, nr_points = (int) cloud_in->size ();
 
     // Segment the largest planar component from the remaining cloud
@@ -290,14 +297,22 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::
         return -1.0;
     }
 
-    // Extract the inliers
+    // Extract the inliers to a cloud with a plane
     extract.setInputCloud(cloud_in);
     extract.setIndices(inliers);
     extract.setNegative(false);
     extract.filter(*cloud_out);
+
+    
     // std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
     //   << "Plane with coefficients: " << *coefficients << std::endl;
 
+    // Extract outliers to the main cloud without the table plane
+    extract2.setInputCloud(cloud_in2);
+    extract2.setIndices(inliers);
+    extract2.setNegative(true);
+    extract2.filter(*cloud_no_plane);
+
     return abs(coefficients->values[3]);
 }
 // cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
@@ -358,6 +373,8 @@ void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud
     }   
 }
 
+
+
 void createNotTableCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud, cv::Mat& canvas, cv::Scalar color)
 
 {
@@ -426,7 +443,7 @@ void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
         }
 }
 
-void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height)
+void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height) // Replace with morphology
 {
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
         for (int i = 0; i < 100; i++)
@@ -572,7 +589,9 @@ int main (int argc, char **argv)
         }
         // std::cout << "converting image to cloud" << std::endl;
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-        double fx = imageToCloud(*image, cloud);
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL (new pcl::PointCloud<pcl::PointXYZRGB>);
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVR (new pcl::PointCloud<pcl::PointXYZRGB>);
+        double fx = imageToCloud(*image, cloud, FOVL);
 
         // transform to base link frame
         Eigen::Matrix4f transform = geolibToEigen(sensor_pose);
@@ -598,7 +617,11 @@ int main (int argc, char **argv)
         pcl::removeNaNFromPointCloud(*floorless_cloud, *floorless_cloud, indices);
 
         std::cout << "SegmentPlane" << std::endl;
-        float height = SegmentPlane(floorless_cloud, floorless_cloud);
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr plane_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr planeless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+
+        // Segment the table plane and return a cloud with the plane and a cloud where the plane is removed
+        float height = SegmentPlane(floorless_cloud, floorless_cloud, plane_cloud, planeless_cloud);
         std::cout << "Found plane height " << height << std::endl;
 
 
@@ -606,13 +629,13 @@ int main (int argc, char **argv)
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.05)));
+        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height)));
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
         pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.30)));
         // build the filter
         pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem2;
         condrem2.setCondition (range_cond2);
-        condrem2.setInputCloud (cloud);
+        condrem2.setInputCloud (planeless_cloud);
         condrem2.setKeepOrganized(true);
         // apply filter
         condrem2.filter (*object_cloud);
@@ -641,14 +664,14 @@ int main (int argc, char **argv)
         occluded_cloud->points[nIndex].y = object_cloud->points[nIndex].y + lambda * dy;
         }
 
-        // Filter out items above table to create not table cloud
+        // Filter out items below table to create not table cloud
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr backup_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond3 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-        range_cond3->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height-0.05)));
+        range_cond3->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height-0.02)));
         // build the filter
         pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem3;
         condrem3.setCondition (range_cond3);
-        condrem3.setInputCloud (cloud);
+        condrem3.setInputCloud (floorless_cloud);
         condrem3.setKeepOrganized(true);
         // apply filter
         condrem3.filter (*backup_cloud);
@@ -692,35 +715,39 @@ int main (int argc, char **argv)
         float placement_margin = 2*0.02 + length;
         
         std::cout << "creating costmap" << std::endl;
-        // Add table plane to costmap
-        createCostmap(floorless_cloud, canvas, table_color);
 
-        // Add not table to costmap
-        createNotTableCostmap(notTable_cloud, canvas, occupied_color); 
+        // Add table plane to costmap
+        createCostmap(plane_cloud, canvas, table_color);
+                
+        // Add objects to costmap
+        createObjectCostmap(object_cloud, canvas, occupied_color);
 
         // Add occluded space to costmap
-        createOccludedCostmap(occluded_cloud, canvas, occluded_color);       
+        createOccludedCostmap(occluded_cloud, canvas, occluded_color); 
+
+
+        ///// Replace the commented steps with image processing technniques instead
 
-        // Add objects to costmap
-        createObjectCostmap(object_cloud, canvas, occupied_color);
 
-        // FOV left
-        createFOVLCostmap(canvas, occluded_color, transform(0,3), transform(1,3), fx);
+        // // Add not table to costmap 
+        // createNotTableCostmap(notTable_cloud, canvas, occupied_color); 
 
-        // FOV right
-        createFOVRCostmap(canvas, occluded_color, transform(0,3), transform(1,3));
+        // // FOV left
+        // createFOVLCostmap(canvas, occluded_color, transform(0,3), transform(1,3), fx);
 
-        // FOV down
-        createFOVHCostmap(canvas, occluded_color, transform(0,3), transform(1,3), transform(2,3), height);
+        // // FOV right
+        // createFOVRCostmap(canvas, occluded_color, transform(0,3), transform(1,3));
+
+        // // FOV down
+        // createFOVHCostmap(canvas, occluded_color, transform(0,3), transform(1,3), transform(2,3), height);
 
         // HERO preferred radius
         createRadiusCostmap(canvas, radius_color, placement_margin);
 
-        // Dilate the costmap
+        // Dilate the costmap and create a new canvas
         dilateCostmap(canvas, dilated_canvas, placement_margin);
 
-        std::cout << "extract placement options" << std::endl;
-
+        // Extract the placement options and choose a placement solution
         ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
 
         std::cout << "showing costmap" << std::endl;

From 1f34b8270e1171ef7941488a0526ca4ff381498e Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Tue, 21 Mar 2023 20:50:35 +0100
Subject: [PATCH 069/136] Use morphological operations instead of PCL data

---
 .../tools/empty_spot_designator.cpp           | 289 +++---------------
 1 file changed, 39 insertions(+), 250 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 225f7fcb..3a63fb79 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -78,9 +78,6 @@ double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>:
             cloud->at(j,i).g = bgr[1];
             cloud->at(j,i).b = bgr[0];
 
-            // FOVL->at(j,0).y = cloud->at(j,0).y;
-            // FOVL->at(j,0).x = cloud->at(j,0).x;
-
         }
     }
 
@@ -124,144 +121,6 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
     return Transform;
 }
 
-// /**
-//  * @brief FilterPlane fit a plane through a pointcloud, filter the points which lie in this plane and return the height of the plane #TODO separation of concerns.
-//  * @param cloud_backup: pointcloud to be filtered.
-//  * @param out: pointcloud with all points that lie within the plane
-//  * @return height (z coordinate) of the fitted plane.
-//  */
-// float FilterPlane (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_backup, pcl::PointCloud<pcl::PointXYZRGB>::Ptr out)
-// {
-//     std::vector<int> indices;
-//     float threshold = 0.03;
-
-//     std::cout << "starting ransac" << std::endl;
-//     // Create SAC model
-//     pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>::Ptr plane (new pcl::SampleConsensusModelHorizontalPlane<pcl::PointXYZRGB>(cloud_backup));
-//     std::cout << "created plane object" << std::endl;
-//     // Create SAC method
-//     pcl::RandomSampleConsensus<pcl::PointXYZRGB>::Ptr sac (new pcl::RandomSampleConsensus<pcl::PointXYZRGB> (plane, threshold));
-//     std::cout << "created ransac object" << std::endl;
-//     sac->setMaxIterations(10000);
-//     sac->setProbability(0.99);
-
-//     // Fit model
-//     sac->computeModel();
-
-//     // Get inliers
-//     std::vector<int> inliers;
-//     sac->getInliers(inliers);
-
-//     // Get the model coefficients
-//     Eigen::VectorXf coeff;
-//     sac->getModelCoefficients (coeff);
-//     std::cout << "ransac complete" << std::endl;
-
-//     pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-//     range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, (coeff[3]-0.01))));
-//     *out = *cloud_backup;
-
-//     //filter out everything below plane
-//     pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
-//     condrem.setCondition (range_cond);
-//     condrem.setInputCloud (out);
-//     condrem.setKeepOrganized(true);
-
-//     condrem.filter (*out);
-//     (*out).is_dense = false;
-//     pcl::removeNaNFromPointCloud(*out, *out, indices);
-
-//     return(coeff[3]);
-    
-
-//  }
-
-// /**
-//  * @brief Segment the pointcloud and return the cluster closest to the camera
-//  * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
-//  * @param x: coordinate of the camera
-//  * @param y: coordinate of the camera
-//  * @param z: coordinate of the camera
-//  * @param [out] height [m]: estimated height of the table based on the cluster.
-//  */
-// void Segment (pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float x, float y, float z,pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud)
-// {
-//     std::cout << "starting segmentation" << std::endl;
-//     std::cout << "x = " << x << ", y = " << y << ", z = " << z << std::endl;
-
-//     // Creating the KdTree object for the search method of the extraction
-//     pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZRGB>);
-//     tree->setInputCloud (cloud);
-
-//     std::vector<pcl::PointIndices> cluster_indices;
-//     pcl::EuclideanClusterExtraction<pcl::PointXYZRGB> ec; //using euclidian cluster extraction
-//     ec.setClusterTolerance (0.1);
-//     ec.setMinClusterSize ((*cloud).size()/100); //#TODO magic number
-//     ec.setMaxClusterSize ((*cloud).size());
-//     ec.setSearchMethod (tree);
-//     ec.setInputCloud (cloud);
-//     ec.extract (cluster_indices);
-
-//     std::cout << "obtained " << cluster_indices.size() << " cluster indices" <<std::endl;
-
-//     //find closest cluster
-//     pcl::PointIndices closest_cluster;
-//     float mindist_sq = INFINITY;
-//     for (std::vector<pcl::PointIndices>::const_iterator it = cluster_indices.begin (); it !=
-//          cluster_indices.end (); ++it) //iterate through all clusters
-//     {
-//         //construct cluster
-//         float sumx = 0, sumy = 0, sumz = 0, dist_sq = 0;
-//         int n = 0;
-//         for (const auto& idx : it->indices)
-//         {
-//             sumx += (*cloud)[idx].x;
-//             sumy += (*cloud)[idx].y;
-//             sumz += (*cloud)[idx].z;
-//             n++;
-//         }
-
-//         //find distance from camera to the middle of the cluster
-//         dist_sq = pow((sumx/n-x),2) + pow((sumy/n-y),2) + pow((sumz/n-z),2);
-//         std::cout << "distance is " << sqrt(dist_sq) << std::endl;
-//         if (dist_sq < mindist_sq) //check if closest so far
-//         {
-//             std::cout << "updating closest cluster" << std::endl;
-//             mindist_sq = dist_sq;
-//             closest_cluster = *it;
-//         }
-//     }
-
-    // //construct cluster
-    // pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out (new pcl::PointCloud<pcl::PointXYZRGB>);
-    // // pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
-    // for (uint i : closest_cluster.indices)
-    //     cloud_out->push_back( (*cloud)[i] ); //*
-
-    // // float height = FilterPlane(cloud_out, cloud_out);
-
-    // std::cout << "writing closest cluster" << std::endl;
-
-    // // Filter out objects and put them in seperate cloud
-    // pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-    // range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-    // pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height+0.02)));
-    // range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-    // pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.30)));
-    // // build the filter
-    // pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
-    // condrem.setCondition (range_cond);
-    // condrem.setInputCloud (cloud);
-    // condrem.setKeepOrganized(true);
-    // // apply filter
-    // condrem.filter (*object_cloud);
-    
-    // Update cloud
-    // *cloud = *cloud_out;
-
-// }
-
-
 /**
  * @brief SegmentPlane segment the pointcloud and return the cluster closest to the camera
  * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
@@ -315,7 +174,7 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const
 
     return abs(coefficients->values[3]);
 }
-// cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(50, 50, 50));
+
 
 cv::Point2d worldToCanvas(double x, double y)
 {
@@ -373,94 +232,28 @@ void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud
     }   
 }
 
-
-
-void createNotTableCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud, cv::Mat& canvas, cv::Scalar color)
-
+void CloseCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin)
 {
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < notTable_cloud->points.size (); nIndex++)
-    {
-        double x = notTable_cloud->points[nIndex].x;
-        double y = notTable_cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
+    float Pixelsize = 5*(placement_margin / resolution);
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::dilate(canvas, closed_canvas, element );
+    cv::erode(closed_canvas, closed_canvas, element);
 }
 
-void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, double fx)
 
+void AlterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin)
 {
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
-        {
-        // double d = image.getDepthImage().at<float>(i,j);
-        // double fx = image.getCameraModel().fx();
-        float dpix = canvas.cols;
-        float initial_x = x;
-        float initial_y = y;
-        double y = initial_y + (0.001)*nIndex;
-        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
-        // double x = y * (1/fx) *dpix;
-        // std::cout << x << std::endl;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-        }
-
-
-        // for (int nIndex = 0; nIndex < 500 ; nIndex++)
-        // {
-        // float dpix = nIndex/2;
-        // double y = 0.005*nIndex;
-        // double x = y * (1/fx) * dpix;
-        // std::cout << x << std::endl;
-        // cv::Point2d p = worldToCanvas(x, y);
-        // if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-        //     canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-
-        // }
+    float Pixelsize = 2*(placement_margin / resolution);
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::erode(closed_canvas, smallplane_canvas, element);
 }
 
-void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
 
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
-        {
-        float initial_x = x;
-        float initial_y = y;
-        double y = initial_y - 0.001*nIndex;
-        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
 
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-        }
-}
-
-void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height) // Replace with morphology
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int i = 0; i < 100; i++)
-        {
-            for (int nIndex = 0; nIndex < 4000; nIndex++)
-            {
-            float initial_x = x;
-            float initial_y = y;
-            double y = initial_y + -2+ 0.001*nIndex;
-            double x = (initial_x + (z-height)*tan(67.0/(180/M_PI))); // 67.5 deg
-
-            cv::Point2d p = worldToCanvas(x, y);
-            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-            }
-        }
-}
 
 void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
 {
@@ -535,7 +328,7 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
     double y = (PlacementPoint.x-canvas_center.x)*-resolution;
     double x = (PlacementPoint.y-canvas_center.y)*-resolution;
 
-    double margin = 0.02;
+    double margin = 0.02; // So the robot does not attempt to place an object in the table
 
     std::cout << "The selected point for placement in (x,y,z) coordinates is:" << std::endl;
     std::cout << "(" << x << ", " << y << ", " << height+margin << ")" << std::endl;
@@ -625,7 +418,7 @@ int main (int argc, char **argv)
         std::cout << "Found plane height " << height << std::endl;
 
 
-        // Filter out objects and put them in seperate cloud
+        // Filter out objects abov the table plane and put them in seperate cloud
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
         pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
         range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
@@ -641,7 +434,7 @@ int main (int argc, char **argv)
         condrem2.filter (*object_cloud);
         pcl::removeNaNFromPointCloud(*object_cloud, *object_cloud, indices);
         
-        // Create pointcloud with occluded space
+        // Create pointcloud with occluded space based on the object cloud
         pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
         occluded_cloud->width=object_cloud->width;
         occluded_cloud->height=object_cloud->height;
@@ -700,6 +493,7 @@ int main (int argc, char **argv)
         // std::cout << "creating costmap" << std::endl;
         cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
         cv::Mat dilated_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+        cv::Mat closed_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
         cv::Mat placement_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
         cv::Scalar table_color(0, 255, 0);
         cv::Scalar occupied_color(0, 0, 255);
@@ -718,48 +512,43 @@ int main (int argc, char **argv)
 
         // Add table plane to costmap
         createCostmap(plane_cloud, canvas, table_color);
+
+        // Fill missing data gaps inside the table sheet cluster
+        CloseCanvas(canvas, closed_canvas, placement_margin);
+
+        // Decrease the size of the table plane to accomodate for the placement radius while taking dilation into account
+        AlterPlane(closed_canvas, closed_canvas, placement_margin);
                 
         // Add objects to costmap
-        createObjectCostmap(object_cloud, canvas, occupied_color);
+        createObjectCostmap(object_cloud, closed_canvas, occupied_color);
 
         // Add occluded space to costmap
-        createOccludedCostmap(occluded_cloud, canvas, occluded_color); 
-
-
-        ///// Replace the commented steps with image processing technniques instead
-
-
-        // // Add not table to costmap 
-        // createNotTableCostmap(notTable_cloud, canvas, occupied_color); 
-
-        // // FOV left
-        // createFOVLCostmap(canvas, occluded_color, transform(0,3), transform(1,3), fx);
-
-        // // FOV right
-        // createFOVRCostmap(canvas, occluded_color, transform(0,3), transform(1,3));
-
-        // // FOV down
-        // createFOVHCostmap(canvas, occluded_color, transform(0,3), transform(1,3), transform(2,3), height);
+        createOccludedCostmap(occluded_cloud, closed_canvas, occluded_color); 
 
         // HERO preferred radius
-        createRadiusCostmap(canvas, radius_color, placement_margin);
+        createRadiusCostmap(closed_canvas, radius_color, placement_margin);
 
         // Dilate the costmap and create a new canvas
-        dilateCostmap(canvas, dilated_canvas, placement_margin);
+        dilateCostmap(closed_canvas, dilated_canvas, placement_margin);
 
         // Extract the placement options and choose a placement solution
         ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
 
-        std::cout << "showing costmap" << std::endl;
+        // Show the different canvasses
+        
+        // std::cout << "showing closed costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
 
-        std::cout << "showing placement costmap" << std::endl;
-        cv::imshow("Placement options costmap topview", placement_canvas);
-
-        std::cout << "showing dilated costmap" << std::endl;
+        // std::cout << "showing costmap" << std::endl;
+        cv::imshow("closed canvas topview", closed_canvas);
+                
+        // std::cout << "showing dilated costmap" << std::endl;
         cv::imshow("Dilated costmap topview", dilated_canvas);
 
-        // show snapshot
+        // std::cout << "showing placement costmap" << std::endl;
+        cv::imshow("Placement options costmap topview", placement_canvas);
+
+        // Show RGB snapshot
         cv::Mat rgbcanvas = image->getRGBImage();
         cv::imshow("RGB", rgbcanvas);
 

From 2c6e4d3d4412826646d02710f6496318e6f11c6a Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 10:28:23 +0200
Subject: [PATCH 070/136] add service PlaceArea

---
 ed_sensor_integration/src/kinect/kinect_plugin.cpp | 7 +++++++
 ed_sensor_integration/src/kinect/kinect_plugin.h   | 4 ++++
 ed_sensor_integration_msgs/CMakeLists.txt          | 1 +
 ed_sensor_integration_msgs/srv/PlaceArea.srv       | 4 ++++
 4 files changed, 16 insertions(+)
 create mode 100644 ed_sensor_integration_msgs/srv/PlaceArea.srv

diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.cpp b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
index e0c15bd5..ec5257ab 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.cpp
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
@@ -61,6 +61,7 @@ void KinectPlugin::initialize(ed::InitData& init)
     srv_get_image_ = nh.advertiseService("kinect/get_image", &KinectPlugin::srvGetImage, this);
     srv_update_ = nh.advertiseService("kinect/update", &KinectPlugin::srvUpdate, this);
     srv_ray_trace_ = nh.advertiseService("ray_trace", &KinectPlugin::srvRayTrace, this);
+    srv_place_area_ = nh.advertiseService("place_area", &KinectPlugin::srvPlaceArea, this);
 
     ray_trace_visualization_publisher_ = nh.advertise<visualization_msgs::Marker>("ray_trace_visualization", 10);
 }
@@ -274,6 +275,12 @@ bool KinectPlugin::srvRayTrace(ed_sensor_integration_msgs::RayTrace::Request& re
     return true;
 }
 
+bool KinectPlugin::srvPlaceArea(ed_sensor_integration_msgs::PlaceArea::Request& req, ed_sensor_integration_msgs::PlaceArea::Response& res)
+{
+    ROS_INFO("Determine place area");
+    return true;
+}
+
 // ----------------------------------------------------------------------------------------------------
 
 ED_REGISTER_PLUGIN(KinectPlugin)
diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.h b/ed_sensor_integration/src/kinect/kinect_plugin.h
index df150eac..3c49e4af 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.h
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.h
@@ -12,6 +12,7 @@
 #include <ed_sensor_integration_msgs/GetImage.h>
 #include <ed_sensor_integration_msgs/Update.h>
 #include <ed_sensor_integration_msgs/RayTrace.h>
+#include <ed_sensor_integration_msgs/PlaceArea.h>
 
 // Visualization
 #include <ros/publisher.h>
@@ -72,6 +73,9 @@ class KinectPlugin : public ed::Plugin
 
     ros::Publisher ray_trace_visualization_publisher_;
 
+    bool srvPlaceArea(ed_sensor_integration_msgs::PlaceArea::Request& req, ed_sensor_integration_msgs::PlaceArea::Response& res);
+
+    ros::ServiceServer srv_place_area_;
 
 
 
diff --git a/ed_sensor_integration_msgs/CMakeLists.txt b/ed_sensor_integration_msgs/CMakeLists.txt
index 47ce1060..269bddb5 100644
--- a/ed_sensor_integration_msgs/CMakeLists.txt
+++ b/ed_sensor_integration_msgs/CMakeLists.txt
@@ -21,6 +21,7 @@ add_service_files(
     GetImage.srv
     Update.srv
     RayTrace.srv
+    PlaceArea.srv
 )
 
 generate_messages(
diff --git a/ed_sensor_integration_msgs/srv/PlaceArea.srv b/ed_sensor_integration_msgs/srv/PlaceArea.srv
new file mode 100644
index 00000000..af1a19b6
--- /dev/null
+++ b/ed_sensor_integration_msgs/srv/PlaceArea.srv
@@ -0,0 +1,4 @@
+# request info
+---
+string error_msg  # empty if no error
+geometry_msgs/PoseStamped[] pose  # pose of a possible place location
\ No newline at end of file

From a448fd635e11752779dfbc85d34fcdba7f51471d Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Sat, 1 Apr 2023 10:39:35 +0200
Subject: [PATCH 071/136] Re-introducing additional PCL data

---
 .../tools/empty_spot_designator.cpp           | 135 +++++++++++++++---
 1 file changed, 118 insertions(+), 17 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 3a63fb79..eb5090ed 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -232,6 +232,76 @@ void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud
     }   
 }
 
+void createNotTableCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud, cv::Mat& canvas, cv::Scalar color)
+
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < notTable_cloud->points.size (); nIndex++)
+    {
+        double x = notTable_cloud->points[nIndex].x;
+        double y = notTable_cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+}
+
+void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, double fx)
+
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
+        {
+        float initial_x = x;
+        float initial_y = y;
+        double y = initial_y + (0.001)*nIndex;
+        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
+
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+        }
+}
+
+void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
+
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
+        {
+        float initial_x = x;
+        float initial_y = y;
+        double y = initial_y - 0.001*nIndex;
+        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+        }
+}
+
+void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height)
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int i = 0; i < 100; i++)
+        {
+            for (int nIndex = 0; nIndex < 4000; nIndex++)
+            {
+            float initial_x = x;
+            float initial_y = y;
+            double y = initial_y + -2+ 0.001*nIndex;
+            double x = (initial_x + (z-height)*tan(67.0/(180/M_PI))); // 67.5 deg
+
+            cv::Point2d p = worldToCanvas(x, y);
+            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+            }
+        }
+}
+
 void CloseCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin)
 {
     float Pixelsize = 5*(placement_margin / resolution);
@@ -513,34 +583,65 @@ int main (int argc, char **argv)
         // Add table plane to costmap
         createCostmap(plane_cloud, canvas, table_color);
 
-        // Fill missing data gaps inside the table sheet cluster
-        CloseCanvas(canvas, closed_canvas, placement_margin);
+        // Adding boundaries with morphological operations
+
+            // // Fill missing data gaps inside the table sheet cluster
+            // CloseCanvas(canvas, closed_canvas, placement_margin);
 
-        // Decrease the size of the table plane to accomodate for the placement radius while taking dilation into account
-        AlterPlane(closed_canvas, closed_canvas, placement_margin);
+            // // Decrease the size of the table plane to accomodate for the placement radius while taking dilation into account
+            // AlterPlane(closed_canvas, closed_canvas, placement_margin);
                 
-        // Add objects to costmap
-        createObjectCostmap(object_cloud, closed_canvas, occupied_color);
+            // // Add objects to costmap
+            // createObjectCostmap(object_cloud, closed_canvas, occupied_color);
+
+            // // Add occluded space to costmap
+            // createOccludedCostmap(occluded_cloud, closed_canvas, occluded_color); 
+
+            // // HERO preferred radius
+            // createRadiusCostmap(closed_canvas, radius_color, placement_margin);
+
+            // // Dilate the costmap and create a new canvas
+            // dilateCostmap(closed_canvas, dilated_canvas, placement_margin);
+
+            // // Extract the placement options and choose a placement solution
+            // ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
+
+        // Adding boundaries with additional PCL data
 
-        // Add occluded space to costmap
-        createOccludedCostmap(occluded_cloud, closed_canvas, occluded_color); 
+            // Add objects to costmap
+            createObjectCostmap(object_cloud, canvas, occupied_color);
 
-        // HERO preferred radius
-        createRadiusCostmap(closed_canvas, radius_color, placement_margin);
+            // Add occluded space to costmap
+            createOccludedCostmap(occluded_cloud, canvas, occluded_color); 
 
-        // Dilate the costmap and create a new canvas
-        dilateCostmap(closed_canvas, dilated_canvas, placement_margin);
+            // Add not_Table to define the table edge                  
+            createNotTableCostmap(notTable_cloud, canvas, occupied_color);             
 
-        // Extract the placement options and choose a placement solution
-        ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
+            // FOV left
+            createFOVLCostmap(canvas, occluded_color, transform(0,3), transform(1,3), fx);
+
+            // FOV right
+            createFOVRCostmap(canvas, occluded_color, transform(0,3), transform(1,3));
+
+            // FOV down
+            createFOVHCostmap(canvas, occluded_color, transform(0,3), transform(1,3), transform(2,3), height);
+
+            // HERO preferred radius
+            createRadiusCostmap(canvas, radius_color, placement_margin);
+
+            // Dilate the costmap and create a new canvas
+            dilateCostmap(canvas, dilated_canvas, placement_margin);
+
+            // Extract the placement options and choose a placement solution
+            ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);            
 
         // Show the different canvasses
         
-        // std::cout << "showing closed costmap" << std::endl;
+        // std::cout << "showing costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
 
-        // std::cout << "showing costmap" << std::endl;
-        cv::imshow("closed canvas topview", closed_canvas);
+        // // std::cout << "showing costmap" << std::endl;
+        // cv::imshow("closed canvas topview", closed_canvas);
                 
         // std::cout << "showing dilated costmap" << std::endl;
         cv::imshow("Dilated costmap topview", dilated_canvas);

From 03ec4b8179532014f68266ebd0c5e6081eac8982 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 10:54:34 +0200
Subject: [PATCH 072/136] add place area class

---
 ed_sensor_integration/CMakeLists.txt          |  2 ++
 .../include/ed/kinect/place_area_finder.h     | 20 +++++++++++++++++++
 .../src/kinect/kinect_plugin.h                |  3 ++-
 .../src/kinect/place_area_finder.cpp          |  6 ++++++
 4 files changed, 30 insertions(+), 1 deletion(-)
 create mode 100644 ed_sensor_integration/include/ed/kinect/place_area_finder.h
 create mode 100644 ed_sensor_integration/src/kinect/place_area_finder.cpp

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index a35f398f..7f9f586c 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -63,6 +63,8 @@ add_library(ed_kinect
     include/ed/kinect/entity_update.h
     src/kinect/renderer.cpp
     include/ed/kinect/renderer.h
+    src/kinect/place_area_finder.cpp
+    include/ed/kinect/place_area_finder.h
 )
 target_link_libraries(ed_kinect ed_association ${catkin_LIBRARIES})
 add_dependencies(ed_kinect ${catkin_EXPORTED_TARGETS})
diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
new file mode 100644
index 00000000..13cfc9f8
--- /dev/null
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -0,0 +1,20 @@
+#ifndef ED_KINECT_PLACE_AREA_FINDER_H_
+#define ED_KINECT_PLACE_AREA_FINDER_H_
+
+class PlaceAreaFinder
+{
+
+public:
+
+    PlaceAreaFinder();
+
+    ~PlaceAreaFinder();
+
+    void find_area();
+
+private:
+
+
+};
+
+#endif
diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.h b/ed_sensor_integration/src/kinect/kinect_plugin.h
index 3c49e4af..79472b44 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.h
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.h
@@ -6,6 +6,7 @@
 
 #include "ed/kinect/image_buffer.h"
 #include "ed/kinect/updater.h"
+#include "ed/kinect/place_area_finder.h"
 
 // Services
 #include <ros/service_server.h>
@@ -45,7 +46,7 @@ class KinectPlugin : public ed::Plugin
 
 
     Updater updater_;
-
+    PlaceAreaFinder place_area_finder_;
 
     // Communication
 
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
new file mode 100644
index 00000000..08a2ba67
--- /dev/null
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -0,0 +1,6 @@
+#include "ed/kinect/place_area_finder.h"
+
+void PlaceAreaFinder::find_area()
+{
+    return;
+}
\ No newline at end of file

From 3ae3ea280980783eacd4446562ea580c731c7f63 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 11:26:41 +0200
Subject: [PATCH 073/136] move implementation to new class

---
 .../include/ed/kinect/place_area_finder.h     |  16 +-
 .../src/kinect/place_area_finder.cpp          | 594 +++++++++++++++++-
 .../tools/empty_spot_designator.cpp           | 564 +----------------
 3 files changed, 616 insertions(+), 558 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index 13cfc9f8..3fac4c52 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -1,6 +1,15 @@
 #ifndef ED_KINECT_PLACE_AREA_FINDER_H_
 #define ED_KINECT_PLACE_AREA_FINDER_H_
 
+
+#include <rgbd/image.h>
+#include <geolib/datatypes.h>
+
+
+#include <opencv2/imgproc/imgproc.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/core/core.hpp>
+
 class PlaceAreaFinder
 {
 
@@ -10,11 +19,12 @@ class PlaceAreaFinder
 
     ~PlaceAreaFinder();
 
-    void find_area();
-
-private:
+    void findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose);
 
+    void getCanvas(cv::Mat& image){ canvas.copyTo(image); }
 
+private:
+    cv::Mat canvas;
 };
 
 #endif
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 08a2ba67..93947513 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -1,6 +1,598 @@
 #include "ed/kinect/place_area_finder.h"
 
-void PlaceAreaFinder::find_area()
+#include <iostream>
+#include <string>
+
+#include "ed/kinect/image_buffer.h"
+
+#include <vector>
+
+#include <ros/ros.h>
+
+//pcl library # TODO remove the unused ones #TODO find out which ones are unused
+#include <pcl/point_cloud.h>
+#include <pcl/point_representation.h>
+#include <pcl/common/common.h>
+#include <pcl/io/pcd_io.h>
+
+#include <pcl/filters/filter.h>
+#include <pcl/filters/extract_indices.h>
+#include <pcl/filters/conditional_removal.h>
+
+#include <pcl/features/normal_3d.h>
+
+#include <pcl/registration/icp.h>
+#include <pcl/registration/icp_nl.h>
+#include <pcl/registration/transforms.h>
+
+#include <pcl/sample_consensus/method_types.h>
+#include <pcl/sample_consensus/model_types.h>
+#include <pcl/sample_consensus/sac_model_parallel_plane.h>
+
+#include <pcl/segmentation/extract_clusters.h>
+#include <pcl/segmentation/sac_segmentation.h>
+#include <pcl/point_types.h>
+#include <pcl/io/pcd_io.h>
+
+#include <pcl/surface/convex_hull.h>
+
+#include "ed_sensor_integration/sac_model_horizontal_plane.h"
+
+
+double resolution = 0.005;
+cv::Point2d canvas_center;
+
+double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL)
+{
+    // Fill in the cloud data
+    cloud->width = image.getDepthImage().cols;
+    cloud->height = image.getDepthImage().rows;
+    cloud->is_dense = false;
+    cloud->resize (cloud->width * cloud->height);
+
+    FOVL->width = cloud->width;
+    FOVL->height = image.getDepthImage().rows;
+    FOVL->is_dense = false;
+    FOVL->resize (FOVL->width * FOVL->height);
+
+    double fx = image.getCameraModel().fx();
+    double fy = image.getCameraModel().fy();
+
+    double half_height = 0.5 * cloud->height;
+    double half_width = 0.5 * cloud->width;
+
+    for (uint i=0; i < cloud->height; ++i)
+    {
+        for (uint j=0; j < cloud->width; ++j)
+        {
+
+            cv::Vec3b bgr = image.getRGBImage().at<cv::Vec3b>(i,j);
+            double d = image.getDepthImage().at<float>(i,j);
+
+            cloud->at(j,i).x = (-half_width+j) * d / fx;
+            cloud->at(j,i).y = (-half_height+i) * d / fy;
+            cloud->at(j,i).z = d;
+            cloud->at(j,i).r = bgr[2];
+            cloud->at(j,i).g = bgr[1];
+            cloud->at(j,i).b = bgr[0];
+
+        }
+    }
+
+return image.getCameraModel().fx();
+}
+
+Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
+{
+    // convert from geolib coordinates to ros coordinates #TODO remove geolib coordinates for camera pose
+    pose.R = pose.R * geo::Mat3(1, 0, 0, 0, -1, 0, 0, 0, -1);
+
+    float x = pose.t.x;
+    float y = pose.t.y;
+    float z = pose.t.z;
+    float xx = pose.R.xx;
+    float xy = pose.R.xy;
+    float xz = pose.R.xz;
+    float yx = pose.R.yx;
+    float yy = pose.R.yy;
+    float yz = pose.R.yz;
+    float zx = pose.R.zx;
+    float zy = pose.R.zy;
+    float zz = pose.R.zz;
+
+    Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();
+
+    Transform(0,0) = xx;
+    Transform(0,1) = xy;
+    Transform(0,2) = xz;
+    Transform(0,3) = x;
+    Transform(1,0) = yx;
+    Transform(1,1) = yy;
+    Transform(1,2) = yz;
+    Transform(1,3) = y;
+    Transform(2,0) = zx;
+    Transform(2,1) = zy;
+    Transform(2,2) = zz;
+    Transform(2,3) = z;
+
+    // std::cout << Transform << std::endl;
+    return Transform;
+}
+
+/**
+ * @brief SegmentPlane segment the pointcloud and return the cluster closest to the camera
+ * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
+ * @return height of the segmented plane
+ */
+float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in2, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_no_plane)
+{
+    pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
+    pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
+    // Create the segmentation object
+    pcl::SACSegmentation<pcl::PointXYZRGB> seg;
+    // Optional
+    seg.setOptimizeCoefficients (true);
+    // Mandatory
+    seg.setModelType (pcl::SACMODEL_PARALLEL_PLANE);
+    seg.setMethodType (pcl::SAC_RANSAC);
+    seg.setMaxIterations (1000);
+    seg.setDistanceThreshold (0.01);
+    seg.setAxis (Eigen::Vector3f(1,0,0));
+    seg.setEpsAngle(5*0.0174532925); //*0.0174532925 to radians
+
+    // Create the filtering object
+    pcl::ExtractIndices<pcl::PointXYZRGB> extract;
+    pcl::ExtractIndices<pcl::PointXYZRGB> extract2;
+    int i = 0, nr_points = (int) cloud_in->size ();
+
+    // Segment the largest planar component from the remaining cloud
+    seg.setInputCloud(cloud_in);
+    seg.segment(*inliers, *coefficients);
+
+    if (inliers->indices.size() == 0) {
+        std::cerr << "Could not estimate a planar model for the given dataset." << std::endl;
+        return -1.0;
+    }
+
+    // Extract the inliers to a cloud with a plane
+    extract.setInputCloud(cloud_in);
+    extract.setIndices(inliers);
+    extract.setNegative(false);
+    extract.filter(*cloud_out);
+
+    
+    // std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
+    //   << "Plane with coefficients: " << *coefficients << std::endl;
+
+    // Extract outliers to the main cloud without the table plane
+    extract2.setInputCloud(cloud_in2);
+    extract2.setIndices(inliers);
+    extract2.setNegative(true);
+    extract2.filter(*cloud_no_plane);
+
+    return abs(coefficients->values[3]);
+}
+
+
+cv::Point2d worldToCanvas(double x, double y)
+{
+    return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
+}
+ 
+void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Mat& canvas, cv::Scalar color)
+
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < cloud->points.size (); nIndex++)
+    {
+        double x = cloud->points[nIndex].x;
+        double y = cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+
+    
+}
+
+void createObjectCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, cv::Mat& canvas, cv::Scalar color)
+
 {
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < object_cloud->points.size (); nIndex++)
+    {
+        double x = object_cloud->points[nIndex].x;
+        double y = object_cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+
+}
+
+void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud, cv::Mat& canvas, cv::Scalar color)
+
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < occluded_cloud->points.size (); nIndex++)
+    {
+        double x = occluded_cloud->points[nIndex].x;
+        double y = occluded_cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }   
+}
+
+void createNotTableCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud, cv::Mat& canvas, cv::Scalar color)
+
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < notTable_cloud->points.size (); nIndex++)
+    {
+        double x = notTable_cloud->points[nIndex].x;
+        double y = notTable_cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+}
+
+void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, double fx)
+
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
+        {
+        float initial_x = x;
+        float initial_y = y;
+        double y = initial_y + (0.001)*nIndex;
+        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
+
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+        }
+}
+
+void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
+
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
+        {
+        float initial_x = x;
+        float initial_y = y;
+        double y = initial_y - 0.001*nIndex;
+        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+        }
+}
+
+void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height)
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int i = 0; i < 100; i++)
+        {
+            for (int nIndex = 0; nIndex < 4000; nIndex++)
+            {
+            float initial_x = x;
+            float initial_y = y;
+            double y = initial_y + -2+ 0.001*nIndex;
+            double x = (initial_x + (z-height)*tan(67.0/(180/M_PI))); // 67.5 deg
+
+            cv::Point2d p = worldToCanvas(x, y);
+            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+            }
+        }
+}
+
+void CloseCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin)
+{
+    float Pixelsize = 5*(placement_margin / resolution);
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::dilate(canvas, closed_canvas, element );
+    cv::erode(closed_canvas, closed_canvas, element);
+}
+
+
+void AlterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin)
+{
+    float Pixelsize = 2*(placement_margin / resolution);
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::erode(closed_canvas, smallplane_canvas, element);
+}
+
+
+
+
+void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        float upper_radius = 0.75 + placement_margin/2;
+        float lower_radius = 0.60 - placement_margin/2;
+            for (float phi = 0; phi < 360; phi++)
+            {
+                for (int i = 0; i < 100; i++)
+                {
+                double y = upper_radius * sin(phi/(180/M_PI)) + 0.03 * i * sin(phi/(180/M_PI));
+                double x = upper_radius * cos(phi/(180/M_PI)) + 0.03 * i * cos(phi/(180/M_PI));
+
+                cv::Point2d p = worldToCanvas(x, y);
+                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+                }
+
+                for (int i = 0; i < 100; i++)
+                {
+                double y = lower_radius * sin(phi/(180/M_PI)) - lower_radius/100 * i * sin(phi/(180/M_PI));
+                double x = lower_radius * cos(phi/(180/M_PI)) - lower_radius/100 * i * cos(phi/(180/M_PI));
+
+                cv::Point2d p = worldToCanvas(x, y);
+                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+                }
+            }
+        
+}
+
+void dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin)
+{
+    float Pixelsize = placement_margin / resolution;
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::dilate(canvas, dilated_canvas, element );
+
+}
+
+void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor, cv::Scalar point_color, double height)
+{
+
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    std::vector<cv::Point> identicalPoints;
+    cv::Point2d PlacementPoint;
+    bool found = false;
+
+    for(int row = canvas.rows; row > 0; --row)
+    {
+        for(int col = canvas.cols; col > 0; --col)
+        {
+            cv::Vec3b currPixel = canvas.at<cv::Vec3b>(row, col);
+            if(currPixel.val[0] == targetColor.val[0] &&
+               currPixel.val[1] == targetColor.val[1] &&
+               currPixel.val[2] == targetColor.val[2])
+            {
+                cv::Point2d p = cv::Point(col, row);
+                PlacementPoint = p;
+                found = true;
+                if (p.x >= 0 && p.y >= 0 && p.x < placement_canvas.cols && p.y < placement_canvas.rows)
+                    placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(targetColor[0], targetColor[1], targetColor[2]);
+            }
+        }
+    }
+
+    if (!found)
+        return;
+
+    double y = (PlacementPoint.x-canvas_center.x)*-resolution;
+    double x = (PlacementPoint.y-canvas_center.y)*-resolution;
+
+    double margin = 0.02; // So the robot does not attempt to place an object in the table
+
+    std::cout << "The selected point for placement in (x,y,z) coordinates is:" << std::endl;
+    std::cout << "(" << x << ", " << y << ", " << height+margin << ")" << std::endl;
+    std::cout << "Which is " << sqrt(pow(x,2)+pow(y,2)) << " cm away from HERO" << std::endl;
+    placement_canvas.at<cv::Vec3b>(PlacementPoint) = cv::Vec3b(point_color[0], point_color[1], point_color[2]); 
+
+}
+
+PlaceAreaFinder::PlaceAreaFinder()
+{
+}
+
+PlaceAreaFinder::~PlaceAreaFinder()
+{
+}
+
+void PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose)
+{
+    // std::cout << "converting image to cloud" << std::endl;
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL(new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVR(new pcl::PointCloud<pcl::PointXYZRGB>);
+    double fx = imageToCloud(*image, cloud, FOVL);
+
+    // transform to base link frame
+    Eigen::Matrix4f transform = geolibToEigen(sensor_pose);
+    pcl::transformPointCloud(*cloud, *cloud, transform);
+
+    // keep track of the indices in the original image
+    std::vector<int> indices;
+
+    // Filter out floor
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr floorless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+
+    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond(new pcl::ConditionAnd<pcl::PointXYZRGB>());
+    range_cond->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::GT, 0.1)));
+    // build the filter
+    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+    condrem.setCondition(range_cond);
+    condrem.setInputCloud(cloud);
+    condrem.setKeepOrganized(true);
+    // apply filter
+    condrem.filter(*floorless_cloud);
+    (*floorless_cloud).is_dense = false;
+    pcl::removeNaNFromPointCloud(*floorless_cloud, *floorless_cloud, indices);
+
+    std::cout << "SegmentPlane" << std::endl;
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr plane_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr planeless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+
+    // Segment the table plane and return a cloud with the plane and a cloud where the plane is removed
+    float height = SegmentPlane(floorless_cloud, floorless_cloud, plane_cloud, planeless_cloud);
+    std::cout << "Found plane height " << height << std::endl;
+
+    // Filter out objects abov the table plane and put them in seperate cloud
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2(new pcl::ConditionAnd<pcl::PointXYZRGB>());
+    range_cond2->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::GT, height)));
+    range_cond2->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::LT, height + 0.30)));
+    // build the filter
+    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem2;
+    condrem2.setCondition(range_cond2);
+    condrem2.setInputCloud(planeless_cloud);
+    condrem2.setKeepOrganized(true);
+    // apply filter
+    condrem2.filter(*object_cloud);
+    pcl::removeNaNFromPointCloud(*object_cloud, *object_cloud, indices);
+
+    // Create pointcloud with occluded space based on the object cloud
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    occluded_cloud->width = object_cloud->width;
+    occluded_cloud->height = object_cloud->height;
+    occluded_cloud->is_dense = false;
+    occluded_cloud->points.resize(occluded_cloud->width * occluded_cloud->height);
+    float x = transform(0, 3);
+    float y = transform(1, 3);
+    float z = transform(2, 3);
+    for (int nIndex = 0; nIndex < object_cloud->points.size(); nIndex++)
+    {
+        auto lower = object_cloud->points[nIndex].z - z;
+        auto upper = height - object_cloud->points[nIndex].z;
+        auto lambda = upper / lower;
+        auto dx = object_cloud->points[nIndex].x - x;
+        auto dy = object_cloud->points[nIndex].y - y;
+
+        occluded_cloud->points[nIndex].z = height;
+        occluded_cloud->points[nIndex].x = object_cloud->points[nIndex].x + lambda * dx;
+        occluded_cloud->points[nIndex].y = object_cloud->points[nIndex].y + lambda * dy;
+    }
+
+    // Filter out items below table to create not table cloud
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr backup_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond3(new pcl::ConditionAnd<pcl::PointXYZRGB>());
+    range_cond3->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::LT, height - 0.02)));
+    // build the filter
+    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem3;
+    condrem3.setCondition(range_cond3);
+    condrem3.setInputCloud(floorless_cloud);
+    condrem3.setKeepOrganized(true);
+    // apply filter
+    condrem3.filter(*backup_cloud);
+    (*backup_cloud).is_dense = false;
+    pcl::removeNaNFromPointCloud(*backup_cloud, *backup_cloud, indices);
+
+    // Not table cloud
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    notTable_cloud->width = backup_cloud->width;
+    notTable_cloud->height = backup_cloud->height;
+    notTable_cloud->is_dense = false;
+    notTable_cloud->points.resize(notTable_cloud->width * notTable_cloud->height);
+    for (int nIndex = 0; nIndex < backup_cloud->points.size(); nIndex++)
+    {
+        auto lower = z - backup_cloud->points[nIndex].z;
+        auto upper = height - backup_cloud->points[nIndex].z;
+        auto lambda = upper / lower;
+        auto dx = x - backup_cloud->points[nIndex].x;
+        auto dy = y - backup_cloud->points[nIndex].y;
+        notTable_cloud->points[nIndex].z = height;
+        notTable_cloud->points[nIndex].x = backup_cloud->points[nIndex].x + lambda * dx;
+        notTable_cloud->points[nIndex].y = backup_cloud->points[nIndex].y + lambda * dy;
+    }
+
+    // std::cout << "creating costmap" << std::endl;
+    canvas = cv::Mat(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+    cv::Mat dilated_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+    cv::Mat closed_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+    cv::Mat placement_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+    cv::Scalar table_color(0, 255, 0);
+    cv::Scalar occupied_color(0, 0, 255);
+    cv::Scalar occluded_color(255, 0, 0);
+    cv::Scalar radius_color(100, 0, 100);
+    cv::Scalar placement_color(100, 255, 100);
+    cv::Scalar point_color(255, 0, 0);
+
+    // Object placement margins
+    float object_diameter = 0.10;
+    float error_margin = 0.02;
+    float length = object_diameter + error_margin;
+    float placement_margin = 2 * 0.02 + length;
+
+    std::cout << "creating costmap" << std::endl;
+
+    // Add table plane to costmap
+    createCostmap(plane_cloud, canvas, table_color);
+
+    // Adding boundaries with morphological operations
+
+    // // Fill missing data gaps inside the table sheet cluster
+    // CloseCanvas(canvas, closed_canvas, placement_margin);
+
+    // // Decrease the size of the table plane to accomodate for the placement radius while taking dilation into account
+    // AlterPlane(closed_canvas, closed_canvas, placement_margin);
+
+    // // Add objects to costmap
+    // createObjectCostmap(object_cloud, closed_canvas, occupied_color);
+
+    // // Add occluded space to costmap
+    // createOccludedCostmap(occluded_cloud, closed_canvas, occluded_color);
+
+    // // HERO preferred radius
+    // createRadiusCostmap(closed_canvas, radius_color, placement_margin);
+
+    // // Dilate the costmap and create a new canvas
+    // dilateCostmap(closed_canvas, dilated_canvas, placement_margin);
+
+    // // Extract the placement options and choose a placement solution
+    // ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
+
+    // Adding boundaries with additional PCL data
+
+    // Add objects to costmap
+    createObjectCostmap(object_cloud, canvas, occupied_color);
+
+    // Add occluded space to costmap
+    createOccludedCostmap(occluded_cloud, canvas, occluded_color);
+
+    // Add not_Table to define the table edge
+    createNotTableCostmap(notTable_cloud, canvas, occupied_color);
+
+    // FOV left
+    createFOVLCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3), fx);
+
+    // FOV right
+    createFOVRCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3));
+
+    // FOV down
+    createFOVHCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3), transform(2, 3), height);
+
+    // HERO preferred radius
+    createRadiusCostmap(canvas, radius_color, placement_margin);
+
+    // Dilate the costmap and create a new canvas
+    dilateCostmap(canvas, dilated_canvas, placement_margin);
+
+    // Extract the placement options and choose a placement solution
+    ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
+
     return;
 }
\ No newline at end of file
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index eb5090ed..7c031726 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -40,373 +40,12 @@
 
