From c1c6697de22860706ead7d9d249ebb6a6ab7cdee Mon Sep 17 00:00:00 2001 From: Jacopo Panerati Date: Tue, 25 Aug 2020 16:29:13 -0400 Subject: [PATCH] Multidrone refactoring (v1) --- .gitignore | 3 + LICENSE | 2 +- README.md | 221 ++++---- examples/compare.py | 84 +++ examples/fly.py | 81 +++ examples/{sa_learning.py => learn.py} | 23 +- examples/physics.py | 77 +++ examples/sa_flight.py | 120 ----- examples/sa_trace.py | 104 ---- examples/test_physics.py | 101 ---- examples/utils.py | 10 +- files/{traces/trace.pkl => example_trace.pkl} | Bin files/readme_images/3_drones.gif | Bin 0 -> 7675848 bytes files/readme_images/3_drones.png | Bin 0 -> 577702 bytes files/{images => readme_images}/crash.gif | Bin files/{images => readme_images}/crash.png | Bin files/{images => readme_images}/learn1.gif | Bin files/{images => readme_images}/learn2.gif | Bin files/{images => readme_images}/learn3.gif | Bin files/{images => readme_images}/learn4.gif | Bin .../trace_comparison.gif | Bin .../trace_comparison.png | Bin files/{images => readme_images}/wp.gif | Bin files/{images => readme_images}/wp.png | Bin files/saves/foo.txt | 0 gym_pybullet_drones/__init__.py | 9 +- gym_pybullet_drones/assets/cf2p.urdf | 2 +- gym_pybullet_drones/assets/cf2x.urdf | 2 +- gym_pybullet_drones/assets/hb.urdf | 2 +- .../control/MultiDroneControl.py | 22 - .../control/SingleDroneControl.py | 264 ---------- gym_pybullet_drones/control/__init__.py | 2 - gym_pybullet_drones/envs/Aviary.py | 489 ++++++++++++++++++ gym_pybullet_drones/envs/Control.py | 296 +++++++++++ gym_pybullet_drones/envs/Logger.py | 86 +++ gym_pybullet_drones/envs/MultiDroneEnv.py | 75 --- .../envs/MultiDroneUserDefinedFunctions.py | 21 - .../envs/ProblemSpecificFunctions.py | 129 +++++ gym_pybullet_drones/envs/SingleDroneEnv.py | 411 --------------- .../envs/SingleDroneUserDefinedFunctions.py | 119 ----- gym_pybullet_drones/envs/__init__.py | 3 +- setup.py | 2 +- 42 files changed, 1390 insertions(+), 1370 deletions(-) create mode 100644 examples/compare.py create mode 100644 examples/fly.py rename examples/{sa_learning.py => learn.py} (55%) create mode 100644 examples/physics.py delete mode 100644 examples/sa_flight.py delete mode 100644 examples/sa_trace.py delete mode 100644 examples/test_physics.py rename files/{traces/trace.pkl => example_trace.pkl} (100%) create mode 100644 files/readme_images/3_drones.gif create mode 100644 files/readme_images/3_drones.png rename files/{images => readme_images}/crash.gif (100%) rename files/{images => readme_images}/crash.png (100%) rename files/{images => readme_images}/learn1.gif (100%) rename files/{images => readme_images}/learn2.gif (100%) rename files/{images => readme_images}/learn3.gif (100%) rename files/{images => readme_images}/learn4.gif (100%) rename files/{images => readme_images}/trace_comparison.gif (100%) rename files/{images => readme_images}/trace_comparison.png (100%) rename files/{images => readme_images}/wp.gif (100%) rename files/{images => readme_images}/wp.png (100%) delete mode 100644 files/saves/foo.txt delete mode 100644 gym_pybullet_drones/control/MultiDroneControl.py delete mode 100644 gym_pybullet_drones/control/SingleDroneControl.py delete mode 100644 gym_pybullet_drones/control/__init__.py create mode 100644 gym_pybullet_drones/envs/Aviary.py create mode 100644 gym_pybullet_drones/envs/Control.py create mode 100644 gym_pybullet_drones/envs/Logger.py delete mode 100644 gym_pybullet_drones/envs/MultiDroneEnv.py delete mode 100644 gym_pybullet_drones/envs/MultiDroneUserDefinedFunctions.py create mode 100644 gym_pybullet_drones/envs/ProblemSpecificFunctions.py delete mode 100644 gym_pybullet_drones/envs/SingleDroneEnv.py