refactor plane finder

robot_calibration/CMakeLists.txt

@@ -19,6 +19,7 @@ endif ()
 
 find_package(orocos_kdl)
 find_package(Ceres REQUIRED)
+find_package(Eigen3 REQUIRED)
 find_package(OpenCV REQUIRED)
 find_package(catkin REQUIRED
   COMPONENTS
@@ -77,6 +78,7 @@ endif()
 include_directories(include ${Boost_INCLUDE_DIRS}
                             ${catkin_INCLUDE_DIRS}
                             ${CERES_INCLUDES}
+                            ${EIGEN3_INCLUDE_DIRS}
                             ${orocos_kdl_INCLUDE_DIRS})
 link_directories(${orocos_kdl_LIBRARY_DIRS}) # this is a hack, will eventually be unneeded once orocos-kdl is fixed
 

robot_calibration/include/robot_calibration/capture/plane_finder.h

@@ -1,4 +1,5 @@
 /*
+ * Copyright (C) 2022 Michael Ferguson
  * Copyright (C) 2014-2017 Fetch Robotics Inc.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
@@ -31,12 +32,52 @@ class PlaneFinder : public FeatureFinder
 {
 public:
   PlaneFinder();
-  bool init(const std::string& name, ros::NodeHandle & n);
-  bool find(robot_calibration_msgs::CalibrationData * msg);
+  virtual ~PlaneFinder() = default;
+  virtual bool init(const std::string& name, ros::NodeHandle & n);
+  virtual bool find(robot_calibration_msgs::CalibrationData * msg);
 
-private:
-  void cameraCallback(const sensor_msgs::PointCloud2& cloud);
-  bool waitForCloud();
+protected:
+  /**
+   * @brief ROS callback - updates cloud_ and resets waiting_ to false
+   */
+  virtual void cameraCallback(const sensor_msgs::PointCloud2& cloud);
+
+  /**
+   * @brief Remove invalid points from a cloud
+   * @param cloud The point cloud to remove invalid points from
+   *
+   * Invalid points include:
+   *  * points with NAN values
+   *  * points with infinite values
+   *  * points with z-distance of 0
+   *  * points outside our min/max x,y,z parameters
+   */
+  virtual void removeInvalidPoints(sensor_msgs::PointCloud2& cloud,
+                                   double min_x, double max_x, double min_y, double max_y, double min_z, double max_z);
+
+  /**
+   * @brief Extract a plane from the point cloud
+   * @brief cloud The cloud to extract plane from - non-plane points will remain
+   * @return New point cloud comprising only the points in the plane
+   */
+  virtual sensor_msgs::PointCloud2 extractPlane(sensor_msgs::PointCloud2& cloud);
+
+  /**
+   * @brief Extract points from a cloud into a calibration message
+   * @param sensor_name Used to fill in observation "sensor_name"
+   * @param cloud Point cloud from which to extract observations
+   * @param msg CalibrationData to fill with observation
+   * @param publisher Optional pointer to publish the observations as a cloud
+   */
+  virtual void extractObservation(const std::string& sensor_name,
+                                  const sensor_msgs::PointCloud2& cloud,
+                                  robot_calibration_msgs::CalibrationData * msg,
+                                  ros::Publisher* publisher);
+
+  /**
+   * @brief Wait until a new cloud has arrived
+   */
+  virtual bool waitForCloud();
 
   ros::Subscriber subscriber_;
   ros::Publisher publisher_;
@@ -48,8 +89,9 @@ class PlaneFinder : public FeatureFinder
   sensor_msgs::PointCloud2 cloud_;
   DepthCameraInfoManager depth_camera_manager_;
 