 #include "ed_sensor_integration/sac_model_horizontal_plane.h"
 
+#include <ed/kinect/place_area_finder.h>
+
 
 double resolution = 0.005;
 cv::Point2d canvas_center;
 
-double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL)
-{
-    // Fill in the cloud data
-    cloud->width = image.getDepthImage().cols;
-    cloud->height = image.getDepthImage().rows;
-    cloud->is_dense = false;
-    cloud->resize (cloud->width * cloud->height);
-
-    FOVL->width = cloud->width;
-    FOVL->height = image.getDepthImage().rows;
-    FOVL->is_dense = false;
-    FOVL->resize (FOVL->width * FOVL->height);
-
-    double fx = image.getCameraModel().fx();
-    double fy = image.getCameraModel().fy();
-
-    double half_height = 0.5 * cloud->height;
-    double half_width = 0.5 * cloud->width;
-
-    for (uint i=0; i < cloud->height; ++i)
-    {
-        for (uint j=0; j < cloud->width; ++j)
-        {
-
-            cv::Vec3b bgr = image.getRGBImage().at<cv::Vec3b>(i,j);
-            double d = image.getDepthImage().at<float>(i,j);
-
-            cloud->at(j,i).x = (-half_width+j) * d / fx;
-            cloud->at(j,i).y = (-half_height+i) * d / fy;
-            cloud->at(j,i).z = d;
-            cloud->at(j,i).r = bgr[2];
-            cloud->at(j,i).g = bgr[1];
-            cloud->at(j,i).b = bgr[0];
-
-        }
-    }
-
-return image.getCameraModel().fx();
-}
-
-Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
-{
-    // convert from geolib coordinates to ros coordinates #TODO remove geolib coordinates for camera pose
-    pose.R = pose.R * geo::Mat3(1, 0, 0, 0, -1, 0, 0, 0, -1);
-
-    float x = pose.t.x;
-    float y = pose.t.y;
-    float z = pose.t.z;
-    float xx = pose.R.xx;
-    float xy = pose.R.xy;
-    float xz = pose.R.xz;
-    float yx = pose.R.yx;
-    float yy = pose.R.yy;
-    float yz = pose.R.yz;
-    float zx = pose.R.zx;
-    float zy = pose.R.zy;
-    float zz = pose.R.zz;
-
-    Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();
-
-    Transform(0,0) = xx;
-    Transform(0,1) = xy;
-    Transform(0,2) = xz;
-    Transform(0,3) = x;
-    Transform(1,0) = yx;
-    Transform(1,1) = yy;
-    Transform(1,2) = yz;
-    Transform(1,3) = y;
-    Transform(2,0) = zx;
-    Transform(2,1) = zy;
-    Transform(2,2) = zz;
-    Transform(2,3) = z;
-
-    // std::cout << Transform << std::endl;
-    return Transform;
-}
-
-/**
- * @brief SegmentPlane segment the pointcloud and return the cluster closest to the camera
- * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
- * @return height of the segmented plane
- */
-float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in2, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_no_plane)
-{
-    pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
-    pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
-    // Create the segmentation object
-    pcl::SACSegmentation<pcl::PointXYZRGB> seg;
-    // Optional
-    seg.setOptimizeCoefficients (true);
-    // Mandatory
-    seg.setModelType (pcl::SACMODEL_PARALLEL_PLANE);
-    seg.setMethodType (pcl::SAC_RANSAC);
-    seg.setMaxIterations (1000);
-    seg.setDistanceThreshold (0.01);
-    seg.setAxis (Eigen::Vector3f(1,0,0));
-    seg.setEpsAngle(5*0.0174532925); //*0.0174532925 to radians
-
-    // Create the filtering object
-    pcl::ExtractIndices<pcl::PointXYZRGB> extract;
-    pcl::ExtractIndices<pcl::PointXYZRGB> extract2;
-    int i = 0, nr_points = (int) cloud_in->size ();
-
-    // Segment the largest planar component from the remaining cloud
-    seg.setInputCloud(cloud_in);
-    seg.segment(*inliers, *coefficients);
-
-    if (inliers->indices.size() == 0) {
-        std::cerr << "Could not estimate a planar model for the given dataset." << std::endl;
-        return -1.0;
-    }
-
-    // Extract the inliers to a cloud with a plane
-    extract.setInputCloud(cloud_in);
-    extract.setIndices(inliers);
-    extract.setNegative(false);
-    extract.filter(*cloud_out);
-
-    
-    // std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
-    //   << "Plane with coefficients: " << *coefficients << std::endl;
-
-    // Extract outliers to the main cloud without the table plane
-    extract2.setInputCloud(cloud_in2);
-    extract2.setIndices(inliers);
-    extract2.setNegative(true);
-    extract2.filter(*cloud_no_plane);
-
-    return abs(coefficients->values[3]);
-}
-
-
-cv::Point2d worldToCanvas(double x, double y)
-{
-    return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
-}
- 
-void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < cloud->points.size (); nIndex++)
-    {
-        double x = cloud->points[nIndex].x;
-        double y = cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
-
-    
-}
-
-void createObjectCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < object_cloud->points.size (); nIndex++)
-    {
-        double x = object_cloud->points[nIndex].x;
-        double y = object_cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
-
-}
-
-void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < occluded_cloud->points.size (); nIndex++)
-    {
-        double x = occluded_cloud->points[nIndex].x;
-        double y = occluded_cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }   
-}
-
-void createNotTableCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < notTable_cloud->points.size (); nIndex++)
-    {
-        double x = notTable_cloud->points[nIndex].x;
-        double y = notTable_cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
-}
-
-void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, double fx)
-
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
-        {
-        float initial_x = x;
-        float initial_y = y;
-        double y = initial_y + (0.001)*nIndex;
-        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
-
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-        }
-}
-
-void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
-
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
-        {
-        float initial_x = x;
-        float initial_y = y;
-        double y = initial_y - 0.001*nIndex;
-        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-        }
-}
-
-void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height)
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int i = 0; i < 100; i++)
-        {
-            for (int nIndex = 0; nIndex < 4000; nIndex++)
-            {
-            float initial_x = x;
-            float initial_y = y;
-            double y = initial_y + -2+ 0.001*nIndex;
-            double x = (initial_x + (z-height)*tan(67.0/(180/M_PI))); // 67.5 deg
-
-            cv::Point2d p = worldToCanvas(x, y);
-            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-            }
-        }
-}
-
-void CloseCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin)
-{
-    float Pixelsize = 5*(placement_margin / resolution);
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::dilate(canvas, closed_canvas, element );
-    cv::erode(closed_canvas, closed_canvas, element);
-}
-
-
-void AlterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin)
-{
-    float Pixelsize = 2*(placement_margin / resolution);
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::erode(closed_canvas, smallplane_canvas, element);
-}
-
-
-
-
-void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        float upper_radius = 0.75 + placement_margin/2;
-        float lower_radius = 0.60 - placement_margin/2;
-            for (float phi = 0; phi < 360; phi++)
-            {
-                for (int i = 0; i < 100; i++)
-                {
-                double y = upper_radius * sin(phi/(180/M_PI)) + 0.03 * i * sin(phi/(180/M_PI));
-                double x = upper_radius * cos(phi/(180/M_PI)) + 0.03 * i * cos(phi/(180/M_PI));
-
-                cv::Point2d p = worldToCanvas(x, y);
-                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-                }
-
-                for (int i = 0; i < 100; i++)
-                {
-                double y = lower_radius * sin(phi/(180/M_PI)) - lower_radius/100 * i * sin(phi/(180/M_PI));
-                double x = lower_radius * cos(phi/(180/M_PI)) - lower_radius/100 * i * cos(phi/(180/M_PI));
-
-                cv::Point2d p = worldToCanvas(x, y);
-                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-                }
-            }
-        
-}
-
-void dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin)
-{
-    float Pixelsize = placement_margin / resolution;
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::dilate(canvas, dilated_canvas, element );
-
-}
-
-void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor, cv::Scalar point_color, double height)
-{
-
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    std::vector<cv::Point> identicalPoints;
-    cv::Point2d PlacementPoint;
-    bool found = false;
-
-    for(int row = canvas.rows; row > 0; --row)
-    {
-        for(int col = canvas.cols; col > 0; --col)
-        {
-            cv::Vec3b currPixel = canvas.at<cv::Vec3b>(row, col);
-            if(currPixel.val[0] == targetColor.val[0] &&
-               currPixel.val[1] == targetColor.val[1] &&
-               currPixel.val[2] == targetColor.val[2])
-            {
-                cv::Point2d p = cv::Point(col, row);
-                PlacementPoint = p;
-                found = true;
-                if (p.x >= 0 && p.y >= 0 && p.x < placement_canvas.cols && p.y < placement_canvas.rows)
-                    placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(targetColor[0], targetColor[1], targetColor[2]);
-            }
-        }
-    }
-
-    if (!found)
-        return;
-
-    double y = (PlacementPoint.x-canvas_center.x)*-resolution;
-    double x = (PlacementPoint.y-canvas_center.y)*-resolution;
-
-    double margin = 0.02; // So the robot does not attempt to place an object in the table
-
-    std::cout << "The selected point for placement in (x,y,z) coordinates is:" << std::endl;
-    std::cout << "(" << x << ", " << y << ", " << height+margin << ")" << std::endl;
-    std::cout << "Which is " << sqrt(pow(x,2)+pow(y,2)) << " cm away from HERO" << std::endl;
-    placement_canvas.at<cv::Vec3b>(PlacementPoint) = cv::Vec3b(point_color[0], point_color[1], point_color[2]); 
-
-}
-
 /**
  * @brief usage, print how the executable should be used and explain the input
  */
@@ -440,6 +79,8 @@ int main (int argc, char **argv)
 
     pcl::PCDWriter writer;
 
+    PlaceAreaFinder place_area_finder;
+
     while(ros::ok())
     {
         rgbd::ImageConstPtr image;
@@ -450,191 +91,11 @@ int main (int argc, char **argv)
             std::cerr << "No image received, will try again." << std::endl;
             continue;
         }
-        // std::cout << "converting image to cloud" << std::endl;
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL (new pcl::PointCloud<pcl::PointXYZRGB>);
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVR (new pcl::PointCloud<pcl::PointXYZRGB>);
-        double fx = imageToCloud(*image, cloud, FOVL);
-
-        // transform to base link frame
-        Eigen::Matrix4f transform = geolibToEigen(sensor_pose);
-        pcl::transformPointCloud(*cloud, *cloud, transform);
-
-        // keep track of the indices in the original image
-        std::vector<int> indices;
-
-
-        // Filter out floor
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr floorless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-
-        pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-        range_cond->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, 0.1)));
-        // build the filter
-        pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
-        condrem.setCondition (range_cond);
-        condrem.setInputCloud (cloud);
-        condrem.setKeepOrganized(true);
-        // apply filter
-        condrem.filter (*floorless_cloud);
-        (*floorless_cloud).is_dense = false;
-        pcl::removeNaNFromPointCloud(*floorless_cloud, *floorless_cloud, indices);
-
-        std::cout << "SegmentPlane" << std::endl;
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr plane_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr planeless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-
-        // Segment the table plane and return a cloud with the plane and a cloud where the plane is removed
-        float height = SegmentPlane(floorless_cloud, floorless_cloud, plane_cloud, planeless_cloud);
-        std::cout << "Found plane height " << height << std::endl;
-
-
-        // Filter out objects abov the table plane and put them in seperate cloud
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-        pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-        range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::GT, height)));
-        range_cond2->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new 
-        pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height+0.30)));
-        // build the filter
-        pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem2;
-        condrem2.setCondition (range_cond2);
-        condrem2.setInputCloud (planeless_cloud);
-        condrem2.setKeepOrganized(true);
-        // apply filter
-        condrem2.filter (*object_cloud);
-        pcl::removeNaNFromPointCloud(*object_cloud, *object_cloud, indices);
-        
-        // Create pointcloud with occluded space based on the object cloud
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
-        occluded_cloud->width=object_cloud->width;
-        occluded_cloud->height=object_cloud->height;
-        occluded_cloud->is_dense = false;
-        occluded_cloud->points.resize(occluded_cloud->width*occluded_cloud->height);
-        float x = transform(0,3);
-        float y = transform(1,3);
-        float z = transform(2,3);
-        for (int nIndex = 0; nIndex < object_cloud->points.size (); nIndex++)
-        {
-        auto lower = object_cloud->points[nIndex].z - z;
-        auto upper = height - object_cloud->points[nIndex].z;
-        auto lambda = upper / lower;
-        auto dx = object_cloud->points[nIndex].x - x;
-        auto dy = object_cloud->points[nIndex].y- y;
-
-        
-        occluded_cloud->points[nIndex].z =  height;
-        occluded_cloud->points[nIndex].x = object_cloud->points[nIndex].x + lambda * dx;
-        occluded_cloud->points[nIndex].y = object_cloud->points[nIndex].y + lambda * dy;
-        }
-
-        // Filter out items below table to create not table cloud
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr backup_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
-        pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond3 (new pcl::ConditionAnd<pcl::PointXYZRGB> ());
-        range_cond3->addComparison (pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr (new pcl::FieldComparison<pcl::PointXYZRGB> ("z", pcl::ComparisonOps::LT, height-0.02)));
-        // build the filter
-        pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem3;
-        condrem3.setCondition (range_cond3);
-        condrem3.setInputCloud (floorless_cloud);
-        condrem3.setKeepOrganized(true);
-        // apply filter
-        condrem3.filter (*backup_cloud);
-        (*backup_cloud).is_dense = false;
-        pcl::removeNaNFromPointCloud(*backup_cloud, *backup_cloud, indices);
-
-        // Not table cloud
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
-        notTable_cloud->width       = backup_cloud->width;
-        notTable_cloud->height      = backup_cloud->height;
-        notTable_cloud->is_dense    = false;
-        notTable_cloud->points.resize(notTable_cloud->width*notTable_cloud->height);
-        for (int nIndex = 0; nIndex < backup_cloud->points.size (); nIndex++)
-        {
-        auto lower  = z - backup_cloud->points[nIndex].z;
-        auto upper  = height - backup_cloud->points[nIndex].z;
-        auto lambda = upper / lower;
-        auto dx     = x - backup_cloud->points[nIndex].x;
-        auto dy     = y - backup_cloud->points[nIndex].y;       
-        notTable_cloud->points[nIndex].z = height;
-        notTable_cloud->points[nIndex].x = backup_cloud->points[nIndex].x + lambda * dx;
-        notTable_cloud->points[nIndex].y = backup_cloud->points[nIndex].y + lambda * dy;
-        }
-
-        
-        // std::cout << "creating costmap" << std::endl;
-        cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-        cv::Mat dilated_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-        cv::Mat closed_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-        cv::Mat placement_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-        cv::Scalar table_color(0, 255, 0);
-        cv::Scalar occupied_color(0, 0, 255);
-        cv::Scalar occluded_color(255,0,0);
-        cv::Scalar radius_color(100,0,100);
-        cv::Scalar placement_color(100, 255, 100);
-        cv::Scalar point_color(255,0,0);
-
-        // Object placement margins
-        float object_diameter = 0.10;
-        float error_margin = 0.02;
-        float length = object_diameter + error_margin; 
-        float placement_margin = 2*0.02 + length;
         
-        std::cout << "creating costmap" << std::endl;
-
-        // Add table plane to costmap
-        createCostmap(plane_cloud, canvas, table_color);
-
-        // Adding boundaries with morphological operations
-
-            // // Fill missing data gaps inside the table sheet cluster
-            // CloseCanvas(canvas, closed_canvas, placement_margin);
-
-            // // Decrease the size of the table plane to accomodate for the placement radius while taking dilation into account
-            // AlterPlane(closed_canvas, closed_canvas, placement_margin);
-                
-            // // Add objects to costmap
-            // createObjectCostmap(object_cloud, closed_canvas, occupied_color);
-
-            // // Add occluded space to costmap
-            // createOccludedCostmap(occluded_cloud, closed_canvas, occluded_color); 
-
-            // // HERO preferred radius
-            // createRadiusCostmap(closed_canvas, radius_color, placement_margin);
-
-            // // Dilate the costmap and create a new canvas
-            // dilateCostmap(closed_canvas, dilated_canvas, placement_margin);
-
-            // // Extract the placement options and choose a placement solution
-            // ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
-
-        // Adding boundaries with additional PCL data
-
-            // Add objects to costmap
-            createObjectCostmap(object_cloud, canvas, occupied_color);
-
-            // Add occluded space to costmap
-            createOccludedCostmap(occluded_cloud, canvas, occluded_color); 
-
-            // Add not_Table to define the table edge                  
-            createNotTableCostmap(notTable_cloud, canvas, occupied_color);             
-
-            // FOV left
-            createFOVLCostmap(canvas, occluded_color, transform(0,3), transform(1,3), fx);
-
-            // FOV right
-            createFOVRCostmap(canvas, occluded_color, transform(0,3), transform(1,3));
-
-            // FOV down
-            createFOVHCostmap(canvas, occluded_color, transform(0,3), transform(1,3), transform(2,3), height);
-
-            // HERO preferred radius
-            createRadiusCostmap(canvas, radius_color, placement_margin);
-
-            // Dilate the costmap and create a new canvas
-            dilateCostmap(canvas, dilated_canvas, placement_margin);
-
-            // Extract the placement options and choose a placement solution
-            ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);            
+        place_area_finder.findArea(image, sensor_pose);
 
+        cv::Mat canvas;
+        place_area_finder.getCanvas(canvas);
         // Show the different canvasses
         
         // std::cout << "showing costmap" << std::endl;
@@ -644,10 +105,10 @@ int main (int argc, char **argv)
         // cv::imshow("closed canvas topview", closed_canvas);
                 
         // std::cout << "showing dilated costmap" << std::endl;
-        cv::imshow("Dilated costmap topview", dilated_canvas);
+        //cv::imshow("Dilated costmap topview", dilated_canvas);
 
         // std::cout << "showing placement costmap" << std::endl;
-        cv::imshow("Placement options costmap topview", placement_canvas);
+        //cv::imshow("Placement options costmap topview", placement_canvas);
 
         // Show RGB snapshot
         cv::Mat rgbcanvas = image->getRGBImage();
@@ -655,12 +116,7 @@ int main (int argc, char **argv)
 
         char key = cv::waitKey(30);
 
-        if (key == 32)
-        {
-            writer.write<pcl::PointXYZRGB> ("segmented_cloud.pcd", *cloud, false);
-            std::cout << "wrote current cloud to 'segmented_cloud.pcd'." << std::endl;
-        }
-        else if (key == 'q')
+        if (key == 'q')
         {
             break;
         }

From d88b1f032f4877b616bea6fb7f99d77aeb1161d9 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 13:08:06 +0200
Subject: [PATCH 074/136] remove global variable

---
 .../include/ed/kinect/place_area_finder.h     |  13 +
 .../src/kinect/place_area_finder.cpp          | 258 +++++++-----------
 2 files changed, 116 insertions(+), 155 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index 3fac4c52..d378cc76 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -10,6 +10,9 @@
 #include <opencv2/highgui.hpp>
 #include <opencv2/core/core.hpp>
 
+#include <pcl/point_cloud.h>
+#include <pcl/point_types.h>
+
 class PlaceAreaFinder
 {
 
@@ -24,7 +27,17 @@ class PlaceAreaFinder
     void getCanvas(cv::Mat& image){ canvas.copyTo(image); }
 
 private:
+    // internal occupancy representation
+    double resolution = 0.005;
+    cv::Point2d canvas_center;
     cv::Mat canvas;
+
+    cv::Point2d worldToCanvas(double x, double y);
+    void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
+    void closeCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin);
+    void alterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin);
+    void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin);
+    void dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin);
 };
 
 #endif
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 93947513..89fd7ac2 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -10,7 +10,6 @@
 #include <ros/ros.h>
 
 //pcl library # TODO remove the unused ones #TODO find out which ones are unused
-#include <pcl/point_cloud.h>
 #include <pcl/point_representation.h>
 #include <pcl/common/common.h>
 #include <pcl/io/pcd_io.h>
@@ -39,9 +38,6 @@
 #include "ed_sensor_integration/sac_model_horizontal_plane.h"
 
 
-double resolution = 0.005;
-cv::Point2d canvas_center;
-
 double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL)
 {
     // Fill in the cloud data
@@ -173,79 +169,7 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const
     return abs(coefficients->values[3]);
 }
 
-
-cv::Point2d worldToCanvas(double x, double y)
-{
-    return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
-}
- 
-void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < cloud->points.size (); nIndex++)
-    {
-        double x = cloud->points[nIndex].x;
-        double y = cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
-
-    
-}
-
-void createObjectCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < object_cloud->points.size (); nIndex++)
-    {
-        double x = object_cloud->points[nIndex].x;
-        double y = object_cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
-
-}
-
-void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < occluded_cloud->points.size (); nIndex++)
-    {
-        double x = occluded_cloud->points[nIndex].x;
-        double y = occluded_cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }   
-}
-
-void createNotTableCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < notTable_cloud->points.size (); nIndex++)
-    {
-        double x = notTable_cloud->points[nIndex].x;
-        double y = notTable_cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
-}
-
+/*
 void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, double fx)
 
 {
@@ -299,74 +223,13 @@ void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, floa
             }
         }
 }
+*/
 
-void CloseCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin)
-{
-    float Pixelsize = 5*(placement_margin / resolution);
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::dilate(canvas, closed_canvas, element );
-    cv::erode(closed_canvas, closed_canvas, element);
-}
-
-
-void AlterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin)
-{
-    float Pixelsize = 2*(placement_margin / resolution);
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::erode(closed_canvas, smallplane_canvas, element);
-}
-
-
-
-
-void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        float upper_radius = 0.75 + placement_margin/2;
-        float lower_radius = 0.60 - placement_margin/2;
-            for (float phi = 0; phi < 360; phi++)
-            {
-                for (int i = 0; i < 100; i++)
-                {
-                double y = upper_radius * sin(phi/(180/M_PI)) + 0.03 * i * sin(phi/(180/M_PI));
-                double x = upper_radius * cos(phi/(180/M_PI)) + 0.03 * i * cos(phi/(180/M_PI));
-
-                cv::Point2d p = worldToCanvas(x, y);
-                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-                }
-
-                for (int i = 0; i < 100; i++)
-                {
-                double y = lower_radius * sin(phi/(180/M_PI)) - lower_radius/100 * i * sin(phi/(180/M_PI));
-                double x = lower_radius * cos(phi/(180/M_PI)) - lower_radius/100 * i * cos(phi/(180/M_PI));
-
-                cv::Point2d p = worldToCanvas(x, y);
-                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-                }
-            }
-        
-}
-
-void dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin)
-{
-    float Pixelsize = placement_margin / resolution;
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::dilate(canvas, dilated_canvas, element );
-
-}
 
 void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor, cv::Scalar point_color, double height)
 {
 
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+    cv::Point2d canvas_center(canvas.rows / 2, canvas.cols);
 
     std::vector<cv::Point> identicalPoints;
     cv::Point2d PlacementPoint;
@@ -393,14 +256,9 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
     if (!found)
         return;
 
-    double y = (PlacementPoint.x-canvas_center.x)*-resolution;
-    double x = (PlacementPoint.y-canvas_center.y)*-resolution;
-
-    double margin = 0.02; // So the robot does not attempt to place an object in the table
+    //double y = (PlacementPoint.x-canvas_center.x)*-resolution;
+    //double x = (PlacementPoint.y-canvas_center.y)*-resolution;
 
-    std::cout << "The selected point for placement in (x,y,z) coordinates is:" << std::endl;
-    std::cout << "(" << x << ", " << y << ", " << height+margin << ")" << std::endl;
-    std::cout << "Which is " << sqrt(pow(x,2)+pow(y,2)) << " cm away from HERO" << std::endl;
     placement_canvas.at<cv::Vec3b>(PlacementPoint) = cv::Vec3b(point_color[0], point_color[1], point_color[2]); 
 
 }
@@ -540,7 +398,7 @@ void PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     std::cout << "creating costmap" << std::endl;
 
     // Add table plane to costmap
-    createCostmap(plane_cloud, canvas, table_color);
+    createCostmap(plane_cloud, table_color);
 
     // Adding boundaries with morphological operations
 
@@ -568,22 +426,22 @@ void PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     // Adding boundaries with additional PCL data
 
     // Add objects to costmap
-    createObjectCostmap(object_cloud, canvas, occupied_color);
+    createCostmap(object_cloud, occupied_color);
 
     // Add occluded space to costmap
-    createOccludedCostmap(occluded_cloud, canvas, occluded_color);
+    createCostmap(occluded_cloud, occluded_color);
 
     // Add not_Table to define the table edge
-    createNotTableCostmap(notTable_cloud, canvas, occupied_color);
+    createCostmap(notTable_cloud, occupied_color);
 
     // FOV left
-    createFOVLCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3), fx);
+//    createFOVLCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3), fx);
 
     // FOV right
-    createFOVRCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3));
+  //  createFOVRCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3));
 
     // FOV down
-    createFOVHCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3), transform(2, 3), height);
+   // createFOVHCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3), transform(2, 3), height);
 
     // HERO preferred radius
     createRadiusCostmap(canvas, radius_color, placement_margin);
@@ -594,5 +452,95 @@ void PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     // Extract the placement options and choose a placement solution
     ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
 
+    // fill result
+    geo::Pose3D placement_pose;
+    placement_pose.t.z = height;
+
     return;
-}
\ No newline at end of file
+}
+
+cv::Point2d PlaceAreaFinder::worldToCanvas(double x, double y)
+{
+    return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
+}
+
+void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
+
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < cloud->points.size (); nIndex++)
+    {
+        double x = cloud->points[nIndex].x;
+        double y = cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+
+    
+}
+
+void PlaceAreaFinder::closeCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin)
+{
+    float Pixelsize = 5*(placement_margin / resolution);
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::dilate(canvas, closed_canvas, element );
+    cv::erode(closed_canvas, closed_canvas, element);
+}
+
+
+void PlaceAreaFinder::alterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin)
+{
+    float Pixelsize = 2*(placement_margin / resolution);
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::erode(closed_canvas, smallplane_canvas, element);
+}
+
+
+
+
+void PlaceAreaFinder::createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        float upper_radius = 0.75 + placement_margin/2;
+        float lower_radius = 0.60 - placement_margin/2;
+            for (float phi = 0; phi < 360; phi++)
+            {
+                for (int i = 0; i < 100; i++)
+                {
+                double y = upper_radius * sin(phi/(180/M_PI)) + 0.03 * i * sin(phi/(180/M_PI));
+                double x = upper_radius * cos(phi/(180/M_PI)) + 0.03 * i * cos(phi/(180/M_PI));
+
+                cv::Point2d p = worldToCanvas(x, y);
+                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+                }
+
+                for (int i = 0; i < 100; i++)
+                {
+                double y = lower_radius * sin(phi/(180/M_PI)) - lower_radius/100 * i * sin(phi/(180/M_PI));
+                double x = lower_radius * cos(phi/(180/M_PI)) - lower_radius/100 * i * cos(phi/(180/M_PI));
+
+                cv::Point2d p = worldToCanvas(x, y);
+                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+                }
+            }
+        
+}
+
+void PlaceAreaFinder::dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin)
+{
+    float Pixelsize = placement_margin / resolution;
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::dilate(canvas, dilated_canvas, element );
+
+}

From 74c81b9436d1d52d9496f9e911e2125713ba12df Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 13:35:05 +0200
Subject: [PATCH 075/136] get placement pose

---
 .../include/ed/kinect/place_area_finder.h     |  1 +
 .../src/kinect/place_area_finder.cpp          | 57 ++++++++++++-------
 2 files changed, 39 insertions(+), 19 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index d378cc76..021179c0 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -33,6 +33,7 @@ class PlaceAreaFinder
     cv::Mat canvas;
 
     cv::Point2d worldToCanvas(double x, double y);
+    geo::Vec2d canvasToWorld(cv::Point2d point);
     void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
     void closeCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin);
     void alterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin);
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 89fd7ac2..ef13f9f4 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -232,8 +232,6 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
     cv::Point2d canvas_center(canvas.rows / 2, canvas.cols);
 
     std::vector<cv::Point> identicalPoints;
-    cv::Point2d PlacementPoint;
-    bool found = false;
 
     for(int row = canvas.rows; row > 0; --row)
     {
@@ -245,22 +243,30 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
                currPixel.val[2] == targetColor.val[2])
             {
                 cv::Point2d p = cv::Point(col, row);
-                PlacementPoint = p;
-                found = true;
                 if (p.x >= 0 && p.y >= 0 && p.x < placement_canvas.cols && p.y < placement_canvas.rows)
                     placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(targetColor[0], targetColor[1], targetColor[2]);
             }
         }
     }
+}
 
-    if (!found)
-        return;
-
-    //double y = (PlacementPoint.x-canvas_center.x)*-resolution;
-    //double x = (PlacementPoint.y-canvas_center.y)*-resolution;
-
-    placement_canvas.at<cv::Vec3b>(PlacementPoint) = cv::Vec3b(point_color[0], point_color[1], point_color[2]); 
-
+bool GetPlacementOption(cv::Mat& canvas, cv::Scalar targetColor, cv::Point2d& point)
+{
+    for(int row = 0; row <canvas.rows; ++row)
+    {
+        for(int col = canvas.cols; col > 0; --col)
+        {
+            cv::Vec3b currPixel = canvas.at<cv::Vec3b>(row, col);
+            if(currPixel.val[0] == targetColor.val[0] &&
+               currPixel.val[1] == targetColor.val[1] &&
+               currPixel.val[2] == targetColor.val[2])
+            {
+                point = cv::Point(col, row);
+                return true;
+            }
+        }
+    }
+    return false;
 }
 
 PlaceAreaFinder::PlaceAreaFinder()
@@ -450,11 +456,21 @@ void PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     dilateCostmap(canvas, dilated_canvas, placement_margin);
 
     // Extract the placement options and choose a placement solution
-    ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
+    cv::Point2d place_point_canvas;
+    if (!GetPlacementOption(dilated_canvas, table_color, place_point_canvas))
+    {
+        return;
+    }
+
+    geo::Vec2d place_point;
+    place_point = canvasToWorld(place_point_canvas);
 
     // fill result
     geo::Pose3D placement_pose;
-    placement_pose.t.z = height;
+
+    placement_pose.t.x = place_point.x;
+    placement_pose.t.y = place_point.y;
+    placement_pose.t.z = height + 0.02;
 
     return;
 }
@@ -464,6 +480,13 @@ cv::Point2d PlaceAreaFinder::worldToCanvas(double x, double y)
     return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
 }
 
+geo::Vec2d PlaceAreaFinder::canvasToWorld(cv::Point2d point)
+{
+    double y = (point.x-canvas_center.x)*-resolution;
+    double x = (point.y-canvas_center.y)*-resolution;
+    return geo::Vec2d(x, y);
+}
+
 void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
 
 {
@@ -477,9 +500,7 @@ void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud
         cv::Point2d p = worldToCanvas(x, y);
         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
-
-    
+    }    
 }
 
 void PlaceAreaFinder::closeCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin)
@@ -503,8 +524,6 @@ void PlaceAreaFinder::alterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_can
 }
 
 
-
-
 void PlaceAreaFinder::createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
 {
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);

From 6e6696e2fb451e6f549e2e66bdf760da93367ccd Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 13:41:21 +0200
Subject: [PATCH 076/136] return from findarea

---
 .../include/ed/kinect/place_area_finder.h           |  2 +-
 .../src/kinect/place_area_finder.cpp                | 13 ++++---------
 .../tools/empty_spot_designator.cpp                 |  3 ++-
 3 files changed, 7 insertions(+), 11 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index 021179c0..b0bd3ff5 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -22,7 +22,7 @@ class PlaceAreaFinder
 
     ~PlaceAreaFinder();
 
-    void findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose);
+    bool findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose);
 
     void getCanvas(cv::Mat& image){ canvas.copyTo(image); }
 
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index ef13f9f4..d4b5c805 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -277,7 +277,7 @@ PlaceAreaFinder::~PlaceAreaFinder()
 {
 }
 
-void PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose)
+bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose)
 {
     // std::cout << "converting image to cloud" << std::endl;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
@@ -459,20 +459,15 @@ void PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     cv::Point2d place_point_canvas;
     if (!GetPlacementOption(dilated_canvas, table_color, place_point_canvas))
     {
-        return;
+        return false;
     }
 
     geo::Vec2d place_point;
     place_point = canvasToWorld(place_point_canvas);
 
     // fill result
-    geo::Pose3D placement_pose;
-
-    placement_pose.t.x = place_point.x;
-    placement_pose.t.y = place_point.y;
-    placement_pose.t.z = height + 0.02;
-
-    return;
+    place_pose = geo::Pose3D(place_point.x, place_point.y, height+0.02);
+    return true;
 }
 
 cv::Point2d PlaceAreaFinder::worldToCanvas(double x, double y)
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 7c031726..4a485e54 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -85,6 +85,7 @@ int main (int argc, char **argv)
     {
         rgbd::ImageConstPtr image;
         geo::Pose3D sensor_pose;
+        geo::Pose3D place_pose;
 
         if (!image_buffer.waitForRecentImage(image, sensor_pose, 2.0))
         {
@@ -92,7 +93,7 @@ int main (int argc, char **argv)
             continue;
         }
         
-        place_area_finder.findArea(image, sensor_pose);
+        place_area_finder.findArea(image, sensor_pose, place_pose);
 
         cv::Mat canvas;
         place_area_finder.getCanvas(canvas);

From 9adbd34825e1aacc0784ff7a61eefe3057b74a29 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 13:49:10 +0200
Subject: [PATCH 077/136] implement service

---
 .../src/kinect/kinect_plugin.cpp              | 22 ++++++++++++++++++-
 1 file changed, 21 insertions(+), 1 deletion(-)

diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.cpp b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
index ec5257ab..8a32a2ef 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.cpp
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
@@ -277,7 +277,27 @@ bool KinectPlugin::srvRayTrace(ed_sensor_integration_msgs::RayTrace::Request& re
 
 bool KinectPlugin::srvPlaceArea(ed_sensor_integration_msgs::PlaceArea::Request& req, ed_sensor_integration_msgs::PlaceArea::Response& res)
 {
-    ROS_INFO("Determine place area");
+    // - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
+    // Get new image
+
+    rgbd::ImageConstPtr image;
+    geo::Pose3D sensor_pose;
+
+    if (!image_buffer_.waitForRecentImage(image, sensor_pose, 2.0))
+    {
+        res.error_msg = "Could not get image";
+        return true;
+    }
+
+    // Determine place area
+    geo::Pose3D place_pose;
+    if (!place_area_finder_.findArea(image, sensor_pose, place_pose))
+    {
+        res.error_msg = "No valid place area found";
+        return true;
+    }
+    //TODO fill res.pose
+
     return true;
 }
 

From 1f046b178e476431008061f4390aff08b33eef78 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 14:12:57 +0200
Subject: [PATCH 078/136] expand emptyspotdesignator tool

---
 ed_sensor_integration/tools/empty_spot_designator.cpp | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 4a485e54..2b1a15d7 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -93,10 +93,16 @@ int main (int argc, char **argv)
             continue;
         }
         
-        place_area_finder.findArea(image, sensor_pose, place_pose);
+        if (!place_area_finder.findArea(image, sensor_pose, place_pose))
+        {
+            std::cout << "no place area found" << std::endl;
+        }
 
         cv::Mat canvas;
         place_area_finder.getCanvas(canvas);
+
+        std::cout << place_pose << std::endl;
+
         // Show the different canvasses
         
         // std::cout << "showing costmap" << std::endl;

From 1d19b63237c19986b536e90ed5076517bab00871 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 14:24:15 +0200
Subject: [PATCH 079/136] fill result of service

---
 ed_sensor_integration/src/kinect/kinect_plugin.cpp | 10 +++++-----
 ed_sensor_integration/src/kinect/kinect_plugin.h   |  1 +
 ed_sensor_integration_msgs/srv/PlaceArea.srv       |  2 +-
 3 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.cpp b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
index 8a32a2ef..5dabaa08 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.cpp
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
@@ -50,6 +50,7 @@ void KinectPlugin::initialize(ed::InitData& init)
     {
         ROS_INFO_STREAM("[ED KINECT PLUGIN] Initializing kinect client with topic '" << topic << "'.");
         image_buffer_.initialize(topic, "map");
+        image_buffer_bl_.initialize(topic, "base_link");
     }
 
     // - - - - - - - - - - - - - - - - - -
@@ -281,23 +282,22 @@ bool KinectPlugin::srvPlaceArea(ed_sensor_integration_msgs::PlaceArea::Request&
     // Get new image
 
     rgbd::ImageConstPtr image;
-    geo::Pose3D sensor_pose;
+    geo::Pose3D sensor_pose; // in base link frame
 
-    if (!image_buffer_.waitForRecentImage(image, sensor_pose, 2.0))
+    if (!image_buffer_bl_.waitForRecentImage(image, sensor_pose, 2.0))
     {
         res.error_msg = "Could not get image";
         return true;
     }
 
     // Determine place area
-    geo::Pose3D place_pose;
+    geo::Pose3D place_pose; // w.r.t base link
     if (!place_area_finder_.findArea(image, sensor_pose, place_pose))
     {
         res.error_msg = "No valid place area found";
         return true;
     }
-    //TODO fill res.pose
-
+    geo::convert(place_pose, res.pose.pose);
     return true;
 }
 
diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.h b/ed_sensor_integration/src/kinect/kinect_plugin.h
index 79472b44..a69b6842 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.h
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.h
@@ -39,6 +39,7 @@ class KinectPlugin : public ed::Plugin
     // Image retrieval
 
     ImageBuffer image_buffer_;
+    ImageBuffer image_buffer_bl_;
 
 //    rgbd::ImageConstPtr last_image_;
 
diff --git a/ed_sensor_integration_msgs/srv/PlaceArea.srv b/ed_sensor_integration_msgs/srv/PlaceArea.srv
index af1a19b6..efd1d087 100644
--- a/ed_sensor_integration_msgs/srv/PlaceArea.srv
+++ b/ed_sensor_integration_msgs/srv/PlaceArea.srv
@@ -1,4 +1,4 @@
 # request info
 ---
 string error_msg  # empty if no error
-geometry_msgs/PoseStamped[] pose  # pose of a possible place location
\ No newline at end of file
+geometry_msgs/PoseStamped pose  # pose of a possible place location
\ No newline at end of file

From bfeac6903c146c638650b0d3c0890c7bba25a848 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 16:08:23 +0200
Subject: [PATCH 080/136] add fov test

---
 .../tools/empty_spot_designator.cpp           | 65 ++++++++++++++++++-
 1 file changed, 63 insertions(+), 2 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 2b1a15d7..04780147 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -46,6 +46,66 @@
 double resolution = 0.005;
 cv::Point2d canvas_center;
 
+geo::Vector3 simpleRayTrace(geo::Vector3 origin, geo::Vector3 direction)
+{
+    if (direction.z > 0)
+    {
+        std::cout << "Raytrace went terribly wrong" << std::endl;
+    }
+    double ratio = origin.z / direction.z;
+
+    return geo::Vector3(origin.x + ratio * direction.x, origin.y + ratio * direction.y, 0);
+}
+
+/**
+ * @brief Draw the fiel of view of the camera on a plane.
+ * 
+ * @param canvas
+ * @param sensor_pose
+ * @param caminfo
+ */
+void drawFieldOfView(cv::Mat& canvas, geo::Pose3D sensor_pose, const rgbd::ImageConstPtr& caminfo)
+{
+    // Get camera info
+    int width = caminfo->getDepthImage().cols;
+    int height = caminfo->getDepthImage().rows;
+    double half_height = 0.5*height;
+    double half_width = 0.5*width;
+
+    double fx = caminfo->getCameraModel().fx();
+    double fy = caminfo->getCameraModel().fy();
+
+    // determine vectors pointing to corners of FoV
+    geo::Vector3 c1(fx*half_width, fy*half_height, 1.0); // upper left of image
+    geo::Vector3 c2(-fx*half_width, fy*half_height, 1.0); // upper right of image
+    geo::Vector3 c3(-fx*half_width, -fy*half_height, 1.0); // lower right of image
+    geo::Vector3 c4(fx*half_width, -fy*half_height, 1.0); // lower left of image
+
+    // convert vectors to world frame
+    c1 = sensor_pose.R.transpose() * c1;
+    c2 = sensor_pose.R.transpose() * c2;
+    c3 = sensor_pose.R.transpose() * c3;
+    c4 = sensor_pose.R.transpose() * c4;
+
+    // project vectors on place
+    geo::Vector3 p1 = simpleRayTrace(sensor_pose.t, c1);
+    geo::Vector3 p2 = simpleRayTrace(sensor_pose.t, c2);
+    geo::Vector3 p3 = simpleRayTrace(sensor_pose.t, c3);
+    geo::Vector3 p4 = simpleRayTrace(sensor_pose.t, c4);
+
+    // draw projected points
+    cv::Point2d p1_canvas = cv::Point2d(-p1.y / resolution, -p1.x / resolution) + canvas_center;
+    cv::Point2d p2_canvas = cv::Point2d(-p2.y / resolution, -p2.x / resolution) + canvas_center;
+    cv::Point2d p3_canvas = cv::Point2d(-p3.y / resolution, -p3.x / resolution) + canvas_center;
+    cv::Point2d p4_canvas = cv::Point2d(-p4.y / resolution, -p4.x / resolution) + canvas_center;
+    cv::Scalar fovcolor(255, 0, 255); // Red
+    cv::circle(canvas, p1_canvas, 5, fovcolor);
+    cv::circle(canvas, p2_canvas, 5, fovcolor);
+    cv::circle(canvas, p3_canvas, 5, fovcolor);
+    cv::circle(canvas, p4_canvas, 5, fovcolor);
+
+}
+
 /**
  * @brief usage, print how the executable should be used and explain the input
  */
@@ -97,12 +157,13 @@ int main (int argc, char **argv)
         {
             std::cout << "no place area found" << std::endl;
         }
+        std::cout << place_pose << std::endl;
 
         cv::Mat canvas;
         place_area_finder.getCanvas(canvas);
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
-        std::cout << place_pose << std::endl;
-
+        drawFieldOfView(canvas, sensor_pose, image);
         // Show the different canvasses
         