delete mode 100644 gym_pybullet_drones/envs/SingleDroneUserDefinedFunctions.py diff --git a/.gitignore b/.gitignore index 81c4d846b..87200fe4d 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,6 @@ +# TO-DO list +TODOs.md + # macOS users .DS_Store diff --git a/LICENSE b/LICENSE index f6ed15e43..5751ab52a 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ MIT License -Copyright (c) 2020 JacopoPan +Copyright (c) 2020 Jacopo Panerati Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/README.md b/README.md index 7af2e31b4..7ebb79bc2 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ # gym-pybullet-drones -Simple [OpenAI Gym environment](https://gym.openai.com/envs/#classic_control) based on [PyBullet](https://github.com/bulletphysics/bullet3) to simulate one (or more, WIP) quadrotors +Simple [OpenAI Gym environment](https://gym.openai.com/envs/#classic_control) based on [PyBullet](https://github.com/bulletphysics/bullet3) to simulate one or more quadrotors -alt text alt text +alt text alt text - The default `DroneModel.CF2X` dynamics are based on [Bitcraze's Crazyflie 2.x nano-quadrotor](https://www.bitcraze.io/documentation/hardware/crazyflie_2_1/crazyflie_2_1-datasheet.pdf) @@ -18,10 +18,10 @@ $ pip install gym $ pip install pybullet $ pip install stable-baselines3 $ pip install `ray[rllib]` -$ brew install ffmpeg # on macOS -$ sudo apt install ffmpeg # on Linux +$ brew install ffmpeg # on macOS +$ sudo apt install ffmpeg # on Linux ``` -With a [`conda` environment](https://github.com/JacopoPan/a-minimalist-guide#install-conda), +Using a [`conda` environment](https://github.com/JacopoPan/a-minimalist-guide#install-conda), dependencies (except `ffmpeg`), can be installed from file ``` $ cd gym-pybullet-drones/ @@ -44,65 +44,65 @@ $ pip install -e . ## Use -There are 4 main scripts in `examples/`: `sa_trace.py`, `sa_flight.py`, `sa_learning.py`, `test_physics.py` +There are 4 main scripts in `examples/`: `compare.py`, `fly.py`, `learn.py`, and `physics.py` -- `test_physics.py` can be used to test the effects of PyBullet's forces and torques to different [URDF links](http://wiki.ros.org/urdf/XML/link) in `p.WORLD_FRAME` and `p.LINK_FRAME` +- `compare.py` replays and compare to a trace saved in [`example_trace.pkl`](https://github.com/JacopoPan/gym-pybullet-drones/tree/master/files/example_trace.pkl) ``` -$ conda activate myenv # If using a conda environment +$ conda activate myenv # If using a conda environment $ cd gym-pybullet-drones/examples/ -$ python test_physics.py +$ python compare.py ``` -> Tip: also check the examples in [pybullet-examples](https://github.com/JacopoPan/pybullet-examples) +alt text alt text -- `sa_trace.py` replays and compare to a trace saved in [`trace.pkl`](https://github.com/JacopoPan/gym-pybullet-drones/tree/master/files/traces) +- `fly.py` runs an independent flight **using PID control** implemented in class [`Control`](https://github.com/JacopoPan/gym-pybullet-drones/tree/master/gym_pybullet_drones/env/Control.py) ``` -$ conda activate myenv # If using a conda environment +$ conda activate myenv # If using a conda environment $ cd gym-pybullet-drones/examples/ -$ python sa_trace.py +$ python fly.py ``` -alt text alt text +> Tip: use the GUI's sliders and button `Use GUI RPM` to override the control with interactive inputs +alt text alt text + +alt text alt text -- `sa_flight.py` runs an independent flight **using PID control** implemented in class [`SingleDroneControl`](https://github.com/JacopoPan/gym-pybullet-drones/tree/master/gym_pybullet_drones/control/SingleDroneControl.py) +- `learn.py` is an **RL example** to learn take-off using `stable-baselines3`'s [A2C](https://stable-baselines3.readthedocs.io/en/master/modules/a2c.html) or `rllib`'s [PPO](https://docs.ray.io/en/master/rllib-algorithms.html#ppo) ``` -$ conda activate myenv # If using a conda environment +$ conda activate myenv # If using a conda environment $ cd gym-pybullet-drones/examples/ -$ python sa_flight.py +$ python learn.py ``` -> Tip: use the GUI's sliders and button `Use GUI RPM` to override the control with interactive inputs - -alt text alt text +alt text alt text +alt text alt text -- `sa_learning.py` is an **RL example** to learn take-off using `stable-baselines3`'s [A2C](https://stable-baselines3.readthedocs.io/en/master/modules/a2c.html) or `rllib`'s [PPO](https://docs.ray.io/en/master/rllib-algorithms.html#ppo) +- `physics.py` is an accessory script that can be used to understand PyBullet's force and torque APIs for different [URDF links](http://wiki.ros.org/urdf/XML/link) in `p.WORLD_FRAME` and `p.LINK_FRAME` ``` -$ conda activate myenv # If using a conda environment +$ conda activate myenv # If using a conda environment $ cd gym-pybullet-drones/examples/ -$ python sa_learning.py +$ python physics.py ``` -alt text alt text -alt text alt text - - +> Tip: also check the examples in [pybullet-examples](https://github.com/JacopoPan/pybullet-examples) -## SingleDroneEnv -A single quadrotor enviroment can be created with `SingleDroneEnv()`—see [`sa_flight.py`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/examples/sa_flight.py) for an example +## Aviary +A `gym.Env` flight arena for one (ore more) quadrotor can be created with `Aviary()`—see [`fly.py`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/examples/fly.py) for an example ``` ->>> env = SingleDroneEnv( \ ->>> drone_model=DroneModel.CF2X, \ # See DroneModel.py for other quadcopter models (remove this comment) ->>> initial_xyz=[0,0,0.1], \ # Initial XYZ position of the drone (remove this comment) ->>> initial_rpy=[0,0,0], \ # Initial roll, pitch, and yaw of the drone in radians (remove this comment) ->>> pybullet=True, \ # Whether to use PyBullet physics or the dynamics in method _noPyBulletDynamics() (remove this comment) ->>> aero_effects=False \ # Whether to include PyBullet-based drag, ground effect, and downwash (WIP) (remove this comment) +>>> env = Aviary( \ +>>> drone_model=DroneModel.CF2X, \ # See DroneModel Enum class for other quadcopter models (remove this comment) +>>> num_drones=1, \ # Number of drones (remove this comment) +>>> visibility_radius=np.inf, \ # Distance at which drones are considered neighbors, only used for multiple drones (remove this comment) +>>> initial_xyzs=None, \ # Initial XYZ positions of the drones (remove this comment) +>>> initial_rpys=None, \ # Initial roll, pitch, and yaw of the drones in radians (remove this comment) +>>> physics: Physics=Physics.PYB, \ # Choice of (PyBullet) physics implementation (remove this comment) >>> normalized_spaces=True, \ # Whether to use normalized action and observation spaces—use True for learning (default), False for simulation (remove this comment) ->>> freq=240, \ # The stepping frequency of the simulation (remove this comment) +>>> freq=240, \ # Stepping frequency of the simulation (remove this comment) >>> gui=True, \ # Whether to display PyBullet's GUI (remove this comment) >>> obstacles=False, \ # Whether to add obstacles to the environment (remove this comment) ->>> record=False, \ # Whether to save a .mp4 video in gym-pybullet-drones/files/saves/ (remove this comment) ->>> user="Default") # String to choose reward and done functions in class SingleDroneUserDefinedFunctions (remove this comment) +>>> record=False, \ # Whether to save a .mp4 video