-  std::string camera_sensor_name_;
-  double points_max_;
+  std::string plane_sensor_name_;
+  int points_max_;
+  double plane_tolerance_;
   double min_x_;
   double max_x_;
   double min_y_;

robot_calibration/package.xml

@@ -13,6 +13,8 @@
 
   <buildtool_depend>catkin</buildtool_depend>
 
+  <build_depend>eigen</build_depend>
+
   <depend>actionlib</depend>
   <depend>camera_calibration_parsers</depend>
   <depend>control_msgs</depend>

robot_calibration/src/finders/plane_finder.cpp

@@ -1,5 +1,5 @@
 /*
- * Copyright (C) 2018 Michael Ferguson
+ * Copyright (C) 2018-2022 Michael Ferguson
  * Copyright (C) 2015-2017 Fetch Robotics Inc.
  * Copyright (C) 2013-2014 Unbounded Robotics Inc.
  *
@@ -19,6 +19,10 @@
 // Author: Niharika Arora, Michael Ferguson
 
 #include <math.h>
+
+#include <Eigen/Core>
+#include <Eigen/Dense>
+
 #include <pluginlib/class_list_macros.h>
 #include <robot_calibration/capture/plane_finder.h>
 #include <sensor_msgs/point_cloud2_iterator.h>
@@ -53,10 +57,13 @@ bool PlaneFinder::init(const std::string& name,
                              this);
 
   // Name of the sensor model that will be used during optimization
-  nh.param<std::string>("camera_sensor_name", camera_sensor_name_, "camera");
+  nh.param<std::string>("camera_sensor_name", plane_sensor_name_, "camera");
 
   // Maximum number of valid points to include in the observation
-  nh.param<double>("points_max", points_max_, 60);
+  nh.param<int>("points_max", points_max_, 60);
+
+  // Maximum distance from plane that point can be located
+  nh.param<double>("tolerance", plane_tolerance_, 0.02);
 
   // Frame to transform point cloud into before applying limits below
   //   if specified as "none", cloud will be processed in sensor frame
@@ -123,10 +130,21 @@ bool PlaneFinder::find(robot_calibration_msgs::CalibrationData * msg)
     return false;
   }
 
+  removeInvalidPoints(cloud_, min_x_, max_x_, min_y_, max_y_, min_z_, max_z_);
+  sensor_msgs::PointCloud2 plane = extractPlane(cloud_);
+  extractObservation(plane_sensor_name_, plane, msg, &publisher_);
+
+  // Report success
+  return true;
+}
+
+void PlaneFinder::removeInvalidPoints(sensor_msgs::PointCloud2& cloud,
+  double min_x, double max_x, double min_y, double max_y, double min_z, double max_z)
+{
   //  Remove any point that is invalid or not with our tolerance
-  size_t num_points = cloud_.width * cloud_.height;
-  sensor_msgs::PointCloud2ConstIterator<float> xyz(cloud_, "x");
-  sensor_msgs::PointCloud2Iterator<float> cloud_iter(cloud_, "x");
+  size_t num_points = cloud.width * cloud.height;
+  sensor_msgs::PointCloud2ConstIterator<float> xyz(cloud, "x");
+  sensor_msgs::PointCloud2Iterator<float> cloud_iter(cloud, "x");
 
   bool do_transform = transform_frame_ != "none";  // This can go away once the cloud gets transformed outside loop 
   size_t j = 0;
@@ -139,12 +157,16 @@ bool PlaneFinder::find(robot_calibration_msgs::CalibrationData * msg)
 
     // Remove the NaNs in the point cloud
     if (!std::isfinite(p.point.x) || !std::isfinite(p.point.y) || !std::isfinite(p.point.z))
+    {
       continue;
+    }
 
     // Remove the points immediately in front of the camera in the point cloud
     // NOTE : This is to handle sensors that publish zeros instead of NaNs in the point cloud
     if (p.point.z == 0)
+    {
       continue;
+    }
 
     // Get transform (if any)
     geometry_msgs::PointStamped p_out;
@@ -169,8 +191,8 @@ bool PlaneFinder::find(robot_calibration_msgs::CalibrationData * msg)
     }
 