         // std::cout << "showing costmap" << std::endl;

From 94e71c9fdd067b418c2632b899ed912b96b079a3 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 16:30:46 +0200
Subject: [PATCH 081/136] DRY

---
 .../tools/empty_spot_designator.cpp           | 62 ++++++++++---------
 1 file changed, 34 insertions(+), 28 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 04780147..a8a548fb 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -57,6 +57,29 @@ geo::Vector3 simpleRayTrace(geo::Vector3 origin, geo::Vector3 direction)
     return geo::Vector3(origin.x + ratio * direction.x, origin.y + ratio * direction.y, 0);
 }
 
+void drawFoVMacro(geo::Vector3 direction, cv::Mat& canvas, geo::Pose3D sensor_pose, const rgbd::ImageConstPtr& caminfo)
+{
+    // convert vectors to world frame
+    direction = sensor_pose.R.transpose() * direction;
+
+    if (direction.z > 0.0)
+    {
+        std::cout << "above plane" << std::endl;
+        return;
+    }
+
+    // project vectors on place
+    geo::Vector3 p1 = simpleRayTrace(sensor_pose.t, direction);
+
+    // draw projected points
+    cv::Point2d p1_canvas = cv::Point2d(-p1.y / resolution, -p1.x / resolution) + canvas_center;
+    cv::Scalar fovcolor(0, 255, 255); // Red
+    cv::circle(canvas, p1_canvas, 5, fovcolor, -1);
+
+    std::cout << "FoV debug info c: " << direction << std::endl;
+    std::cout << "p1: " << p1 << std::endl;
+    std::cout << "cvpoint: x: " << p1_canvas.x << ", y: " << p1_canvas.y << std::endl;
+}
 /**
  * @brief Draw the fiel of view of the camera on a plane.
  * 
@@ -76,34 +99,17 @@ void drawFieldOfView(cv::Mat& canvas, geo::Pose3D sensor_pose, const rgbd::Image
     double fy = caminfo->getCameraModel().fy();
 
     // determine vectors pointing to corners of FoV
-    geo::Vector3 c1(fx*half_width, fy*half_height, 1.0); // upper left of image
-    geo::Vector3 c2(-fx*half_width, fy*half_height, 1.0); // upper right of image
-    geo::Vector3 c3(-fx*half_width, -fy*half_height, 1.0); // lower right of image
-    geo::Vector3 c4(fx*half_width, -fy*half_height, 1.0); // lower left of image
-
-    // convert vectors to world frame
-    c1 = sensor_pose.R.transpose() * c1;
-    c2 = sensor_pose.R.transpose() * c2;
-    c3 = sensor_pose.R.transpose() * c3;
-    c4 = sensor_pose.R.transpose() * c4;
-
-    // project vectors on place
-    geo::Vector3 p1 = simpleRayTrace(sensor_pose.t, c1);
-    geo::Vector3 p2 = simpleRayTrace(sensor_pose.t, c2);
-    geo::Vector3 p3 = simpleRayTrace(sensor_pose.t, c3);
-    geo::Vector3 p4 = simpleRayTrace(sensor_pose.t, c4);
-
-    // draw projected points
-    cv::Point2d p1_canvas = cv::Point2d(-p1.y / resolution, -p1.x / resolution) + canvas_center;
-    cv::Point2d p2_canvas = cv::Point2d(-p2.y / resolution, -p2.x / resolution) + canvas_center;
-    cv::Point2d p3_canvas = cv::Point2d(-p3.y / resolution, -p3.x / resolution) + canvas_center;
-    cv::Point2d p4_canvas = cv::Point2d(-p4.y / resolution, -p4.x / resolution) + canvas_center;
-    cv::Scalar fovcolor(255, 0, 255); // Red
-    cv::circle(canvas, p1_canvas, 5, fovcolor);
-    cv::circle(canvas, p2_canvas, 5, fovcolor);
-    cv::circle(canvas, p3_canvas, 5, fovcolor);
-    cv::circle(canvas, p4_canvas, 5, fovcolor);
-
+    geo::Vector3 c0(0, 0, -1.0); // upper left of image
+    geo::Vector3 c1(fx*half_width, fy*half_height, -1.0); // upper left of image
+    geo::Vector3 c2(-fx*half_width, fy*half_height, -1.0); // upper right of image
+    geo::Vector3 c3(-fx*half_width, -fy*half_height, -1.0); // lower right of image
+    geo::Vector3 c4(fx*half_width, -fy*half_height, -1.0); // lower left of image
+
+    // draw
+    drawFoVMacro(c1, canvas, sensor_pose, caminfo);
+    drawFoVMacro(c2, canvas, sensor_pose, caminfo);
+    drawFoVMacro(c3, canvas, sensor_pose, caminfo);
+    drawFoVMacro(c4, canvas, sensor_pose, caminfo);
 }
 
 /**

From 2b0eceadb7296851c98e61ee67b0af5e88bc1f56 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 16:36:39 +0200
Subject: [PATCH 082/136] fix focal lenght

---
 .../tools/empty_spot_designator.cpp                  | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index a8a548fb..a53cce5d 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -76,8 +76,8 @@ void drawFoVMacro(geo::Vector3 direction, cv::Mat& canvas, geo::Pose3D sensor_po
     cv::Scalar fovcolor(0, 255, 255); // Red
     cv::circle(canvas, p1_canvas, 5, fovcolor, -1);
 
-    std::cout << "FoV debug info c: " << direction << std::endl;
-    std::cout << "p1: " << p1 << std::endl;
+    std::cout << "FoV debug info direction: " << direction << std::endl;
+    std::cout << "projection: " << p1 << std::endl;
     std::cout << "cvpoint: x: " << p1_canvas.x << ", y: " << p1_canvas.y << std::endl;
 }
 /**
@@ -100,10 +100,10 @@ void drawFieldOfView(cv::Mat& canvas, geo::Pose3D sensor_pose, const rgbd::Image
 
     // determine vectors pointing to corners of FoV
     geo::Vector3 c0(0, 0, -1.0); // upper left of image
-    geo::Vector3 c1(fx*half_width, fy*half_height, -1.0); // upper left of image
-    geo::Vector3 c2(-fx*half_width, fy*half_height, -1.0); // upper right of image
-    geo::Vector3 c3(-fx*half_width, -fy*half_height, -1.0); // lower right of image
-    geo::Vector3 c4(fx*half_width, -fy*half_height, -1.0); // lower left of image
+    geo::Vector3 c1(half_width / fx, half_height / fy, -1.0); // upper left of image
+    geo::Vector3 c2(-half_width / fx, half_height / fy, -1.0); // upper right of image
+    geo::Vector3 c3(-half_width / fx, -half_height / fy, -1.0); // lower right of image
+    geo::Vector3 c4(half_width / fx, -half_height / fy, -1.0); // lower left of image
 
     // draw
     drawFoVMacro(c1, canvas, sensor_pose, caminfo);

From f4a449614d05c93179492646b575e179e4440d9d Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 18:08:54 +0200
Subject: [PATCH 083/136] add comments and output

---
 .../tools/empty_spot_designator.cpp                  | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index a53cce5d..2746702d 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -83,9 +83,9 @@ void drawFoVMacro(geo::Vector3 direction, cv::Mat& canvas, geo::Pose3D sensor_po
 /**
  * @brief Draw the fiel of view of the camera on a plane.
  * 
- * @param canvas
- * @param sensor_pose
- * @param caminfo
+ * @param canvas image representing a plane
+ * @param sensor_pose pose of the camera with respect to the plane. It is assumed that the origin corresponds to the canvas_center point on the plane.
+ * @param caminfo Used to get focal lengths of the camera
  */
 void drawFieldOfView(cv::Mat& canvas, geo::Pose3D sensor_pose, const rgbd::ImageConstPtr& caminfo)
 {
@@ -106,9 +106,15 @@ void drawFieldOfView(cv::Mat& canvas, geo::Pose3D sensor_pose, const rgbd::Image
     geo::Vector3 c4(half_width / fx, -half_height / fy, -1.0); // lower left of image
 
     // draw
+    std::cout << "center" << std::endl;
+    drawFoVMacro(c0, canvas, sensor_pose, caminfo);
+    std::cout << "upper left" << std::endl;
     drawFoVMacro(c1, canvas, sensor_pose, caminfo);
+    std::cout << "upper right" << std::endl;
     drawFoVMacro(c2, canvas, sensor_pose, caminfo);
+    std::cout << "lower right" << std::endl;
     drawFoVMacro(c3, canvas, sensor_pose, caminfo);
+    std::cout << "lower left" << std::endl;
     drawFoVMacro(c4, canvas, sensor_pose, caminfo);
 }
 

From 4562a0e58d27d4ca554c32d64810f56c9bd4780f Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Sat, 1 Apr 2023 18:38:33 +0200
Subject: [PATCH 084/136] debugging

---
 .../tools/empty_spot_designator.cpp           | 22 +++++++++++--------
 1 file changed, 13 insertions(+), 9 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 2746702d..ce5425ea 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -52,7 +52,7 @@ geo::Vector3 simpleRayTrace(geo::Vector3 origin, geo::Vector3 direction)
     {
         std::cout << "Raytrace went terribly wrong" << std::endl;
     }
-    double ratio = origin.z / direction.z;
+    double ratio = -origin.z / direction.z;
 
     return geo::Vector3(origin.x + ratio * direction.x, origin.y + ratio * direction.y, 0);
 }
@@ -60,25 +60,26 @@ geo::Vector3 simpleRayTrace(geo::Vector3 origin, geo::Vector3 direction)
 void drawFoVMacro(geo::Vector3 direction, cv::Mat& canvas, geo::Pose3D sensor_pose, const rgbd::ImageConstPtr& caminfo)
 {
     // convert vectors to world frame
-    direction = sensor_pose.R.transpose() * direction;
+    geo::Vector3 direction_world = sensor_pose.R * direction;
 
-    if (direction.z > 0.0)
+    if (direction_world.z > 0.0)
     {
         std::cout << "above plane" << std::endl;
         return;
     }
 
     // project vectors on place
-    geo::Vector3 p1 = simpleRayTrace(sensor_pose.t, direction);
+    geo::Vector3 projected_point = simpleRayTrace(sensor_pose.t, direction_world);
 
     // draw projected points
-    cv::Point2d p1_canvas = cv::Point2d(-p1.y / resolution, -p1.x / resolution) + canvas_center;
+    cv::Point2d p1_canvas = cv::Point2d(-projected_point.y / resolution, -projected_point.x / resolution) + canvas_center;
     cv::Scalar fovcolor(0, 255, 255); // Red
     cv::circle(canvas, p1_canvas, 5, fovcolor, -1);
 
-    std::cout << "FoV debug info direction: " << direction << std::endl;
-    std::cout << "projection: " << p1 << std::endl;
-    std::cout << "cvpoint: x: " << p1_canvas.x << ", y: " << p1_canvas.y << std::endl;
+    std::cout << "direction in camera frame: " << direction << std::endl;
+    std::cout << "direction in world frame: " << direction_world << std::endl;
+    std::cout << "projection in world frame: " << projected_point << std::endl;
+    std::cout << "cvpoint in canvas frame: x: " << p1_canvas.x << ", y: " << p1_canvas.y << std::endl;
 }
 /**
  * @brief Draw the fiel of view of the camera on a plane.
@@ -175,7 +176,10 @@ int main (int argc, char **argv)
         place_area_finder.getCanvas(canvas);
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
-        drawFieldOfView(canvas, sensor_pose, image);
+        geo::Pose3D sensor_pose_canvas = sensor_pose;
+        sensor_pose_canvas.t.z = sensor_pose.t.z - place_pose.t.z;
+        drawFieldOfView(canvas, sensor_pose_canvas, image);
+
         // Show the different canvasses
         
         // std::cout << "showing costmap" << std::endl;

From 9c5500ecc318928d9481cd81700ac4b4e4fa7b91 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Fri, 7 Apr 2023 20:48:36 +0200
Subject: [PATCH 085/136] fix image buffer import

---
 ed_sensor_integration/src/kinect/place_area_finder.cpp | 2 --
 ed_sensor_integration/tools/empty_spot_designator.cpp  | 4 ++--
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index d4b5c805..2cd5a137 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -3,8 +3,6 @@
 #include <iostream>
 #include <string>
 
-#include "ed/kinect/image_buffer.h"
-
 #include <vector>
 
 #include <ros/ros.h>
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index ce5425ea..b96dc2a7 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -1,7 +1,7 @@
 #include <iostream>
 #include <string>
 
-#include "ed/kinect/image_buffer.h"
+#include <rgbd/image_buffer/image_buffer.h>
 
 #include <opencv2/imgproc/imgproc.hpp>
 #include <opencv2/highgui.hpp>
@@ -147,7 +147,7 @@ int main (int argc, char **argv)
     std::string topic = argv[1];
     std::cout << "Using topic: " << topic << std::endl;
 
-    ImageBuffer image_buffer;
+    rgbd::ImageBuffer image_buffer;
     image_buffer.initialize(topic, "base_link");
 
     pcl::PCDWriter writer;

From 5e38ce1e134da14a0dc4cd97f16dd1d626a3ff82 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Fri, 7 Apr 2023 20:49:12 +0200
Subject: [PATCH 086/136] fix unused parameter warnings

---
 .../src/kinect/place_area_finder.cpp                 |  5 ++---
 .../tools/empty_spot_designator.cpp                  | 12 ++++++------
 2 files changed, 8 insertions(+), 9 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 2cd5a137..3298f21c 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -137,7 +137,6 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const
     // Create the filtering object
     pcl::ExtractIndices<pcl::PointXYZRGB> extract;
     pcl::ExtractIndices<pcl::PointXYZRGB> extract2;
-    int i = 0, nr_points = (int) cloud_in->size ();
 
     // Segment the largest planar component from the remaining cloud
     seg.setInputCloud(cloud_in);
@@ -224,7 +223,7 @@ void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, floa
 */
 
 
-void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor, cv::Scalar point_color, double height)
+void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor)
 {
 
     cv::Point2d canvas_center(canvas.rows / 2, canvas.cols);
@@ -281,7 +280,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL(new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVR(new pcl::PointCloud<pcl::PointXYZRGB>);
-    double fx = imageToCloud(*image, cloud, FOVL);
+    imageToCloud(*image, cloud, FOVL);
 
     // transform to base link frame
     Eigen::Matrix4f transform = geolibToEigen(sensor_pose);
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index b96dc2a7..3b3d8fde 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -57,7 +57,7 @@ geo::Vector3 simpleRayTrace(geo::Vector3 origin, geo::Vector3 direction)
     return geo::Vector3(origin.x + ratio * direction.x, origin.y + ratio * direction.y, 0);
 }
 
-void drawFoVMacro(geo::Vector3 direction, cv::Mat& canvas, geo::Pose3D sensor_pose, const rgbd::ImageConstPtr& caminfo)
+void drawFoVMacro(geo::Vector3 direction, cv::Mat& canvas, geo::Pose3D sensor_pose)
 {
     // convert vectors to world frame
     geo::Vector3 direction_world = sensor_pose.R * direction;
@@ -108,15 +108,15 @@ void drawFieldOfView(cv::Mat& canvas, geo::Pose3D sensor_pose, const rgbd::Image
 
     // draw
     std::cout << "center" << std::endl;
-    drawFoVMacro(c0, canvas, sensor_pose, caminfo);
+    drawFoVMacro(c0, canvas, sensor_pose);
     std::cout << "upper left" << std::endl;
-    drawFoVMacro(c1, canvas, sensor_pose, caminfo);
+    drawFoVMacro(c1, canvas, sensor_pose);
     std::cout << "upper right" << std::endl;
-    drawFoVMacro(c2, canvas, sensor_pose, caminfo);
+    drawFoVMacro(c2, canvas, sensor_pose);
     std::cout << "lower right" << std::endl;
-    drawFoVMacro(c3, canvas, sensor_pose, caminfo);
+    drawFoVMacro(c3, canvas, sensor_pose);
     std::cout << "lower left" << std::endl;
-    drawFoVMacro(c4, canvas, sensor_pose, caminfo);
+    drawFoVMacro(c4, canvas, sensor_pose);
 }
 
 /**

From 3c52d99525972fcf2ae7430aa872870144797bea Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Fri, 7 Apr 2023 20:49:43 +0200
Subject: [PATCH 087/136] fixed sign comparison warning

---
 ed_sensor_integration/src/kinect/place_area_finder.cpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 3298f21c..0ce74017 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -335,7 +335,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     float x = transform(0, 3);
     float y = transform(1, 3);
     float z = transform(2, 3);
-    for (int nIndex = 0; nIndex < object_cloud->points.size(); nIndex++)
+    for (uint nIndex = 0; nIndex < object_cloud->points.size(); nIndex++)
     {
         auto lower = object_cloud->points[nIndex].z - z;
         auto upper = height - object_cloud->points[nIndex].z;
@@ -368,7 +368,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     notTable_cloud->height = backup_cloud->height;
     notTable_cloud->is_dense = false;
     notTable_cloud->points.resize(notTable_cloud->width * notTable_cloud->height);
-    for (int nIndex = 0; nIndex < backup_cloud->points.size(); nIndex++)
+    for (uint nIndex = 0; nIndex < backup_cloud->points.size(); nIndex++)
     {
         auto lower = z - backup_cloud->points[nIndex].z;
         auto upper = height - backup_cloud->points[nIndex].z;
@@ -484,7 +484,7 @@ void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud
 {
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
-    for (int nIndex = 0; nIndex < cloud->points.size (); nIndex++)
+    for (uint nIndex = 0; nIndex < cloud->points.size (); nIndex++)
     {
         double x = cloud->points[nIndex].x;
         double y = cloud->points[nIndex].y;

From 17ef6e5e953c5beb5916b6d80808e60b8fb38a71 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Fri, 7 Apr 2023 20:49:57 +0200
Subject: [PATCH 088/136] mark req as unused parameter for now

---
 ed_sensor_integration/src/kinect/kinect_plugin.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.cpp b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
index dfee23a1..73053fab 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.cpp
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
@@ -275,7 +275,7 @@ bool KinectPlugin::srvRayTrace(ed_sensor_integration_msgs::RayTrace::Request& re
     return true;
 }
 
-bool KinectPlugin::srvPlaceArea(ed_sensor_integration_msgs::PlaceArea::Request& req, ed_sensor_integration_msgs::PlaceArea::Response& res)
+bool KinectPlugin::srvPlaceArea(__attribute__((unused)) ed_sensor_integration_msgs::PlaceArea::Request& req, ed_sensor_integration_msgs::PlaceArea::Response& res)
 {
     // - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     // Get new image

From e310862494fa54f99c6994ad6eff8c95d747b4d1 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Fri, 7 Apr 2023 21:34:26 +0200
Subject: [PATCH 089/136] add docstring

---
 .../include/ed/kinect/place_area_finder.h     | 74 ++++++++++++++++++-
 .../src/kinect/place_area_finder.cpp          | 41 ++++++++--
 2 files changed, 109 insertions(+), 6 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index b0bd3ff5..5b5604c3 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -13,6 +13,10 @@
 #include <pcl/point_cloud.h>
 #include <pcl/point_types.h>
 
+/**
+ * @brief Tool for finding placement options using rgbd sensor information.
+ *
+ */
 class PlaceAreaFinder
 {
 
@@ -22,8 +26,22 @@ class PlaceAreaFinder
 
     ~PlaceAreaFinder();
 
+
+    /**
+     * @brief find a horizontal surface suitable to place an object
+     *
+     * @param image image in which to find a place position
+     * @param sensor_pose pose of the sensor with respect to a horizontal plane 'base_link' recommended
+     * @param[out] place_pose one of the possible poses where an object may be placed
+     * @return whether or not a suitable place was found
+     */
     bool findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose);
 
+    /**
+     * @brief Get an image of the analysed space, used for introspection
+     *
+     * @param[out] image canvas to write the image to.
+     */
     void getCanvas(cv::Mat& image){ canvas.copyTo(image); }
 
 private:
@@ -32,13 +50,67 @@ class PlaceAreaFinder
     cv::Point2d canvas_center;
     cv::Mat canvas;
 
+    /**
+     * @brief transform a point in meters to a pixel on the canvas
+     *
+     * @param x in meters
+     * @param y in meters
+     * @return cv::Point2d
+     */
     cv::Point2d worldToCanvas(double x, double y);
+
+    /**
+     * @brief inverse of WorldToCanvas
+     *
+     * @param point point on the canvas
+     * @return geo::Vec2d matching point in 2D space
+     */
     geo::Vec2d canvasToWorld(cv::Point2d point);
+
+    /**
+     * @brief Draw the points in a pointcloud on the canvas. will ignore the z direction of the points
+     *
+     * @param cloud pointcloud to be rendered
+     * @param color color to render the points
+     */
     void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
+
+    /**
+     * @brief morphological closing operation
+     *
+     * @param canvas image to close
+     * @param closed_canvas image after closing
+     * @param placement_margin radius for closing in meters! will be converted internally. #TODO remove
+     */
     void closeCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin);
+
+    /**
+     * @brief morphological dilation
+     *
+     * @param canvas image to dilate
+     * @param dilated_canvas image after dilation
+     * @param placement_margin radius for dilation in meters! will be converted internally. #TODO remove
+     */
+    void dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin);
+
+    /**
+     * @brief not a clue, appears to be an erosion operation
+     *
+     * @param closed_canvas
+     * @param smallplane_canvas
+     * @param placement_margin
+     */
     void alterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin);
+
+    /**
+     * @brief Draw a Circle on the canvas indicating the prefered distance to the robot. This distance is currently hardcoded.
+     *
+     * @param canvas canvas to draw on
+     * @param color color to draw with
+     * @param placement_margin width of the semi-circle.
+     */
     void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin);
-    void dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin);
+
 };
 
 #endif
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 0ce74017..9167940f 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -36,6 +36,14 @@
 #include "ed_sensor_integration/sac_model_horizontal_plane.h"
 
 
+/**
+ * @brief transform an rgbd image to a pointcloud
+ * 
+ * @param image rgbd image
+ * @param[out] cloud pcl pointcloud, points are expressed in the frame of the camera according to pcl conventions
+ * @param FOVL to be removed
+ * @return double to be removed
+ */
 double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL)
 {
     // Fill in the cloud data
@@ -76,6 +84,12 @@ double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>:
 return image.getCameraModel().fx();
 }
 
+/**
+ * @brief transform a geolib pose into a transformation matrix from the Eigen library
+ * 
+ * @param pose geolib pose
+ * @return Eigen::Matrix4f 
+ */
 Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
 {
     // convert from geolib coordinates to ros coordinates #TODO remove geolib coordinates for camera pose
@@ -114,9 +128,12 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
 }
 
 /**
- * @brief SegmentPlane segment the pointcloud and return the cluster closest to the camera
- * @param cloud: pointcloud to be segmented, this function will change the pointcloud to only include the segmented cluster.
- * @return height of the segmented plane
+ * @brief segment the larges horizontal plane in the pointcloud. Horizontal is assumed to be normal to the z-axis. The plane is also assumed to be above z=0.0
+ * @param cloud_in pointcloud to be segmented
+ * @param cloud_in2 ? todo remove input, it is same as cloud_in
+ * @param cloud_out A pointcloud containing all points within the found plane
+ * @param cloud_no_plane A pointcloud containing all points not within the found plane
+ * @return height of the segmented plane OR -1.0 if no plane could be found
  */
 float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in2, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_no_plane)
 {
@@ -147,7 +164,7 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const
         return -1.0;
     }
 
-    // Extract the inliers to a cloud with a plane
+    // Extract the inliers to a cloud with just the plane
     extract.setInputCloud(cloud_in);
     extract.setIndices(inliers);
     extract.setNegative(false);
@@ -222,7 +239,13 @@ void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, floa
 }
 */
 
-
+/**
+ * @brief extract all pixels of a certain color from a canvas
+ * 
+ * @param canvas original image
+ * @param[out] placement_canvas image to draw the extracted pixels on must be the same size as canvas 
+ * @param targetColor color to be extracted
+ */
 void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor)
 {
 
@@ -247,6 +270,14 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
     }
 }
 
+/**
+ * @brief Get the coordinates of a point in an image which matches the target color
+ * 
+ * @param canvas image to check
+ * @param targetColor color to be found
+ * @param point coordinates of one point which has the targetColor
+ * @return whether or not a pixel was found
+ */
 bool GetPlacementOption(cv::Mat& canvas, cv::Scalar targetColor, cv::Point2d& point)
 {
     for(int row = 0; row <canvas.rows; ++row)

From ce693122ea9b3f528e6f6a597541b0849fa71b78 Mon Sep 17 00:00:00 2001
From: PetervDooren <19806646+PetervDooren@users.noreply.github.com>
Date: Fri, 7 Apr 2023 21:37:16 +0200
Subject: [PATCH 090/136] newline at eof

---
 ed_sensor_integration_msgs/srv/PlaceArea.srv | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration_msgs/srv/PlaceArea.srv b/ed_sensor_integration_msgs/srv/PlaceArea.srv
index efd1d087..f575de18 100644
--- a/ed_sensor_integration_msgs/srv/PlaceArea.srv
+++ b/ed_sensor_integration_msgs/srv/PlaceArea.srv
@@ -1,4 +1,4 @@
 # request info
 ---
 string error_msg  # empty if no error
-geometry_msgs/PoseStamped pose  # pose of a possible place location
\ No newline at end of file
+geometry_msgs/PoseStamped pose  # pose of a possible place location

From 633d15ee1738ad661cd3e773b15645e4b3313584 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Thu, 27 Apr 2023 20:49:46 +0100
Subject: [PATCH 091/136] Dilating per colour basis (not finished)

---
 .../tools/empty_spot_designator.cpp           | 319 ++++++++++++++++++
 1 file changed, 319 insertions(+)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 3b3d8fde..dc53a22a 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -64,7 +64,223 @@ void drawFoVMacro(geo::Vector3 direction, cv::Mat& canvas, geo::Pose3D sensor_po
 
     if (direction_world.z > 0.0)
     {
+<<<<<<< HEAD
         std::cout << "above plane" << std::endl;
+=======
+        double x = cloud->points[nIndex].x;
+        double y = cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+
+    
+}
+
+void createObjectCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, cv::Mat& canvas, cv::Scalar color)
+
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < object_cloud->points.size (); nIndex++)
+    {
+        double x = object_cloud->points[nIndex].x;
+        double y = object_cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+
+}
+
+void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud, cv::Mat& canvas, cv::Scalar color)
+
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < occluded_cloud->points.size (); nIndex++)
+    {
+        double x = occluded_cloud->points[nIndex].x;
+        double y = occluded_cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }   
+}
+
+void createNotTableCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud, cv::Mat& canvas, cv::Scalar color)
+
+{
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    for (int nIndex = 0; nIndex < notTable_cloud->points.size (); nIndex++)
+    {
+        double x = notTable_cloud->points[nIndex].x;
+        double y = notTable_cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }
+}
+
+void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, double fx)
+
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
+        {
+        float initial_x = x;
+        float initial_y = y;
+        double y = initial_y + (0.001)*nIndex;
+        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
+
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+        }
+}
+
+void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
+
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
+        {
+        float initial_x = x;
+        float initial_y = y;
+        double y = initial_y - 0.001*nIndex;
+        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
+
+        cv::Point2d p = worldToCanvas(x, y);
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+        }
+}
+
+void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height)
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        for (int i = 0; i < 100; i++)
+        {
+            for (int nIndex = 0; nIndex < 4000; nIndex++)
+            {
+            float initial_x = x;
+            float initial_y = y;
+            double y = initial_y + -2+ 0.001*nIndex;
+            double x = (initial_x + (z-height)*tan(67.0/(180/M_PI))); // 67.5 deg
+
+            cv::Point2d p = worldToCanvas(x, y);
+            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+            }
+        }
+}
+
+void CloseCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin)
+{
+    float Pixelsize = 5*(placement_margin / resolution);
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::dilate(canvas, closed_canvas, element );
+    cv::erode(closed_canvas, closed_canvas, element);
+}
+
+
+void AlterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin)
+{
+    float Pixelsize = 2*(placement_margin / resolution);
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::erode(closed_canvas, smallplane_canvas, element);
+}
+
+
+
+
+void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
+{
+        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+        float upper_radius = 0.75 + placement_margin/2;
+        float lower_radius = 0.60 - placement_margin/2;
+            for (float phi = 0; phi < 360; phi++)
+            {
+                for (int i = 0; i < 100; i++)
+                {
+                double y = upper_radius * sin(phi/(180/M_PI)) + 0.03 * i * sin(phi/(180/M_PI));
+                double x = upper_radius * cos(phi/(180/M_PI)) + 0.03 * i * cos(phi/(180/M_PI));
+
+                cv::Point2d p = worldToCanvas(x, y);
+                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+                }
+
+                for (int i = 0; i < 100; i++)
+                {
+                double y = lower_radius * sin(phi/(180/M_PI)) - lower_radius/100 * i * sin(phi/(180/M_PI));
+                double x = lower_radius * cos(phi/(180/M_PI)) - lower_radius/100 * i * cos(phi/(180/M_PI));
+
+                cv::Point2d p = worldToCanvas(x, y);
+                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+                }
+            }
+        
+}
+
+void dilateCostmap(cv::Mat& canvas, float placement_margin)
+{
+    float Pixelsize = placement_margin / resolution;
+    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
+                                             cv::Size( Pixelsize, Pixelsize),
+                                             cv::Point(-1, -1) );
+    cv::Scalar lower_red = cv::Scalar(0,0,100);
+    cv::Scalar upper_red = cv::Scalar(0,0,255);
+    cv::Mat red_mask;
+    cv::inRange(canvas, lower_red, upper_red, red_mask);
+    cv::Mat dilated_canvas;
+    cv::dilate(canvas, dilated_canvas, element, cv::Point(-1,-1),1,cv::BORDER_CONSTANT, cv::morphologyDefaultBorderValue());
+    dilated_canvas.setTo(cv::Scalar(0,0,255),red_mask);
+
+    // std::cout << "showing dilated costmap" << std::endl;
+    cv::imshow("Dilated costmap topview", dilated_canvas);
+}
+
+void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor, cv::Scalar point_color, double height)
+{
+
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    std::vector<cv::Point> identicalPoints;
+    cv::Point2d PlacementPoint;
+    bool found = false;
+
+    for(int row = canvas.rows; row > 0; --row)
+    {
+        for(int col = canvas.cols; col > 0; --col)
+        {
+            cv::Vec3b currPixel = canvas.at<cv::Vec3b>(row, col);
+            if(currPixel.val[0] == targetColor.val[0] &&
+               currPixel.val[1] == targetColor.val[1] &&
+               currPixel.val[2] == targetColor.val[2])
+            {
+                cv::Point2d p = cv::Point(col, row);
+                PlacementPoint = p;
+                found = true;
+                if (p.x >= 0 && p.y >= 0 && p.x < placement_canvas.cols && p.y < placement_canvas.rows)
+                    placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(targetColor[0], targetColor[1], targetColor[2]);
+            }
+        }
+    }
+
+    if (!found)
+>>>>>>> b07be61 (Dilating per colour basis (not finished))
         return;
     }
 
@@ -176,9 +392,105 @@ int main (int argc, char **argv)
         place_area_finder.getCanvas(canvas);
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
+<<<<<<< HEAD
         geo::Pose3D sensor_pose_canvas = sensor_pose;
         sensor_pose_canvas.t.z = sensor_pose.t.z - place_pose.t.z;
         drawFieldOfView(canvas, sensor_pose_canvas, image);
+=======
+        // Not table cloud
+        pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
+        notTable_cloud->width       = backup_cloud->width;
+        notTable_cloud->height      = backup_cloud->height;
+        notTable_cloud->is_dense    = false;
+        notTable_cloud->points.resize(notTable_cloud->width*notTable_cloud->height);
+        for (int nIndex = 0; nIndex < backup_cloud->points.size (); nIndex++)
+        {
+        auto lower  = z - backup_cloud->points[nIndex].z;
+        auto upper  = height - backup_cloud->points[nIndex].z;
+        auto lambda = upper / lower;
+        auto dx     = x - backup_cloud->points[nIndex].x;
+        auto dy     = y - backup_cloud->points[nIndex].y;       
+        notTable_cloud->points[nIndex].z = height;
+        notTable_cloud->points[nIndex].x = backup_cloud->points[nIndex].x + lambda * dx;
+        notTable_cloud->points[nIndex].y = backup_cloud->points[nIndex].y + lambda * dy;
+        }
+
+        
+        // std::cout << "creating costmap" << std::endl;
+        cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+        // cv::Mat dilated_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+        cv::Mat closed_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+        cv::Mat placement_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+        cv::Scalar table_color(0, 255, 0);
+        cv::Scalar occupied_color(0, 0, 255);
+        cv::Scalar occluded_color(255,0,0);
+        cv::Scalar radius_color(100,0,100);
+        cv::Scalar placement_color(100, 255, 100);
+        cv::Scalar point_color(255,0,0);
+
+        // Object placement margins
+        float object_diameter = 0.10;
+        float error_margin = 0.02;
+        float length = object_diameter + error_margin; 
+        float placement_margin = 2*0.02 + length;
+        
+        std::cout << "creating costmap" << std::endl;
+
+        // Add table plane to costmap
+        createCostmap(plane_cloud, canvas, table_color);
+
+        // Adding boundaries with morphological operations
+
+            // // Fill missing data gaps inside the table sheet cluster
+            // CloseCanvas(canvas, closed_canvas, placement_margin);
+
+            // // Decrease the size of the table plane to accomodate for the placement radius while taking dilation into account
+            // AlterPlane(closed_canvas, closed_canvas, placement_margin);
+                
+            // // Add objects to costmap
+            // createObjectCostmap(object_cloud, closed_canvas, occupied_color);
+
+            // // Add occluded space to costmap
+            // createOccludedCostmap(occluded_cloud, closed_canvas, occluded_color); 
+
+            // // HERO preferred radius
+            // createRadiusCostmap(closed_canvas, radius_color, placement_margin);
+
+            // // Dilate the costmap and create a new canvas
+            // dilateCostmap(closed_canvas, dilated_canvas, placement_margin);
+
+            // // Extract the placement options and choose a placement solution
+            // ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
+
+        // Adding boundaries with additional PCL data
+
+            // Add objects to costmap
+            createObjectCostmap(object_cloud, canvas, occupied_color);
+
+            // Add occluded space to costmap
+            createOccludedCostmap(occluded_cloud, canvas, occluded_color); 
+
+            // // Add not_Table to define the table edge                  
+            // createNotTableCostmap(notTable_cloud, canvas, occupied_color);             
+
+            // // FOV left
+            // createFOVLCostmap(canvas, occluded_color, transform(0,3), transform(1,3), fx);
+
+            // // FOV right
+            // createFOVRCostmap(canvas, occluded_color, transform(0,3), transform(1,3));
+
+            // // FOV down
+            // createFOVHCostmap(canvas, occluded_color, transform(0,3), transform(1,3), transform(2,3), height);
+
+            // // HERO preferred radius
+            // createRadiusCostmap(canvas, radius_color, placement_margin);
+
+            // Dilate the costmap and create a new canvas
+            dilateCostmap(canvas, placement_margin);
+
+            // // Extract the placement options and choose a placement solution
+            // ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);            
+>>>>>>> b07be61 (Dilating per colour basis (not finished))
 
         // Show the different canvasses
         
@@ -188,11 +500,18 @@ int main (int argc, char **argv)
         // // std::cout << "showing costmap" << std::endl;
         // cv::imshow("closed canvas topview", closed_canvas);
                 
+<<<<<<< HEAD
         // std::cout << "showing dilated costmap" << std::endl;
         //cv::imshow("Dilated costmap topview", dilated_canvas);
 
         // std::cout << "showing placement costmap" << std::endl;
         //cv::imshow("Placement options costmap topview", placement_canvas);
+=======
+
+
+        // // std::cout << "showing placement costmap" << std::endl;
+        // cv::imshow("Placement options costmap topview", placement_canvas);
+>>>>>>> b07be61 (Dilating per colour basis (not finished))
 
         // Show RGB snapshot
         cv::Mat rgbcanvas = image->getRGBImage();

From 6b58a001140c4f77c69d20c1772fec06b93e369f Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Thu, 27 Apr 2023 21:06:25 +0100
Subject: [PATCH 092/136] fix faulty merge

---
 .../tools/empty_spot_designator.cpp           | 319 ------------------
 1 file changed, 319 deletions(-)

diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index dc53a22a..3b3d8fde 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -64,223 +64,7 @@ void drawFoVMacro(geo::Vector3 direction, cv::Mat& canvas, geo::Pose3D sensor_po
 
     if (direction_world.z > 0.0)
     {
-<<<<<<< HEAD
         std::cout << "above plane" << std::endl;
-=======
-        double x = cloud->points[nIndex].x;
-        double y = cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
-
-    
-}
-
-void createObjectCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < object_cloud->points.size (); nIndex++)
-    {
-        double x = object_cloud->points[nIndex].x;
-        double y = object_cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
-
-}
-
-void createOccludedCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < occluded_cloud->points.size (); nIndex++)
-    {
-        double x = occluded_cloud->points[nIndex].x;
-        double y = occluded_cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }   
-}
-
-void createNotTableCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud, cv::Mat& canvas, cv::Scalar color)
-
-{
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    for (int nIndex = 0; nIndex < notTable_cloud->points.size (); nIndex++)
-    {
-        double x = notTable_cloud->points[nIndex].x;
-        double y = notTable_cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }
-}
-
-void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, double fx)
-
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
-        {
-        float initial_x = x;
-        float initial_y = y;
-        double y = initial_y + (0.001)*nIndex;
-        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
-
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-        }
-}
-
-void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
-
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
-        {
-        float initial_x = x;
-        float initial_y = y;
-        double y = initial_y - 0.001*nIndex;
-        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-        }
-}
-
-void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height)
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int i = 0; i < 100; i++)
-        {
-            for (int nIndex = 0; nIndex < 4000; nIndex++)
-            {
-            float initial_x = x;
-            float initial_y = y;
-            double y = initial_y + -2+ 0.001*nIndex;
-            double x = (initial_x + (z-height)*tan(67.0/(180/M_PI))); // 67.5 deg
-
-            cv::Point2d p = worldToCanvas(x, y);
-            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-            }
-        }
-}
-
-void CloseCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin)
-{
-    float Pixelsize = 5*(placement_margin / resolution);
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::dilate(canvas, closed_canvas, element );
-    cv::erode(closed_canvas, closed_canvas, element);
-}
-
-
-void AlterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin)
-{
-    float Pixelsize = 2*(placement_margin / resolution);
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::erode(closed_canvas, smallplane_canvas, element);
-}
-
-
-
-
-void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        float upper_radius = 0.75 + placement_margin/2;
-        float lower_radius = 0.60 - placement_margin/2;
-            for (float phi = 0; phi < 360; phi++)
-            {
-                for (int i = 0; i < 100; i++)
-                {
-                double y = upper_radius * sin(phi/(180/M_PI)) + 0.03 * i * sin(phi/(180/M_PI));
-                double x = upper_radius * cos(phi/(180/M_PI)) + 0.03 * i * cos(phi/(180/M_PI));
-
-                cv::Point2d p = worldToCanvas(x, y);
-                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-                }
-
-                for (int i = 0; i < 100; i++)
-                {
-                double y = lower_radius * sin(phi/(180/M_PI)) - lower_radius/100 * i * sin(phi/(180/M_PI));
-                double x = lower_radius * cos(phi/(180/M_PI)) - lower_radius/100 * i * cos(phi/(180/M_PI));
-
-                cv::Point2d p = worldToCanvas(x, y);
-                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-                }
-            }
-        
-}
-
-void dilateCostmap(cv::Mat& canvas, float placement_margin)
-{
-    float Pixelsize = placement_margin / resolution;
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::Scalar lower_red = cv::Scalar(0,0,100);
-    cv::Scalar upper_red = cv::Scalar(0,0,255);
-    cv::Mat red_mask;
-    cv::inRange(canvas, lower_red, upper_red, red_mask);
-    cv::Mat dilated_canvas;
-    cv::dilate(canvas, dilated_canvas, element, cv::Point(-1,-1),1,cv::BORDER_CONSTANT, cv::morphologyDefaultBorderValue());
-    dilated_canvas.setTo(cv::Scalar(0,0,255),red_mask);
-
-    // std::cout << "showing dilated costmap" << std::endl;
-    cv::imshow("Dilated costmap topview", dilated_canvas);
-}
-
-void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor, cv::Scalar point_color, double height)
-{
-
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    std::vector<cv::Point> identicalPoints;
-    cv::Point2d PlacementPoint;
-    bool found = false;
-
-    for(int row = canvas.rows; row > 0; --row)
-    {
-        for(int col = canvas.cols; col > 0; --col)
-        {
-            cv::Vec3b currPixel = canvas.at<cv::Vec3b>(row, col);
-            if(currPixel.val[0] == targetColor.val[0] &&
-               currPixel.val[1] == targetColor.val[1] &&
-               currPixel.val[2] == targetColor.val[2])
-            {
-                cv::Point2d p = cv::Point(col, row);
-                PlacementPoint = p;
-                found = true;
-                if (p.x >= 0 && p.y >= 0 && p.x < placement_canvas.cols && p.y < placement_canvas.rows)
-                    placement_canvas.at<cv::Vec3b>(p) = cv::Vec3b(targetColor[0], targetColor[1], targetColor[2]);
-            }
-        }
-    }
-
-    if (!found)
->>>>>>> b07be61 (Dilating per colour basis (not finished))
         return;
     }
 
@@ -392,105 +176,9 @@ int main (int argc, char **argv)
         place_area_finder.getCanvas(canvas);
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
-<<<<<<< HEAD
         geo::Pose3D sensor_pose_canvas = sensor_pose;
         sensor_pose_canvas.t.z = sensor_pose.t.z - place_pose.t.z;
         drawFieldOfView(canvas, sensor_pose_canvas, image);
-=======
-        // Not table cloud
-        pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud (new pcl::PointCloud<pcl::PointXYZRGB>);
-        notTable_cloud->width       = backup_cloud->width;
-        notTable_cloud->height      = backup_cloud->height;
-        notTable_cloud->is_dense    = false;
-        notTable_cloud->points.resize(notTable_cloud->width*notTable_cloud->height);
-        for (int nIndex = 0; nIndex < backup_cloud->points.size (); nIndex++)
-        {
-        auto lower  = z - backup_cloud->points[nIndex].z;
-        auto upper  = height - backup_cloud->points[nIndex].z;
-        auto lambda = upper / lower;
-        auto dx     = x - backup_cloud->points[nIndex].x;
-        auto dy     = y - backup_cloud->points[nIndex].y;       
-        notTable_cloud->points[nIndex].z = height;
-        notTable_cloud->points[nIndex].x = backup_cloud->points[nIndex].x + lambda * dx;
-        notTable_cloud->points[nIndex].y = backup_cloud->points[nIndex].y + lambda * dy;
-        }
-
-        
-        // std::cout << "creating costmap" << std::endl;
-        cv::Mat canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-        // cv::Mat dilated_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-        cv::Mat closed_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-        cv::Mat placement_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-        cv::Scalar table_color(0, 255, 0);
-        cv::Scalar occupied_color(0, 0, 255);
-        cv::Scalar occluded_color(255,0,0);
-        cv::Scalar radius_color(100,0,100);
-        cv::Scalar placement_color(100, 255, 100);
-        cv::Scalar point_color(255,0,0);
-
-        // Object placement margins
-        float object_diameter = 0.10;
-        float error_margin = 0.02;
-        float length = object_diameter + error_margin; 
-        float placement_margin = 2*0.02 + length;
-        
-        std::cout << "creating costmap" << std::endl;
-
-        // Add table plane to costmap
-        createCostmap(plane_cloud, canvas, table_color);
-
-        // Adding boundaries with morphological operations
-
-            // // Fill missing data gaps inside the table sheet cluster
-            // CloseCanvas(canvas, closed_canvas, placement_margin);
-
-            // // Decrease the size of the table plane to accomodate for the placement radius while taking dilation into account
-            // AlterPlane(closed_canvas, closed_canvas, placement_margin);
-                
-            // // Add objects to costmap
-            // createObjectCostmap(object_cloud, closed_canvas, occupied_color);
-
-            // // Add occluded space to costmap
-            // createOccludedCostmap(occluded_cloud, closed_canvas, occluded_color); 
-
-            // // HERO preferred radius
-            // createRadiusCostmap(closed_canvas, radius_color, placement_margin);
-
-            // // Dilate the costmap and create a new canvas
-            // dilateCostmap(closed_canvas, dilated_canvas, placement_margin);
-
-            // // Extract the placement options and choose a placement solution
-            // ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
-
-        // Adding boundaries with additional PCL data
-
-            // Add objects to costmap
-            createObjectCostmap(object_cloud, canvas, occupied_color);
-
-            // Add occluded space to costmap
-            createOccludedCostmap(occluded_cloud, canvas, occluded_color); 
-
-            // // Add not_Table to define the table edge                  
-            // createNotTableCostmap(notTable_cloud, canvas, occupied_color);             
-
-            // // FOV left
-            // createFOVLCostmap(canvas, occluded_color, transform(0,3), transform(1,3), fx);
-
-            // // FOV right
-            // createFOVRCostmap(canvas, occluded_color, transform(0,3), transform(1,3));
-
-            // // FOV down
-            // createFOVHCostmap(canvas, occluded_color, transform(0,3), transform(1,3), transform(2,3), height);
-
-            // // HERO preferred radius
-            // createRadiusCostmap(canvas, radius_color, placement_margin);
-
-            // Dilate the costmap and create a new canvas
-            dilateCostmap(canvas, placement_margin);
-
-            // // Extract the placement options and choose a placement solution
-            // ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);            
->>>>>>> b07be61 (Dilating per colour basis (not finished))
 
         // Show the different canvasses
         
@@ -500,18 +188,11 @@ int main (int argc, char **argv)
         // // std::cout << "showing costmap" << std::endl;
         // cv::imshow("closed canvas topview", closed_canvas);
                 
-<<<<<<< HEAD
         // std::cout << "showing dilated costmap" << std::endl;
         //cv::imshow("Dilated costmap topview", dilated_canvas);
 
         // std::cout << "showing placement costmap" << std::endl;
         //cv::imshow("Placement options costmap topview", placement_canvas);
-=======
-
-
-        // // std::cout << "showing placement costmap" << std::endl;
-        // cv::imshow("Placement options costmap topview", placement_canvas);
->>>>>>> b07be61 (Dilating per colour basis (not finished))
 
         // Show RGB snapshot
         cv::Mat rgbcanvas = image->getRGBImage();

From fbb6fe1f29c1f495a765b942d5191446b3cd04a5 Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Sun, 30 Apr 2023 08:40:06 +0100
Subject: [PATCH 093/136] Remove morphological implementation + fix comments

---
 .../include/ed/kinect/place_area_finder.h     |  22 +---
 .../src/kinect/place_area_finder.cpp          | 122 ++----------------
 .../tools/empty_spot_designator.cpp           |   9 +-
 3 files changed, 14 insertions(+), 139 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index 5b5604c3..c70ca021 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -32,7 +32,7 @@ class PlaceAreaFinder
      *
      * @param image image in which to find a place position
      * @param sensor_pose pose of the sensor with respect to a horizontal plane 'base_link' recommended
-     * @param[out] place_pose one of the possible poses where an object may be placed
+     * @param[out] place_pose one of the possible poses where an object may be placed, currently returns the pose furthest on the table
      * @return whether or not a suitable place was found
      */
     bool findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose);
@@ -75,15 +75,6 @@ class PlaceAreaFinder
      */
     void createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
 
-    /**
-     * @brief morphological closing operation
-     *
-     * @param canvas image to close
-     * @param closed_canvas image after closing
-     * @param placement_margin radius for closing in meters! will be converted internally. #TODO remove
-     */
-    void closeCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin);
-
     /**
      * @brief morphological dilation
      *
@@ -93,21 +84,12 @@ class PlaceAreaFinder
      */
     void dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin);
 
-    /**
-     * @brief not a clue, appears to be an erosion operation
-     *
-     * @param closed_canvas
-     * @param smallplane_canvas
-     * @param placement_margin
-     */
-    void alterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin);
-
     /**
      * @brief Draw a Circle on the canvas indicating the prefered distance to the robot. This distance is currently hardcoded.
      *
      * @param canvas canvas to draw on
      * @param color color to draw with
-     * @param placement_margin width of the semi-circle.
+     * @param placement_margin 
      */
     void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin);
 
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 9167940f..add6c6a6 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -183,61 +183,6 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const
     return abs(coefficients->values[3]);
 }
 
-/*
-void createFOVLCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, double fx)
-
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
-        {
-        float initial_x = x;
-        float initial_y = y;
-        double y = initial_y + (0.001)*nIndex;
-        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
-
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-        }
-}
-
-void createFOVRCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y)
-
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int nIndex = 0; nIndex < 3000 ; nIndex++)
-        {
-        float initial_x = x;
-        float initial_y = y;
-        double y = initial_y - 0.001*nIndex;
-        double x = initial_x + 0.001*nIndex*tan(60/(180/M_PI));
-
-        cv::Point2d p = worldToCanvas(x, y);
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-        }
-}
-
-void createFOVHCostmap(cv::Mat& canvas, cv::Scalar color, float x, float y, float z, float height)
-{
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        for (int i = 0; i < 100; i++)
-        {
-            for (int nIndex = 0; nIndex < 4000; nIndex++)
-            {
-            float initial_x = x;
-            float initial_y = y;
-            double y = initial_y + -2+ 0.001*nIndex;
-            double x = (initial_x + (z-height)*tan(67.0/(180/M_PI))); // 67.5 deg
-
-            cv::Point2d p = worldToCanvas(x, y);
-            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-            }
-        }
-}
-*/
 
 /**
  * @brief extract all pixels of a certain color from a canvas
@@ -434,48 +379,16 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     // Add table plane to costmap
     createCostmap(plane_cloud, table_color);
 
-    // Adding boundaries with morphological operations
-
-    // // Fill missing data gaps inside the table sheet cluster
-    // CloseCanvas(canvas, closed_canvas, placement_margin);
-
-    // // Decrease the size of the table plane to accomodate for the placement radius while taking dilation into account
-    // AlterPlane(closed_canvas, closed_canvas, placement_margin);
-
-    // // Add objects to costmap
-    // createObjectCostmap(object_cloud, closed_canvas, occupied_color);
-
-    // // Add occluded space to costmap
-    // createOccludedCostmap(occluded_cloud, closed_canvas, occluded_color);
-
-    // // HERO preferred radius
-    // createRadiusCostmap(closed_canvas, radius_color, placement_margin);
-
-    // // Dilate the costmap and create a new canvas
-    // dilateCostmap(closed_canvas, dilated_canvas, placement_margin);
-
-    // // Extract the placement options and choose a placement solution
-    // ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color, point_color, height);
-
     // Adding boundaries with additional PCL data
 
-    // Add objects to costmap
-    createCostmap(object_cloud, occupied_color);
-
-    // Add occluded space to costmap
-    createCostmap(occluded_cloud, occluded_color);
-
-    // Add not_Table to define the table edge
-    createCostmap(notTable_cloud, occupied_color);
+        // Add objects to costmap
+        createCostmap(object_cloud, occupied_color);
 
-    // FOV left
-//    createFOVLCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3), fx);
+        // Add occluded space to costmap
+        createCostmap(occluded_cloud, occluded_color);
 
-    // FOV right
-  //  createFOVRCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3));
-
-    // FOV down
-   // createFOVHCostmap(canvas, occluded_color, transform(0, 3), transform(1, 3), transform(2, 3), height);
+        // Add not_Table to define the table edge
+        createCostmap(notTable_cloud, occupied_color);
 
     // HERO preferred radius
     createRadiusCostmap(canvas, radius_color, placement_margin);
@@ -526,28 +439,8 @@ void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud
     }    
 }
 
-void PlaceAreaFinder::closeCanvas(cv::Mat& canvas, cv::Mat& closed_canvas, float placement_margin)
-{
-    float Pixelsize = 5*(placement_margin / resolution);
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::dilate(canvas, closed_canvas, element );
-    cv::erode(closed_canvas, closed_canvas, element);
-}
-
-
-void PlaceAreaFinder::alterPlane(cv::Mat& closed_canvas, cv::Mat& smallplane_canvas, float placement_margin)
-{
-    float Pixelsize = 2*(placement_margin / resolution);
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::erode(closed_canvas, smallplane_canvas, element);
-}
-
-
 void PlaceAreaFinder::createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
+
 {
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
         float upper_radius = 0.75 + placement_margin/2;
@@ -586,3 +479,4 @@ void PlaceAreaFinder::dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, fl
     cv::dilate(canvas, dilated_canvas, element );
 
 }
+
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 3b3d8fde..3faaaf9d 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -175,7 +175,6 @@ int main (int argc, char **argv)
         cv::Mat canvas;
         place_area_finder.getCanvas(canvas);
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
         geo::Pose3D sensor_pose_canvas = sensor_pose;
         sensor_pose_canvas.t.z = sensor_pose.t.z - place_pose.t.z;
         drawFieldOfView(canvas, sensor_pose_canvas, image);
@@ -188,11 +187,11 @@ int main (int argc, char **argv)
         // // std::cout << "showing costmap" << std::endl;
         // cv::imshow("closed canvas topview", closed_canvas);
                 
-        // std::cout << "showing dilated costmap" << std::endl;
-        //cv::imshow("Dilated costmap topview", dilated_canvas);
+        // // std::cout << "showing dilated costmap" << std::endl;
+        // cv::imshow("Dilated costmap topview", dilated_canvas);
 
-        // std::cout << "showing placement costmap" << std::endl;
-        //cv::imshow("Placement options costmap topview", placement_canvas);
+        // // std::cout << "showing placement costmap" << std::endl;
+        // cv::imshow("Placement options costmap topview", placement_canvas);
 
         // Show RGB snapshot
         cv::Mat rgbcanvas = image->getRGBImage();

From d93ef33f975504a7f53446e230c4f7a3e2ac54ca Mon Sep 17 00:00:00 2001
From: MaxVroonhoven <m.l.m.v.vroonhoven@student.tue.nl>
Date: Tue, 16 May 2023 20:14:38 +0200
Subject: [PATCH 094/136] Add dilated/placement canvas for introspection

---
 .../include/ed/kinect/place_area_finder.h     | 19 ++++++++++++++++++-
 ed_sensor_integration/src/kinect/fitter.cpp   |  6 +++---
 .../src/kinect/place_area_finder.cpp          | 10 +++++++---
 .../tools/empty_spot_designator.cpp           | 16 ++++++++--------
 4 files changed, 36 insertions(+), 15 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index c70ca021..a434fa41 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -42,13 +42,30 @@ class PlaceAreaFinder
      *
      * @param[out] image canvas to write the image to.
      */
-    void getCanvas(cv::Mat& image){ canvas.copyTo(image); }
+    void getCanvas(cv::Mat& image){ canvas.copyTo(image);}
+
+    /**
+     * @brief Dilate the image, used for introspection
+     *
+     * @param[out] image canvas to write the image to.
+     */
+    void getDilatedCanvas(cv::Mat& image){ dilated_canvas.copyTo(image);}
+
+    /**
+     * @brief Shows the available placement points, used for introspection
+     *
+     * @param[out] image canvas to write the image to.
+     */
+    void getPlacementCanvas(cv::Mat& image){ placement_canvas.copyTo(image);}
+
 
 private:
     // internal occupancy representation
     double resolution = 0.005;
     cv::Point2d canvas_center;
     cv::Mat canvas;
+    cv::Mat dilated_canvas;
+    cv::Mat placement_canvas;
 
     /**
      * @brief transform a point in meters to a pixel on the canvas
diff --git a/ed_sensor_integration/src/kinect/fitter.cpp b/ed_sensor_integration/src/kinect/fitter.cpp
index 59f6783a..40e8e90b 100644
--- a/ed_sensor_integration/src/kinect/fitter.cpp
+++ b/ed_sensor_integration/src/kinect/fitter.cpp
@@ -416,7 +416,7 @@ bool Fitter::evaluateCandidate(const EstimationInputData &static_data, Candidate
 
 Shape2D Fitter::get2DShape(ed::EntityConstPtr entity_ptr) const
 {
-    if (!entity_ptr->shape())
+    if (!entity_ptr->visual())
         throw FitterError("Entity " + entity_ptr->id().str() + " has no shape");
 
     EntityRepresentation2D repr_2d = GetOrCreateEntity2D(entity_ptr);
@@ -538,7 +538,7 @@ EntityRepresentation2D Fitter::GetOrCreateEntity2D(const ed::EntityConstPtr& e)
     decomposePose(e->pose(), pose_xya, pose_zrp);
 
     EntityRepresentation2D& entity_model = entity_shapes_[e->id()];
-    dml::project2D(e->shape()->getMesh().getTransformed(pose_zrp), entity_model.shape_2d);
+    dml::project2D(e->visual()->getMesh().getTransformed(pose_zrp), entity_model.shape_2d);
 
     return entity_model;
 }
@@ -553,7 +553,7 @@ void Fitter::renderEntity(const ed::EntityConstPtr& e, const geo::Pose3D& sensor
     if (model_ranges.size() != beam_model_.num_beams())
         model_ranges.resize(beam_model_.num_beams(), 0);
 
-    if (!e->shape() || !e->has_pose())
+    if (!e->visual() || !e->has_pose())
         return;
 
     // Decompose entity pose into X Y YAW and Z ROLL PITCH
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index add6c6a6..4d48f631 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -358,9 +358,8 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
 
     // std::cout << "creating costmap" << std::endl;
     canvas = cv::Mat(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-    cv::Mat dilated_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-    cv::Mat closed_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
-    cv::Mat placement_canvas(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+    dilated_canvas = cv::Mat(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
+    placement_canvas = cv::Mat(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
     cv::Scalar table_color(0, 255, 0);
     cv::Scalar occupied_color(0, 0, 255);
     cv::Scalar occluded_color(255, 0, 0);
@@ -396,6 +395,11 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     // Dilate the costmap and create a new canvas
     dilateCostmap(canvas, dilated_canvas, placement_margin);
 
+    ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color);
+    
+
+
+
     // Extract the placement options and choose a placement solution
     cv::Point2d place_point_canvas;
     if (!GetPlacementOption(dilated_canvas, table_color, place_point_canvas))
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 3faaaf9d..c6040775 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -173,25 +173,25 @@ int main (int argc, char **argv)
         std::cout << place_pose << std::endl;
 
         cv::Mat canvas;
+        cv::Mat dilated_canvas;
+        cv::Mat placement_canvas;
         place_area_finder.getCanvas(canvas);
+        place_area_finder.getDilatedCanvas(dilated_canvas);
+        place_area_finder.getPlacementCanvas(placement_canvas);
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
         geo::Pose3D sensor_pose_canvas = sensor_pose;
         sensor_pose_canvas.t.z = sensor_pose.t.z - place_pose.t.z;
         drawFieldOfView(canvas, sensor_pose_canvas, image);
-
         // Show the different canvasses
         
         // std::cout << "showing costmap" << std::endl;
         cv::imshow("Costmap topview", canvas);
-
-        // // std::cout << "showing costmap" << std::endl;
-        // cv::imshow("closed canvas topview", closed_canvas);
                 
-        // // std::cout << "showing dilated costmap" << std::endl;
-        // cv::imshow("Dilated costmap topview", dilated_canvas);
+        // std::cout << "showing dilated costmap" << std::endl;
+        cv::imshow("Dilated costmap topview", dilated_canvas);
 
-        // // std::cout << "showing placement costmap" << std::endl;
-        // cv::imshow("Placement options costmap topview", placement_canvas);
+        // std::cout << "showing placement costmap" << std::endl;
+        cv::imshow("Placement options costmap topview", placement_canvas);
 
         // Show RGB snapshot
         cv::Mat rgbcanvas = image->getRGBImage();

From 87188285c7dc39f77b8ccf448034ccae32724c39 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Mon, 17 Jul 2023 16:20:59 +0200
Subject: [PATCH 095/136] spacing

---
 .../include/ed/kinect/place_area_finder.h     |  2 +-
 .../src/kinect/place_area_finder.cpp          | 66 ++++++++-----------
 2 files changed, 30 insertions(+), 38 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index a434fa41..9675b0a8 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -32,7 +32,7 @@ class PlaceAreaFinder
      *
      * @param image image in which to find a place position
      * @param sensor_pose pose of the sensor with respect to a horizontal plane 'base_link' recommended
-     * @param[out] place_pose one of the possible poses where an object may be placed, currently returns the pose furthest on the table
+     * @param[out] place_pose expressed in the same frame as sensor pose. One of the possible poses where an object may be placed, currently returns the pose furthest on the table
      * @return whether or not a suitable place was found
      */
     bool findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose);
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 4d48f631..2f84d9c5 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -170,7 +170,6 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const
     extract.setNegative(false);
     extract.filter(*cloud_out);
 
-    
     // std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
     //   << "Plane with coefficients: " << *coefficients << std::endl;
 
@@ -193,7 +192,6 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const
  */
 void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor)
 {
-
     cv::Point2d canvas_center(canvas.rows / 2, canvas.cols);
 
     std::vector<cv::Point> identicalPoints;
@@ -380,14 +378,14 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
 
     // Adding boundaries with additional PCL data
 
-        // Add objects to costmap
-        createCostmap(object_cloud, occupied_color);
+    // Add objects to costmap
+    createCostmap(object_cloud, occupied_color);
 
-        // Add occluded space to costmap
-        createCostmap(occluded_cloud, occluded_color);
+    // Add occluded space to costmap
+    createCostmap(occluded_cloud, occluded_color);
 
-        // Add not_Table to define the table edge
-        createCostmap(notTable_cloud, occupied_color);
+    // Add not_Table to define the table edge
+    createCostmap(notTable_cloud, occupied_color);
 
     // HERO preferred radius
     createRadiusCostmap(canvas, radius_color, placement_margin);
@@ -396,9 +394,6 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     dilateCostmap(canvas, dilated_canvas, placement_margin);
 
     ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color);
-    
-
-
 
     // Extract the placement options and choose a placement solution
     cv::Point2d place_point_canvas;
@@ -444,34 +439,32 @@ void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud
 }
 
 void PlaceAreaFinder::createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
-
 {
-        canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-        float upper_radius = 0.75 + placement_margin/2;
-        float lower_radius = 0.60 - placement_margin/2;
-            for (float phi = 0; phi < 360; phi++)
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+    float upper_radius = 0.75 + placement_margin/2;
+    float lower_radius = 0.60 - placement_margin/2;
+        for (float phi = 0; phi < 360; phi++)
+        {
+            for (int i = 0; i < 100; i++)
             {
-                for (int i = 0; i < 100; i++)
-                {
-                double y = upper_radius * sin(phi/(180/M_PI)) + 0.03 * i * sin(phi/(180/M_PI));
-                double x = upper_radius * cos(phi/(180/M_PI)) + 0.03 * i * cos(phi/(180/M_PI));
-
-                cv::Point2d p = worldToCanvas(x, y);
-                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-                }
-
-                for (int i = 0; i < 100; i++)
-                {
-                double y = lower_radius * sin(phi/(180/M_PI)) - lower_radius/100 * i * sin(phi/(180/M_PI));
-                double x = lower_radius * cos(phi/(180/M_PI)) - lower_radius/100 * i * cos(phi/(180/M_PI));
-
-                cv::Point2d p = worldToCanvas(x, y);
-                if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-                }
+            double y = upper_radius * sin(phi/(180/M_PI)) + 0.03 * i * sin(phi/(180/M_PI));
+            double x = upper_radius * cos(phi/(180/M_PI)) + 0.03 * i * cos(phi/(180/M_PI));
+
+            cv::Point2d p = worldToCanvas(x, y);
+            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
             }
-        
+
+            for (int i = 0; i < 100; i++)
+            {
+            double y = lower_radius * sin(phi/(180/M_PI)) - lower_radius/100 * i * sin(phi/(180/M_PI));
+            double x = lower_radius * cos(phi/(180/M_PI)) - lower_radius/100 * i * cos(phi/(180/M_PI));
+
+            cv::Point2d p = worldToCanvas(x, y);
+            if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+            }
+        }
 }
 
 void PlaceAreaFinder::dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin)
@@ -481,6 +474,5 @@ void PlaceAreaFinder::dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, fl
                                              cv::Size( Pixelsize, Pixelsize),
                                              cv::Point(-1, -1) );
     cv::dilate(canvas, dilated_canvas, element );
-
 }
 

From 305acab19673011c4b2d7932b7deadf52cdeaad0 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Wed, 19 Jul 2023 15:31:06 +0200
Subject: [PATCH 096/136] cleanup functions

---
 .../src/kinect/place_area_finder.cpp          | 208 +++++++++---------
 1 file changed, 103 insertions(+), 105 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 2f84d9c5..ffdb3136 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -41,10 +41,9 @@
  * 
  * @param image rgbd image
  * @param[out] cloud pcl pointcloud, points are expressed in the frame of the camera according to pcl conventions
- * @param FOVL to be removed
  * @return double to be removed
  */
-double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL)
+double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
 {
     // Fill in the cloud data
     cloud->width = image.getDepthImage().cols;
@@ -52,11 +51,6 @@ double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>:
     cloud->is_dense = false;
     cloud->resize (cloud->width * cloud->height);
 
-    FOVL->width = cloud->width;
-    FOVL->height = image.getDepthImage().rows;
-    FOVL->is_dense = false;
-    FOVL->resize (FOVL->width * FOVL->height);
-
     double fx = image.getCameraModel().fx();
     double fy = image.getCameraModel().fy();
 
@@ -130,14 +124,13 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
 /**
  * @brief segment the larges horizontal plane in the pointcloud. Horizontal is assumed to be normal to the z-axis. The plane is also assumed to be above z=0.0
  * @param cloud_in pointcloud to be segmented
- * @param cloud_in2 ? todo remove input, it is same as cloud_in
+ * @param plane_coefficients the 4 coefficients that define a parallel plane
  * @param cloud_out A pointcloud containing all points within the found plane
  * @param cloud_no_plane A pointcloud containing all points not within the found plane
  * @return height of the segmented plane OR -1.0 if no plane could be found
  */
-float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in2, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_no_plane)
+bool SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::ModelCoefficients::Ptr plane_coefficients, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_no_plane)
 {
-    pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ());
     pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
     // Create the segmentation object
     pcl::SACSegmentation<pcl::PointXYZRGB> seg;
@@ -157,11 +150,11 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const
 
     // Segment the largest planar component from the remaining cloud
     seg.setInputCloud(cloud_in);
-    seg.segment(*inliers, *coefficients);
+    seg.segment(*inliers, *plane_coefficients);
 
     if (inliers->indices.size() == 0) {
         std::cerr << "Could not estimate a planar model for the given dataset." << std::endl;
-        return -1.0;
+        return false;
     }
 
     // Extract the inliers to a cloud with just the plane
@@ -174,12 +167,12 @@ float SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, const
     //   << "Plane with coefficients: " << *coefficients << std::endl;
 
     // Extract outliers to the main cloud without the table plane
-    extract2.setInputCloud(cloud_in2);
+    extract2.setInputCloud(cloud_in);
     extract2.setIndices(inliers);
     extract2.setNegative(true);
     extract2.filter(*cloud_no_plane);
 
-    return abs(coefficients->values[3]);
+    return true;
 }
 
 
@@ -240,6 +233,76 @@ bool GetPlacementOption(cv::Mat& canvas, cv::Scalar targetColor, cv::Point2d& po
     return false;
 }
 
+/**
+ * @brief remove the floor from a pointcloud cloud_in and return the cloud_out with index. It is assumed the floor is aligned with the plane z=0
+ * 
+ * @param cloud_in 
+ * @param cloud_out 
+ * @param index 
+ */
+void removeFloor(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::Indices &index)
+{
+    float buffer = 0.1;
+    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond(new pcl::ConditionAnd<pcl::PointXYZRGB>());
+    range_cond->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::GT, buffer)));
+    // build the filter
+    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
+    condrem.setCondition(range_cond);
+    condrem.setInputCloud(cloud_in);
+    condrem.setKeepOrganized(true);
+    // apply filter
+    condrem.filter(*cloud_out);
+    (*cloud_out).is_dense = false;
+    pcl::removeNaNFromPointCloud(*cloud_out, *cloud_out, index);
+}
+
+void filterHeight(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, float height_min, float height_max, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::Indices &index)
+{
+    // Filter out objects above the table plane and put them in seperate cloud
+    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond(new pcl::ConditionAnd<pcl::PointXYZRGB>());
+    range_cond->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::GT, height_min)));
+    range_cond->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::LT, height_max)));
+    // build the filter
+    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem2;
+    condrem2.setCondition(range_cond);
+    condrem2.setInputCloud(cloud_in);
+    condrem2.setKeepOrganized(true);
+    // apply filter
+    condrem2.filter(*cloud_out);
+    pcl::removeNaNFromPointCloud(*cloud_out, *cloud_out, index);
+}
+
+/**
+ * @brief Project a plane onto a a plane along the beams of the camera
+ * 
+ * @param cloud_in cloud with points to be projected
+ * @param transform transform between the camera and the origin of the cloud in
+ * @param plane_height height of the plane to be projected onto.
+ * @param cloud_out cloud containing points with z=height
+ */
+void projectToPlane(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, Eigen::Matrix4f transform, float plane_height, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out)
+{
+    cloud_out->width = cloud_in->width;
+    cloud_out->height = cloud_in->height;
+    cloud_out->is_dense = cloud_in->is_dense;
+    cloud_out->points.resize(cloud_out->width * cloud_out->height);
+    float x = transform(0, 3);
+    float y = transform(1, 3);
+    float z = transform(2, 3);
+    for (uint nIndex = 0; nIndex < cloud_in->points.size(); nIndex++)
+    {
+        float lower = cloud_in->points[nIndex].z - z; // height between camera and point. 
+        float upper = plane_height - cloud_in->points[nIndex].z; // height between the point and the table
+        float lambda = upper / lower; // ratio between camera-point distance and point-projection distance
+        float dx = cloud_in->points[nIndex].x - x; // difference between point x and camera x
+        float dy = cloud_in->points[nIndex].y - y; // difference between point y and camera y
+
+        cloud_out->points[nIndex].z = plane_height;
+        cloud_out->points[nIndex].x = cloud_in->points[nIndex].x + lambda * dx;
+        cloud_out->points[nIndex].y = cloud_in->points[nIndex].y + lambda * dy;
+    }
+}
+
 PlaceAreaFinder::PlaceAreaFinder()
 {
 }
@@ -252,9 +315,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
 {
     // std::cout << "converting image to cloud" << std::endl;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-    pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVL(new pcl::PointCloud<pcl::PointXYZRGB>);
-    pcl::PointCloud<pcl::PointXYZRGB>::Ptr FOVR(new pcl::PointCloud<pcl::PointXYZRGB>);
-    imageToCloud(*image, cloud, FOVL);
+    imageToCloud(*image, cloud);
 
     // transform to base link frame
     Eigen::Matrix4f transform = geolibToEigen(sensor_pose);
@@ -262,97 +323,42 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
 
     // keep track of the indices in the original image
     std::vector<int> indices;
+    pcl::Indices floorless_index;
 
     // Filter out floor
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr floorless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    removeFloor(cloud, floorless_cloud, floorless_index);
 
-    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond(new pcl::ConditionAnd<pcl::PointXYZRGB>());
-    range_cond->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::GT, 0.1)));
-    // build the filter
-    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem;
-    condrem.setCondition(range_cond);
-    condrem.setInputCloud(cloud);
-    condrem.setKeepOrganized(true);
-    // apply filter
-    condrem.filter(*floorless_cloud);
-    (*floorless_cloud).is_dense = false;
-    pcl::removeNaNFromPointCloud(*floorless_cloud, *floorless_cloud, indices);
-
+    // Segment the table plane and return a cloud with the plane and a cloud where the plane is removed
     std::cout << "SegmentPlane" << std::endl;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr plane_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr planeless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-
-    // Segment the table plane and return a cloud with the plane and a cloud where the plane is removed
-    float height = SegmentPlane(floorless_cloud, floorless_cloud, plane_cloud, planeless_cloud);
+    pcl::ModelCoefficients::Ptr plane_coefficients (new pcl::ModelCoefficients ());
+    if (!SegmentPlane(floorless_cloud, plane_coefficients, plane_cloud, planeless_cloud))
+    {
+        std::cout << "Could not find plane" << std::endl;
+        return false;
+    }
+    float height = abs(plane_coefficients->values[3]); // take the absolute value in case the plane is fitted upside down
     std::cout << "Found plane height " << height << std::endl;
 
-    // Filter out objects abov the table plane and put them in seperate cloud
+    // Filter out objects above the table plane and put them in seperate cloud
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond2(new pcl::ConditionAnd<pcl::PointXYZRGB>());
-    range_cond2->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::GT, height)));
-    range_cond2->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::LT, height + 0.30)));
-    // build the filter
-    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem2;
-    condrem2.setCondition(range_cond2);
-    condrem2.setInputCloud(planeless_cloud);
-    condrem2.setKeepOrganized(true);
-    // apply filter
-    condrem2.filter(*object_cloud);
-    pcl::removeNaNFromPointCloud(*object_cloud, *object_cloud, indices);
+    pcl::Indices object_index;
+    filterHeight(planeless_cloud, height, height+0.30, object_cloud, object_index);
 
     // Create pointcloud with occluded space based on the object cloud
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-    occluded_cloud->width = object_cloud->width;
-    occluded_cloud->height = object_cloud->height;
-    occluded_cloud->is_dense = false;
-    occluded_cloud->points.resize(occluded_cloud->width * occluded_cloud->height);
-    float x = transform(0, 3);
-    float y = transform(1, 3);
-    float z = transform(2, 3);
-    for (uint nIndex = 0; nIndex < object_cloud->points.size(); nIndex++)
-    {
-        auto lower = object_cloud->points[nIndex].z - z;
-        auto upper = height - object_cloud->points[nIndex].z;
-        auto lambda = upper / lower;
-        auto dx = object_cloud->points[nIndex].x - x;
-        auto dy = object_cloud->points[nIndex].y - y;
-
-        occluded_cloud->points[nIndex].z = height;
-        occluded_cloud->points[nIndex].x = object_cloud->points[nIndex].x + lambda * dx;
-        occluded_cloud->points[nIndex].y = object_cloud->points[nIndex].y + lambda * dy;
-    }
+    projectToPlane(object_cloud, transform, height, occluded_cloud);
 
-    // Filter out items below table to create not table cloud
-    pcl::PointCloud<pcl::PointXYZRGB>::Ptr backup_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-    pcl::ConditionAnd<pcl::PointXYZRGB>::Ptr range_cond3(new pcl::ConditionAnd<pcl::PointXYZRGB>());
-    range_cond3->addComparison(pcl::FieldComparison<pcl::PointXYZRGB>::ConstPtr(new pcl::FieldComparison<pcl::PointXYZRGB>("z", pcl::ComparisonOps::LT, height - 0.02)));
-    // build the filter
-    pcl::ConditionalRemoval<pcl::PointXYZRGB> condrem3;
-    condrem3.setCondition(range_cond3);
-    condrem3.setInputCloud(floorless_cloud);
-    condrem3.setKeepOrganized(true);
-    // apply filter
-    condrem3.filter(*backup_cloud);
-    (*backup_cloud).is_dense = false;
-    pcl::removeNaNFromPointCloud(*backup_cloud, *backup_cloud, indices);
-
-    // Not table cloud
-    pcl::PointCloud<pcl::PointXYZRGB>::Ptr notTable_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-    notTable_cloud->width = backup_cloud->width;
-    notTable_cloud->height = backup_cloud->height;
-    notTable_cloud->is_dense = false;
-    notTable_cloud->points.resize(notTable_cloud->width * notTable_cloud->height);
-    for (uint nIndex = 0; nIndex < backup_cloud->points.size(); nIndex++)
-    {
-        auto lower = z - backup_cloud->points[nIndex].z;
-        auto upper = height - backup_cloud->points[nIndex].z;
-        auto lambda = upper / lower;
-        auto dx = x - backup_cloud->points[nIndex].x;
-        auto dy = y - backup_cloud->points[nIndex].y;
-        notTable_cloud->points[nIndex].z = height;
-        notTable_cloud->points[nIndex].x = backup_cloud->points[nIndex].x + lambda * dx;
-        notTable_cloud->points[nIndex].y = backup_cloud->points[nIndex].y + lambda * dy;
-    }
+    // Filter out objects below the table plane and put them in seperate cloud
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr below_table_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::Indices below_index;
+    filterHeight(planeless_cloud, 0.0, height-0.02, below_table_cloud, below_index);
+
+    // Create pointcloud with unoccluded space based on the bewow table cloud
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr not_table_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    projectToPlane(below_table_cloud, transform, height, not_table_cloud);    
 
     // std::cout << "creating costmap" << std::endl;
     canvas = cv::Mat(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
@@ -365,7 +371,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     cv::Scalar placement_color(100, 255, 100);
     cv::Scalar point_color(255, 0, 0);
 
-    // Object placement margins
+    // Object placement margins #TODO hardcoded parameters
     float object_diameter = 0.10;
     float error_margin = 0.02;
     float length = object_diameter + error_margin;
@@ -373,19 +379,11 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
 
     std::cout << "creating costmap" << std::endl;
 
-    // Add table plane to costmap
+    // draw clouds to costmap
     createCostmap(plane_cloud, table_color);
-
-    // Adding boundaries with additional PCL data
-
-    // Add objects to costmap
     createCostmap(object_cloud, occupied_color);
-
-    // Add occluded space to costmap
     createCostmap(occluded_cloud, occluded_color);
-
-    // Add not_Table to define the table edge
-    createCostmap(notTable_cloud, occupied_color);
+    createCostmap(not_table_cloud, occupied_color);
 
     // HERO preferred radius
     createRadiusCostmap(canvas, radius_color, placement_margin);

From 6ca80380845f7c03f692e0cb629bee81084834e4 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Wed, 19 Jul 2023 16:52:34 +0200
Subject: [PATCH 097/136] add annotated image functionality (still need to draw
 the right things)

---
 .../include/ed/kinect/place_area_finder.h      | 18 ++++++++++++++++++
 .../src/kinect/place_area_finder.cpp           | 18 ++++++++++++++++++
 .../tools/empty_spot_designator.cpp            |  6 ++++++
 3 files changed, 42 insertions(+)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index 9675b0a8..2444059e 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -10,6 +10,7 @@
 #include <opencv2/highgui.hpp>
 #include <opencv2/core/core.hpp>
 
+#include <pcl/filters/filter.h>
 #include <pcl/point_cloud.h>
 #include <pcl/point_types.h>
 
@@ -58,6 +59,13 @@ class PlaceAreaFinder
      */
     void getPlacementCanvas(cv::Mat& image){ placement_canvas.copyTo(image);}
 
+    /**
+     * @brief Shows the annotated image, used for introspection
+     *
+     * @param[out] image canvas to write the image to.
+     */
+    void getAnnotatedImage(cv::Mat& image){ annotated_image.copyTo(image);}
+
 
 private:
     // internal occupancy representation
@@ -67,6 +75,8 @@ class PlaceAreaFinder
     cv::Mat dilated_canvas;
     cv::Mat placement_canvas;
 
+    cv::Mat annotated_image;
+
     /**
      * @brief transform a point in meters to a pixel on the canvas
      *
@@ -110,6 +120,14 @@ class PlaceAreaFinder
      */
     void createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin);
 
+    /**
+     * @brief fill the selected pixels with a color for annotation
+     * 
+     * @param indeces 
+     * @param color
+     */
+    void annotateImage(const rgbd::Image& image, const pcl::Indices index, cv::Scalar color);
+
 };
 
 #endif
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index ffdb3136..3376f266 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -377,6 +377,10 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     float length = object_diameter + error_margin;
     float placement_margin = 2 * 0.02 + length;
 
+    std::cout << "annotating image" << std::endl;
+    annotated_image = image->getRGBImage().clone();
+    annotateImage(*image, floorless_index, table_color);
+
     std::cout << "creating costmap" << std::endl;
 
     // draw clouds to costmap
@@ -474,3 +478,17 @@ void PlaceAreaFinder::dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, fl
     cv::dilate(canvas, dilated_canvas, element );
 }
 
+void PlaceAreaFinder::annotateImage(const rgbd::Image& image, const pcl::Indices index, cv::Scalar color)
+{
+    int width = image.getDepthImage().cols;
+    
+    for (uint i = 0; i < index.size(); i++)
+    {
+        int col = index[i] % width;
+        int row = index[i] / width;
+
+        cv::Point2d p = cv::Point2d(col, row);
+        if (p.x >= 0 && p.y >= 0 && p.x < annotated_image.cols && p.y < annotated_image.rows)
+            annotated_image.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+    }    
+}
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index c6040775..4c0aad96 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -193,6 +193,12 @@ int main (int argc, char **argv)
         // std::cout << "showing placement costmap" << std::endl;
         cv::imshow("Placement options costmap topview", placement_canvas);
 
+        if (true)
+        {
+            cv::Mat annotated_image;
+            place_area_finder.getAnnotatedImage(annotated_image);
+            cv::imshow("Annotated_image", annotated_image);
+        }
         // Show RGB snapshot
         cv::Mat rgbcanvas = image->getRGBImage();
         cv::imshow("RGB", rgbcanvas);

From b44fd375b5e40a42bf7c17e436d1e10b06ba5aa3 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Thu, 20 Jul 2023 14:00:42 +0200
Subject: [PATCH 098/136] annotate plane, objects and not table

---
 .../src/kinect/place_area_finder.cpp          | 50 +++++++++++++++++--
 .../tools/empty_spot_designator.cpp           |  3 ++
 2 files changed, 50 insertions(+), 3 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 3376f266..bfeac405 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -129,7 +129,9 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
  * @param cloud_no_plane A pointcloud containing all points not within the found plane
  * @return height of the segmented plane OR -1.0 if no plane could be found
  */
-bool SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::ModelCoefficients::Ptr plane_coefficients, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_no_plane)
+bool SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::ModelCoefficients::Ptr plane_coefficients,
+                 pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::Indices &plane_index, 
+                 pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_no_plane, pcl::Indices &planeless_index)
 {
     pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
     // Create the segmentation object
@@ -163,6 +165,8 @@ bool SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::M
     extract.setNegative(false);
     extract.filter(*cloud_out);
 
+    plane_index = inliers->indices;
+
     // std::cout << "PointCloud representing the planar component: " << inliers->indices.size() << " data points."
     //   << "Plane with coefficients: " << *coefficients << std::endl;
 
@@ -172,6 +176,23 @@ bool SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::M
     extract2.setNegative(true);
     extract2.filter(*cloud_no_plane);
 
+    // handcraft the planeless index
+    planeless_index.resize(cloud_in->size()-plane_index.size());
+    int plane_i = 0; //most recent index of plane_index
+    int planeless_i = 0;
+    for (int i = 0; i<int(cloud_in->size()); i++)
+    {
+        if (i==plane_index[plane_i])
+        {
+            plane_i++;
+        }
+        else
+        {
+            planeless_index[planeless_i] = i;
+            planeless_i++;
+        }
+    }
+
     return true;
 }
 
@@ -303,6 +324,22 @@ void projectToPlane(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, Eigen
     }
 }
 
+/**
+ * @brief returns indexes of cloud C to cloud A given the index of cloud B to A and cloud C to B)
+ * 
+ * @param index1 
+ * @param index2 
+ * @return pcl::Indices 
+ */
+pcl::Indices multiplyIndex(pcl::Indices indexBA, pcl::Indices indexCB)
+{
+    for (uint i=0; i<indexCB.size(); i++)
+    {
+        indexCB[i] = indexBA[indexCB[i]];
+    }
+    return indexCB;
+}
+
 PlaceAreaFinder::PlaceAreaFinder()
 {
 }
@@ -332,9 +369,11 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     // Segment the table plane and return a cloud with the plane and a cloud where the plane is removed
     std::cout << "SegmentPlane" << std::endl;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr plane_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::Indices plane_index;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr planeless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::Indices planeless_index;
     pcl::ModelCoefficients::Ptr plane_coefficients (new pcl::ModelCoefficients ());
-    if (!SegmentPlane(floorless_cloud, plane_coefficients, plane_cloud, planeless_cloud))
+    if (!SegmentPlane(floorless_cloud, plane_coefficients, plane_cloud, plane_index, planeless_cloud, planeless_index))
     {
         std::cout << "Could not find plane" << std::endl;
         return false;
@@ -379,7 +418,12 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
 
     std::cout << "annotating image" << std::endl;
     annotated_image = image->getRGBImage().clone();
-    annotateImage(*image, floorless_index, table_color);
+    pcl::Indices plane_cloud_index = multiplyIndex(floorless_index, plane_index);
+    annotateImage(*image, plane_cloud_index, table_color);
+    pcl::Indices object_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, object_index));
+    annotateImage(*image, object_cloud_index, occupied_color);
+    pcl::Indices below_table_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, below_index));
+    annotateImage(*image, below_table_cloud_index, occluded_color);
 
     std::cout << "creating costmap" << std::endl;
 
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 4c0aad96..ba381a13 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -169,6 +169,7 @@ int main (int argc, char **argv)
         if (!place_area_finder.findArea(image, sensor_pose, place_pose))
         {
             std::cout << "no place area found" << std::endl;
+            continue;
         }
         std::cout << place_pose << std::endl;
 
@@ -178,10 +179,12 @@ int main (int argc, char **argv)
         place_area_finder.getCanvas(canvas);
         place_area_finder.getDilatedCanvas(dilated_canvas);
         place_area_finder.getPlacementCanvas(placement_canvas);
+        /*
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
         geo::Pose3D sensor_pose_canvas = sensor_pose;
         sensor_pose_canvas.t.z = sensor_pose.t.z - place_pose.t.z;
         drawFieldOfView(canvas, sensor_pose_canvas, image);
+        */
         // Show the different canvasses
         
         // std::cout << "showing costmap" << std::endl;

From c2fe8c6dd8e35e342dfd7326d701cf45708375e0 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Thu, 20 Jul 2023 14:15:59 +0200
Subject: [PATCH 099/136] fix segfault (i think)

---
 ed_sensor_integration/src/kinect/place_area_finder.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index bfeac405..9767ade7 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -458,7 +458,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
 
 cv::Point2d PlaceAreaFinder::worldToCanvas(double x, double y)
 {
-    return cv::Point2d(-y / resolution, -x / resolution) + canvas_center;
+    return cv::Point2d(round(-y / resolution), round(-x / resolution)) + canvas_center;
 }
 
 geo::Vec2d PlaceAreaFinder::canvasToWorld(cv::Point2d point)

From 2b80af5d0196217dc5e72acd92b924a067d9d70f Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Thu, 20 Jul 2023 15:03:22 +0200
Subject: [PATCH 100/136] add marker publishers

---
 .../src/kinect/kinect_plugin.cpp              | 31 +++++++++++++++++++
 .../src/kinect/kinect_plugin.h                |  3 +-
 2 files changed, 33 insertions(+), 1 deletion(-)

diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.cpp b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
index d843b845..0593adbe 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.cpp
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
@@ -69,6 +69,8 @@ void KinectPlugin::initialize(ed::InitData& init)
     srv_place_area_ = nh.advertiseService("place_area", &KinectPlugin::srvPlaceArea, this);
 
     ray_trace_visualization_publisher_ = nh.advertise<visualization_msgs::Marker>("ray_trace_visualization", 10);
+    place_area_publisher_ = nh.advertise<visualization_msgs::Marker>("place_area", 10);
+    place_marker_publisher_ = nh.advertise<visualization_msgs::Marker>("place_pose", 10);
 }
 