     // Test the transformed point
-    if (p_out.point.x < min_x_ || p_out.point.x > max_x_ || p_out.point.y < min_y_ || p_out.point.y > max_y_ ||
-        p_out.point.z < min_z_ || p_out.point.z > max_z_)
+    if (p_out.point.x < min_x || p_out.point.x > max_x || p_out.point.y < min_y || p_out.point.y > max_y ||
+        p_out.point.z < min_z || p_out.point.z > max_z)
     {
       continue;
     }
@@ -181,35 +203,130 @@ bool PlaneFinder::find(robot_calibration_msgs::CalibrationData * msg)
     (cloud_iter + j)[Z] = (xyz + i)[Z];
     j++;
   }
-  cloud_.height = 1;
-  cloud_.width  = j;
-  cloud_.data.resize(cloud_.width * cloud_.point_step);
+  cloud.height = 1;
+  cloud.width  = j;
+  cloud.data.resize(cloud.width * cloud.point_step);
+}
+
+sensor_msgs::PointCloud2 PlaneFinder::extractPlane(sensor_msgs::PointCloud2& cloud)
+{
+  sensor_msgs::PointCloud2ConstIterator<float> xyz(cloud, "x");
+
+  // Copy cloud to eigen matrix for SVD
+  Eigen::MatrixXd points(3, cloud.width);
+  for (size_t i = 0; i < cloud.width; ++i)
+  {
+    points(0, i) = (xyz + i)[X];
+    points(1, i) = (xyz + i)[Y];
+    points(2, i) = (xyz + i)[Z];
+  }
+
+  // Find centroid
+  Eigen::Vector3d centroid(points.row(0).mean(), points.row(1).mean(), points.row(2).mean());
+
+  // Center the cloud
+  points.row(0).array() -= centroid(0);
+  points.row(1).array() -= centroid(1);
+  points.row(2).array() -= centroid(2);
+
+  // Find the plane
+  auto svd = points.jacobiSvd(Eigen::ComputeThinU | Eigen::ComputeThinV);
+  Eigen::Vector3d normal = svd.matrixU().rightCols<1>();
+
+  // Get the rest of plane equation
+  double d = -(normal(0) * centroid(0) + normal(1) * centroid(1) + normal(2) * centroid(2));
+
+  ROS_INFO("Found plane with parameters: %f %f %f %f", normal(0), normal(1), normal(2), d);
+
+  // Create a point cloud for the plane
+  sensor_msgs::PointCloud2 plane_cloud;
+  plane_cloud.width = 0;
+  plane_cloud.height = 0;
+  plane_cloud.header.stamp = ros::Time::now();
+  plane_cloud.header.frame_id = cloud.header.frame_id;
+  sensor_msgs::PointCloud2Modifier plane_cloud_mod(plane_cloud);
+  plane_cloud_mod.setPointCloud2FieldsByString(1, "xyz");
+  plane_cloud_mod.resize(cloud.width);
+  sensor_msgs::PointCloud2Iterator<float> plane_iter(plane_cloud, "x");
+
+  // Extract points close to plane
+  sensor_msgs::PointCloud2Iterator<float> cloud_iter(cloud, "x");
+  size_t plane_points = 0;
+  size_t cloud_points = 0;
+  for (size_t i = 0; i < cloud.width; ++i)
+  {
+    // Compute distance to plane
+    double dist = normal(0) * (xyz + i)[X] + normal(1) * (xyz + i)[Y] + normal(2) * (xyz + i)[Z] + d;
+
+    if (std::fabs(dist) < plane_tolerance_)
+    {
+      // Part of the plane
+      (plane_iter + plane_points)[X] = (xyz + i)[X];
+      (plane_iter + plane_points)[Y] = (xyz + i)[Y];
+      (plane_iter + plane_points)[Z] = (xyz + i)[Z];
+      ++plane_points;
+    }
+    else
+    {
+      // Part of cloud, move it forward
+      (cloud_iter + cloud_points)[X] = (xyz + i)[X];
+      (cloud_iter + cloud_points)[Y] = (xyz + i)[Y];
+      (cloud_iter + cloud_points)[Z] = (xyz + i)[Z];
+      ++cloud_points;
+    }
+  }
+
+  // Resize clouds
+  cloud.height = 1;
+  cloud.width  = cloud_points;
+  cloud.data.resize(cloud.width * cloud.point_step);
+
+  plane_cloud.height = 1;
+  plane_cloud.width  = plane_points;
+  plane_cloud.data.resize(plane_cloud.width * plane_cloud.point_step);
+
+  ROS_INFO("Extracted plane with %d points", plane_cloud.width);
+
+  return plane_cloud;
+}
+
+void PlaneFinder::extractObservation(const std::string& sensor_name,
+                                     const sensor_msgs::PointCloud2& cloud,
+                                     robot_calibration_msgs::CalibrationData * msg,
+                                     ros::Publisher* publisher)
+{
+  if (static_cast<int>(cloud.width) == 0)
+  {
+    ROS_WARN("No points in observation, skipping");
+    return;
+  }
 