 // ----------------------------------------------------------------------------------------------------
@@ -305,6 +307,35 @@ bool KinectPlugin::srvPlaceArea(__attribute__((unused)) ed_sensor_integration_ms
         return true;
     }
     geo::convert(place_pose, res.pose.pose);
+
+    // Publish marker
+    visualization_msgs::Marker marker_msg;
+    marker_msg.header.frame_id = "base_link";
+    marker_msg.header.stamp = ros::Time::now();
+    marker_msg.action = visualization_msgs::Marker::ADD;
+    marker_msg.color.a = 0.5;
+    marker_msg.lifetime = ros::Duration(10.0);
+    double r = 0.05;
+    marker_msg.scale.x = r; 
+    marker_msg.scale.y = r;
+    marker_msg.scale.z = r;
+
+    static int iter = 0;
+    if (++iter % 2 == 0)
+    {
+        marker_msg.color.b = marker_msg.color.r = 1;
+    }
+    else
+    {
+        marker_msg.color.b = marker_msg.color.g = 1;
+    }
+
+    marker_msg.type = visualization_msgs::Marker::SPHERE;
+
+    marker_msg.pose = res.pose.pose;
+
+    place_marker_publisher_.publish(marker_msg);
+
     return true;
 }
 
diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.h b/ed_sensor_integration/src/kinect/kinect_plugin.h
index cc8d436f..4de26947 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.h
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.h
@@ -79,7 +79,8 @@ class KinectPlugin : public ed::Plugin
     bool srvPlaceArea(ed_sensor_integration_msgs::PlaceArea::Request& req, ed_sensor_integration_msgs::PlaceArea::Response& res);
 
     ros::ServiceServer srv_place_area_;
-
+    ros::Publisher place_area_publisher_;
+    ros::Publisher place_marker_publisher_;
 
 
 };

From 90f2cb1694451e3ca1bb0fab340fcfc6c0d9c4d4 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Thu, 20 Jul 2023 15:28:20 +0200
Subject: [PATCH 101/136] draw place pose on canvas

---
 ed_sensor_integration/src/kinect/place_area_finder.cpp | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 9767ade7..8c4a2fbf 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -407,7 +407,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     cv::Scalar occupied_color(0, 0, 255);
     cv::Scalar occluded_color(255, 0, 0);
     cv::Scalar radius_color(100, 0, 100);
-    cv::Scalar placement_color(100, 255, 100);
+    cv::Scalar placement_color(255, 255, 255);
     cv::Scalar point_color(255, 0, 0);
 
     // Object placement margins #TODO hardcoded parameters
@@ -448,6 +448,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
         return false;
     }
 
+    cv::circle(canvas, place_point_canvas, 3, placement_color, -1);
     geo::Vec2d place_point;
     place_point = canvasToWorld(place_point_canvas);
 

From f9488681ccd7839c17fa3008cb161b955e28c31e Mon Sep 17 00:00:00 2001
From: Peter van Dooren <pepevandooren@hotmail.com>
Date: Thu, 20 Jul 2023 15:53:50 +0200
Subject: [PATCH 102/136] toggle visualization

---
 .../src/kinect/place_area_finder.cpp          | 21 ++++++++++++-------
 .../tools/empty_spot_designator.cpp           |  1 -
 2 files changed, 13 insertions(+), 9 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 8c4a2fbf..9e2c89f2 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -350,6 +350,7 @@ PlaceAreaFinder::~PlaceAreaFinder()
 
 bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose)
 {
+    bool visualize = true;
     // std::cout << "converting image to cloud" << std::endl;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     imageToCloud(*image, cloud);
@@ -416,14 +417,17 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     float length = object_diameter + error_margin;
     float placement_margin = 2 * 0.02 + length;
 
-    std::cout << "annotating image" << std::endl;
-    annotated_image = image->getRGBImage().clone();
-    pcl::Indices plane_cloud_index = multiplyIndex(floorless_index, plane_index);
-    annotateImage(*image, plane_cloud_index, table_color);
-    pcl::Indices object_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, object_index));
-    annotateImage(*image, object_cloud_index, occupied_color);
-    pcl::Indices below_table_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, below_index));
-    annotateImage(*image, below_table_cloud_index, occluded_color);
+    if (visualize)
+    {
+        std::cout << "annotating image" << std::endl;
+        annotated_image = image->getRGBImage().clone();
+        pcl::Indices plane_cloud_index = multiplyIndex(floorless_index, plane_index);
+        annotateImage(*image, plane_cloud_index, table_color);
+        pcl::Indices object_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, object_index));
+        annotateImage(*image, object_cloud_index, occupied_color);
+        pcl::Indices below_table_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, below_index));
+        annotateImage(*image, below_table_cloud_index, occluded_color);
+    }
 
     std::cout << "creating costmap" << std::endl;
 
@@ -445,6 +449,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     cv::Point2d place_point_canvas;
     if (!GetPlacementOption(dilated_canvas, table_color, place_point_canvas))
     {
+        std::cout << "No valid place options" << std::endl;
         return false;
     }
 
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index ba381a13..fe4209fc 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -169,7 +169,6 @@ int main (int argc, char **argv)
         if (!place_area_finder.findArea(image, sensor_pose, place_pose))
         {
             std::cout << "no place area found" << std::endl;
-            continue;
         }
         std::cout << place_pose << std::endl;
 

From 269d14efc8f6903d0f38fe3731c5154ef2886ee1 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?D=C3=B3nal?= <donal.ryan36765@gmail.com>
Date: Thu, 19 Oct 2023 10:21:28 +0200
Subject: [PATCH 103/136] Yolov8 for image segmentation

Donal BEP progress testing yolov8
---
 ed_sensor_integration/CMakeLists.txt          |   4 +
 .../scripts/YOLOv8_single_image.py            | 165 ++++++++++++++++++
 .../scripts/YOLOv8_video_optimized.py         |  61 +++++++
 ed_sensor_integration/scripts/listener.py     |  60 +++++++
 ed_sensor_integration/scripts/talker.py       |  56 ++++++
 5 files changed, 346 insertions(+)
 create mode 100644 ed_sensor_integration/scripts/YOLOv8_single_image.py
 create mode 100644 ed_sensor_integration/scripts/YOLOv8_video_optimized.py
 create mode 100755 ed_sensor_integration/scripts/listener.py
 create mode 100755 ed_sensor_integration/scripts/talker.py

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index b150630f..c6796338 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -179,6 +179,10 @@ install(
 
 add_executable(ed_empty_spot_designator tools/empty_spot_designator.cpp)
 target_link_libraries(ed_empty_spot_designator ed_kinect ${catkin_LIBRARIES})
+
+catkin_install_python(PROGRAMS scripts/talker.py scripts/listener.py
+  DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
+)
 # ------------------------------------------------------------------------------------------------
 #                                           TESTS
 # ------------------------------------------------------------------------------------------------
diff --git a/ed_sensor_integration/scripts/YOLOv8_single_image.py b/ed_sensor_integration/scripts/YOLOv8_single_image.py
new file mode 100644
index 00000000..89fa6717
--- /dev/null
+++ b/ed_sensor_integration/scripts/YOLOv8_single_image.py
@@ -0,0 +1,165 @@
+import cv2
+from matplotlib import image as img
+from ultralytics import YOLO
+import numpy as np
+import time
+def detect(model,img):
+    
+        results = model.predict(source=img.copy(),save=False,save_txt=False)
+        result=results[0]
+        segmentation_contours_idx = []
+        for seg in result.masks.xy:
+            segment = np.array(seg,dtype=np.int32)
+            segmentation_contours_idx.append(segment)
+        bboxes = np.array(result.boxes.xyxy.cpu(),dtype="int")
+        class_ids = np.array(result.boxes.cls.cpu(),dtype="int")
+        #scores = np.array(result.boxes.conf.cpu(),dtype="float").round(2)
+        return bboxes, class_ids, segmentation_contours_idx#, scores
+
+# def brightness(image,brightness_factor): #positive value -> brighter, negative -> darker
+#     # Convert the image to 32-bit float
+#     image_float = image.astype(np.float32)
+#     # Apply the darkness factor to each pixel
+#     darkened_image_float = image_float + brightness_factor
+#     # Clip the values to ensure they stay within the valid range [0, 255]
+#     darkened_image_float = np.clip(darkened_image_float, 0, 255)
+#     # Convert the result back to 8-bit unsigned integer
+#     darkened_image = darkened_image_float.astype(np.uint8)
+#     return darkened_image
+
+# def change_saturation(image, saturation_factor):
+#     # Convert the image from BGR to HSV color space
+#     hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
+
+#     # Split the HSV image into its components
+#     h, s, v = cv2.split(hsv_image)
+
+#     # Apply the saturation factor
+#     s = np.clip(s * saturation_factor, 0, 255).astype(np.uint8)
+
+#     # Merge the modified components back into an HSV image
+#     modified_hsv = cv2.merge((h, s, v))
+
+#     # Convert the modified HSV image back to BGR color space
+#     modified_image = cv2.cvtColor(modified_hsv, cv2.COLOR_HSV2BGR)
+
+#     return modified_image
+#Colours dict
+colours = {
+    'red': (0, 0, 255),
+    'green': (0, 255, 0),
+    'blue': (255, 0, 0),
+    'yellow': (0, 255, 255),
+    'purple': (128, 0, 128),
+    # Add more colors as needed
+}
+
+#Inputs
+#image_path = r"C:\Users\Dónal\Desktop\segment_any\images\corner2.jpg"
+model_path = "/home/donal/ros/noetic/system/src/ed_sensor_integration/scripts/yolov8n-seg.pt"
+device = "cuda"
+
+#Loads image, converts to BGR colour channel, darkens image and loads model
+#image = img.imread(image_path)
+#image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+# darkness_factor = -25  # Decrease the brightness by 50 units
+# image = brightness(image,darkness_factor) 
+# saturation_factor = 0.8
+# image = change_saturation(image,saturation_factor)
+
+class_id_to_extract = 0
+colours = {
+    'yellow': (0, 255, 255),
+    'blue': (255, 0, 0),
+}
+
+cap = cv2.VideoCapture(0)  # Open the webcam
+
+if not cap.isOpened():
+    print("Error: Could not open the camera.")
+    exit()
+
+while True:
+    ret, frame = cap.read()
+
+    if not ret:
+        print("Error: Could not read a frame.")
+        break
+    model = YOLO(model_path)
+    bboxes, classes, segmentations = detect(model, frame) #, scores = detect(model, frame)
+
+    # Extract the segment of class id 60 (table)
+    table_indices = [i for i, class_id in enumerate(classes) if class_id == class_id_to_extract]
+
+    for i in table_indices:
+        x, y, x2, y2 = bboxes[i]
+        seg = segmentations[i]
+
+        cv2.rectangle(frame, (x, y), (x2, y2), colours['yellow'], 2)
+        cv2.polylines(frame, [seg], True, colours['blue'], 2)
+        cv2.putText(frame, "Table", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, colours['yellow'], 2)
+
+    cv2.imshow("Video Feed", frame)
+    
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()
+# cap = cv2.VideoCapture(0)
+
+# while cap.isOpened():
+#     success, frame = cap.read()
+
+#     if success:
+#         start = time.perf_counter()
+          
+#         model = YOLO(model_path)
+
+#         end = time.perf_counter()
+#         total_time = end -start
+#         dps = 1/ total_time
+
+#         #extracts data from model
+#         bboxes, classes, segmentations, scores = detect(model,frame)
+
+#         #Extracting only table mask
+#         for bbox, class_id, seg, score in zip(bboxes, classes, segmentations, scores):
+#             (x, y, x2, y2) = bbox
+#                 # Table id from trained dataset is 60
+#             if class_id == 0:
+#                 cv2.rectangle(frame, (x, y), (x2, y2), colours['yellow'], 2) #Colour is Blue Green Red BGR
+#                 cv2.polylines(frame, [seg], True, colours['blue'], 2)
+#                 # cv2.fillPoly(image, [seg], colours['purple'])
+#                 cv2.putText(frame, "Table", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, colours['yellow'], 2)
+#         cv2.imshow("Video Feed",frame)
+#         if cv2.waitKey(1) & 0xFF == ord('q'): 
+#             break
+  
+# # After the loop release the cap object 
+# cap.release() 
+# # Destroy all the windows 
+# cv2.destroyAllWindows() 
+
+
+
+
+# model = YOLO(model_path)
+
+# #extracts data from model
+# bboxes, classes, segmentations, scores = detect(model,image)
+
+# #Extracting only table mask
+# for bbox, class_id, seg, score in zip(bboxes, classes, segmentations, scores):
+#     (x, y, x2, y2) = bbox
+#     # Table id from trained dataset is 60
+#     if class_id == 60:
+#         cv2.rectangle(image, (x, y), (x2, y2), colours['yellow'], 2) #Colour is Blue Green Red BGR
+#         cv2.polylines(image, [seg], True, colours['blue'], 2)
+#         # cv2.fillPoly(image, [seg], colours['purple'])
+#         cv2.putText(image, "Table", (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, colours['yellow'], 2)
+
+# #Visualization
+# cv2.imshow('Result Image', image)
+# cv2.waitKey(0)
+# cv2.destroyAllWindows()
\ No newline at end of file
diff --git a/ed_sensor_integration/scripts/YOLOv8_video_optimized.py b/ed_sensor_integration/scripts/YOLOv8_video_optimized.py
new file mode 100644
index 00000000..8950266d
--- /dev/null
+++ b/ed_sensor_integration/scripts/YOLOv8_video_optimized.py
@@ -0,0 +1,61 @@
+import cv2
+from ultralytics import YOLO
+import numpy as np
+import time
+
+def detect(model, frame):
+    results = model(frame)
+    result = results[0]
+    segmentation_contours_idx = [np.array(seg, dtype=np.int32) for seg in result.masks.xy]
+    class_ids = np.array(result.boxes.cls.cpu(), dtype="int")
+    return class_ids, segmentation_contours_idx
+
+colours = {
+    'yellow': (0, 255, 255),
+    'blue': (255, 0, 0),
+}
+
+model_path = "/home/donal/ros/noetic/system/src/ed_sensor_integration/scripts/yolov8n-seg.pt"
+device = "cpu"
+model = YOLO(model_path).to(device)
+table_class = 0 #table class defined with index 60 (person = 0)
+
+# Detection Loop with webcam
+cap = cv2.VideoCapture(0)  
+
+if not cap.isOpened():
+    print("Error: Could not open the camera.")
+    exit()
+
+# Initialize refresh rate calc
+start_time = time.time()
+frame_count = 0
+
+while True:
+    ret, frame = cap.read()
+
+    if not ret:
+        print("Error: Could not read a frame.")
+        break
+    #Get classes and segments
+    classes, segmentations = detect(model, frame)
+    #extract table segment and add to frame
+    for class_id, seg in zip(classes, segmentations):
+        if class_id == table_class: 
+            cv2.polylines(frame, [seg], True, colours['blue'], 2)
+    # Calculate the refresh rate for segmentation
+    frame_count += 1
+    end_time = time.time()
+    elapsed_time = end_time - start_time
+    segmentation_frame_rate = int(frame_count / elapsed_time)
+    start_time = end_time
+    frame_count = 0
+    # Display segmentation refresh rate
+    cv2.putText(frame, f"Seg FPS: {segmentation_frame_rate}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
+    cv2.imshow("Video Feed", frame)
+    #press q to quit window
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()
\ No newline at end of file
diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
new file mode 100755
index 00000000..ed27e1e5
--- /dev/null
+++ b/ed_sensor_integration/scripts/listener.py
@@ -0,0 +1,60 @@
+#!/usr/bin/env python
+# Software License Agreement (BSD License)
+#
+# Copyright (c) 2008, Willow Garage, Inc.
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions
+# are met:
+#
+#  * Redistributions of source code must retain the above copyright
+#    notice, this list of conditions and the following disclaimer.
+#  * Redistributions in binary form must reproduce the above
+#    copyright notice, this list of conditions and the following
+#    disclaimer in the documentation and/or other materials provided
+#    with the distribution.
+#  * Neither the name of Willow Garage, Inc. nor the names of its
+#    contributors may be used to endorse or promote products derived
+#    from this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+# POSSIBILITY OF SUCH DAMAGE.
+#
+# Revision $Id$
+
+## Simple talker demo that listens to std_msgs/Strings published 
+## to the 'chatter' topic
+
+import rospy
+from std_msgs.msg import String
+
+def callback(data):
+    rospy.loginfo(rospy.get_caller_id() + 'I heard %s', data.data)
+
+def listener():
+
+    # In ROS, nodes are uniquely named. If two nodes with the same
+    # name are launched, the previous one is kicked off. The
+    # anonymous=True flag means that rospy will choose a unique
+    # name for our 'listener' node so that multiple listeners can
+    # run simultaneously.
+    rospy.init_node('listener', anonymous=True)
+
+    rospy.Subscriber('chatter', String, callback)
+
+    # spin() simply keeps python from exiting until this node is stopped
+    rospy.spin()
+
+if __name__ == '__main__':
+    listener()
diff --git a/ed_sensor_integration/scripts/talker.py b/ed_sensor_integration/scripts/talker.py
new file mode 100755
index 00000000..033dc449
--- /dev/null
+++ b/ed_sensor_integration/scripts/talker.py
@@ -0,0 +1,56 @@
+#!/usr/bin/env python
+# Software License Agreement (BSD License)
+#
+# Copyright (c) 2008, Willow Garage, Inc.
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions
+# are met:
+#
+#  * Redistributions of source code must retain the above copyright
+#    notice, this list of conditions and the following disclaimer.
+#  * Redistributions in binary form must reproduce the above
+#    copyright notice, this list of conditions and the following
+#    disclaimer in the documentation and/or other materials provided
+#    with the distribution.
+#  * Neither the name of Willow Garage, Inc. nor the names of its
+#    contributors may be used to endorse or promote products derived
+#    from this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+# POSSIBILITY OF SUCH DAMAGE.
+#
+# Revision $Id$
+
+## Simple talker demo that published std_msgs/Strings messages
+## to the 'chatter' topic
+
+import rospy
+from std_msgs.msg import String
+
+def talker():
+    pub = rospy.Publisher('chatter', String, queue_size=10)
+    rospy.init_node('talker', anonymous=True)
+    rate = rospy.Rate(10) # 10hz
+    while not rospy.is_shutdown():
+        hello_str = "hello world %s" % rospy.get_time()
+        rospy.loginfo(hello_str)
+        pub.publish(hello_str)
+        rate.sleep()
+
+if __name__ == '__main__':
+    try:
+        talker()
+    except rospy.ROSInterruptException:
+        pass

From f115703af353db79791700bf5e905908abb697fa Mon Sep 17 00:00:00 2001
From: Peter van Dooren <p.v.dooren@tue.nl>
Date: Thu, 19 Oct 2023 12:14:06 +0200
Subject: [PATCH 104/136] add yolo to listener

---
 ed_sensor_integration/scripts/listener.py | 68 ++++++++++++++++++-----
 1 file changed, 53 insertions(+), 15 deletions(-)

diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
index ed27e1e5..f420c3d4 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/listener.py
@@ -33,28 +33,66 @@
 #
 # Revision $Id$
 
-## Simple talker demo that listens to std_msgs/Strings published 
+## Simple talker demo that listens to std_msgs/Strings published
 ## to the 'chatter' topic
 
 import rospy
-from std_msgs.msg import String
+import cv2
+import numpy as np
+from ultralytics import YOLO
+from cv_bridge import CvBridge
+from sensor_msgs.msg import Image
 
-def callback(data):
-    rospy.loginfo(rospy.get_caller_id() + 'I heard %s', data.data)
+class table_segmentor:
+    def __init__(self) -> None:
+        rospy.init_node('listener', anonymous=True)
+        self.publisher = rospy.Publisher('/hero/segmented_image',Image)
+        self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
 
-def listener():
+    @staticmethod
+    def detect(model, frame):
+        results = model(frame)
+        result = results[0]
+        segmentation_contours_idx = [np.array(seg, dtype=np.int32) for seg in result.masks.xy]
+        class_ids = np.array(result.boxes.cls.cpu(), dtype="int")
+        return class_ids, segmentation_contours_idx
 
-    # In ROS, nodes are uniquely named. If two nodes with the same
-    # name are launched, the previous one is kicked off. The
-    # anonymous=True flag means that rospy will choose a unique
-    # name for our 'listener' node so that multiple listeners can
-    # run simultaneously.
-    rospy.init_node('listener', anonymous=True)
 
-    rospy.Subscriber('chatter', String, callback)
+    def callback(self, data):
+        rospy.loginfo("got message")
+        bridge = CvBridge()
+        cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')
+        rospy.loginfo("converted message")
+        #Yolov8 model code
+
+        model_path = "~/MEGA/developers/Donal/yolov8x-seg.pt"
+        device = "cuda"
+        model = YOLO(model_path).to(device)
+        table_class = 60 #table class defined with index 60 (person = 0)
+        classes, segmentations = self.detect(model, cv_image)
+        #extract table segment and add to frame
+        for class_id, seg in zip(classes, segmentations):
+            if class_id == table_class:
+                cv2.polylines(cv_image, [seg], True, (255,0,0), 2)
+        # cv2.imshow("Segmented Image", cv_image)
+        # cv2.waitKey(1)
+        image_message = bridge.cv2_to_imgmsg(cv_image, encoding="passthrough")
+        self.publisher.publish(image_message)
+
+    def listener():
+
+        # In ROS, nodes are uniquely named. If two nodes with the same
+        # name are launched, the previous one is kicked off. The
+        # anonymous=True flag means that rospy will choose a unique
+        # name for our 'listener' node so that multiple listeners can
+        # run simultaneously.
 
-    # spin() simply keeps python from exiting until this node is stopped
-    rospy.spin()
+
+        rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , callback)
+
+        # spin() simply keeps python from exiting until this node is stopped
+        rospy.spin()
 
 if __name__ == '__main__':
-    listener()
+    ts = table_segmentor()
+    rospy.spin()

From ff08f4d71cb0491b5e31fbe6119344076501b56c Mon Sep 17 00:00:00 2001
From: Peter van Dooren <p.v.dooren@tue.nl>
Date: Thu, 19 Oct 2023 12:31:55 +0200
Subject: [PATCH 105/136] move model into class

---
 ed_sensor_integration/scripts/listener.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
index f420c3d4..202ebc2f 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/listener.py
@@ -45,6 +45,11 @@
 
 class table_segmentor:
     def __init__(self) -> None:
+        model_path = "~/MEGA/developers/Donal/yolov8x-seg.pt"
+        device = "cuda"
+        self.model = YOLO(model_path).to(device)
+        self.table_class = 60 #table class defined with index 60 (person = 0)
+
         rospy.init_node('listener', anonymous=True)
         self.publisher = rospy.Publisher('/hero/segmented_image',Image)
         self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
@@ -63,16 +68,11 @@ def callback(self, data):
         bridge = CvBridge()
         cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')
         rospy.loginfo("converted message")
-        #Yolov8 model code
 
-        model_path = "~/MEGA/developers/Donal/yolov8x-seg.pt"
-        device = "cuda"
-        model = YOLO(model_path).to(device)
-        table_class = 60 #table class defined with index 60 (person = 0)
-        classes, segmentations = self.detect(model, cv_image)
+        classes, segmentations = self.detect(self.model, cv_image)
         #extract table segment and add to frame
         for class_id, seg in zip(classes, segmentations):
-            if class_id == table_class:
+            if class_id == self.table_class:
                 cv2.polylines(cv_image, [seg], True, (255,0,0), 2)
         # cv2.imshow("Segmented Image", cv_image)
         # cv2.waitKey(1)

From ca39649f2c153b385e2968b3b3623e5ef6afd1b6 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <p.v.dooren@tue.nl>
Date: Thu, 19 Oct 2023 13:30:37 +0200
Subject: [PATCH 106/136] changed model from XL to M

---
 ed_sensor_integration/scripts/listener.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
index 202ebc2f..da7fdd79 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/listener.py
@@ -45,7 +45,7 @@
 
 class table_segmentor:
     def __init__(self) -> None:
-        model_path = "~/MEGA/developers/Donal/yolov8x-seg.pt"
+        model_path = "~/MEGA/developers/Donal/yolov8m-seg.pt"
         device = "cuda"
         self.model = YOLO(model_path).to(device)
         self.table_class = 60 #table class defined with index 60 (person = 0)

From 6dc0ca905246d3b38e6f3b07e13ac23c5968d49a Mon Sep 17 00:00:00 2001
From: Peter van Dooren <p.v.dooren@tue.nl>
Date: Thu, 19 Oct 2023 13:35:34 +0200
Subject: [PATCH 107/136] converts image to correct colour channel

---
 ed_sensor_integration/scripts/listener.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
index da7fdd79..c2baab28 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/listener.py
@@ -67,6 +67,7 @@ def callback(self, data):
         rospy.loginfo("got message")
         bridge = CvBridge()
         cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')
+        cv_image = cv2.cvtColor(cv_image, cv2.COLOR_RGB2BGR)
         rospy.loginfo("converted message")
 
         classes, segmentations = self.detect(self.model, cv_image)

From 256ba86eaeec10417f251d268921a6296b057b99 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <p.v.dooren@tue.nl>
Date: Thu, 19 Oct 2023 14:08:12 +0200
Subject: [PATCH 108/136] changed model from M to N

---
 ed_sensor_integration/scripts/listener.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
index c2baab28..4bce96b9 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/listener.py
@@ -45,7 +45,7 @@
 
 class table_segmentor:
     def __init__(self) -> None:
-        model_path = "~/MEGA/developers/Donal/yolov8m-seg.pt"
+        model_path = "~/MEGA/developers/Donal/yolov8n-seg.pt"
         device = "cuda"
         self.model = YOLO(model_path).to(device)
         self.table_class = 60 #table class defined with index 60 (person = 0)

From 2ac18d9f0d122bda7bd472649616fb2f7d433ca0 Mon Sep 17 00:00:00 2001
From: Peter van Dooren <p.v.dooren@tue.nl>
Date: Thu, 19 Oct 2023 14:22:44 +0200
Subject: [PATCH 109/136] added filter for noise onto image

---
 ed_sensor_integration/scripts/listener.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
index 4bce96b9..ff026b92 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/listener.py
@@ -67,6 +67,7 @@ def callback(self, data):
         rospy.loginfo("got message")
         bridge = CvBridge()
         cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')
+        cv_image = cv2.GaussianBlur(cv_image,(5,5),0)
         cv_image = cv2.cvtColor(cv_image, cv2.COLOR_RGB2BGR)
         rospy.loginfo("converted message")
 

From 8a9ead869f17354c1e89dafeb07b7acfee64e33b Mon Sep 17 00:00:00 2001
From: Peter van Dooren <p.v.dooren@tue.nl>
Date: Thu, 19 Oct 2023 14:31:48 +0200
Subject: [PATCH 110/136] removed colour channel change

---
 ed_sensor_integration/scripts/listener.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
index ff026b92..5ead98fe 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/listener.py
@@ -68,7 +68,7 @@ def callback(self, data):
         bridge = CvBridge()
         cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')
         cv_image = cv2.GaussianBlur(cv_image,(5,5),0)
-        cv_image = cv2.cvtColor(cv_image, cv2.COLOR_RGB2BGR)
+        #cv_image = cv2.cvtColor(cv_image, cv2.COLOR_RGB2BGR)
         rospy.loginfo("converted message")
 
         classes, segmentations = self.detect(self.model, cv_image)

From 817ae8012b746b92cd550b527d33c98e5364c29f Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 15:08:20 +0100
Subject: [PATCH 111/136] renamed python script and added cpp script for
 mapping mask onto image

---
 ed_sensor_integration/scripts/listener.py     |  2 +-
 ed_sensor_integration/scripts/mask_mapper.cpp | 61 +++++++++++++++++++
 .../scripts/table_segmentor.py                | 54 ++++++++++++++++
 3 files changed, 116 insertions(+), 1 deletion(-)
 create mode 100644 ed_sensor_integration/scripts/mask_mapper.cpp
 create mode 100755 ed_sensor_integration/scripts/table_segmentor.py

diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
index 5ead98fe..d0541868 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/listener.py
@@ -46,7 +46,7 @@
 class table_segmentor:
     def __init__(self) -> None:
         model_path = "~/MEGA/developers/Donal/yolov8n-seg.pt"
-        device = "cuda"
+        device = "cpu"
         self.model = YOLO(model_path).to(device)
         self.table_class = 60 #table class defined with index 60 (person = 0)
 
diff --git a/ed_sensor_integration/scripts/mask_mapper.cpp b/ed_sensor_integration/scripts/mask_mapper.cpp
new file mode 100644
index 00000000..4d4f4cd3
--- /dev/null
+++ b/ed_sensor_integration/scripts/mask_mapper.cpp
@@ -0,0 +1,61 @@
+#include "ros/ros.h"
+#include "sensor_msgs/Image.h"
+#include "cv_bridge/cv_bridge.h"
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/imgproc/imgproc.hpp"
+
+class ImageSubscriber {
+public:
+    ImageSubscriber() : it_(nh_) {
+        //subscribe to image and mask topics
+        mask_sub_ = it_.subscribe("/hero/segmented_table_mask", 1, &ImageSubscriber::maskCallback, this); 
+        original_image_sub_ = it_.subscribe("/hero/head_rgbd_sensor/rgb/image_raw", 1, &ImageSubscriber::imageCallback, this);
+        cv::namedWindow("Overlay", cv::WINDOW_NORMAL);
+    }
+
+    void maskCallback(const sensor_msgs::ImageConstPtr& mask_msg) {
+        try {
+            //convert mask msg to opencv image
+            cv::Mat mask = cv_bridge::toCvShare(mask_msg, "mono8")->image;
+            updateOverlay(mask);
+        } catch (cv_bridge::Exception& e) {
+            ROS_ERROR("cv_bridge exception: %s", e.what());
+        }
+    }
+
+    void imageCallback(const sensor_msgs::ImageConstPtr& image_msg) {
+        try {
+            //convert image msg to opencv image
+            cv::Mat image = cv_bridge::toCvShare(image_msg, "passthrough")->image;
+            overlayMask(image);
+            cv::imshow("Overlay", image);
+            cv::waitKey(1); 
+        } catch (cv_bridge::Exception& e) {
+            ROS_ERROR("cv_bridge exception: %s", e.what());
+        }
+    }
+
+    void overlayMask(cv::Mat& image) {
+        //maps mask onto image
+        cv::bitwise_and(image, image, image, mask);
+    }
+
+    void updateOverlay(const cv::Mat& mask) {
+
+        overlayMask(original_image_);
+    }
+
+private:
+    ros::NodeHandle nh_;
+    image_transport::ImageTransport it_;
+    image_transport::Subscriber mask_sub_;
+    image_transport::Subscriber original_image_sub_;
+    cv::Mat original_image_;
+};
+
+int main(int argc, char** argv) {
+    ros::init(argc, argv, "image_subscriber");
+    ImageSubscriber image_subscriber;
+    ros::spin();
+    return 0;
+}
diff --git a/ed_sensor_integration/scripts/table_segmentor.py b/ed_sensor_integration/scripts/table_segmentor.py
new file mode 100755
index 00000000..ba730472
--- /dev/null
+++ b/ed_sensor_integration/scripts/table_segmentor.py
@@ -0,0 +1,54 @@
+import rospy
+import cv2
+import numpy as np
+from ultralytics import YOLO
+from cv_bridge import CvBridge
+from sensor_msgs.msg import Image
+
+class table_segmentor:
+    def __init__(self) -> None:
+        model_path = "~/MEGA/developers/Donal/yolov8n-seg.pt"
+        device = "cuda"
+        self.model = YOLO(model_path).to(device)
+        self.table_class = 60 #table class defined with index 60 ( for laptop testing->person = 0)
+
+        rospy.init_node('listener', anonymous=True)
+        self.publisher = rospy.Publisher('/hero/segmented_image',Image)
+        self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
+
+    @staticmethod
+    def detect(model, frame):
+        results = model(frame)
+        result = results[0]
+        segmentation_contours_idx = [np.array(seg, dtype=np.int32) for seg in result.masks.xy]
+        class_ids = np.array(result.boxes.cls.cpu(), dtype="int")
+        return class_ids, segmentation_contours_idx
+
+
+    def callback(self, data):
+        rospy.loginfo("got message")
+        bridge = CvBridge()
+        cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')
+        cv_image = cv2.GaussianBlur(cv_image,(5,5),0)
+        rospy.loginfo("converted message")
+
+        classes, segmentations = self.detect(self.model, cv_image)
+        #extract table segment and add to frame
+        table_mask = np.zeros_like(cv_image, dtype=np.uint8)
+        for class_id, seg in zip(classes, segmentations):
+            if class_id == self.table_class:
+                cv2.polylines(cv_image, [seg], True, (255,0,0), 2)
+                cv2.polylines(table_mask, [seg], True, (255,0,0), 2)
+        image_message = bridge.cv2_to_imgmsg(cv_image, encoding="passthrough")
+        table_mask_message = bridge.cv2_to_imgmsg(table_mask, encoding="mono8")
+        self.publisher.publish(table_mask_message)
+
+    def listener():
+        rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , callback)
+
+        # spin() simply keeps python from exiting until this node is stopped
+        rospy.spin()
+
+if __name__ == '__main__':
+    ts = table_segmentor()
+    rospy.spin()

From 6414516510907392d0ac563c238da35db57f4f99 Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 15:40:16 +0100
Subject: [PATCH 112/136] renamed segmentor to segmentation

---
 .../scripts/{table_segmentor.py => table_segmentation.py}         | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 rename ed_sensor_integration/scripts/{table_segmentor.py => table_segmentation.py} (100%)

diff --git a/ed_sensor_integration/scripts/table_segmentor.py b/ed_sensor_integration/scripts/table_segmentation.py
similarity index 100%
rename from ed_sensor_integration/scripts/table_segmentor.py
rename to ed_sensor_integration/scripts/table_segmentation.py

From 7f3050afc522bcfa76b3966e209383fd2b1b0271 Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 15:52:29 +0100
Subject: [PATCH 113/136] added queue size to publisher function

---
 ed_sensor_integration/scripts/table_segmentation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/table_segmentation.py b/ed_sensor_integration/scripts/table_segmentation.py
index ba730472..0b17c7a6 100755
--- a/ed_sensor_integration/scripts/table_segmentation.py
+++ b/ed_sensor_integration/scripts/table_segmentation.py
@@ -13,7 +13,7 @@ def __init__(self) -> None:
         self.table_class = 60 #table class defined with index 60 ( for laptop testing->person = 0)
 
         rospy.init_node('listener', anonymous=True)
-        self.publisher = rospy.Publisher('/hero/segmented_image',Image)
+        self.publisher = rospy.Publisher('/hero/segmented_image',Image,queue_size=None)
         self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
 
     @staticmethod

From 5ab597039dfc924d075fdfd338511ec104362bf4 Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 15:57:02 +0100
Subject: [PATCH 114/136] added queue size to publisher function to listener.py

---
 ed_sensor_integration/scripts/listener.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
index d0541868..87f86336 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/listener.py
@@ -51,7 +51,7 @@ def __init__(self) -> None:
         self.table_class = 60 #table class defined with index 60 (person = 0)
 
         rospy.init_node('listener', anonymous=True)
-        self.publisher = rospy.Publisher('/hero/segmented_image',Image)
+        self.publisher = rospy.Publisher('/hero/segmented_image',Image,queue_size=None)
         self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
 
     @staticmethod

From 1b312e72a53c5bd0aa8bd12ecfd27f7f90d2b66d Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 15:59:05 +0100
Subject: [PATCH 115/136] changed queue_size =10

---
 ed_sensor_integration/scripts/listener.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/listener.py
index 87f86336..fac990b0 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/listener.py
@@ -51,7 +51,7 @@ def __init__(self) -> None:
         self.table_class = 60 #table class defined with index 60 (person = 0)
 
         rospy.init_node('listener', anonymous=True)
-        self.publisher = rospy.Publisher('/hero/segmented_image',Image,queue_size=None)
+        self.publisher = rospy.Publisher('/hero/segmented_image',Image,queue_size=10)
         self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
 
     @staticmethod

From 13820321192ebc4f5584f5b0fe437b8f24718a5b Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 16:21:29 +0100
Subject: [PATCH 116/136] renamed listener to yolo_table_segmentor, changed
 from cpu to gpu

---
 .../scripts/table_segmentation.py             | 54 -------------------
 .../{listener.py => yolo_table_segmentor.py}  |  2 +-
 2 files changed, 1 insertion(+), 55 deletions(-)
 delete mode 100755 ed_sensor_integration/scripts/table_segmentation.py
 rename ed_sensor_integration/scripts/{listener.py => yolo_table_segmentor.py} (99%)

diff --git a/ed_sensor_integration/scripts/table_segmentation.py b/ed_sensor_integration/scripts/table_segmentation.py
deleted file mode 100755
index 0b17c7a6..00000000
--- a/ed_sensor_integration/scripts/table_segmentation.py
+++ /dev/null
@@ -1,54 +0,0 @@
-import rospy
-import cv2
-import numpy as np
-from ultralytics import YOLO
-from cv_bridge import CvBridge
-from sensor_msgs.msg import Image
-
-class table_segmentor:
-    def __init__(self) -> None:
-        model_path = "~/MEGA/developers/Donal/yolov8n-seg.pt"
-        device = "cuda"
-        self.model = YOLO(model_path).to(device)
-        self.table_class = 60 #table class defined with index 60 ( for laptop testing->person = 0)
-
-        rospy.init_node('listener', anonymous=True)
-        self.publisher = rospy.Publisher('/hero/segmented_image',Image,queue_size=None)
-        self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
-
-    @staticmethod
-    def detect(model, frame):
-        results = model(frame)
-        result = results[0]
-        segmentation_contours_idx = [np.array(seg, dtype=np.int32) for seg in result.masks.xy]
-        class_ids = np.array(result.boxes.cls.cpu(), dtype="int")
-        return class_ids, segmentation_contours_idx
-
-
-    def callback(self, data):
-        rospy.loginfo("got message")
-        bridge = CvBridge()
-        cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')
-        cv_image = cv2.GaussianBlur(cv_image,(5,5),0)
-        rospy.loginfo("converted message")
-
-        classes, segmentations = self.detect(self.model, cv_image)
-        #extract table segment and add to frame
-        table_mask = np.zeros_like(cv_image, dtype=np.uint8)
-        for class_id, seg in zip(classes, segmentations):
-            if class_id == self.table_class:
-                cv2.polylines(cv_image, [seg], True, (255,0,0), 2)
-                cv2.polylines(table_mask, [seg], True, (255,0,0), 2)
-        image_message = bridge.cv2_to_imgmsg(cv_image, encoding="passthrough")
-        table_mask_message = bridge.cv2_to_imgmsg(table_mask, encoding="mono8")
-        self.publisher.publish(table_mask_message)
-
-    def listener():
-        rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , callback)
-
-        # spin() simply keeps python from exiting until this node is stopped
-        rospy.spin()
-
-if __name__ == '__main__':
-    ts = table_segmentor()
-    rospy.spin()
diff --git a/ed_sensor_integration/scripts/listener.py b/ed_sensor_integration/scripts/yolo_table_segmentor.py
similarity index 99%
rename from ed_sensor_integration/scripts/listener.py
rename to ed_sensor_integration/scripts/yolo_table_segmentor.py
index fac990b0..f96bd917 100755
--- a/ed_sensor_integration/scripts/listener.py
+++ b/ed_sensor_integration/scripts/yolo_table_segmentor.py
@@ -46,7 +46,7 @@
 class table_segmentor:
     def __init__(self) -> None:
         model_path = "~/MEGA/developers/Donal/yolov8n-seg.pt"
-        device = "cpu"
+        device = "gpu"
         self.model = YOLO(model_path).to(device)
         self.table_class = 60 #table class defined with index 60 (person = 0)
 

From e17fe83ff28cdd6f97ea48faae4c5937342beb79 Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 16:23:04 +0100
Subject: [PATCH 117/136] mistake made, assign model to 'cuda' not 'gpu'

---
 ed_sensor_integration/scripts/yolo_table_segmentor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/yolo_table_segmentor.py b/ed_sensor_integration/scripts/yolo_table_segmentor.py
index f96bd917..93556405 100755
--- a/ed_sensor_integration/scripts/yolo_table_segmentor.py
+++ b/ed_sensor_integration/scripts/yolo_table_segmentor.py
@@ -46,7 +46,7 @@
 class table_segmentor:
     def __init__(self) -> None:
         model_path = "~/MEGA/developers/Donal/yolov8n-seg.pt"
-        device = "gpu"
+        device = "cuda"
         self.model = YOLO(model_path).to(device)
         self.table_class = 60 #table class defined with index 60 (person = 0)
 

From 7dd6eee46e2ff2a9556c3b868aa773feebbdcc5c Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 16:24:45 +0100
Subject: [PATCH 118/136] converted colour channel from BGR to RGB

---
 ed_sensor_integration/scripts/yolo_table_segmentor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/yolo_table_segmentor.py b/ed_sensor_integration/scripts/yolo_table_segmentor.py
index 93556405..c46d674a 100755
--- a/ed_sensor_integration/scripts/yolo_table_segmentor.py
+++ b/ed_sensor_integration/scripts/yolo_table_segmentor.py
@@ -68,7 +68,7 @@ def callback(self, data):
         bridge = CvBridge()
         cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')
         cv_image = cv2.GaussianBlur(cv_image,(5,5),0)
-        #cv_image = cv2.cvtColor(cv_image, cv2.COLOR_RGB2BGR)
+        cv_image = cv2.cvtColor(cv_image, cv2.COLOR_RGB2BGR)
         rospy.loginfo("converted message")
 
         classes, segmentations = self.detect(self.model, cv_image)

From 86a0ff4e2ff427574aa0fac6a4931b09d022a619 Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 16:52:56 +0100
Subject: [PATCH 119/136] export only mask as binary image

---
 ed_sensor_integration/CMakeLists.txt          |  2 +-
 .../scripts/yolo_table_segmentor.py           | 21 ++++++++++++++-----
 2 files changed, 17 insertions(+), 6 deletions(-)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index c6796338..3b4542e9 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -180,7 +180,7 @@ install(
 add_executable(ed_empty_spot_designator tools/empty_spot_designator.cpp)
 target_link_libraries(ed_empty_spot_designator ed_kinect ${catkin_LIBRARIES})
 
-catkin_install_python(PROGRAMS scripts/talker.py scripts/listener.py
+catkin_install_python(PROGRAMS scripts/talker.py scripts/yolo_table_segmentor.py
   DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
 )
 # ------------------------------------------------------------------------------------------------
diff --git a/ed_sensor_integration/scripts/yolo_table_segmentor.py b/ed_sensor_integration/scripts/yolo_table_segmentor.py
index c46d674a..58e446cf 100755
--- a/ed_sensor_integration/scripts/yolo_table_segmentor.py
+++ b/ed_sensor_integration/scripts/yolo_table_segmentor.py
@@ -62,6 +62,12 @@ def detect(model, frame):
         class_ids = np.array(result.boxes.cls.cpu(), dtype="int")
         return class_ids, segmentation_contours_idx
 
+    def extract_table_segment(self, image, class_ids, segmentations):
+        table_mask = np.zeros_like(image, dtype=np.uint8)
+        for class_id, seg in zip(class_ids, segmentations):
+            if class_id == self.table_class:
+                cv2.fillPoly(table_mask, [seg], 255)
+        return table_mask
 
     def callback(self, data):
         rospy.loginfo("got message")
@@ -73,13 +79,18 @@ def callback(self, data):
 
         classes, segmentations = self.detect(self.model, cv_image)
         #extract table segment and add to frame
-        for class_id, seg in zip(classes, segmentations):
-            if class_id == self.table_class:
-                cv2.polylines(cv_image, [seg], True, (255,0,0), 2)
+        # for class_id, seg in zip(classes, segmentations):
+        #     if class_id == self.table_class:
+        #         cv2.polylines(cv_image, [seg], True, (255,0,0), 2)
         # cv2.imshow("Segmented Image", cv_image)
         # cv2.waitKey(1)
-        image_message = bridge.cv2_to_imgmsg(cv_image, encoding="passthrough")
-        self.publisher.publish(image_message)
+        # image_message = bridge.cv2_to_imgmsg(cv_image, encoding="passthrough")
+        # self.publisher.publish(image_message)
+        table_segment = self.extract_table_segment(cv_image, classes, segmentations)
+        
+        # Publish the table segment as a binary mask
+        table_message = bridge.cv2_to_imgmsg(table_segment, encoding="mono8")
+        self.publisher.publish(table_message)
 
     def listener():
 

From d78fc5fae01bffc87adb20cb4608c8499ec8a4fb Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 16:54:41 +0100
Subject: [PATCH 120/136] export only mask using passthrough instead of mono8

---
 ed_sensor_integration/scripts/yolo_table_segmentor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/yolo_table_segmentor.py b/ed_sensor_integration/scripts/yolo_table_segmentor.py
index 58e446cf..07ffa960 100755
--- a/ed_sensor_integration/scripts/yolo_table_segmentor.py
+++ b/ed_sensor_integration/scripts/yolo_table_segmentor.py
@@ -89,7 +89,7 @@ def callback(self, data):
         table_segment = self.extract_table_segment(cv_image, classes, segmentations)
         
         # Publish the table segment as a binary mask
-        table_message = bridge.cv2_to_imgmsg(table_segment, encoding="mono8")
+        table_message = bridge.cv2_to_imgmsg(table_segment, encoding="passthrough")
         self.publisher.publish(table_message)
 
     def listener():

From fae31d3d73d0e715516fc7adeb518b1c49debb5a Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 17:03:41 +0100
Subject: [PATCH 121/136] changed from nano model to large model of yolo

---
 ed_sensor_integration/scripts/yolo_table_segmentor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/yolo_table_segmentor.py b/ed_sensor_integration/scripts/yolo_table_segmentor.py
index 07ffa960..8318aa46 100755
--- a/ed_sensor_integration/scripts/yolo_table_segmentor.py
+++ b/ed_sensor_integration/scripts/yolo_table_segmentor.py
@@ -45,7 +45,7 @@
 
 class table_segmentor:
     def __init__(self) -> None:
-        model_path = "~/MEGA/developers/Donal/yolov8n-seg.pt"
+        model_path = "~/MEGA/developers/Donal/yolov8x-seg.pt"
         device = "cuda"
         self.model = YOLO(model_path).to(device)
         self.table_class = 60 #table class defined with index 60 (person = 0)

From 53e76fabb210d3e51524382e4ad9af4f62019833 Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 17:38:31 +0100
Subject: [PATCH 122/136] edited cmakelists for mask_mapper.cpp

---
 ed_sensor_integration/CMakeLists.txt | 14 ++++++++++++++
 1 file changed, 14 insertions(+)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index 3b4542e9..c575b0e8 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -24,8 +24,12 @@ find_package(catkin REQUIRED COMPONENTS
   tue_config
   tue_filesystem
   visualization_msgs
+  image_transport
+  cv_bridge
 )
 
+
+
 # ------------------------------------------------------------------------------------------------
 #                                        CATKIN EXPORT
 # ------------------------------------------------------------------------------------------------
@@ -35,6 +39,7 @@ catkin_package(
   LIBRARIES ed_kinect
   CATKIN_DEPENDS code_profiler ed ${PROJECT_NAME}_msgs geolib2 image_geometry rgbd rgbd_image_buffer roscpp tue_config visualization_msgs
   DEPENDS OpenCV PCL
+  
 )
 
 # ------------------------------------------------------------------------------------------------
@@ -46,6 +51,7 @@ include_directories(
   SYSTEM
   ${OpenCV_INCLUDE_DIRS}
   ${catkin_INCLUDE_DIRS}
+  
 )
 
 # ------------------------------------------------------------------------------------------------
@@ -184,6 +190,14 @@ catkin_install_python(PROGRAMS scripts/talker.py scripts/yolo_table_segmentor.py
   DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
 )
 # ------------------------------------------------------------------------------------------------
+add_executable(mask_mapper scripts/mask_mapper.cpp)  # Update the source file name accordingly
+target_link_libraries(mask_mapper
+  ${OpenCV_LIBRARIES}
+  ${catkin_LIBRARIES}
+)
+install(TARGETS mask_mapper
+  RUNTIME DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
+)
 #                                           TESTS
 # ------------------------------------------------------------------------------------------------
 if (CATKIN_ENABLE_TESTING)

From 922c0c069bb4089be5e2c222ca714a1e1cd4c681 Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 17:40:08 +0100
Subject: [PATCH 123/136] reverted changes to cmakelists

---
 ed_sensor_integration/CMakeLists.txt | 14 --------------
 1 file changed, 14 deletions(-)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index c575b0e8..3b4542e9 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -24,12 +24,8 @@ find_package(catkin REQUIRED COMPONENTS
   tue_config
   tue_filesystem
   visualization_msgs
-  image_transport
-  cv_bridge
 )
 
-
-
 # ------------------------------------------------------------------------------------------------
 #                                        CATKIN EXPORT
 # ------------------------------------------------------------------------------------------------
@@ -39,7 +35,6 @@ catkin_package(
   LIBRARIES ed_kinect
   CATKIN_DEPENDS code_profiler ed ${PROJECT_NAME}_msgs geolib2 image_geometry rgbd rgbd_image_buffer roscpp tue_config visualization_msgs
   DEPENDS OpenCV PCL
-  
 )
 
 # ------------------------------------------------------------------------------------------------
@@ -51,7 +46,6 @@ include_directories(
   SYSTEM
   ${OpenCV_INCLUDE_DIRS}
   ${catkin_INCLUDE_DIRS}
-  
 )
 
 # ------------------------------------------------------------------------------------------------
@@ -190,14 +184,6 @@ catkin_install_python(PROGRAMS scripts/talker.py scripts/yolo_table_segmentor.py
   DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
 )
 # ------------------------------------------------------------------------------------------------
-add_executable(mask_mapper scripts/mask_mapper.cpp)  # Update the source file name accordingly
-target_link_libraries(mask_mapper
-  ${OpenCV_LIBRARIES}
-  ${catkin_LIBRARIES}
-)
-install(TARGETS mask_mapper
-  RUNTIME DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
-)
 #                                           TESTS
 # ------------------------------------------------------------------------------------------------
 if (CATKIN_ENABLE_TESTING)

From 46452be6a1715211d95b69f56b144e5b655c468f Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 17:56:28 +0100
Subject: [PATCH 124/136] swap from rgb image topic to rgbd image topic

---
 ed_sensor_integration/scripts/yolo_table_segmentor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/yolo_table_segmentor.py b/ed_sensor_integration/scripts/yolo_table_segmentor.py
index 8318aa46..6d5f47ae 100755
--- a/ed_sensor_integration/scripts/yolo_table_segmentor.py
+++ b/ed_sensor_integration/scripts/yolo_table_segmentor.py
@@ -52,7 +52,7 @@ def __init__(self) -> None:
 
         rospy.init_node('listener', anonymous=True)
         self.publisher = rospy.Publisher('/hero/segmented_image',Image,queue_size=10)
-        self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
+        self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgbd',Image , self.callback)#'/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
 
     @staticmethod
     def detect(model, frame):

From 0f1eab420a11133d6cdcfd284d024e9197a865e8 Mon Sep 17 00:00:00 2001
From: Donal Ryan <donal.ryan36765@gmail.com>
Date: Thu, 7 Dec 2023 17:58:25 +0100
Subject: [PATCH 125/136] reverted topic change

---
 ed_sensor_integration/scripts/yolo_table_segmentor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/scripts/yolo_table_segmentor.py b/ed_sensor_integration/scripts/yolo_table_segmentor.py
index 6d5f47ae..8318aa46 100755
--- a/ed_sensor_integration/scripts/yolo_table_segmentor.py
+++ b/ed_sensor_integration/scripts/yolo_table_segmentor.py
@@ -52,7 +52,7 @@ def __init__(self) -> None:
 
         rospy.init_node('listener', anonymous=True)
         self.publisher = rospy.Publisher('/hero/segmented_image',Image,queue_size=10)
-        self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgbd',Image , self.callback)#'/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
+        self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
 
     @staticmethod
     def detect(model, frame):

From 348cb31b93d1bbf879de592aae794ec234595316 Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Mon, 11 Dec 2023 12:03:41 +0100
Subject: [PATCH 126/136] empty_sport_visualizer node now subs to
 hero/segmented_image and can read the data properly

---
 ed_sensor_integration/CMakeLists.txt          |  7 +-
 ed_sensor_integration/package.xml             |  2 +
 ed_sensor_integration/scripts/mask_mapper.cpp | 89 ++++++-------------
 .../tools/empty_spot_designator.cpp           | 43 ++++++++-
 4 files changed, 79 insertions(+), 62 deletions(-)

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index 3b4542e9..be5e546b 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -24,6 +24,8 @@ find_package(catkin REQUIRED COMPONENTS
   tue_config
   tue_filesystem
   visualization_msgs
+  image_transport
+  cv_bridge
 )
 
 # ------------------------------------------------------------------------------------------------
@@ -33,7 +35,7 @@ find_package(catkin REQUIRED COMPONENTS
 catkin_package(
   INCLUDE_DIRS include
   LIBRARIES ed_kinect
-  CATKIN_DEPENDS code_profiler ed ${PROJECT_NAME}_msgs geolib2 image_geometry rgbd rgbd_image_buffer roscpp tue_config visualization_msgs
+  CATKIN_DEPENDS code_profiler ed ${PROJECT_NAME}_msgs geolib2 image_geometry rgbd rgbd_image_buffer roscpp tue_config visualization_msgs image_transport cv_bridge
   DEPENDS OpenCV PCL
 )
 
@@ -180,6 +182,9 @@ install(
 add_executable(ed_empty_spot_designator tools/empty_spot_designator.cpp)
 target_link_libraries(ed_empty_spot_designator ed_kinect ${catkin_LIBRARIES})
 
+add_executable(mask_mapper scripts/mask_mapper.cpp)
+target_link_libraries(mask_mapper ed_kinect ${catkin_LIBRARIES})
+
 catkin_install_python(PROGRAMS scripts/talker.py scripts/yolo_table_segmentor.py
   DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
 )
diff --git a/ed_sensor_integration/package.xml b/ed_sensor_integration/package.xml
index 1d2cd4ac..3e7efcc9 100644
--- a/ed_sensor_integration/package.xml
+++ b/ed_sensor_integration/package.xml
@@ -28,6 +28,8 @@
   <depend>roscpp</depend>
   <depend>tue_config</depend>
   <depend>visualization_msgs</depend>
+  <depend>cv_bridge</depend>
+  <depend>image_transport</depend>
 
   <build_depend>geometry_msgs</build_depend>
   <exec_depend>geometry_msgs</exec_depend>
diff --git a/ed_sensor_integration/scripts/mask_mapper.cpp b/ed_sensor_integration/scripts/mask_mapper.cpp
index 4d4f4cd3..f5f01b02 100644
--- a/ed_sensor_integration/scripts/mask_mapper.cpp
+++ b/ed_sensor_integration/scripts/mask_mapper.cpp
@@ -1,61 +1,30 @@
-#include "ros/ros.h"
-#include "sensor_msgs/Image.h"
-#include "cv_bridge/cv_bridge.h"
-#include "opencv2/highgui/highgui.hpp"
-#include "opencv2/imgproc/imgproc.hpp"
-
-class ImageSubscriber {
-public:
-    ImageSubscriber() : it_(nh_) {
-        //subscribe to image and mask topics
-        mask_sub_ = it_.subscribe("/hero/segmented_table_mask", 1, &ImageSubscriber::maskCallback, this); 
-        original_image_sub_ = it_.subscribe("/hero/head_rgbd_sensor/rgb/image_raw", 1, &ImageSubscriber::imageCallback, this);
-        cv::namedWindow("Overlay", cv::WINDOW_NORMAL);
-    }
-
-    void maskCallback(const sensor_msgs::ImageConstPtr& mask_msg) {
-        try {
-            //convert mask msg to opencv image
-            cv::Mat mask = cv_bridge::toCvShare(mask_msg, "mono8")->image;
-            updateOverlay(mask);
-        } catch (cv_bridge::Exception& e) {
-            ROS_ERROR("cv_bridge exception: %s", e.what());
-        }
-    }
-
-    void imageCallback(const sensor_msgs::ImageConstPtr& image_msg) {
-        try {
-            //convert image msg to opencv image
-            cv::Mat image = cv_bridge::toCvShare(image_msg, "passthrough")->image;
-            overlayMask(image);
-            cv::imshow("Overlay", image);
-            cv::waitKey(1); 
-        } catch (cv_bridge::Exception& e) {
-            ROS_ERROR("cv_bridge exception: %s", e.what());
-        }
-    }
-
-    void overlayMask(cv::Mat& image) {
-        //maps mask onto image
-        cv::bitwise_and(image, image, image, mask);
-    }
-
-    void updateOverlay(const cv::Mat& mask) {
-
-        overlayMask(original_image_);
-    }
-
-private:
-    ros::NodeHandle nh_;
-    image_transport::ImageTransport it_;
-    image_transport::Subscriber mask_sub_;
-    image_transport::Subscriber original_image_sub_;
-    cv::Mat original_image_;
-};
-
-int main(int argc, char** argv) {
-    ros::init(argc, argv, "image_subscriber");
-    ImageSubscriber image_subscriber;
-    ros::spin();
-    return 0;
+#include <ros/ros.h>
+#include <image_transport/image_transport.h>
+#include <opencv2/highgui.hpp>
+#include <cv_bridge/cv_bridge.h>
+
+void imageCallback(const sensor_msgs::ImageConstPtr& msg)
+{
+  try
+  {
+    cv::imshow("view", cv_bridge::toCvShare(msg, "8UC3")->image);
+    cv::waitKey(30);
+  }
+  catch (cv_bridge::Exception& e)
+  {
+    ROS_ERROR("Could not convert from '%s' to 'bgr8'.", msg->encoding.c_str());
+  }
 }
+
+int main(int argc, char **argv)
+{
+  std::string mask_topic = "/hero/segmented_image";
+  ros::init(argc, argv, "image_listener");
+  ros::NodeHandle nh;
+  cv::namedWindow("view");
+
+  image_transport::ImageTransport it(nh);
+  image_transport::Subscriber sub = it.subscribe(mask_topic, 1, imageCallback);
+  ros::spin();
+  cv::destroyWindow("view");
+}
\ No newline at end of file
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index fe4209fc..04c1f00d 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -8,6 +8,10 @@
 #include <opencv2/core/core.hpp>
 #include <vector>
 
+//
+#include <cv_bridge/cv_bridge.h>
+#include <image_transport/image_transport.h>
+//
 #include <ros/ros.h>
 #include <rgbd/image.h>
 
@@ -45,6 +49,8 @@
 
 double resolution = 0.005;
 cv::Point2d canvas_center;
+cv::Mat mask; // global variable for a\passing the image mask
+std::mutex mutex;
 
 geo::Vector3 simpleRayTrace(geo::Vector3 origin, geo::Vector3 direction)
 {
@@ -119,6 +125,29 @@ void drawFieldOfView(cv::Mat& canvas, geo::Pose3D sensor_pose, const rgbd::Image
     drawFoVMacro(c4, canvas, sensor_pose);
 }
 
+void imageCallback(const sensor_msgs::ImageConstPtr& msg)
+{
+  std::cout << "Mask received!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!" << std::endl;
+  try
+  {
+    if(mutex.try_lock())
+    {
+        mask = cv_bridge::toCvCopy(msg, "8UC3")->image;
+        std::cout << "Mask received" << std::endl;
+        mutex.unlock();
+    }
+    else
+    {
+        std::cout << "Mutex not locked!!!!!!!!!!!!!!!!!!!!!!!!!!!!" << std::endl;
+    }
+    //cv::waitKey(30);
+  }
+  catch (cv_bridge::Exception& e)
+  {
+    ROS_ERROR("Could not convert from '%s' to 'bgr8'.", msg->encoding.c_str());
+  }
+}
+
 /**
  * @brief usage, print how the executable should be used and explain the input
  */
@@ -153,7 +182,13 @@ int main (int argc, char **argv)
     pcl::PCDWriter writer;
 
     PlaceAreaFinder place_area_finder;
+    //
+    std::string mask_topic = "/hero/segmented_image";
+    ros::NodeHandle nh;
+    image_transport::ImageTransport it(nh);
+    image_transport::Subscriber sub = it.subscribe(mask_topic, 1, imageCallback);
 
+    //
     while(ros::ok())
     {
         rgbd::ImageConstPtr image;
@@ -195,6 +230,12 @@ int main (int argc, char **argv)
         // std::cout << "showing placement costmap" << std::endl;
         cv::imshow("Placement options costmap topview", placement_canvas);
 
+        if (mutex.try_lock()){
+
+            if (mask.rows > 0)
+            cv::imshow("Mask", mask);
+            mutex.unlock();
+        }
         if (true)
         {
             cv::Mat annotated_image;
@@ -211,7 +252,7 @@ int main (int argc, char **argv)
         {
             break;
         }
-
+        ros::spinOnce();
     }
     cv::destroyAllWindows();
     return 0;

From ae8fb391617baf4756ec666b0d229afafadbd2db Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Sun, 17 Dec 2023 21:26:47 +0100
Subject: [PATCH 127/136] find common z depth

---
 ed_sensor_integration/CMakeLists.txt          |   5 +-
 .../include/ed/kinect/place_area_finder.h     |   5 +
 ed_sensor_integration/package.xml             |   1 +
 .../scripts/yolo_table_segmentor.py           | 111 ------------------
 .../src/kinect/place_area_finder.cpp          |  63 ++++++++++
 .../YOLOv8_single_image.py                    |   0
 .../YOLOv8_video_optimized.py                 |   0
 .../previous_iterations}/mask_mapper.cpp      |   0
 .../previous_iterations}/talker.py            |   0
 .../yolo_python/yolo_table_segmentor.py       |  56 +++++++++
 10 files changed, 126 insertions(+), 115 deletions(-)
 delete mode 100755 ed_sensor_integration/scripts/yolo_table_segmentor.py
 rename ed_sensor_integration/{scripts => yolo_python/previous_iterations}/YOLOv8_single_image.py (100%)
 rename ed_sensor_integration/{scripts => yolo_python/previous_iterations}/YOLOv8_video_optimized.py (100%)
 rename ed_sensor_integration/{scripts => yolo_python/previous_iterations}/mask_mapper.cpp (100%)
 rename ed_sensor_integration/{scripts => yolo_python/previous_iterations}/talker.py (100%)
 create mode 100755 ed_sensor_integration/yolo_python/yolo_table_segmentor.py

diff --git a/ed_sensor_integration/CMakeLists.txt b/ed_sensor_integration/CMakeLists.txt
index be5e546b..5f414bbf 100644
--- a/ed_sensor_integration/CMakeLists.txt
+++ b/ed_sensor_integration/CMakeLists.txt
@@ -182,10 +182,7 @@ install(
 add_executable(ed_empty_spot_designator tools/empty_spot_designator.cpp)
 target_link_libraries(ed_empty_spot_designator ed_kinect ${catkin_LIBRARIES})
 
-add_executable(mask_mapper scripts/mask_mapper.cpp)
-target_link_libraries(mask_mapper ed_kinect ${catkin_LIBRARIES})
-
-catkin_install_python(PROGRAMS scripts/talker.py scripts/yolo_table_segmentor.py
+catkin_install_python(PROGRAMS yolo_python/yolo_table_segmentor.py
   DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
 )
 # ------------------------------------------------------------------------------------------------
diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index 2444059e..6611251a 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -94,6 +94,11 @@ class PlaceAreaFinder
      */
     geo::Vec2d canvasToWorld(cv::Point2d point);
 
+    //--------------------------------------------------------------------------------------------------------------------------------------
+    float findModeZValue(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud);
+    void drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float targetDepth);
+    //--------------------------------------------------------------------------------------------------------------------------------------
+
     /**
      * @brief Draw the points in a pointcloud on the canvas. will ignore the z direction of the points
      *
diff --git a/ed_sensor_integration/package.xml b/ed_sensor_integration/package.xml
index 3e7efcc9..ffd8c420 100644
--- a/ed_sensor_integration/package.xml
+++ b/ed_sensor_integration/package.xml
@@ -31,6 +31,7 @@
   <depend>cv_bridge</depend>
   <depend>image_transport</depend>
 
+
   <build_depend>geometry_msgs</build_depend>
   <exec_depend>geometry_msgs</exec_depend>
   <build_depend>rosconsole_bridge</build_depend>
diff --git a/ed_sensor_integration/scripts/yolo_table_segmentor.py b/ed_sensor_integration/scripts/yolo_table_segmentor.py
deleted file mode 100755
index 8318aa46..00000000
--- a/ed_sensor_integration/scripts/yolo_table_segmentor.py
+++ /dev/null
@@ -1,111 +0,0 @@
-#!/usr/bin/env python
-# Software License Agreement (BSD License)
-#
-# Copyright (c) 2008, Willow Garage, Inc.
-# All rights reserved.
-#
-# Redistribution and use in source and binary forms, with or without
-# modification, are permitted provided that the following conditions
-# are met:
-#
-#  * Redistributions of source code must retain the above copyright
-#    notice, this list of conditions and the following disclaimer.
-#  * Redistributions in binary form must reproduce the above
-#    copyright notice, this list of conditions and the following
-#    disclaimer in the documentation and/or other materials provided
-#    with the distribution.
-#  * Neither the name of Willow Garage, Inc. nor the names of its
-#    contributors may be used to endorse or promote products derived
-#    from this software without specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
-# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
-# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
-# FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
-# COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
-# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
-# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
-# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
-# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
-# LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
-# ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-# POSSIBILITY OF SUCH DAMAGE.
-#
-# Revision $Id$
-
-## Simple talker demo that listens to std_msgs/Strings published
-## to the 'chatter' topic
-
-import rospy
-import cv2
-import numpy as np
-from ultralytics import YOLO
-from cv_bridge import CvBridge
-from sensor_msgs.msg import Image
-
-class table_segmentor:
-    def __init__(self) -> None:
-        model_path = "~/MEGA/developers/Donal/yolov8x-seg.pt"
-        device = "cuda"
-        self.model = YOLO(model_path).to(device)
-        self.table_class = 60 #table class defined with index 60 (person = 0)
-
-        rospy.init_node('listener', anonymous=True)
-        self.publisher = rospy.Publisher('/hero/segmented_image',Image,queue_size=10)
-        self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
-
-    @staticmethod
-    def detect(model, frame):
-        results = model(frame)
-        result = results[0]
-        segmentation_contours_idx = [np.array(seg, dtype=np.int32) for seg in result.masks.xy]
-        class_ids = np.array(result.boxes.cls.cpu(), dtype="int")
-        return class_ids, segmentation_contours_idx
-
-    def extract_table_segment(self, image, class_ids, segmentations):
-        table_mask = np.zeros_like(image, dtype=np.uint8)
-        for class_id, seg in zip(class_ids, segmentations):
-            if class_id == self.table_class:
-                cv2.fillPoly(table_mask, [seg], 255)
-        return table_mask
-
-    def callback(self, data):
-        rospy.loginfo("got message")
-        bridge = CvBridge()
-        cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')
-        cv_image = cv2.GaussianBlur(cv_image,(5,5),0)
-        cv_image = cv2.cvtColor(cv_image, cv2.COLOR_RGB2BGR)
-        rospy.loginfo("converted message")
-
-        classes, segmentations = self.detect(self.model, cv_image)
-        #extract table segment and add to frame
-        # for class_id, seg in zip(classes, segmentations):
-        #     if class_id == self.table_class:
-        #         cv2.polylines(cv_image, [seg], True, (255,0,0), 2)
-        # cv2.imshow("Segmented Image", cv_image)
-        # cv2.waitKey(1)
-        # image_message = bridge.cv2_to_imgmsg(cv_image, encoding="passthrough")
-        # self.publisher.publish(image_message)
-        table_segment = self.extract_table_segment(cv_image, classes, segmentations)
-        
-        # Publish the table segment as a binary mask
-        table_message = bridge.cv2_to_imgmsg(table_segment, encoding="passthrough")
-        self.publisher.publish(table_message)
-
-    def listener():
-
-        # In ROS, nodes are uniquely named. If two nodes with the same
-        # name are launched, the previous one is kicked off. The
-        # anonymous=True flag means that rospy will choose a unique
-        # name for our 'listener' node so that multiple listeners can
-        # run simultaneously.
-
-
-        rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , callback)
-
-        # spin() simply keeps python from exiting until this node is stopped
-        rospy.spin()
-
-if __name__ == '__main__':
-    ts = table_segmentor()
-    rospy.spin()
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 9e2c89f2..713150a5 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -7,6 +7,9 @@
 
 #include <ros/ros.h>
 
+//donal
+#include <map>
+//
 //pcl library # TODO remove the unused ones #TODO find out which ones are unused
 #include <pcl/point_representation.h>
 #include <pcl/common/common.h>
@@ -436,6 +439,12 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     createCostmap(object_cloud, occupied_color);
     createCostmap(occluded_cloud, occluded_color);
     createCostmap(not_table_cloud, occupied_color);
+    
+    //donal changes-----------------------------------------------------------------------------------------------------------------------------
+    float mode_z_value =findModeZValue(plane_cloud);
+    std::cout << "Mode Z Value: " << mode_z_value << std::endl;
+    drawContour(plane_cloud,mode_z_value);
+    //donal changes--------------------------------------------------------------------------------------------------------------------------    
 
     // HERO preferred radius
     createRadiusCostmap(canvas, radius_color, placement_margin);
@@ -472,8 +481,62 @@ geo::Vec2d PlaceAreaFinder::canvasToWorld(cv::Point2d point)
     double y = (point.x-canvas_center.x)*-resolution;
     double x = (point.y-canvas_center.y)*-resolution;
     return geo::Vec2d(x, y);
+}
+ //donal changes-------------------------------------------------------------------------------------------------------------------
+float PlaceAreaFinder::findModeZValue(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
+{
+    float mode_z_value = std::numeric_limits<float>::quiet_NaN();  // Using NaN as a default value
+    // Create a map to store Z values and their occurrences
+    std::map<float, int> z_count;
+
+    // Iterate through the points and count occurrences of each Z value
+    for (const auto &point : cloud->points)
+    {
+        float z_value = point.z;
+        z_count[z_value]++;
+    }
+
+    // Find the Z value with the maximum count (mode)
+    int max_count = 0;
+    for (const auto &entry : z_count)
+    {
+        if (entry.second > max_count)
+        {
+            max_count = entry.second;
+            mode_z_value = entry.first;
+        }
+    }
+    return mode_z_value;
+}
+
+
+void PlaceAreaFinder::drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float targetDepth)
+{
+    // Create an OpenCV Mat to store the image
+    cv::Mat image = cv::Mat::zeros(500, 500, CV_8UC3);
+
+    // Convert 3D points to 2D points based on their depth
+    std::vector<cv::Point> contourPoints;
+    for (const pcl::PointXYZRGB& point : cloud->points) {
+        if (std::fabs(point.z - targetDepth) < 0.005) {
+            // Scale the x and y coordinates for visualization
+            int x = static_cast<int>(point.x * 50 + image.cols / 2);
+            int y = static_cast<int>(point.y * 50 + image.rows / 2);
+            contourPoints.emplace_back(x, y);
+        }
+    }
+
+    // Draw the contour
+    std::vector<std::vector<cv::Point>> contours;
+    contours.push_back(contourPoints);
+    cv::drawContours(image, contours, 0, cv::Scalar(255, 255, 255), 2);
+
+    // Display the image
+    cv::imshow("Contour Image", image);
+
 }
 
+//donal changes
 void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
 
 {
diff --git a/ed_sensor_integration/scripts/YOLOv8_single_image.py b/ed_sensor_integration/yolo_python/previous_iterations/YOLOv8_single_image.py
similarity index 100%
rename from ed_sensor_integration/scripts/YOLOv8_single_image.py
rename to ed_sensor_integration/yolo_python/previous_iterations/YOLOv8_single_image.py
diff --git a/ed_sensor_integration/scripts/YOLOv8_video_optimized.py b/ed_sensor_integration/yolo_python/previous_iterations/YOLOv8_video_optimized.py
similarity index 100%
rename from ed_sensor_integration/scripts/YOLOv8_video_optimized.py
rename to ed_sensor_integration/yolo_python/previous_iterations/YOLOv8_video_optimized.py
diff --git a/ed_sensor_integration/scripts/mask_mapper.cpp b/ed_sensor_integration/yolo_python/previous_iterations/mask_mapper.cpp
similarity index 100%
rename from ed_sensor_integration/scripts/mask_mapper.cpp
rename to ed_sensor_integration/yolo_python/previous_iterations/mask_mapper.cpp
diff --git a/ed_sensor_integration/scripts/talker.py b/ed_sensor_integration/yolo_python/previous_iterations/talker.py
similarity index 100%
rename from ed_sensor_integration/scripts/talker.py
rename to ed_sensor_integration/yolo_python/previous_iterations/talker.py
diff --git a/ed_sensor_integration/yolo_python/yolo_table_segmentor.py b/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
new file mode 100755
index 00000000..452ed4ff
--- /dev/null
+++ b/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
@@ -0,0 +1,56 @@
+
+import rospy
+import cv2
+import numpy as np
+from ultralytics import YOLO
+from cv_bridge import CvBridge
+from sensor_msgs.msg import Image
+
+class table_segmentor:
+    def __init__(self) -> None:
+        model_path = "~/MEGA/developers/Donal/yolov8x-seg.pt"
+        device = "cuda"
+        self.model = YOLO(model_path).to(device)
+        self.table_class = 60 #table class defined with index 60 (person = 0)
+
+        rospy.init_node('listener', anonymous=True)
+        self.publisher = rospy.Publisher('/hero/segmented_image',Image,queue_size=10)
+        self.subscriber = rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , self.callback)
+
+    @staticmethod
+    def detect(model, frame):
+        results = model(frame)
+        result = results[0]
+        segmentation_contours_idx = [np.array(seg, dtype=np.int32) for seg in result.masks.xy]
+        class_ids = np.array(result.boxes.cls.cpu(), dtype="int")
+        return class_ids, segmentation_contours_idx
+
+    def extract_table_segment(self, image, class_ids, segmentations):
+        table_mask = np.zeros_like(image, dtype=np.uint8)
+        for class_id, seg in zip(class_ids, segmentations):
+            if class_id == self.table_class:
+                cv2.fillPoly(table_mask, [seg], 255)
+        return table_mask
+
+    def callback(self, data):
+        rospy.loginfo("got message")
+        bridge = CvBridge()
+        cv_image = bridge.imgmsg_to_cv2(data, desired_encoding='passthrough')
+        cv_image = cv2.GaussianBlur(cv_image,(5,5),0)
+        cv_image = cv2.cvtColor(cv_image, cv2.COLOR_RGB2BGR)
+        rospy.loginfo("converted message")
+
+        classes, segmentations = self.detect(self.model, cv_image)
+        table_segment = self.extract_table_segment(cv_image, classes, segmentations)
+        
+        # Publish the table segment as a binary mask
+        table_message = bridge.cv2_to_imgmsg(table_segment, encoding="passthrough")
+        self.publisher.publish(table_message)
+
+    def listener():
+        rospy.Subscriber('/hero/head_rgbd_sensor/rgb/image_raw',Image , callback)
+        rospy.spin()
+
+if __name__ == '__main__':
+    ts = table_segmentor()
+    rospy.spin()

From 9862a02d40613e863080da21ac4187891bc209e2 Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Mon, 18 Dec 2023 18:34:54 +0100
Subject: [PATCH 128/136] paint contour of depth data

---
 .../include/ed/kinect/place_area_finder.h     |   7 +-
 .../src/kinect/place_area_finder.cpp          | 483 ++++++++++++------
 2 files changed, 334 insertions(+), 156 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index 6611251a..bdd285d0 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -95,8 +95,11 @@ class PlaceAreaFinder
     geo::Vec2d canvasToWorld(cv::Point2d point);
 
     //--------------------------------------------------------------------------------------------------------------------------------------
-    float findModeZValue(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud);
-    void drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float targetDepth);
+    void drawfilledContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
+    void drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
+    //void mapCanvasToWorldAndVisualize(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
+    void mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
+
     //--------------------------------------------------------------------------------------------------------------------------------------
 
     /**
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 713150a5..a47f63f1 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -7,10 +7,10 @@
 
 #include <ros/ros.h>
 
-//donal
+// donal
 #include <map>
 //
-//pcl library # TODO remove the unused ones #TODO find out which ones are unused
+// pcl library # TODO remove the unused ones #TODO find out which ones are unused
 #include <pcl/point_representation.h>
 #include <pcl/common/common.h>
 #include <pcl/io/pcd_io.h>
@@ -38,21 +38,20 @@
 
 #include "ed_sensor_integration/sac_model_horizontal_plane.h"
 
-
 /**
  * @brief transform an rgbd image to a pointcloud
- * 
+ *
  * @param image rgbd image
  * @param[out] cloud pcl pointcloud, points are expressed in the frame of the camera according to pcl conventions
  * @return double to be removed
  */
-double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
+double imageToCloud(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
 {
     // Fill in the cloud data
     cloud->width = image.getDepthImage().cols;
     cloud->height = image.getDepthImage().rows;
     cloud->is_dense = false;
-    cloud->resize (cloud->width * cloud->height);
+    cloud->resize(cloud->width * cloud->height);
 
     double fx = image.getCameraModel().fx();
     double fy = image.getCameraModel().fy();
@@ -60,32 +59,31 @@ double imageToCloud(const rgbd::Image& image, pcl::PointCloud<pcl::PointXYZRGB>:
     double half_height = 0.5 * cloud->height;
     double half_width = 0.5 * cloud->width;
 
-    for (uint i=0; i < cloud->height; ++i)
+    for (uint i = 0; i < cloud->height; ++i)
     {
-        for (uint j=0; j < cloud->width; ++j)
+        for (uint j = 0; j < cloud->width; ++j)
         {
 
-            cv::Vec3b bgr = image.getRGBImage().at<cv::Vec3b>(i,j);
-            double d = image.getDepthImage().at<float>(i,j);
-
-            cloud->at(j,i).x = (-half_width+j) * d / fx;
-            cloud->at(j,i).y = (-half_height+i) * d / fy;
-            cloud->at(j,i).z = d;
-            cloud->at(j,i).r = bgr[2];
-            cloud->at(j,i).g = bgr[1];
-            cloud->at(j,i).b = bgr[0];
+            cv::Vec3b bgr = image.getRGBImage().at<cv::Vec3b>(i, j);
+            double d = image.getDepthImage().at<float>(i, j);
 
+            cloud->at(j, i).x = (-half_width + j) * d / fx;
+            cloud->at(j, i).y = (-half_height + i) * d / fy;
+            cloud->at(j, i).z = d;
+            cloud->at(j, i).r = bgr[2];
+            cloud->at(j, i).g = bgr[1];
+            cloud->at(j, i).b = bgr[0];
         }
     }
 
-return image.getCameraModel().fx();
+    return image.getCameraModel().fx();
 }
 
 /**
  * @brief transform a geolib pose into a transformation matrix from the Eigen library
- * 
+ *
  * @param pose geolib pose
- * @return Eigen::Matrix4f 
+ * @return Eigen::Matrix4f
  */
 Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
 {
@@ -107,18 +105,18 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
 
     Eigen::Matrix4f Transform = Eigen::Matrix4f::Identity();
 
-    Transform(0,0) = xx;
-    Transform(0,1) = xy;
-    Transform(0,2) = xz;
-    Transform(0,3) = x;
-    Transform(1,0) = yx;
-    Transform(1,1) = yy;
-    Transform(1,2) = yz;
-    Transform(1,3) = y;
-    Transform(2,0) = zx;
-    Transform(2,1) = zy;
-    Transform(2,2) = zz;
-    Transform(2,3) = z;
+    Transform(0, 0) = xx;
+    Transform(0, 1) = xy;
+    Transform(0, 2) = xz;
+    Transform(0, 3) = x;
+    Transform(1, 0) = yx;
+    Transform(1, 1) = yy;
+    Transform(1, 2) = yz;
+    Transform(1, 3) = y;
+    Transform(2, 0) = zx;
+    Transform(2, 1) = zy;
+    Transform(2, 2) = zz;
+    Transform(2, 3) = z;
 
     // std::cout << Transform << std::endl;
     return Transform;
@@ -132,22 +130,22 @@ Eigen::Matrix4f geolibToEigen(geo::Pose3D pose)
  * @param cloud_no_plane A pointcloud containing all points not within the found plane
  * @return height of the segmented plane OR -1.0 if no plane could be found
  */
-bool SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::ModelCoefficients::Ptr plane_coefficients,
-                 pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::Indices &plane_index, 
-                 pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_no_plane, pcl::Indices &planeless_index)
+bool SegmentPlane(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::ModelCoefficients::Ptr plane_coefficients,
+                  pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::Indices &plane_index,
+                  pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_no_plane, pcl::Indices &planeless_index)
 {
-    pcl::PointIndices::Ptr inliers (new pcl::PointIndices ());
+    pcl::PointIndices::Ptr inliers(new pcl::PointIndices());
     // Create the segmentation object
     pcl::SACSegmentation<pcl::PointXYZRGB> seg;
     // Optional
-    seg.setOptimizeCoefficients (true);
+    seg.setOptimizeCoefficients(true);
     // Mandatory
-    seg.setModelType (pcl::SACMODEL_PARALLEL_PLANE);
-    seg.setMethodType (pcl::SAC_RANSAC);
-    seg.setMaxIterations (1000);
-    seg.setDistanceThreshold (0.01);
-    seg.setAxis (Eigen::Vector3f(1,0,0));
-    seg.setEpsAngle(5*0.0174532925); //*0.0174532925 to radians
+    seg.setModelType(pcl::SACMODEL_PARALLEL_PLANE);
+    seg.setMethodType(pcl::SAC_RANSAC);
+    seg.setMaxIterations(1000);
+    seg.setDistanceThreshold(0.01);
+    seg.setAxis(Eigen::Vector3f(1, 0, 0));
+    seg.setEpsAngle(5 * 0.0174532925); //*0.0174532925 to radians
 
     // Create the filtering object
     pcl::ExtractIndices<pcl::PointXYZRGB> extract;
@@ -157,7 +155,8 @@ bool SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::M
     seg.setInputCloud(cloud_in);
     seg.segment(*inliers, *plane_coefficients);
 
-    if (inliers->indices.size() == 0) {
+    if (inliers->indices.size() == 0)
+    {
         std::cerr << "Could not estimate a planar model for the given dataset." << std::endl;
         return false;
     }
@@ -180,12 +179,12 @@ bool SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::M
     extract2.filter(*cloud_no_plane);
 
     // handcraft the planeless index
-    planeless_index.resize(cloud_in->size()-plane_index.size());
-    int plane_i = 0; //most recent index of plane_index
+    planeless_index.resize(cloud_in->size() - plane_index.size());
+    int plane_i = 0; // most recent index of plane_index
     int planeless_i = 0;
-    for (int i = 0; i<int(cloud_in->size()); i++)
+    for (int i = 0; i < int(cloud_in->size()); i++)
     {
-        if (i==plane_index[plane_i])
+        if (i == plane_index[plane_i])
         {
             plane_i++;
         }
@@ -199,28 +198,27 @@ bool SegmentPlane (const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::M
     return true;
 }
 
-
 /**
  * @brief extract all pixels of a certain color from a canvas
- * 
+ *
  * @param canvas original image
- * @param[out] placement_canvas image to draw the extracted pixels on must be the same size as canvas 
+ * @param[out] placement_canvas image to draw the extracted pixels on must be the same size as canvas
  * @param targetColor color to be extracted
  */
-void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Scalar targetColor)
+void ExtractPlacementOptions(cv::Mat &canvas, cv::Mat &placement_canvas, cv::Scalar targetColor)
 {
     cv::Point2d canvas_center(canvas.rows / 2, canvas.cols);
 
     std::vector<cv::Point> identicalPoints;
 
-    for(int row = canvas.rows; row > 0; --row)
+    for (int row = canvas.rows; row > 0; --row)
     {
-        for(int col = canvas.cols; col > 0; --col)
+        for (int col = canvas.cols; col > 0; --col)
         {
             cv::Vec3b currPixel = canvas.at<cv::Vec3b>(row, col);
-            if(currPixel.val[0] == targetColor.val[0] &&
-               currPixel.val[1] == targetColor.val[1] &&
-               currPixel.val[2] == targetColor.val[2])
+            if (currPixel.val[0] == targetColor.val[0] &&
+                currPixel.val[1] == targetColor.val[1] &&
+                currPixel.val[2] == targetColor.val[2])
             {
                 cv::Point2d p = cv::Point(col, row);
                 if (p.x >= 0 && p.y >= 0 && p.x < placement_canvas.cols && p.y < placement_canvas.rows)
@@ -232,22 +230,22 @@ void ExtractPlacementOptions(cv::Mat& canvas, cv::Mat& placement_canvas, cv::Sca
 
 /**
  * @brief Get the coordinates of a point in an image which matches the target color
- * 
+ *
  * @param canvas image to check
  * @param targetColor color to be found
  * @param point coordinates of one point which has the targetColor
  * @return whether or not a pixel was found
  */
-bool GetPlacementOption(cv::Mat& canvas, cv::Scalar targetColor, cv::Point2d& point)
+bool GetPlacementOption(cv::Mat &canvas, cv::Scalar targetColor, cv::Point2d &point)
 {
-    for(int row = 0; row <canvas.rows; ++row)
+    for (int row = 0; row < canvas.rows; ++row)
     {
-        for(int col = canvas.cols; col > 0; --col)
+        for (int col = canvas.cols; col > 0; --col)
         {
             cv::Vec3b currPixel = canvas.at<cv::Vec3b>(row, col);
-            if(currPixel.val[0] == targetColor.val[0] &&
-               currPixel.val[1] == targetColor.val[1] &&
-               currPixel.val[2] == targetColor.val[2])
+            if (currPixel.val[0] == targetColor.val[0] &&
+                currPixel.val[1] == targetColor.val[1] &&
+                currPixel.val[2] == targetColor.val[2])
             {
                 point = cv::Point(col, row);
                 return true;
@@ -259,10 +257,10 @@ bool GetPlacementOption(cv::Mat& canvas, cv::Scalar targetColor, cv::Point2d& po
 
 /**
  * @brief remove the floor from a pointcloud cloud_in and return the cloud_out with index. It is assumed the floor is aligned with the plane z=0
- * 
- * @param cloud_in 
- * @param cloud_out 
- * @param index 
+ *
+ * @param cloud_in
+ * @param cloud_out
+ * @param index
  */
 void removeFloor(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_out, pcl::Indices &index)
 {
@@ -298,7 +296,7 @@ void filterHeight(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, float h
 
 /**
  * @brief Project a plane onto a a plane along the beams of the camera
- * 
+ *
  * @param cloud_in cloud with points to be projected
  * @param transform transform between the camera and the origin of the cloud in
  * @param plane_height height of the plane to be projected onto.
@@ -315,11 +313,11 @@ void projectToPlane(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, Eigen
     float z = transform(2, 3);
     for (uint nIndex = 0; nIndex < cloud_in->points.size(); nIndex++)
     {
-        float lower = cloud_in->points[nIndex].z - z; // height between camera and point. 
+        float lower = cloud_in->points[nIndex].z - z;            // height between camera and point.
         float upper = plane_height - cloud_in->points[nIndex].z; // height between the point and the table
-        float lambda = upper / lower; // ratio between camera-point distance and point-projection distance
-        float dx = cloud_in->points[nIndex].x - x; // difference between point x and camera x
-        float dy = cloud_in->points[nIndex].y - y; // difference between point y and camera y
+        float lambda = upper / lower;                            // ratio between camera-point distance and point-projection distance
+        float dx = cloud_in->points[nIndex].x - x;               // difference between point x and camera x
+        float dy = cloud_in->points[nIndex].y - y;               // difference between point y and camera y
 
         cloud_out->points[nIndex].z = plane_height;
         cloud_out->points[nIndex].x = cloud_in->points[nIndex].x + lambda * dx;
@@ -329,14 +327,14 @@ void projectToPlane(const pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud_in, Eigen
 
 /**
  * @brief returns indexes of cloud C to cloud A given the index of cloud B to A and cloud C to B)
- * 
- * @param index1 
- * @param index2 
- * @return pcl::Indices 
+ *
+ * @param index1
+ * @param index2
+ * @return pcl::Indices
  */
 pcl::Indices multiplyIndex(pcl::Indices indexBA, pcl::Indices indexCB)
 {
-    for (uint i=0; i<indexCB.size(); i++)
+    for (uint i = 0; i < indexCB.size(); i++)
     {
         indexCB[i] = indexBA[indexCB[i]];
     }
@@ -351,7 +349,7 @@ PlaceAreaFinder::~PlaceAreaFinder()
 {
 }
 
-bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose)
+bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sensor_pose, geo::Pose3D &place_pose)
 {
     bool visualize = true;
     // std::cout << "converting image to cloud" << std::endl;
@@ -376,7 +374,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     pcl::Indices plane_index;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr planeless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::Indices planeless_index;
-    pcl::ModelCoefficients::Ptr plane_coefficients (new pcl::ModelCoefficients ());
+    pcl::ModelCoefficients::Ptr plane_coefficients(new pcl::ModelCoefficients());
     if (!SegmentPlane(floorless_cloud, plane_coefficients, plane_cloud, plane_index, planeless_cloud, planeless_index))
     {
         std::cout << "Could not find plane" << std::endl;
@@ -388,7 +386,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     // Filter out objects above the table plane and put them in seperate cloud
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr object_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::Indices object_index;
-    filterHeight(planeless_cloud, height, height+0.30, object_cloud, object_index);
+    filterHeight(planeless_cloud, height, height + 0.30, object_cloud, object_index);
 