   // Determine number of points to output
-  size_t points_total = std::min(static_cast<size_t>(points_max_), j);
-  ROS_INFO_STREAM("Got " << j << " points from plane, using " << points_total);
+  size_t points_total = std::min(points_max_, static_cast<int>(cloud.width));
+  ROS_INFO_STREAM("Got " << cloud.width << " points for observation, using " << points_total);
 
   // Create PointCloud2 to publish
   sensor_msgs::PointCloud2 viz_cloud;
   viz_cloud.width = 0;
   viz_cloud.height = 0;
   viz_cloud.header.stamp = ros::Time::now();
-  viz_cloud.header.frame_id = cloud_.header.frame_id;
+  viz_cloud.header.frame_id = cloud.header.frame_id;
   sensor_msgs::PointCloud2Modifier cloud_mod(viz_cloud);
   cloud_mod.setPointCloud2FieldsByString(1, "xyz");
   cloud_mod.resize(points_total);
-  sensor_msgs::PointCloud2Iterator<float> viz_cloud_iter(viz_cloud, "x");
 
   // Setup observation
   int idx_cam = msg->observations.size();
   msg->observations.resize(msg->observations.size() + 1);
-  msg->observations[idx_cam].sensor_name = camera_sensor_name_;
+  msg->observations[idx_cam].sensor_name = sensor_name;
   msg->observations[idx_cam].ext_camera_info = depth_camera_manager_.getDepthCameraInfo();
 
   // Fill in observation
-  size_t step = cloud_.width / points_total;
+  size_t step = cloud.width / points_total;
   size_t index = step / 2;
-  for (size_t i = 0; index < cloud_.width; i++)
+  sensor_msgs::PointCloud2Iterator<float> viz_cloud_iter(viz_cloud, "x");
+  sensor_msgs::PointCloud2ConstIterator<float> xyz(cloud, "x");
+  for (size_t i = 0; index < cloud.width && i < points_total; ++i)
   {
     // Get (untransformed) 3d point
     geometry_msgs::PointStamped rgbd;
@@ -233,14 +350,14 @@ bool PlaneFinder::find(robot_calibration_msgs::CalibrationData * msg)
   // Add debug cloud to message
   if (output_debug_)
   {
-    msg->observations[idx_cam].cloud = cloud_;
+    msg->observations[idx_cam].cloud = cloud;
   }
 
-  // Publish debug info
-  publisher_.publish(viz_cloud);
-
-  // Report success
-  return true;
+  if (publisher)
+  {
+    // Publish debug info
+    publisher->publish(viz_cloud);
+  }
 }
 
 }  // namespace robot_calibration