     // Create pointcloud with occluded space based on the object cloud
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr occluded_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
@@ -397,11 +395,11 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     // Filter out objects below the table plane and put them in seperate cloud
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr below_table_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::Indices below_index;
-    filterHeight(planeless_cloud, 0.0, height-0.02, below_table_cloud, below_index);
+    filterHeight(planeless_cloud, 0.0, height - 0.02, below_table_cloud, below_index);
 
     // Create pointcloud with unoccluded space based on the bewow table cloud
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr not_table_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
-    projectToPlane(below_table_cloud, transform, height, not_table_cloud);    
+    projectToPlane(below_table_cloud, transform, height, not_table_cloud);
 
     // std::cout << "creating costmap" << std::endl;
     canvas = cv::Mat(500, 500, CV_8UC3, cv::Scalar(0, 0, 0));
@@ -439,12 +437,13 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     createCostmap(object_cloud, occupied_color);
     createCostmap(occluded_cloud, occluded_color);
     createCostmap(not_table_cloud, occupied_color);
-    
-    //donal changes-----------------------------------------------------------------------------------------------------------------------------
-    float mode_z_value =findModeZValue(plane_cloud);
-    std::cout << "Mode Z Value: " << mode_z_value << std::endl;
-    drawContour(plane_cloud,mode_z_value);
-    //donal changes--------------------------------------------------------------------------------------------------------------------------    
+
+    // donal changes-----------------------------------------------------------------------------------------------------------------------------
+    cv::Scalar donal_colour(255, 255, 0);
+    drawContour(plane_cloud, donal_colour);
+    mapCanvasToWorldAndPlaceInAnnotatedImage(*image,plane_cloud, donal_colour);
+    // drawfilledContour(plane_cloud,table_color);
+    // donal changes--------------------------------------------------------------------------------------------------------------------------
 
     // HERO preferred radius
     createRadiusCostmap(canvas, radius_color, placement_margin);
@@ -467,7 +466,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sen
     place_point = canvasToWorld(place_point_canvas);
 
     // fill result
-    place_pose = geo::Pose3D(place_point.x, place_point.y, height+0.02);
+    place_pose = geo::Pose3D(place_point.x, place_point.y, height + 0.02);
     return true;
 }
 
@@ -478,71 +477,247 @@ cv::Point2d PlaceAreaFinder::worldToCanvas(double x, double y)
 
 geo::Vec2d PlaceAreaFinder::canvasToWorld(cv::Point2d point)
 {
-    double y = (point.x-canvas_center.x)*-resolution;
-    double x = (point.y-canvas_center.y)*-resolution;
+    double y = (point.x - canvas_center.x) * -resolution;
+    double x = (point.y - canvas_center.y) * -resolution;
     return geo::Vec2d(x, y);
 }
- //donal changes-------------------------------------------------------------------------------------------------------------------
-float PlaceAreaFinder::findModeZValue(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
+// donal changes-------------------------------------------------------------------------------------------------------------------
+void PlaceAreaFinder::drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
 {
-    float mode_z_value = std::numeric_limits<float>::quiet_NaN();  // Using NaN as a default value
-    // Create a map to store Z values and their occurrences
-    std::map<float, int> z_count;
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    // Create a binary mask
+    cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
 
-    // Iterate through the points and count occurrences of each Z value
-    for (const auto &point : cloud->points)
+    std::vector<cv::Point> points; // Vector to store points for convex hull
+
+    for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
     {
-        float z_value = point.z;
-        z_count[z_value]++;
+        double x = cloud->points[nIndex].x;
+        double y = cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+        {
+            // Update the canvas with the color
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+
+            // Set corresponding pixel in the mask to 255 (white)
+            mask.at<uchar>(p) = 255;
+
+            // Store the point for convex hull
+            points.push_back(p);
+        }
     }
 
-    // Find the Z value with the maximum count (mode)
-    int max_count = 0;
-    for (const auto &entry : z_count)
+    // Check if there are enough points to compute convex hull
+    if (points.size() >= 3)
     {
-        if (entry.second > max_count)
+        // Find convex hull of the points
+        std::vector<cv::Point> hull;
+        cv::convexHull(points, hull);
+
+        // Draw the convex hull on the canvas
+        std::vector<std::vector<cv::Point>> contours = {hull};
+        cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 255), 2);
+    }
+    else
+    {
+        // Handle the case when there are not enough points for convex hull
+        std::cerr << "Not enough points for convex hull." << std::endl;
+    }
+}
+
+void PlaceAreaFinder::drawfilledContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
+{
+    const double fixedOpacity = 0.2; // Set the desired fixed opacity
+
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    // Create a binary mask
+    cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
+
+    std::vector<cv::Point> points; // Vector to store points for convex hull
+
+    for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
+    {
+        double x = cloud->points[nIndex].x;
+        double y = cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
         {
-            max_count = entry.second;
-            mode_z_value = entry.first;
+            // Update the canvas with the color
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+
+            // Set corresponding pixel in the mask to 255 (white)
+            mask.at<uchar>(p) = 255;
+
+            // Store the point for convex hull
+            points.push_back(p);
         }
     }
-    return mode_z_value;
-}
 
+    // Check if there are enough points to compute convex hull
+    if (points.size() >= 3)
+    {
+        // Find convex hull of the points
+        std::vector<cv::Point> hull;
+        cv::convexHull(points, hull);
 
-void PlaceAreaFinder::drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, float targetDepth)
+        // Fill the convex hull with fixed opacity
+        cv::fillPoly(canvas, std::vector<std::vector<cv::Point>>{hull}, cv::Scalar(color[0], color[1], color[2], fixedOpacity * 255));
+    }
+    else
+    {
+        // Handle the case when there are not enough points for convex hull
+        std::cerr << "Not enough points for convex hull." << std::endl;
+    }
+}
+
+void PlaceAreaFinder::mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
 {
-    // Create an OpenCV Mat to store the image
-    cv::Mat image = cv::Mat::zeros(500, 500, CV_8UC3);
-
-    // Convert 3D points to 2D points based on their depth
-    std::vector<cv::Point> contourPoints;
-    for (const pcl::PointXYZRGB& point : cloud->points) {
-        if (std::fabs(point.z - targetDepth) < 0.005) {
-            // Scale the x and y coordinates for visualization
-            int x = static_cast<int>(point.x * 50 + image.cols / 2);
-            int y = static_cast<int>(point.y * 50 + image.rows / 2);
-            contourPoints.emplace_back(x, y);
+    const double fixedOpacity = 0.2; // Set the desired fixed opacity
+
+    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+    // Access width and height directly from the depth image
+    int imageWidth = image.getDepthImage().cols;
+    int imageHeight = image.getDepthImage().rows;
+
+    // Create a binary mask
+    cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
+
+    std::vector<cv::Point> points; // Vector to store points for convex hull
+
+    for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
+    {
+        double x = cloud->points[nIndex].x;
+        double y = cloud->points[nIndex].y;
+
+        cv::Point2d p = worldToCanvas(x, y);
+
+        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+        {
+            // Update the canvas with the color
+            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+
+            // Set corresponding pixel in the mask to 255 (white)
+            mask.at<uchar>(p) = 255;
+
+            // Store the point for convex hull
+            points.push_back(p);
         }
     }
 
-    // Draw the contour
-    std::vector<std::vector<cv::Point>> contours;
-    contours.push_back(contourPoints);
-    cv::drawContours(image, contours, 0, cv::Scalar(255, 255, 255), 2);
+    // Check if there are enough points to compute convex hull
+    if (points.size() >= 3)
+    {
+        // Find convex hull of the points
+        std::vector<cv::Point> hull;
+        cv::convexHull(points, hull);
 
-    // Display the image
-    cv::imshow("Contour Image", image);
+        // Fill the convex hull with fixed opacity
+        cv::fillPoly(canvas, std::vector<std::vector<cv::Point>>{hull}, cv::Scalar(color[0], color[1], color[2], fixedOpacity * 255));
 
+        // Map the convex hull points to world coordinates and place in annotated image
+        for (const auto &point : hull)
+        {
+            geo::Vec2d worldPoint = canvasToWorld(point);
+
+            int row = static_cast<int>(worldPoint.y);
+            int col = static_cast<int>(worldPoint.x);
+
+            // Check if the point is within the bounds of the annotated image
+            if (row >= 0 && col >= 0 && row < imageHeight && col < imageWidth)
+            {
+                int index = row * imageWidth + col;
+                annotateImage(image, pcl::Indices(1, index), color);
+            }
+        }
+    }
+    else
+    {
+        // Handle the case when there are not enough points for convex hull
+        std::cerr << "Not enough points for convex hull." << std::endl;
+    }
 }
 
-//donal changes
+
+// void PlaceAreaFinder::mapCanvasToWorldAndVisualize(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
+// {
+//     const double fixedOpacity = 0.2; // Set the desired fixed opacity
+
+//     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+
+//     // Create a binary mask
+//     cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
+
+//     std::vector<cv::Point> points; // Vector to store points for convex hull
+
+//     for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
+//     {
+//         double x = cloud->points[nIndex].x;
+//         double y = cloud->points[nIndex].y;
+
+//         cv::Point2d p = worldToCanvas(x, y);
+
+//         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+//         {
+//             // Update the canvas with the color
+//             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+
+//             // Set corresponding pixel in the mask to 255 (white)
+//             mask.at<uchar>(p) = 255;
+
+//             // Store the point for convex hull
+//             points.push_back(p);
+//         }
+//     }
+
+//     // Check if there are enough points to compute convex hull
+//     if (points.size() >= 3)
+//     {
+//         // Find convex hull of the points
+//         std::vector<cv::Point> hull;
+//         cv::convexHull(points, hull);
+
+//         // Fill the convex hull with fixed opacity
+//         cv::fillPoly(canvas, std::vector<std::vector<cv::Point>>{hull}, cv::Scalar(color[0], color[1], color[2], fixedOpacity * 255));
+
+//         // Create a new canvas for visualization
+//         cv::Mat visualizationCanvas = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC3);
+
+//         // Map the convex hull points to world coordinates and visualize
+//         for (const auto &point : hull)
+//         {
+//             geo::Vec2d worldPoint = canvasToWorld(point);
+
+//             // Draw a point on the visualization canvas
+//             cv::circle(visualizationCanvas, worldToCanvas(worldPoint.x, worldPoint.y), 5, cv::Scalar(0, 255, 0), -1);
+//         }
+
+//         // Display the visualization canvas (you can customize this part based on your visualization tool or library)
+//         cv::imshow("Mapped Points in World Coordinates", visualizationCanvas);
+//     }
+//     else
+//     {
+//         // Handle the case when there are not enough points for convex hull
+//         std::cerr << "Not enough points for convex hull." << std::endl;
+//     }
+// }
+
+
+// donal changes----------------------------------------------------------------------------------------------------------------------------------
+
 void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
 
 {
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
-    for (uint nIndex = 0; nIndex < cloud->points.size (); nIndex++)
+    for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
     {
         double x = cloud->points[nIndex].x;
         double y = cloud->points[nIndex].y;
@@ -550,51 +725,51 @@ void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud
         cv::Point2d p = worldToCanvas(x, y);
         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }    
+    }
 }
 
-void PlaceAreaFinder::createRadiusCostmap(cv::Mat& canvas, cv::Scalar color, float placement_margin)
+void PlaceAreaFinder::createRadiusCostmap(cv::Mat &canvas, cv::Scalar color, float placement_margin)
 {
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-    float upper_radius = 0.75 + placement_margin/2;
-    float lower_radius = 0.60 - placement_margin/2;
-        for (float phi = 0; phi < 360; phi++)
+    float upper_radius = 0.75 + placement_margin / 2;
+    float lower_radius = 0.60 - placement_margin / 2;
+    for (float phi = 0; phi < 360; phi++)
+    {
+        for (int i = 0; i < 100; i++)
         {
-            for (int i = 0; i < 100; i++)
-            {
-            double y = upper_radius * sin(phi/(180/M_PI)) + 0.03 * i * sin(phi/(180/M_PI));
-            double x = upper_radius * cos(phi/(180/M_PI)) + 0.03 * i * cos(phi/(180/M_PI));
+            double y = upper_radius * sin(phi / (180 / M_PI)) + 0.03 * i * sin(phi / (180 / M_PI));
+            double x = upper_radius * cos(phi / (180 / M_PI)) + 0.03 * i * cos(phi / (180 / M_PI));
 
             cv::Point2d p = worldToCanvas(x, y);
             if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-            }
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+        }
 
-            for (int i = 0; i < 100; i++)
-            {
-            double y = lower_radius * sin(phi/(180/M_PI)) - lower_radius/100 * i * sin(phi/(180/M_PI));
-            double x = lower_radius * cos(phi/(180/M_PI)) - lower_radius/100 * i * cos(phi/(180/M_PI));
+        for (int i = 0; i < 100; i++)
+        {
+            double y = lower_radius * sin(phi / (180 / M_PI)) - lower_radius / 100 * i * sin(phi / (180 / M_PI));
+            double x = lower_radius * cos(phi / (180 / M_PI)) - lower_radius / 100 * i * cos(phi / (180 / M_PI));
 
             cv::Point2d p = worldToCanvas(x, y);
             if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-            }
+                canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
         }
+    }
 }
 
-void PlaceAreaFinder::dilateCostmap(cv::Mat& canvas, cv::Mat& dilated_canvas, float placement_margin)
+void PlaceAreaFinder::dilateCostmap(cv::Mat &canvas, cv::Mat &dilated_canvas, float placement_margin)
 {
     float Pixelsize = placement_margin / resolution;
-    cv::Mat element = cv::getStructuringElement( cv::MORPH_ELLIPSE,
-                                             cv::Size( Pixelsize, Pixelsize),
-                                             cv::Point(-1, -1) );
-    cv::dilate(canvas, dilated_canvas, element );
+    cv::Mat element = cv::getStructuringElement(cv::MORPH_ELLIPSE,
+                                                cv::Size(Pixelsize, Pixelsize),
+                                                cv::Point(-1, -1));
+    cv::dilate(canvas, dilated_canvas, element);
 }
 
-void PlaceAreaFinder::annotateImage(const rgbd::Image& image, const pcl::Indices index, cv::Scalar color)
+void PlaceAreaFinder::annotateImage(const rgbd::Image &image, const pcl::Indices index, cv::Scalar color)
 {
     int width = image.getDepthImage().cols;
-    
+
     for (uint i = 0; i < index.size(); i++)
     {
         int col = index[i] % width;
@@ -603,5 +778,5 @@ void PlaceAreaFinder::annotateImage(const rgbd::Image& image, const pcl::Indices
         cv::Point2d p = cv::Point2d(col, row);
         if (p.x >= 0 && p.y >= 0 && p.x < annotated_image.cols && p.y < annotated_image.rows)
             annotated_image.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-    }    
+    }
 }

From eb18b487ae3d1138310e0ace830ee9cfdb877705 Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Sat, 23 Dec 2023 17:58:34 +0100
Subject: [PATCH 129/136] filtered annotated image using segmentation mask

---
 .../include/ed/kinect/place_area_finder.h     |   6 +-
 .../src/kinect/kinect_plugin.cpp              |   4 +-
 .../src/kinect/place_area_finder.cpp          | 214 ++++++++++++------
 .../tools/empty_spot_designator.cpp           |  18 +-
 4 files changed, 167 insertions(+), 75 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index bdd285d0..80fa5a30 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -36,7 +36,7 @@ class PlaceAreaFinder
      * @param[out] place_pose expressed in the same frame as sensor pose. One of the possible poses where an object may be placed, currently returns the pose furthest on the table
      * @return whether or not a suitable place was found
      */
-    bool findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose);
+    bool findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose,const cv::Mat &mask);
 
     /**
      * @brief Get an image of the analysed space, used for introspection
@@ -98,7 +98,7 @@ class PlaceAreaFinder
     void drawfilledContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
     void drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
     //void mapCanvasToWorldAndVisualize(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
-    void mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
+    // void mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
 
     //--------------------------------------------------------------------------------------------------------------------------------------
 
@@ -134,7 +134,7 @@ class PlaceAreaFinder
      * @param indeces 
      * @param color
      */
-    void annotateImage(const rgbd::Image& image, const pcl::Indices index, cv::Scalar color);
+    void annotateImage(const rgbd::Image& image, const pcl::Indices index, cv::Scalar color,const cv::Mat &mask);
 
 };
 
diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.cpp b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
index 0593adbe..9b5d8d12 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.cpp
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
@@ -289,7 +289,7 @@ bool KinectPlugin::srvPlaceArea(__attribute__((unused)) ed_sensor_integration_ms
 {
     // - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     // Get new image
-
+    cv::Mat mask;
     rgbd::ImageConstPtr image;
     geo::Pose3D sensor_pose; // in base link frame
 
@@ -301,7 +301,7 @@ bool KinectPlugin::srvPlaceArea(__attribute__((unused)) ed_sensor_integration_ms
 
     // Determine place area
     geo::Pose3D place_pose; // w.r.t base link
-    if (!place_area_finder_.findArea(image, sensor_pose, place_pose))
+    if (!place_area_finder_.findArea(image, sensor_pose, place_pose,mask))
     {
         res.error_msg = "No valid place area found";
         return true;
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index a47f63f1..5e414a85 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -341,6 +341,7 @@ pcl::Indices multiplyIndex(pcl::Indices indexBA, pcl::Indices indexCB)
     return indexCB;
 }
 
+
 PlaceAreaFinder::PlaceAreaFinder()
 {
 }
@@ -349,7 +350,7 @@ PlaceAreaFinder::~PlaceAreaFinder()
 {
 }
 
-bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sensor_pose, geo::Pose3D &place_pose)
+bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sensor_pose, geo::Pose3D &place_pose,const cv::Mat &mask)
 {
     bool visualize = true;
     // std::cout << "converting image to cloud" << std::endl;
@@ -363,7 +364,6 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     // keep track of the indices in the original image
     std::vector<int> indices;
     pcl::Indices floorless_index;
-
     // Filter out floor
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr floorless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     removeFloor(cloud, floorless_cloud, floorless_index);
@@ -418,16 +418,16 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     float length = object_diameter + error_margin;
     float placement_margin = 2 * 0.02 + length;
 
-    if (visualize)
+    if (visualize && !mask.empty())
     {
         std::cout << "annotating image" << std::endl;
         annotated_image = image->getRGBImage().clone();
         pcl::Indices plane_cloud_index = multiplyIndex(floorless_index, plane_index);
-        annotateImage(*image, plane_cloud_index, table_color);
+        annotateImage(*image, plane_cloud_index, table_color,mask);
         pcl::Indices object_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, object_index));
-        annotateImage(*image, object_cloud_index, occupied_color);
+        annotateImage(*image, object_cloud_index, occupied_color,mask);
         pcl::Indices below_table_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, below_index));
-        annotateImage(*image, below_table_cloud_index, occluded_color);
+        annotateImage(*image, below_table_cloud_index, occluded_color,mask);
     }
 
     std::cout << "creating costmap" << std::endl;
@@ -441,7 +441,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     // donal changes-----------------------------------------------------------------------------------------------------------------------------
     cv::Scalar donal_colour(255, 255, 0);
     drawContour(plane_cloud, donal_colour);
-    mapCanvasToWorldAndPlaceInAnnotatedImage(*image,plane_cloud, donal_colour);
+    // mapCanvasToWorldAndPlaceInAnnotatedImage(*image,plane_cloud, donal_colour);
     // drawfilledContour(plane_cloud,table_color);
     // donal changes--------------------------------------------------------------------------------------------------------------------------
 
@@ -577,73 +577,139 @@ void PlaceAreaFinder::drawfilledContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr c
     }
 }
 
-void PlaceAreaFinder::mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
-{
-    const double fixedOpacity = 0.2; // Set the desired fixed opacity
+// void PlaceAreaFinder::mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
+// {
+//     const double fixedOpacity = 0.2; // Set the desired fixed opacity
 
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
+//     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
-    // Access width and height directly from the depth image
-    int imageWidth = image.getDepthImage().cols;
-    int imageHeight = image.getDepthImage().rows;
+//     // Access width and height directly from the depth image
+//     int imageWidth = image.getDepthImage().cols;
+//     int imageHeight = image.getDepthImage().rows;
 
-    // Create a binary mask
-    cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
+//     // Create a binary mask
+//     cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
 
-    std::vector<cv::Point> points; // Vector to store points for convex hull
+//     std::vector<cv::Point> points; // Vector to store points for convex hull
 
-    for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
-    {
-        double x = cloud->points[nIndex].x;
-        double y = cloud->points[nIndex].y;
+//     for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
+//     {
+//         double x = cloud->points[nIndex].x;
+//         double y = cloud->points[nIndex].y;
 
-        cv::Point2d p = worldToCanvas(x, y);
+//         cv::Point2d p = worldToCanvas(x, y);
 
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-        {
-            // Update the canvas with the color
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+//         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+//         {
+//             // Update the canvas with the color
+//             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
 
-            // Set corresponding pixel in the mask to 255 (white)
-            mask.at<uchar>(p) = 255;
+//             // Set corresponding pixel in the mask to 255 (white)
+//             mask.at<uchar>(p) = 255;
 
-            // Store the point for convex hull
-            points.push_back(p);
-        }
-    }
+//             // Store the point for convex hull
+//             points.push_back(p);
+//         }
+//     }
 
-    // Check if there are enough points to compute convex hull
-    if (points.size() >= 3)
-    {
-        // Find convex hull of the points
-        std::vector<cv::Point> hull;
-        cv::convexHull(points, hull);
+//     // Check if there are enough points to compute convex hull
+//     if (points.size() >= 3)
+//     {
+//         // Find convex hull of the points
+//         std::vector<cv::Point> hull;
+//         cv::convexHull(points, hull);
 
-        // Fill the convex hull with fixed opacity
-        cv::fillPoly(canvas, std::vector<std::vector<cv::Point>>{hull}, cv::Scalar(color[0], color[1], color[2], fixedOpacity * 255));
+//         // Fill the convex hull with fixed opacity
+//         cv::fillPoly(canvas, std::vector<std::vector<cv::Point>>{hull}, cv::Scalar(color[0], color[1], color[2], fixedOpacity * 255));
+// void PlaceAreaFinder::mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
+// {
+//     const double fixedOpacity = 0.2; // Set the desired fixed opacity
 
-        // Map the convex hull points to world coordinates and place in annotated image
-        for (const auto &point : hull)
-        {
-            geo::Vec2d worldPoint = canvasToWorld(point);
+//     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
-            int row = static_cast<int>(worldPoint.y);
-            int col = static_cast<int>(worldPoint.x);
+//     // Access width and height directly from the depth image
+//     int imageWidth = image.getDepthImage().cols;
+//     int imageHeight = image.getDepthImage().rows;
 
-            // Check if the point is within the bounds of the annotated image
-            if (row >= 0 && col >= 0 && row < imageHeight && col < imageWidth)
-            {
-                int index = row * imageWidth + col;
-                annotateImage(image, pcl::Indices(1, index), color);
-            }
-        }
-    }
-    else
-    {
-        // Handle the case when there are not enough points for convex hull
-        std::cerr << "Not enough points for convex hull." << std::endl;
-    }
-}
+//     // Create a binary mask
+//     cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
+
+//     std::vector<cv::Point> points; // Vector to store points for convex hull
+
+//     for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
+//     {
+//         double x = cloud->points[nIndex].x;
+//         double y = cloud->points[nIndex].y;
+
+//         cv::Point2d p = worldToCanvas(x, y);
+
+//         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+//         {
+//             // Update the canvas with the color
+//             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+
+//             // Set corresponding pixel in the mask to 255 (white)
+//             mask.at<uchar>(p) = 255;
+
+//             // Store the point for convex hull
+//             points.push_back(p);
+//         }
+//     }
+
+//     // Check if there are enough points to compute convex hull
+//     if (points.size() >= 3)
+//     {
+//         // Find convex hull of the points
+//         std::vector<cv::Point> hull;
+//         cv::convexHull(points, hull);
+
+//         // Fill the convex hull with fixed opacity
+//         cv::fillPoly(canvas, std::vector<std::vector<cv::Point>>{hull}, cv::Scalar(color[0], color[1], color[2], fixedOpacity * 255));
+
+//         // Map the convex hull points to world coordinates and place in annotated image
+//         for (const auto &point : hull)
+//         {
+//             geo::Vec2d worldPoint = canvasToWorld(point);
+
+//             int row = static_cast<int>(worldPoint.y);
+//             int col = static_cast<int>(worldPoint.x);
+
+//             // Check if the point is within the bounds of the annotated image
+//             if (row >= 0 && col >= 0 && row < imageHeight && col < imageWidth)
+//             {
+//                 int index = row * imageWidth + col;
+//                 annotateImage(image, pcl::Indices(1, index), color,mask);
+//             }
+//         }
+//     }
+//     else
+//     {
+//         // Handle the case when there are not enough points for convex hull
+//         std::cerr << "Not enough points for convex hull." << std::endl;
+//     }
+// }
+//         // Map the convex hull points to world coordinates and place in annotated image
+//         for (const auto &point : hull)
+//         {
+//             geo::Vec2d worldPoint = canvasToWorld(point);
+
+//             int row = static_cast<int>(worldPoint.y);
+//             int col = static_cast<int>(worldPoint.x);
+
+//             // Check if the point is within the bounds of the annotated image
+//             if (row >= 0 && col >= 0 && row < imageHeight && col < imageWidth)
+//             {
+//                 int index = row * imageWidth + col;
+//                 annotateImage(image, pcl::Indices(1, index), color,mask);
+//             }
+//         }
+//     }
+//     else
+//     {
+//         // Handle the case when there are not enough points for convex hull
+//         std::cerr << "Not enough points for convex hull." << std::endl;
+//     }
+// }
 
 
 // void PlaceAreaFinder::mapCanvasToWorldAndVisualize(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
@@ -711,9 +777,7 @@ void PlaceAreaFinder::mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image
 
 
 // donal changes----------------------------------------------------------------------------------------------------------------------------------
-
 void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
-
 {
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
@@ -766,17 +830,37 @@ void PlaceAreaFinder::dilateCostmap(cv::Mat &canvas, cv::Mat &dilated_canvas, fl
     cv::dilate(canvas, dilated_canvas, element);
 }
 
-void PlaceAreaFinder::annotateImage(const rgbd::Image &image, const pcl::Indices index, cv::Scalar color)
+// void PlaceAreaFinder::annotateImage(const rgbd::Image &image, const pcl::Indices index, cv::Scalar color)
+// {
+//     int width = image.getDepthImage().cols;
+
+//     for (uint i = 0; i < index.size(); i++)
+//     {
+//         int col = index[i] % width;
+//         int row = index[i] / width;
+
+//         cv::Point2d p = cv::Point2d(col, row);
+//         if (p.x >= 0 && p.y >= 0 && p.x < annotated_image.cols && p.y < annotated_image.rows)
+//             annotated_image.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+//     }
+// }
+void PlaceAreaFinder::annotateImage(const rgbd::Image &image, const pcl::Indices index, cv::Scalar color, const cv::Mat &mask)
 {
     int width = image.getDepthImage().cols;
 
+    cv::Mat seg_mask = mask;
+
     for (uint i = 0; i < index.size(); i++)
     {
         int col = index[i] % width;
         int row = index[i] / width;
 
         cv::Point2d p = cv::Point2d(col, row);
-        if (p.x >= 0 && p.y >= 0 && p.x < annotated_image.cols && p.y < annotated_image.rows)
+
+        // Check if the point is within the segmentation mask
+        if (p.x >= 0 && p.y >= 0 && p.x < annotated_image.cols && p.y < annotated_image.rows && seg_mask.at<uchar>(p.x,p.y) > 0)
+        {
             annotated_image.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+        }
     }
-}
+}
\ No newline at end of file
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 04c1f00d..8728da6d 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -195,15 +195,22 @@ int main (int argc, char **argv)
         geo::Pose3D sensor_pose;
         geo::Pose3D place_pose;
 
+        int mask_type = mask.type();
+        std::cout << "mask type is " << mask_type << std::endl;
+
         if (!image_buffer.waitForRecentImage(image, sensor_pose, 2.0))
         {
             std::cerr << "No image received, will try again." << std::endl;
             continue;
         }
         
-        if (!place_area_finder.findArea(image, sensor_pose, place_pose))
-        {
-            std::cout << "no place area found" << std::endl;
+        if(mutex.try_lock()){
+
+            if (!place_area_finder.findArea(image, sensor_pose, place_pose,mask))
+            {
+                std::cout << "no place area found" << std::endl;
+            }
+            mutex.unlock();
         }
         std::cout << place_pose << std::endl;
 
@@ -232,11 +239,12 @@ int main (int argc, char **argv)
 
         if (mutex.try_lock()){
 
-            if (mask.rows > 0)
+            if (!mask.empty()) {
             cv::imshow("Mask", mask);
+            }
             mutex.unlock();
         }
-        if (true)
+        if (!mask.empty())
         {
             cv::Mat annotated_image;
             place_area_finder.getAnnotatedImage(annotated_image);

From 37b37de2a8d2c6f6f7ad2c6eb5445a4f80570eee Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Sun, 24 Dec 2023 17:14:56 +0100
Subject: [PATCH 130/136] successfully mapped mask into rgbd image using
 setRGBImage(mask)

---
 .../include/ed/kinect/place_area_finder.h     |   9 +-
 .../src/kinect/place_area_finder.cpp          | 331 ++++--------------
 .../tools/empty_spot_designator.cpp           | 105 ++++--
 3 files changed, 149 insertions(+), 296 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index 80fa5a30..71bb3082 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -95,11 +95,10 @@ class PlaceAreaFinder
     geo::Vec2d canvasToWorld(cv::Point2d point);
 
     //--------------------------------------------------------------------------------------------------------------------------------------
-    void drawfilledContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
+    cv::Point2d canvasToWorld2(double u, double v);
     void drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
-    //void mapCanvasToWorldAndVisualize(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
-    // void mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
-
+    void drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color,float height);
+    rgbd::ImageConstPtr createModifiedImage(const rgbd::ImageConstPtr& originalImagePtr, const cv::Mat& newRGBValues);
     //--------------------------------------------------------------------------------------------------------------------------------------
 
     /**
@@ -134,7 +133,7 @@ class PlaceAreaFinder
      * @param indeces 
      * @param color
      */
-    void annotateImage(const rgbd::Image& image, const pcl::Indices index, cv::Scalar color,const cv::Mat &mask);
+    void annotateImage(const rgbd::Image& image, const pcl::Indices index, cv::Scalar color);
 
 };
 
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 5e414a85..35325d4f 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -9,12 +9,15 @@
 
 // donal
 #include <map>
+#include <pcl/visualization/pcl_visualizer.h>
+
 //
 // pcl library # TODO remove the unused ones #TODO find out which ones are unused
 #include <pcl/point_representation.h>
 #include <pcl/common/common.h>
 #include <pcl/io/pcd_io.h>
 
+
 #include <pcl/filters/filter.h>
 #include <pcl/filters/extract_indices.h>
 #include <pcl/filters/conditional_removal.h>
@@ -63,8 +66,9 @@ double imageToCloud(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>:
     {
         for (uint j = 0; j < cloud->width; ++j)
         {
-
             cv::Vec3b bgr = image.getRGBImage().at<cv::Vec3b>(i, j);
+            if (bgr[0]==255)
+            {
             double d = image.getDepthImage().at<float>(i, j);
 
             cloud->at(j, i).x = (-half_width + j) * d / fx;
@@ -73,6 +77,7 @@ double imageToCloud(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>:
             cloud->at(j, i).r = bgr[2];
             cloud->at(j, i).g = bgr[1];
             cloud->at(j, i).b = bgr[0];
+            }
         }
     }
 
@@ -342,6 +347,7 @@ pcl::Indices multiplyIndex(pcl::Indices indexBA, pcl::Indices indexCB)
 }
 
 
+
 PlaceAreaFinder::PlaceAreaFinder()
 {
 }
@@ -357,10 +363,13 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     imageToCloud(*image, cloud);
 
+
     // transform to base link frame
     Eigen::Matrix4f transform = geolibToEigen(sensor_pose);
     pcl::transformPointCloud(*cloud, *cloud, transform);
 
+    
+
     // keep track of the indices in the original image
     std::vector<int> indices;
     pcl::Indices floorless_index;
@@ -368,6 +377,8 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr floorless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     removeFloor(cloud, floorless_cloud, floorless_index);
 
+    
+
     // Segment the table plane and return a cloud with the plane and a cloud where the plane is removed
     std::cout << "SegmentPlane" << std::endl;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr plane_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
@@ -375,7 +386,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr planeless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::Indices planeless_index;
     pcl::ModelCoefficients::Ptr plane_coefficients(new pcl::ModelCoefficients());
-    if (!SegmentPlane(floorless_cloud, plane_coefficients, plane_cloud, plane_index, planeless_cloud, planeless_index))
+    if (!SegmentPlane(cloud, plane_coefficients, plane_cloud, plane_index, planeless_cloud, planeless_index))
     {
         std::cout << "Could not find plane" << std::endl;
         return false;
@@ -423,11 +434,11 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
         std::cout << "annotating image" << std::endl;
         annotated_image = image->getRGBImage().clone();
         pcl::Indices plane_cloud_index = multiplyIndex(floorless_index, plane_index);
-        annotateImage(*image, plane_cloud_index, table_color,mask);
+        annotateImage(*image, plane_cloud_index, table_color);
         pcl::Indices object_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, object_index));
-        annotateImage(*image, object_cloud_index, occupied_color,mask);
+        annotateImage(*image, object_cloud_index, occupied_color);
         pcl::Indices below_table_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, below_index));
-        annotateImage(*image, below_table_cloud_index, occluded_color,mask);
+        annotateImage(*image, below_table_cloud_index, occluded_color);
     }
 
     std::cout << "creating costmap" << std::endl;
@@ -440,7 +451,15 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
 
     // donal changes-----------------------------------------------------------------------------------------------------------------------------
     cv::Scalar donal_colour(255, 255, 0);
-    drawContour(plane_cloud, donal_colour);
+    cv::Scalar test_colour(255, 255, 255);
+    // drawContour(plane_cloud, table_color);
+
+    drawContourAndTransformToWorld(plane_cloud,donal_colour,height);
+
+
+    createCostmap(plane_cloud,test_colour);
+    
+
     // mapCanvasToWorldAndPlaceInAnnotatedImage(*image,plane_cloud, donal_colour);
     // drawfilledContour(plane_cloud,table_color);
     // donal changes--------------------------------------------------------------------------------------------------------------------------
@@ -475,6 +494,15 @@ cv::Point2d PlaceAreaFinder::worldToCanvas(double x, double y)
     return cv::Point2d(round(-y / resolution), round(-x / resolution)) + canvas_center;
 }
 
+cv::Point2d PlaceAreaFinder::canvasToWorld2(double u, double v)
+{
+    // Assuming canvas_center is defined in your class
+    double x = -(v - canvas_center.y) * resolution;
+    double y = -(u - canvas_center.x) * resolution;
+
+    return cv::Point2d(y, x);
+}
+
 geo::Vec2d PlaceAreaFinder::canvasToWorld(cv::Point2d point)
 {
     double y = (point.x - canvas_center.x) * -resolution;
@@ -482,7 +510,7 @@ geo::Vec2d PlaceAreaFinder::canvasToWorld(cv::Point2d point)
     return geo::Vec2d(x, y);
 }
 // donal changes-------------------------------------------------------------------------------------------------------------------
-void PlaceAreaFinder::drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
+void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color,float height)
 {
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
@@ -518,57 +546,32 @@ void PlaceAreaFinder::drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud,
         std::vector<cv::Point> hull;
         cv::convexHull(points, hull);
 
-        // Draw the convex hull on the canvas
-        std::vector<std::vector<cv::Point>> contours = {hull};
-        cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 255), 2);
-    }
-    else
-    {
-        // Handle the case when there are not enough points for convex hull
-        std::cerr << "Not enough points for convex hull." << std::endl;
-    }
-}
-
-void PlaceAreaFinder::drawfilledContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
-{
-    const double fixedOpacity = 0.2; // Set the desired fixed opacity
-
-    canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-    // Create a binary mask
-    cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
-
-    std::vector<cv::Point> points; // Vector to store points for convex hull
+        // Fill the convex hull on the canvas
+        cv::fillConvexPoly(mask, hull, cv::Scalar(255, 255, 255));
 
-    for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
-    {
-        double x = cloud->points[nIndex].x;
-        double y = cloud->points[nIndex].y;
-
-        cv::Point2d p = worldToCanvas(x, y);
-
-        if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
+        // Transform the hull points to the world frame
+        std::vector<pcl::PointXYZRGB> worldPoints;
+        for (const auto& point : hull)
         {
-            // Update the canvas with the color
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
+            cv::Point2d worldPoint = canvasToWorld2(point.x, point.y);
 
-            // Set corresponding pixel in the mask to 255 (white)
-            mask.at<uchar>(p) = 255;
+            pcl::PointXYZRGB pclPoint;
+            pclPoint.x = worldPoint.x;
+            pclPoint.y = worldPoint.y;
+            pclPoint.z = height;
 
-            // Store the point for convex hull
-            points.push_back(p);
-        }
-    }
+            // Set the RGB color for visualization
+            pclPoint.r = color[2];
+            pclPoint.g = color[1];
+            pclPoint.b = color[0];
 
-    // Check if there are enough points to compute convex hull
-    if (points.size() >= 3)
-    {
-        // Find convex hull of the points
-        std::vector<cv::Point> hull;
-        cv::convexHull(points, hull);
+            worldPoints.push_back(pclPoint);
+        }
 
-        // Fill the convex hull with fixed opacity
-        cv::fillPoly(canvas, std::vector<std::vector<cv::Point>>{hull}, cv::Scalar(color[0], color[1], color[2], fixedOpacity * 255));
+        // Draw the convex hull on the canvas
+        std::vector<std::vector<cv::Point>> contours = { hull };
+        cv::drawContours(canvas, contours, -1, color, cv::FILLED); // Use CV_FILLED to fill the contour
+        cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 255), 2);
     }
     else
     {
@@ -577,203 +580,9 @@ void PlaceAreaFinder::drawfilledContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr c
     }
 }
 
-// void PlaceAreaFinder::mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
-// {
-//     const double fixedOpacity = 0.2; // Set the desired fixed opacity
 
-//     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
-//     // Access width and height directly from the depth image
-//     int imageWidth = image.getDepthImage().cols;
-//     int imageHeight = image.getDepthImage().rows;
-
-//     // Create a binary mask
-//     cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
-
-//     std::vector<cv::Point> points; // Vector to store points for convex hull
-
-//     for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
-//     {
-//         double x = cloud->points[nIndex].x;
-//         double y = cloud->points[nIndex].y;
-
-//         cv::Point2d p = worldToCanvas(x, y);
-
-//         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-//         {
-//             // Update the canvas with the color
-//             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-
-//             // Set corresponding pixel in the mask to 255 (white)
-//             mask.at<uchar>(p) = 255;
-
-//             // Store the point for convex hull
-//             points.push_back(p);
-//         }
-//     }
-
-//     // Check if there are enough points to compute convex hull
-//     if (points.size() >= 3)
-//     {
-//         // Find convex hull of the points
-//         std::vector<cv::Point> hull;
-//         cv::convexHull(points, hull);
-
-//         // Fill the convex hull with fixed opacity
-//         cv::fillPoly(canvas, std::vector<std::vector<cv::Point>>{hull}, cv::Scalar(color[0], color[1], color[2], fixedOpacity * 255));
-// void PlaceAreaFinder::mapCanvasToWorldAndPlaceInAnnotatedImage(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
-// {
-//     const double fixedOpacity = 0.2; // Set the desired fixed opacity
-
-//     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-//     // Access width and height directly from the depth image
-//     int imageWidth = image.getDepthImage().cols;
-//     int imageHeight = image.getDepthImage().rows;
-
-//     // Create a binary mask
-//     cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
-
-//     std::vector<cv::Point> points; // Vector to store points for convex hull
-
-//     for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
-//     {
-//         double x = cloud->points[nIndex].x;
-//         double y = cloud->points[nIndex].y;
-
-//         cv::Point2d p = worldToCanvas(x, y);
-
-//         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-//         {
-//             // Update the canvas with the color
-//             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-
-//             // Set corresponding pixel in the mask to 255 (white)
-//             mask.at<uchar>(p) = 255;
-
-//             // Store the point for convex hull
-//             points.push_back(p);
-//         }
-//     }
-
-//     // Check if there are enough points to compute convex hull
-//     if (points.size() >= 3)
-//     {
-//         // Find convex hull of the points
-//         std::vector<cv::Point> hull;
-//         cv::convexHull(points, hull);
-
-//         // Fill the convex hull with fixed opacity
-//         cv::fillPoly(canvas, std::vector<std::vector<cv::Point>>{hull}, cv::Scalar(color[0], color[1], color[2], fixedOpacity * 255));
-
-//         // Map the convex hull points to world coordinates and place in annotated image
-//         for (const auto &point : hull)
-//         {
-//             geo::Vec2d worldPoint = canvasToWorld(point);
-
-//             int row = static_cast<int>(worldPoint.y);
-//             int col = static_cast<int>(worldPoint.x);
-
-//             // Check if the point is within the bounds of the annotated image
-//             if (row >= 0 && col >= 0 && row < imageHeight && col < imageWidth)
-//             {
-//                 int index = row * imageWidth + col;
-//                 annotateImage(image, pcl::Indices(1, index), color,mask);
-//             }
-//         }
-//     }
-//     else
-//     {
-//         // Handle the case when there are not enough points for convex hull
-//         std::cerr << "Not enough points for convex hull." << std::endl;
-//     }
-// }
-//         // Map the convex hull points to world coordinates and place in annotated image
-//         for (const auto &point : hull)
-//         {
-//             geo::Vec2d worldPoint = canvasToWorld(point);
-
-//             int row = static_cast<int>(worldPoint.y);
-//             int col = static_cast<int>(worldPoint.x);
-
-//             // Check if the point is within the bounds of the annotated image
-//             if (row >= 0 && col >= 0 && row < imageHeight && col < imageWidth)
-//             {
-//                 int index = row * imageWidth + col;
-//                 annotateImage(image, pcl::Indices(1, index), color,mask);
-//             }
-//         }
-//     }
-//     else
-//     {
-//         // Handle the case when there are not enough points for convex hull
-//         std::cerr << "Not enough points for convex hull." << std::endl;
-//     }
-// }
-
-
-// void PlaceAreaFinder::mapCanvasToWorldAndVisualize(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
-// {
-//     const double fixedOpacity = 0.2; // Set the desired fixed opacity
-
-//     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
-
-//     // Create a binary mask
-//     cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
-
-//     std::vector<cv::Point> points; // Vector to store points for convex hull
-
-//     for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
-//     {
-//         double x = cloud->points[nIndex].x;
-//         double y = cloud->points[nIndex].y;
-
-//         cv::Point2d p = worldToCanvas(x, y);
-
-//         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
-//         {
-//             // Update the canvas with the color
-//             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-
-//             // Set corresponding pixel in the mask to 255 (white)
-//             mask.at<uchar>(p) = 255;
-
-//             // Store the point for convex hull
-//             points.push_back(p);
-//         }
-//     }
-
-//     // Check if there are enough points to compute convex hull
-//     if (points.size() >= 3)
-//     {
-//         // Find convex hull of the points
-//         std::vector<cv::Point> hull;
-//         cv::convexHull(points, hull);
-
-//         // Fill the convex hull with fixed opacity
-//         cv::fillPoly(canvas, std::vector<std::vector<cv::Point>>{hull}, cv::Scalar(color[0], color[1], color[2], fixedOpacity * 255));
-
-//         // Create a new canvas for visualization
-//         cv::Mat visualizationCanvas = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC3);
-
-//         // Map the convex hull points to world coordinates and visualize
-//         for (const auto &point : hull)
-//         {
-//             geo::Vec2d worldPoint = canvasToWorld(point);
-
-//             // Draw a point on the visualization canvas
-//             cv::circle(visualizationCanvas, worldToCanvas(worldPoint.x, worldPoint.y), 5, cv::Scalar(0, 255, 0), -1);
-//         }
-
-//         // Display the visualization canvas (you can customize this part based on your visualization tool or library)
-//         cv::imshow("Mapped Points in World Coordinates", visualizationCanvas);
-//     }
-//     else
-//     {
-//         // Handle the case when there are not enough points for convex hull
-//         std::cerr << "Not enough points for convex hull." << std::endl;
-//     }
-// }
+
 
 
 // donal changes----------------------------------------------------------------------------------------------------------------------------------
@@ -830,37 +639,19 @@ void PlaceAreaFinder::dilateCostmap(cv::Mat &canvas, cv::Mat &dilated_canvas, fl
     cv::dilate(canvas, dilated_canvas, element);
 }
 
-// void PlaceAreaFinder::annotateImage(const rgbd::Image &image, const pcl::Indices index, cv::Scalar color)
-// {
-//     int width = image.getDepthImage().cols;
-
-//     for (uint i = 0; i < index.size(); i++)
-//     {
-//         int col = index[i] % width;
-//         int row = index[i] / width;
-
-//         cv::Point2d p = cv::Point2d(col, row);
-//         if (p.x >= 0 && p.y >= 0 && p.x < annotated_image.cols && p.y < annotated_image.rows)
-//             annotated_image.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-//     }
-// }
-void PlaceAreaFinder::annotateImage(const rgbd::Image &image, const pcl::Indices index, cv::Scalar color, const cv::Mat &mask)
+void PlaceAreaFinder::annotateImage(const rgbd::Image &image, const pcl::Indices index, cv::Scalar color)
 {
     int width = image.getDepthImage().cols;
 
-    cv::Mat seg_mask = mask;
-
     for (uint i = 0; i < index.size(); i++)
     {
         int col = index[i] % width;
         int row = index[i] / width;
 
         cv::Point2d p = cv::Point2d(col, row);
-
-        // Check if the point is within the segmentation mask
-        if (p.x >= 0 && p.y >= 0 && p.x < annotated_image.cols && p.y < annotated_image.rows && seg_mask.at<uchar>(p.x,p.y) > 0)
-        {
+        if (p.x >= 0 && p.y >= 0 && p.x < annotated_image.cols && p.y < annotated_image.rows)
             annotated_image.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-        }
     }
-}
\ No newline at end of file
+}
+
+
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 8728da6d..dde662f2 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -157,6 +157,40 @@ void usage()
               << "RGBD_TOPIC topic on which the rgbd image is published, example /hero/head_rgbd_sensor/rgbd" << std::endl;
 }
 
+void drawMaskContour(cv::Mat& image, const cv::Mat& mask)
+{
+    // Convert the mask to grayscale if it's not already
+    cv::Mat grayMask;
+    if (mask.channels() > 1)
+    {
+        cv::cvtColor(mask, grayMask, cv::COLOR_BGR2GRAY);
+    }
+    else
+    {
+        grayMask = mask.clone(); // If it's already single-channel, create a copy
+    }
+
+    // Find contours in the binary mask
+    std::vector<std::vector<cv::Point>> contours;
+    cv::findContours(grayMask, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);
+
+    // Draw the contours on the image in white
+    cv::Scalar contourColor(255, 255, 255); // White color
+    cv::drawContours(image, contours, -1, contourColor, 2); // -1 means draw all contours, 2 is the thickness
+}
+
+rgbd::ImageConstPtr createModifiedImage(const rgbd::ImageConstPtr& originalImagePtr, const cv::Mat& newRGBValues) {
+    // Create a copy of the original image
+    rgbd::Image modifiedImage = originalImagePtr->clone();
+
+    // Set the new RGB values
+    modifiedImage.setRGBImage(newRGBValues);
+
+    // Create a shared pointer to the modified image
+    rgbd::ImageConstPtr modifiedImagePtr = std::make_shared<const rgbd::Image>(modifiedImage);
+
+    return modifiedImagePtr;
+}
 
 /**
  * @brief main executable to visualise the empty spot finder of live images.
@@ -195,31 +229,53 @@ int main (int argc, char **argv)
         geo::Pose3D sensor_pose;
         geo::Pose3D place_pose;
 
-        int mask_type = mask.type();
-        std::cout << "mask type is " << mask_type << std::endl;
+
 
         if (!image_buffer.waitForRecentImage(image, sensor_pose, 2.0))
         {
             std::cerr << "No image received, will try again." << std::endl;
             continue;
         }
-        
-        if(mutex.try_lock()){
 
-            if (!place_area_finder.findArea(image, sensor_pose, place_pose,mask))
-            {
-                std::cout << "no place area found" << std::endl;
+        std::cout << "Trying to replace RGB with mask" << std::endl;
+        if(!mask.empty())
+        {
+            if(mutex.try_lock()){
+                rgbd::ImageConstPtr new_image_ptr = createModifiedImage(image, mask.clone());
+                cv::Mat rgbcanvas = new_image_ptr->getRGBImage();
+                cv::imshow("RGB remapped to mask", rgbcanvas);
+                mutex.unlock();
             }
-            mutex.unlock();
+            // createModifiedImage()
+            // rgbd::Image new_image = *image;
+            // if(mutex.try_lock()){
+            //     new_image.setRGBImage(mask);
+            //     mutex.unlock();
+            // }
+            
+            
+            // rgbd::ImageConstPtr new_image_ptr(&new_image);
+            // std::cout << "Replaced RGB with mask!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!" << std::endl;
+        
+            // if(mutex.try_lock()){
+            //     if (!place_area_finder.findArea(new_image_ptr, sensor_pose, place_pose,mask))
+            //     {
+            //     std::cout << "no place area found" << std::endl;
+            //     }
+            //     mutex.unlock();
+            // }
+            
         }
+            
+        
         std::cout << place_pose << std::endl;
 
         cv::Mat canvas;
         cv::Mat dilated_canvas;
         cv::Mat placement_canvas;
-        place_area_finder.getCanvas(canvas);
-        place_area_finder.getDilatedCanvas(dilated_canvas);
-        place_area_finder.getPlacementCanvas(placement_canvas);
+        // place_area_finder.getCanvas(canvas);
+        // place_area_finder.getDilatedCanvas(dilated_canvas);
+        // place_area_finder.getPlacementCanvas(placement_canvas);
         /*
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
         geo::Pose3D sensor_pose_canvas = sensor_pose;
@@ -229,14 +285,18 @@ int main (int argc, char **argv)
         // Show the different canvasses
         
         // std::cout << "showing costmap" << std::endl;
+        if(!canvas.empty()){
         cv::imshow("Costmap topview", canvas);
+        }
                 
         // std::cout << "showing dilated costmap" << std::endl;
+        if(!dilated_canvas.empty()){
         cv::imshow("Dilated costmap topview", dilated_canvas);
-
+        }
         // std::cout << "showing placement costmap" << std::endl;
+        if(!placement_canvas.empty()){
         cv::imshow("Placement options costmap topview", placement_canvas);
-
+        }
         if (mutex.try_lock()){
 
             if (!mask.empty()) {
@@ -244,15 +304,18 @@ int main (int argc, char **argv)
             }
             mutex.unlock();
         }
-        if (!mask.empty())
-        {
-            cv::Mat annotated_image;
-            place_area_finder.getAnnotatedImage(annotated_image);
-            cv::imshow("Annotated_image", annotated_image);
-        }
+        // if (!mask.empty())
+        // {
+        //     cv::Mat annotated_image;
+        //     cv::Mat annotated_image_with_mask;
+        //     place_area_finder.getAnnotatedImage(annotated_image);
+        //     annotated_image_with_mask = annotated_image.clone();
+        //     drawMaskContour(annotated_image_with_mask, mask);
+        //     cv::imshow("Annotated_image", annotated_image_with_mask);
+        // }
         // Show RGB snapshot
-        cv::Mat rgbcanvas = image->getRGBImage();
-        cv::imshow("RGB", rgbcanvas);
+        // cv::Mat rgbcanvas = image->getRGBImage();
+        // cv::imshow("RGB", rgbcanvas);
 
         char key = cv::waitKey(30);
 

From 5068594f344c28ebfd077f7340599aca5ed4c5a1 Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Sun, 24 Dec 2023 18:03:45 +0100
Subject: [PATCH 131/136] successfully filtered point cloud using segmentation
 mask from yolo

---
 .../src/kinect/place_area_finder.cpp          | 16 +++---
 .../tools/empty_spot_designator.cpp           | 53 +++++++------------
 2 files changed, 28 insertions(+), 41 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 35325d4f..e0fa86e0 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -67,7 +67,7 @@ double imageToCloud(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>:
         for (uint j = 0; j < cloud->width; ++j)
         {
             cv::Vec3b bgr = image.getRGBImage().at<cv::Vec3b>(i, j);
-            if (bgr[0]==255)
+            if (bgr[0]==255 || bgr[1]==255 || bgr[2]==225)
             {
             double d = image.getDepthImage().at<float>(i, j);
 
@@ -386,7 +386,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr planeless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::Indices planeless_index;
     pcl::ModelCoefficients::Ptr plane_coefficients(new pcl::ModelCoefficients());
-    if (!SegmentPlane(cloud, plane_coefficients, plane_cloud, plane_index, planeless_cloud, planeless_index))
+    if (!SegmentPlane(floorless_cloud, plane_coefficients, plane_cloud, plane_index, planeless_cloud, planeless_index))
     {
         std::cout << "Could not find plane" << std::endl;
         return false;
@@ -561,17 +561,17 @@ void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointX
             pclPoint.z = height;
 
             // Set the RGB color for visualization
-            pclPoint.r = color[2];
-            pclPoint.g = color[1];
-            pclPoint.b = color[0];
+            pclPoint.r = 0;
+            pclPoint.g = 225;
+            pclPoint.b = 0;
 
             worldPoints.push_back(pclPoint);
         }
 
         // Draw the convex hull on the canvas
-        std::vector<std::vector<cv::Point>> contours = { hull };
-        cv::drawContours(canvas, contours, -1, color, cv::FILLED); // Use CV_FILLED to fill the contour
-        cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 255), 2);
+        // std::vector<std::vector<cv::Point>> contours = { hull };
+        // cv::drawContours(canvas, contours, -1, color, cv::FILLED); // Use CV_FILLED to fill the contour
+        // cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 255), 2);
     }
     else
     {
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index dde662f2..8d7edf60 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -230,7 +230,6 @@ int main (int argc, char **argv)
         geo::Pose3D place_pose;
 
 
-
         if (!image_buffer.waitForRecentImage(image, sensor_pose, 2.0))
         {
             std::cerr << "No image received, will try again." << std::endl;
@@ -244,26 +243,14 @@ int main (int argc, char **argv)
                 rgbd::ImageConstPtr new_image_ptr = createModifiedImage(image, mask.clone());
                 cv::Mat rgbcanvas = new_image_ptr->getRGBImage();
                 cv::imshow("RGB remapped to mask", rgbcanvas);
+                std::cout << "Replaced RGB with mask!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!" << std::endl;
+
+                if (!place_area_finder.findArea(new_image_ptr, sensor_pose, place_pose,mask))
+                {
+                    std::cout << "no place area found" << std::endl;
+                }
                 mutex.unlock();
             }
-            // createModifiedImage()
-            // rgbd::Image new_image = *image;
-            // if(mutex.try_lock()){
-            //     new_image.setRGBImage(mask);
-            //     mutex.unlock();
-            // }
-            
-            
-            // rgbd::ImageConstPtr new_image_ptr(&new_image);
-            // std::cout << "Replaced RGB with mask!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!" << std::endl;
-        
-            // if(mutex.try_lock()){
-            //     if (!place_area_finder.findArea(new_image_ptr, sensor_pose, place_pose,mask))
-            //     {
-            //     std::cout << "no place area found" << std::endl;
-            //     }
-            //     mutex.unlock();
-            // }
             
         }
             
@@ -273,9 +260,9 @@ int main (int argc, char **argv)
         cv::Mat canvas;
         cv::Mat dilated_canvas;
         cv::Mat placement_canvas;
-        // place_area_finder.getCanvas(canvas);
-        // place_area_finder.getDilatedCanvas(dilated_canvas);
-        // place_area_finder.getPlacementCanvas(placement_canvas);
+        place_area_finder.getCanvas(canvas);
+        place_area_finder.getDilatedCanvas(dilated_canvas);
+        place_area_finder.getPlacementCanvas(placement_canvas);
         /*
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
         geo::Pose3D sensor_pose_canvas = sensor_pose;
@@ -304,18 +291,18 @@ int main (int argc, char **argv)
             }
             mutex.unlock();
         }
-        // if (!mask.empty())
-        // {
-        //     cv::Mat annotated_image;
-        //     cv::Mat annotated_image_with_mask;
-        //     place_area_finder.getAnnotatedImage(annotated_image);
-        //     annotated_image_with_mask = annotated_image.clone();
-        //     drawMaskContour(annotated_image_with_mask, mask);
-        //     cv::imshow("Annotated_image", annotated_image_with_mask);
-        // }
+        if (!mask.empty())
+        {
+            cv::Mat annotated_image;
+            cv::Mat annotated_image_with_mask;
+            place_area_finder.getAnnotatedImage(annotated_image);
+            annotated_image_with_mask = annotated_image.clone();
+            drawMaskContour(annotated_image_with_mask, mask);
+            cv::imshow("Annotated_image", annotated_image_with_mask);
+        }
         // Show RGB snapshot
-        // cv::Mat rgbcanvas = image->getRGBImage();
-        // cv::imshow("RGB", rgbcanvas);
+        cv::Mat rgbcanvas = image->getRGBImage();
+        cv::imshow("Original RGB", rgbcanvas);
 
         char key = cv::waitKey(30);
 

From 8b0e8fda6cf70ab11f7bfbd5974d378fa4f16447 Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Sun, 24 Dec 2023 22:18:11 +0100
Subject: [PATCH 132/136] perform planar segmentation then filter cloud
 afterwards so correct height is obtained

---
 .../include/ed/kinect/place_area_finder.h     |  1 +
 .../src/kinect/place_area_finder.cpp          | 64 +++++++++++++++++--
 2 files changed, 61 insertions(+), 4 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index 71bb3082..ad06b1d5 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -99,6 +99,7 @@ class PlaceAreaFinder
     void drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
     void drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color,float height);
     rgbd::ImageConstPtr createModifiedImage(const rgbd::ImageConstPtr& originalImagePtr, const cv::Mat& newRGBValues);
+    void extractMaskPoints(pcl::PointCloud<pcl::PointXYZRGB>::Ptr inputCloud);
     //--------------------------------------------------------------------------------------------------------------------------------------
 
     /**
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index e0fa86e0..125f32b3 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -62,6 +62,40 @@ double imageToCloud(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>:
     double half_height = 0.5 * cloud->height;
     double half_width = 0.5 * cloud->width;
 
+    for (uint i = 0; i < cloud->height; ++i)
+    {
+        for (uint j = 0; j < cloud->width; ++j)
+        {
+            cv::Vec3b bgr = image.getRGBImage().at<cv::Vec3b>(i, j);
+            double d = image.getDepthImage().at<float>(i, j);
+
+            cloud->at(j, i).x = (-half_width + j) * d / fx;
+            cloud->at(j, i).y = (-half_height + i) * d / fy;
+            cloud->at(j, i).z = d;
+            cloud->at(j, i).r = bgr[2];
+            cloud->at(j, i).g = bgr[1];
+            cloud->at(j, i).b = bgr[0];
+            
+        }
+    }
+
+    return image.getCameraModel().fx();
+}
+
+double imageToMaskFilteredCloud(const rgbd::Image &image, pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud)
+{
+    // Fill in the cloud data
+    cloud->width = image.getDepthImage().cols;
+    cloud->height = image.getDepthImage().rows;
+    cloud->is_dense = false;
+    cloud->resize(cloud->width * cloud->height);
+
+    double fx = image.getCameraModel().fx();
+    double fy = image.getCameraModel().fy();
+
+    double half_height = 0.5 * cloud->height;
+    double half_width = 0.5 * cloud->width;
+
     for (uint i = 0; i < cloud->height; ++i)
     {
         for (uint j = 0; j < cloud->width; ++j)
@@ -362,6 +396,8 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     // std::cout << "converting image to cloud" << std::endl;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     imageToCloud(*image, cloud);
+    // convert image to cloud and filter using cnn segmentation mask
+    //imageToMaskFilteredCloud(*image,cloud)
 
 
     // transform to base link frame
@@ -450,14 +486,18 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     createCostmap(not_table_cloud, occupied_color);
 
     // donal changes-----------------------------------------------------------------------------------------------------------------------------
-    cv::Scalar donal_colour(255, 255, 0);
-    cv::Scalar test_colour(255, 255, 255);
+    cv::Scalar cyan(255, 255, 0);
+    cv::Scalar white(255, 255, 255);
+    cv::Scalar yellow(0, 255, 255);
     // drawContour(plane_cloud, table_color);
 
-    drawContourAndTransformToWorld(plane_cloud,donal_colour,height);
+    drawContourAndTransformToWorld(plane_cloud,cyan,height);
 
+    //createCostmap(plane_cloud,white);
 
-    createCostmap(plane_cloud,test_colour);
+    extractMaskPoints(plane_cloud);
+
+    createCostmap(plane_cloud,yellow);
     
 
     // mapCanvasToWorldAndPlaceInAnnotatedImage(*image,plane_cloud, donal_colour);
@@ -580,7 +620,23 @@ void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointX
     }
 }
 
+void PlaceAreaFinder::extractMaskPoints(pcl::PointCloud<pcl::PointXYZRGB>::Ptr inputCloud) {
+    pcl::PointIndices::Ptr FilteredByMaskIndices(new pcl::PointIndices);
 
+    for (size_t i = 0; i < inputCloud->points.size(); ++i) {
+        // Check for mask color (this case mask is blue)
+        uint8_t b = inputCloud->points[i].b;
+        if (b == 255) {
+            FilteredByMaskIndices->indices.push_back(static_cast<int>(i));
+        }
+    }
+
+    pcl::ExtractIndices<pcl::PointXYZRGB> extract;
+    extract.setInputCloud(inputCloud);
+    extract.setIndices(FilteredByMaskIndices);
+    extract.setNegative(true); // Keep points not in the indices list
+    extract.filter(*inputCloud);
+}
 
 
 

From 3a1e3d7a2c82f01f2e1f6bec3c968522c7e2e085 Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Tue, 26 Dec 2023 23:43:46 +0100
Subject: [PATCH 133/136] Cleaned up code, removed unused functions, added
 extra arguement to select whether to run Max's version or Donal's version of
 ed_empty_sport_designator

---
 .../include/ed/kinect/place_area_finder.h     |   6 +--
 ed_sensor_integration/scripts/yolov8n-seg.pt  | Bin 0 -> 7054355 bytes
 .../src/kinect/kinect_plugin.cpp              |   3 +-
 .../src/kinect/place_area_finder.cpp          |  37 ++++--------------
 .../tools/empty_spot_designator.cpp           |  31 ++++++++++-----
 5 files changed, 34 insertions(+), 43 deletions(-)
 create mode 100644 ed_sensor_integration/scripts/yolov8n-seg.pt

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index ad06b1d5..1135cea6 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -34,9 +34,11 @@ class PlaceAreaFinder
      * @param image image in which to find a place position
      * @param sensor_pose pose of the sensor with respect to a horizontal plane 'base_link' recommended
      * @param[out] place_pose expressed in the same frame as sensor pose. One of the possible poses where an object may be placed, currently returns the pose furthest on the table
+     * @param mask input mask of table obtained from yolov8 segmentation of the rgb image
+     * @param donal bool used to run either max or donals version of the solution to speed up comparisons
      * @return whether or not a suitable place was found
      */
-    bool findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose,const cv::Mat &mask);
+    bool findArea(const rgbd::ImageConstPtr& image, geo::Pose3D sensor_pose, geo::Pose3D& place_pose,const cv::Mat &mask,bool donal);
 
     /**
      * @brief Get an image of the analysed space, used for introspection
@@ -96,9 +98,7 @@ class PlaceAreaFinder
 
     //--------------------------------------------------------------------------------------------------------------------------------------
     cv::Point2d canvasToWorld2(double u, double v);
-    void drawContour(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color);
     void drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color,float height);
-    rgbd::ImageConstPtr createModifiedImage(const rgbd::ImageConstPtr& originalImagePtr, const cv::Mat& newRGBValues);
     void extractMaskPoints(pcl::PointCloud<pcl::PointXYZRGB>::Ptr inputCloud);
     //--------------------------------------------------------------------------------------------------------------------------------------
 
diff --git a/ed_sensor_integration/scripts/yolov8n-seg.pt b/ed_sensor_integration/scripts/yolov8n-seg.pt
new file mode 100644
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diff --git a/ed_sensor_integration/src/kinect/kinect_plugin.cpp b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
index 9b5d8d12..a6579c14 100644
--- a/ed_sensor_integration/src/kinect/kinect_plugin.cpp
+++ b/ed_sensor_integration/src/kinect/kinect_plugin.cpp
@@ -290,6 +290,7 @@ bool KinectPlugin::srvPlaceArea(__attribute__((unused)) ed_sensor_integration_ms
     // - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     // Get new image
     cv::Mat mask;
+    bool donal = true;
     rgbd::ImageConstPtr image;
     geo::Pose3D sensor_pose; // in base link frame
 
@@ -301,7 +302,7 @@ bool KinectPlugin::srvPlaceArea(__attribute__((unused)) ed_sensor_integration_ms
 
     // Determine place area
     geo::Pose3D place_pose; // w.r.t base link
-    if (!place_area_finder_.findArea(image, sensor_pose, place_pose,mask))
+    if (!place_area_finder_.findArea(image, sensor_pose, place_pose,mask,donal))
     {
         res.error_msg = "No valid place area found";
         return true;
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 125f32b3..5e3376de 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -390,7 +390,7 @@ PlaceAreaFinder::~PlaceAreaFinder()
 {
 }
 
-bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sensor_pose, geo::Pose3D &place_pose,const cv::Mat &mask)
+bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sensor_pose, geo::Pose3D &place_pose,const cv::Mat &mask,bool donal)
 {
     bool visualize = true;
     // std::cout << "converting image to cloud" << std::endl;
@@ -413,8 +413,6 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr floorless_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     removeFloor(cloud, floorless_cloud, floorless_index);
 
-    
-
     // Segment the table plane and return a cloud with the plane and a cloud where the plane is removed
     std::cout << "SegmentPlane" << std::endl;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr plane_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
@@ -465,7 +463,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     float length = object_diameter + error_margin;
     float placement_margin = 2 * 0.02 + length;
 
-    if (visualize && !mask.empty())
+    if ((visualize && !mask.empty())| !donal)
     {
         std::cout << "annotating image" << std::endl;
         annotated_image = image->getRGBImage().clone();
@@ -486,22 +484,14 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     createCostmap(not_table_cloud, occupied_color);
 
     // donal changes-----------------------------------------------------------------------------------------------------------------------------
+    if (donal){
     cv::Scalar cyan(255, 255, 0);
     cv::Scalar white(255, 255, 255);
     cv::Scalar yellow(0, 255, 255);
-    // drawContour(plane_cloud, table_color);
-
     drawContourAndTransformToWorld(plane_cloud,cyan,height);
-
-    //createCostmap(plane_cloud,white);
-
     extractMaskPoints(plane_cloud);
-
     createCostmap(plane_cloud,yellow);
-    
-
-    // mapCanvasToWorldAndPlaceInAnnotatedImage(*image,plane_cloud, donal_colour);
-    // drawfilledContour(plane_cloud,table_color);
+    }
     // donal changes--------------------------------------------------------------------------------------------------------------------------
 
     // HERO preferred radius
@@ -536,7 +526,6 @@ cv::Point2d PlaceAreaFinder::worldToCanvas(double x, double y)
 
 cv::Point2d PlaceAreaFinder::canvasToWorld2(double u, double v)
 {
-    // Assuming canvas_center is defined in your class
     double x = -(v - canvas_center.y) * resolution;
     double y = -(u - canvas_center.x) * resolution;
 
@@ -557,7 +546,7 @@ void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointX
     // Create a binary mask
     cv::Mat mask = cv::Mat::zeros(canvas.rows, canvas.cols, CV_8UC1);
 
-    std::vector<cv::Point> points; // Vector to store points for convex hull
+    std::vector<cv::Point> points;
 
     for (uint nIndex = 0; nIndex < cloud->points.size(); nIndex++)
     {
@@ -568,13 +557,8 @@ void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointX
 
         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
         {
-            // Update the canvas with the color
             canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
-
-            // Set corresponding pixel in the mask to 255 (white)
             mask.at<uchar>(p) = 255;
-
-            // Store the point for convex hull
             points.push_back(p);
         }
     }
@@ -585,8 +569,6 @@ void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointX
         // Find convex hull of the points
         std::vector<cv::Point> hull;
         cv::convexHull(points, hull);
-
-        // Fill the convex hull on the canvas
         cv::fillConvexPoly(mask, hull, cv::Scalar(255, 255, 255));
 
         // Transform the hull points to the world frame
@@ -609,13 +591,12 @@ void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointX
         }
 
         // Draw the convex hull on the canvas
-        // std::vector<std::vector<cv::Point>> contours = { hull };
-        // cv::drawContours(canvas, contours, -1, color, cv::FILLED); // Use CV_FILLED to fill the contour
-        // cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 255), 2);
+        std::vector<std::vector<cv::Point>> contours = { hull };
+        cv::drawContours(canvas, contours, -1, color, cv::FILLED); // Use CV_FILLED to fill the contour
+        cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 255), 2);// Draws white border contour
     }
     else
     {
-        // Handle the case when there are not enough points for convex hull
         std::cerr << "Not enough points for convex hull." << std::endl;
     }
 }
@@ -639,8 +620,6 @@ void PlaceAreaFinder::extractMaskPoints(pcl::PointCloud<pcl::PointXYZRGB>::Ptr i
 }
 
 
-
-
 // donal changes----------------------------------------------------------------------------------------------------------------------------------
 void PlaceAreaFinder::createCostmap(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color)
 {
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 8d7edf60..34feeb05 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -153,8 +153,9 @@ void imageCallback(const sensor_msgs::ImageConstPtr& msg)
  */
 void usage()
 {
-    std::cout << "Usage: ed_empty_spot_designator RGBD_TOPIC" << std::endl
-              << "RGBD_TOPIC topic on which the rgbd image is published, example /hero/head_rgbd_sensor/rgbd" << std::endl;
+    std::cout << "Usage: ed_empty_spot_designator RGBD_TOPIC BOOL" << std::endl
+              << "RGBD_TOPIC topic on which the rgbd image is published, example /hero/head_rgbd_sensor/rgbd" << std::endl
+              << "Set second argument to donal or max to run that version of the code" << std::endl;
 }
 
 void drawMaskContour(cv::Mat& image, const cv::Mat& mask)
@@ -180,13 +181,8 @@ void drawMaskContour(cv::Mat& image, const cv::Mat& mask)
 }
 
 rgbd::ImageConstPtr createModifiedImage(const rgbd::ImageConstPtr& originalImagePtr, const cv::Mat& newRGBValues) {
-    // Create a copy of the original image
     rgbd::Image modifiedImage = originalImagePtr->clone();
-
-    // Set the new RGB values
     modifiedImage.setRGBImage(newRGBValues);
-
-    // Create a shared pointer to the modified image
     rgbd::ImageConstPtr modifiedImagePtr = std::make_shared<const rgbd::Image>(modifiedImage);
 
     return modifiedImagePtr;
@@ -199,7 +195,7 @@ rgbd::ImageConstPtr createModifiedImage(const rgbd::ImageConstPtr& originalImage
  */
 int main (int argc, char **argv)
 {
-    if (argc != 2)
+    if (argc != 3)
     {
         usage();
         return 0;
@@ -210,6 +206,15 @@ int main (int argc, char **argv)
     std::string topic = argv[1];
     std::cout << "Using topic: " << topic << std::endl;
 
+    std::string arg = argv[2];
+    bool donal = (arg == "donal");
+    if (donal){
+        std::cout <<"Running Donal's version!"<<std::endl;
+    }
+    else{
+        std::cout<<"Running Max's version!"<<std::endl;
+    }
+
     rgbd::ImageBuffer image_buffer;
     image_buffer.initialize(topic, "base_link");
 
@@ -237,7 +242,7 @@ int main (int argc, char **argv)
         }
 
         std::cout << "Trying to replace RGB with mask" << std::endl;
-        if(!mask.empty())
+        if(!mask.empty() && donal)
         {
             if(mutex.try_lock()){
                 rgbd::ImageConstPtr new_image_ptr = createModifiedImage(image, mask.clone());
@@ -245,7 +250,7 @@ int main (int argc, char **argv)
                 cv::imshow("RGB remapped to mask", rgbcanvas);
                 std::cout << "Replaced RGB with mask!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!" << std::endl;
 
-                if (!place_area_finder.findArea(new_image_ptr, sensor_pose, place_pose,mask))
+                if (!place_area_finder.findArea(new_image_ptr, sensor_pose, place_pose,mask,donal))
                 {
                     std::cout << "no place area found" << std::endl;
                 }
@@ -253,6 +258,12 @@ int main (int argc, char **argv)
             }
             
         }
+        else{
+            if (!place_area_finder.findArea(image, sensor_pose, place_pose,mask,donal))
+                {
+                    std::cout << "no place area found" << std::endl;
+                }
+        }
             
         
         std::cout << place_pose << std::endl;

From 2013883e8aea3df03fab6ecfa4090aa5a024d5e2 Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Mon, 8 Jan 2024 11:43:50 +0100
Subject: [PATCH 134/136] final changes, extractMaskFilter needed to be
 inverted

---
 .../include/ed/kinect/place_area_finder.h     |  2 +-
 .../src/kinect/place_area_finder.cpp          | 34 +++++++++++--------
 .../yolo_python/yolo_table_segmentor.py       |  3 +-
 3 files changed, 22 insertions(+), 17 deletions(-)

diff --git a/ed_sensor_integration/include/ed/kinect/place_area_finder.h b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
index 1135cea6..3ae369f7 100644
--- a/ed_sensor_integration/include/ed/kinect/place_area_finder.h
+++ b/ed_sensor_integration/include/ed/kinect/place_area_finder.h
@@ -98,7 +98,7 @@ class PlaceAreaFinder
 
     //--------------------------------------------------------------------------------------------------------------------------------------
     cv::Point2d canvasToWorld2(double u, double v);
-    void drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color,float height);
+    void CreateAndVisConvexHull(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud,float height,pcl::PointCloud<pcl::PointXYZRGB>::Ptr& world_points);
     void extractMaskPoints(pcl::PointCloud<pcl::PointXYZRGB>::Ptr inputCloud);
     //--------------------------------------------------------------------------------------------------------------------------------------
 
diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index 5e3376de..f450a9bb 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -21,6 +21,7 @@
 #include <pcl/filters/filter.h>
 #include <pcl/filters/extract_indices.h>
 #include <pcl/filters/conditional_removal.h>
+#include <pcl/filters/statistical_outlier_removal.h>
 
 #include <pcl/features/normal_3d.h>
 
@@ -101,7 +102,7 @@ double imageToMaskFilteredCloud(const rgbd::Image &image, pcl::PointCloud<pcl::P
         for (uint j = 0; j < cloud->width; ++j)
         {
             cv::Vec3b bgr = image.getRGBImage().at<cv::Vec3b>(i, j);
-            if (bgr[0]==255 || bgr[1]==255 || bgr[2]==225)
+            if (bgr[0]==255 && bgr[2]==225)
             {
             double d = image.getDepthImage().at<float>(i, j);
 
@@ -381,7 +382,6 @@ pcl::Indices multiplyIndex(pcl::Indices indexBA, pcl::Indices indexCB)
 }
 
 
-
 PlaceAreaFinder::PlaceAreaFinder()
 {
 }
@@ -396,9 +396,11 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     // std::cout << "converting image to cloud" << std::endl;
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     imageToCloud(*image, cloud);
+    
     // convert image to cloud and filter using cnn segmentation mask
-    //imageToMaskFilteredCloud(*image,cloud)
-
+    // if(donal){
+    // imageToMaskFilteredCloud(*image,cloud);
+    // }
 
     // transform to base link frame
     Eigen::Matrix4f transform = geolibToEigen(sensor_pose);
@@ -458,7 +460,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     cv::Scalar point_color(255, 0, 0);
 
     // Object placement margins #TODO hardcoded parameters
-    float object_diameter = 0.10;
+    float object_diameter = 0.10;// removeOutliers(plane_cloud,filtered_plane_cloud);
     float error_margin = 0.02;
     float length = object_diameter + error_margin;
     float placement_margin = 2 * 0.02 + length;
@@ -488,9 +490,12 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     cv::Scalar cyan(255, 255, 0);
     cv::Scalar white(255, 255, 255);
     cv::Scalar yellow(0, 255, 255);
-    drawContourAndTransformToWorld(plane_cloud,cyan,height);
+    cv::Scalar purple(255, 0, 255);
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr filtered_plane_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
+    pcl::PointCloud<pcl::PointXYZRGB>::Ptr convex_hull_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     extractMaskPoints(plane_cloud);
     createCostmap(plane_cloud,yellow);
+    CreateAndVisConvexHull(plane_cloud,height,convex_hull_cloud);
     }
     // donal changes--------------------------------------------------------------------------------------------------------------------------
 
@@ -539,7 +544,7 @@ geo::Vec2d PlaceAreaFinder::canvasToWorld(cv::Point2d point)
     return geo::Vec2d(x, y);
 }
 // donal changes-------------------------------------------------------------------------------------------------------------------
-void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud, cv::Scalar color,float height)
+void PlaceAreaFinder::CreateAndVisConvexHull(pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud,float height,pcl::PointCloud<pcl::PointXYZRGB>::Ptr& world_points)
 {
     canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
 
@@ -557,7 +562,6 @@ void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointX
 
         if (p.x >= 0 && p.y >= 0 && p.x < canvas.cols && p.y < canvas.rows)
         {
-            canvas.at<cv::Vec3b>(p) = cv::Vec3b(color[0], color[1], color[2]);
             mask.at<uchar>(p) = 255;
             points.push_back(p);
         }
@@ -572,7 +576,6 @@ void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointX
         cv::fillConvexPoly(mask, hull, cv::Scalar(255, 255, 255));
 
         // Transform the hull points to the world frame
-        std::vector<pcl::PointXYZRGB> worldPoints;
         for (const auto& point : hull)
         {
             cv::Point2d worldPoint = canvasToWorld2(point.x, point.y);
@@ -584,15 +587,15 @@ void PlaceAreaFinder::drawContourAndTransformToWorld(pcl::PointCloud<pcl::PointX
 
             // Set the RGB color for visualization
             pclPoint.r = 0;
-            pclPoint.g = 225;
-            pclPoint.b = 0;
+            pclPoint.g = 0;
+            pclPoint.b = 255;
 
-            worldPoints.push_back(pclPoint);
+            world_points->push_back(pclPoint);
         }
 
         // Draw the convex hull on the canvas
         std::vector<std::vector<cv::Point>> contours = { hull };
-        cv::drawContours(canvas, contours, -1, color, cv::FILLED); // Use CV_FILLED to fill the contour
+        cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 0), cv::FILLED); // Use CV_FILLED to fill the contour
         cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 255), 2);// Draws white border contour
     }
     else
@@ -607,7 +610,8 @@ void PlaceAreaFinder::extractMaskPoints(pcl::PointCloud<pcl::PointXYZRGB>::Ptr i
     for (size_t i = 0; i < inputCloud->points.size(); ++i) {
         // Check for mask color (this case mask is blue)
         uint8_t b = inputCloud->points[i].b;
-        if (b == 255) {
+        uint8_t r = inputCloud->points[i].r;
+        if (b == 255 && r == 255) {
             FilteredByMaskIndices->indices.push_back(static_cast<int>(i));
         }
     }
@@ -615,7 +619,7 @@ void PlaceAreaFinder::extractMaskPoints(pcl::PointCloud<pcl::PointXYZRGB>::Ptr i
     pcl::ExtractIndices<pcl::PointXYZRGB> extract;
     extract.setInputCloud(inputCloud);
     extract.setIndices(FilteredByMaskIndices);
-    extract.setNegative(true); // Keep points not in the indices list
+    extract.setNegative(false); // Keep points not in the indices list
     extract.filter(*inputCloud);
 }
 
diff --git a/ed_sensor_integration/yolo_python/yolo_table_segmentor.py b/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
index 452ed4ff..57780a28 100755
--- a/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
+++ b/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
@@ -27,9 +27,10 @@ def detect(model, frame):
 
     def extract_table_segment(self, image, class_ids, segmentations):
         table_mask = np.zeros_like(image, dtype=np.uint8)
+        purple_colour = (255, 0, 255)
         for class_id, seg in zip(class_ids, segmentations):
             if class_id == self.table_class:
-                cv2.fillPoly(table_mask, [seg], 255)
+                cv2.fillPoly(table_mask, [seg], purple_colour)
         return table_mask
 
     def callback(self, data):

From 4d03daddd5bb81b8b6e2496e74c3292ae9196dfc Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Tue, 16 Jan 2024 18:09:52 +0100
Subject: [PATCH 135/136] using nano model for yolo

---
 .../src/kinect/place_area_finder.cpp          | 21 +++++++++----------
 .../tools/empty_spot_designator.cpp           | 20 ++++++++++--------
 .../yolo_python/yolo_table_segmentor.py       |  2 +-
 3 files changed, 22 insertions(+), 21 deletions(-)

diff --git a/ed_sensor_integration/src/kinect/place_area_finder.cpp b/ed_sensor_integration/src/kinect/place_area_finder.cpp
index f450a9bb..115d312a 100644
--- a/ed_sensor_integration/src/kinect/place_area_finder.cpp
+++ b/ed_sensor_integration/src/kinect/place_area_finder.cpp
@@ -469,12 +469,12 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     {
         std::cout << "annotating image" << std::endl;
         annotated_image = image->getRGBImage().clone();
-        pcl::Indices plane_cloud_index = multiplyIndex(floorless_index, plane_index);
-        annotateImage(*image, plane_cloud_index, table_color);
-        pcl::Indices object_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, object_index));
-        annotateImage(*image, object_cloud_index, occupied_color);
-        pcl::Indices below_table_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, below_index));
-        annotateImage(*image, below_table_cloud_index, occluded_color);
+        // pcl::Indices plane_cloud_index = multiplyIndex(floorless_index, plane_index);
+        // annotateImage(*image, plane_cloud_index, table_color);
+        // pcl::Indices object_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, object_index));
+        // annotateImage(*image, object_cloud_index, occupied_color);
+        // pcl::Indices below_table_cloud_index = multiplyIndex(floorless_index, multiplyIndex(planeless_index, below_index));
+        // annotateImage(*image, below_table_cloud_index, occluded_color);
     }
 
     std::cout << "creating costmap" << std::endl;
@@ -491,7 +491,6 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     cv::Scalar white(255, 255, 255);
     cv::Scalar yellow(0, 255, 255);
     cv::Scalar purple(255, 0, 255);
-    pcl::PointCloud<pcl::PointXYZRGB>::Ptr filtered_plane_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     pcl::PointCloud<pcl::PointXYZRGB>::Ptr convex_hull_cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
     extractMaskPoints(plane_cloud);
     createCostmap(plane_cloud,yellow);
@@ -502,7 +501,7 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
     // HERO preferred radius
     createRadiusCostmap(canvas, radius_color, placement_margin);
 
-    // Dilate the costmap and create a new canvas
+    // // Dilate the costmap and create a new canvas
     dilateCostmap(canvas, dilated_canvas, placement_margin);
 
     ExtractPlacementOptions(dilated_canvas, placement_canvas, table_color);
@@ -515,11 +514,11 @@ bool PlaceAreaFinder::findArea(const rgbd::ImageConstPtr &image, geo::Pose3D sen
         return false;
     }
 
-    cv::circle(canvas, place_point_canvas, 3, placement_color, -1);
+    // // cv::circle(canvas, place_point_canvas, 3, placement_color, -1);
     geo::Vec2d place_point;
     place_point = canvasToWorld(place_point_canvas);
 
-    // fill result
+    // // fill result
     place_pose = geo::Pose3D(place_point.x, place_point.y, height + 0.02);
     return true;
 }
@@ -595,7 +594,7 @@ void PlaceAreaFinder::CreateAndVisConvexHull(pcl::PointCloud<pcl::PointXYZRGB>::
 
         // Draw the convex hull on the canvas
         std::vector<std::vector<cv::Point>> contours = { hull };
-        cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 0), cv::FILLED); // Use CV_FILLED to fill the contour
+        // cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 0), cv::FILLED); // Use CV_FILLED to fill the contour
         cv::drawContours(canvas, contours, -1, cv::Scalar(255, 255, 255), 2);// Draws white border contour
     }
     else
diff --git a/ed_sensor_integration/tools/empty_spot_designator.cpp b/ed_sensor_integration/tools/empty_spot_designator.cpp
index 34feeb05..22efab95 100644
--- a/ed_sensor_integration/tools/empty_spot_designator.cpp
+++ b/ed_sensor_integration/tools/empty_spot_designator.cpp
@@ -247,7 +247,7 @@ int main (int argc, char **argv)
             if(mutex.try_lock()){
                 rgbd::ImageConstPtr new_image_ptr = createModifiedImage(image, mask.clone());
                 cv::Mat rgbcanvas = new_image_ptr->getRGBImage();
-                cv::imshow("RGB remapped to mask", rgbcanvas);
+                // cv::imshow("RGB remapped to mask", rgbcanvas);
                 std::cout << "Replaced RGB with mask!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!" << std::endl;
 
                 if (!place_area_finder.findArea(new_image_ptr, sensor_pose, place_pose,mask,donal))
@@ -272,8 +272,8 @@ int main (int argc, char **argv)
         cv::Mat dilated_canvas;
         cv::Mat placement_canvas;
         place_area_finder.getCanvas(canvas);
-        place_area_finder.getDilatedCanvas(dilated_canvas);
-        place_area_finder.getPlacementCanvas(placement_canvas);
+        // place_area_finder.getDilatedCanvas(dilated_canvas);
+        // place_area_finder.getPlacementCanvas(placement_canvas);
         /*
         canvas_center = cv::Point2d(canvas.rows / 2, canvas.cols);
         geo::Pose3D sensor_pose_canvas = sensor_pose;
@@ -295,13 +295,13 @@ int main (int argc, char **argv)
         if(!placement_canvas.empty()){
         cv::imshow("Placement options costmap topview", placement_canvas);
         }
-        if (mutex.try_lock()){
+        // if (mutex.try_lock()){
 
-            if (!mask.empty()) {
-            cv::imshow("Mask", mask);
-            }
-            mutex.unlock();
-        }
+        //     if (!mask.empty()) {
+        //     cv::imshow("Mask", mask);
+        //     }
+        //     mutex.unlock();
+        // }
         if (!mask.empty())
         {
             cv::Mat annotated_image;
@@ -314,6 +314,8 @@ int main (int argc, char **argv)
         // Show RGB snapshot
         cv::Mat rgbcanvas = image->getRGBImage();
         cv::imshow("Original RGB", rgbcanvas);
+        drawMaskContour(rgbcanvas, mask);
+        cv::imshow("Original RGB with Table Mask", rgbcanvas);
 
         char key = cv::waitKey(30);
 
diff --git a/ed_sensor_integration/yolo_python/yolo_table_segmentor.py b/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
index 57780a28..b62642aa 100755
--- a/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
+++ b/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
@@ -8,7 +8,7 @@
 
 class table_segmentor:
     def __init__(self) -> None:
-        model_path = "~/MEGA/developers/Donal/yolov8x-seg.pt"
+        model_path = "~/MEGA/developers/Donal/yolov8n-seg.pt"
         device = "cuda"
         self.model = YOLO(model_path).to(device)
         self.table_class = 60 #table class defined with index 60 (person = 0)

From 5ef89fd0c1685e4a174a2648a7ea6abc9b8aaa04 Mon Sep 17 00:00:00 2001
From: Donal <donal.ryan36765@gmail.com>
Date: Tue, 16 Jan 2024 18:15:57 +0100
Subject: [PATCH 136/136] using XL model for yolo

---
 ed_sensor_integration/yolo_python/yolo_table_segmentor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ed_sensor_integration/yolo_python/yolo_table_segmentor.py b/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
index b62642aa..57780a28 100755
--- a/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
+++ b/ed_sensor_integration/yolo_python/yolo_table_segmentor.py
@@ -8,7 +8,7 @@
 
 class table_segmentor:
     def __init__(self) -> None:
-        model_path = "~/MEGA/developers/Donal/yolov8n-seg.pt"
+        model_path = "~/MEGA/developers/Donal/yolov8x-seg.pt"
         device = "cuda"
         self.model = YOLO(model_path).to(device)
         self.table_class = 60 #table class defined with index 60 (person = 0)