in gym-pybullet-drones/files/ (remove this comment) +>>> problem: Problem=Problem.DEFAULT) # Choice of reward and done functions in class ProblemSpecificFunctions (remove this comment) ```` -Or using `gym.make()`—see [`sa_learning.py`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/examples/sa_learning.py) for an example +Or using `gym.make()`—see [`learn.py`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/examples/learn.py) for an example ``` ->>> env = gym.make('single-drone-v0') # See sa_learning.py +>>> env = gym.make('the-aviary-v1') # See learn.py ``` Then, the environment can be stepped with ``` @@ -118,97 +118,122 @@ Then, the environment can be stepped with ### Action Space -The action space is a [`Box(4,)`](https://github.com/openai/gym/blob/master/gym/spaces/box.py) containing the desired rotation speed of each motor, if `normalized_spaces=True`, they range from -1 to 1, if `False` from 0 to `SingleDroneEnv.MAX_RPM` +The action space is a [`Dict()`](https://github.com/openai/gym/blob/master/gym/spaces/dict.py) of [`Box(4,)`](https://github.com/openai/gym/blob/master/gym/spaces/box.py)'s containing the desired control inputs + +Keys are `"0"`, `"1"`, .., `"n"`, where `n` is the number of drones + +For all `Physics` implementations, except `PYB_PM` and `PYB_KIN`, these are the rotation speeds of all motors ranging from `-1` to `1` if `normalized_spaces=True`, or from `0` to `SingleDroneEnv.MAX_RPM` otherwise + +For `physics=Physics.PYB_PM` and `Physics.PYB_KIN`, the control inputs are the desired acceleration and velocity, respectively + + + ### Observation Space -The observation space is a [`Box(20,)`](https://github.com/openai/gym/blob/master/gym/spaces/box.py) containing the drone's -- XYZ position -- Quaternion pose -- Roll, Pitch and Yaw angles -- Velocity -- Angular velocity -- Motors' speeds +The observation space is a [`Dict()`](https://github.com/openai/gym/blob/master/gym/spaces/dict.py) of pairs `{"state": Box(20,), "neighbors": MultiBinary(num_drones)}` + +Keys are `"0"`, `"1"`, .., `"n"`, where `n` is the number of drones + +Each [`Box(20,)`](https://github.com/openai/gym/blob/master/gym/spaces/box.py) contains the drone's +- X, Y, Z position in `WORLD_FRAME` (3 value, meters unless normalized) +- Quaternion orientation in `WORLD_FRAME` (4 values) +- Roll, pitch and yaw angles in `WORLD_FRAME` (3 values, radians unless normalized) +- The velocity vector in `WORLD_FRAME` (3 values, m/s unless normalized) +- Angular velocities in `WORLD_FRAME` (3 values, rad/s unless normalized) +- Motors' speeds (4 values, RPM) + +Check [`ProblemSpecificFunctions.clipAndNormalizeState()`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/ProblemSpecificFunctions.py) for the mapping from raw simulation data to normalized observations in the `[-1,1]` range (i.e., when `normalized_spaces==True`) + +Each [`MultiBinary(num_drones)`](https://github.com/openai/gym/blob/master/gym/spaces/multi_binary.py) contains the drone's own row of the multi-robot system adjacency matrix + + +### IMPORTANT NOTE: Single Agent Action and Observation Spaces +When `num_drones==1`, action and observations spaces are simplified to [`Box(4,)`](https://github.com/openai/gym/blob/master/gym/spaces/box.py) and [`Box(20,)`](https://github.com/openai/gym/blob/master/gym/spaces/box.py), respectively + + + + +## ProblemSpecificFunctions +Class [`ProblemSpecificFunctions`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/ProblemSpecificFunctions.py) contains implementations of reward, done, and normalization functions that can be selected when create an environment with `problem=Problem.CUSTOM` + + -Check [`SingleDroneUserDefinedFunctions.clipAndNormalizeState()`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/SingleDroneUserDefinedFunctions.py) for the mapping from raw simulation data to normalized observations in the [-1,1] range (i.e., when using `normalized_spaces=True`) ### Reward -The reward function can/should be modified in class [`SingleDroneUserDefinedFunctions`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/SingleDroneUserDefinedFunctions.py), for example +Reward functions can/should be modified in class [`ProblemSpecificFunctions`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/ProblemSpecificFunctions.py), for example ``` ->>> def rewardFunction(self, state): ->>> if self.USER == "Default": +>>> def rewardFunction(self, obs): +>>> if self.PROBLEM==Problem.DEFAULT: >>> ... ->>> elif self.USER == "Custom": # Use with: >>> env = SingleDroneEnv(user="Custom") ->>> height = state[2] +>>> elif self.PROBLEM==Problem.CUSTOM: # Use with: >>> env = Aviary(problem=Problem.CUSTOM) +>>> height = obs[2] >>> if height > 0.5: return 1000 >>> elif height > 0.1: return 100 >>> else: return -1 ->>> else: print("[ERROR] in rewardFunction(), unknown user") +>>> else: print("[ERROR] unknown user") ``` + + + ### Done -The halting conditions can/should be modified in class [`SingleDroneUserDefinedFunctions`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/SingleDroneUserDefinedFunctions.py), for example +Stopping conditions can/should be modified in class [`ProblemSpecificFunctions`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/ProblemSpecificFunctions.py), for example ``` ->>> def doneFunction(self, state, sim_time): ->>> if self.USER == "Default": +>>> def doneFunction(self, obs, sim_time): +>>> if self.PROBLEM==Problem.DEFAULT: >>> ... ->>> elif self.USER == "Custom": # Use with: >>> env = SingleDroneEnv(user="Custom") ->>> x = state[0]; y = state[1]; z = state[2] ->>> roll = state[7]; pitch = state[8] +>>> elif self.PROBLEM==Problem.CUSTOM: # Use with: >>> env = Aviary(problem=Problem.CUSTOM) +>>> x = obs[0]; y = obs[1]; z = obs[2] +>>> roll = obs[7]; pitch = obs[8] >>> if np.abs(x)>.5 or np.abs(y)>.5 or z>=1 \ >>> or np.abs(roll)>np.pi/2 or np.abs(pitch)>np.pi/2 \ >>> or sim_time > 5: >>> return True >>> else: >>> return False ->>> else: print("[ERROR] in doneFunction(), unknown user") +>>> else: print("[ERROR] unknown user") ``` -### Drag and Ground Effect Models -Simple drag and ground effect models can be included in the simulation initializing `SingleDroneEnv()` with `aero_effects=True`, these are based on the system identification of [Forster (2015)](http://mikehamer.info/assets/papers/Crazyflie%20Modelling.pdf) (see Eq. 4.2) -and the analytical model used as a baseline for comparison by [Shi et al. (2019)](https://arxiv.org/pdf/1811.08027.pdf) (see Eq. 15) - -Check the implementation of `_simpleAerodynamicEffects()` in class [`SingleDroneEnv`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/SingleDroneEnv.py) for more detail +### Drag, Ground Effect, and Downwash Models +Simple drag, ground effect, and downwash models can be included in the simulation initializing `Aviary()` with `physics=Physics.PYB_GND_DRAG_DW`; these are based on the system identification of [Forster (2015)](http://mikehamer.info/assets/papers/Crazyflie%20Modelling.pdf) (see Eq. 4.2), the analytical model used as a baseline for comparison by [Shi et al. (2019)](https://arxiv.org/pdf/1811.08027.pdf) (see Eq. 15), and [DSL](https://www.dynsyslab.org/vision-news/)'s experimental work by SiQi Zhou - - - -## MultiDroneEnv -A multi-agent extension of SingleDroneEnv (WIP) -### Actions -... -### Observation Space -... -### Reward -... -### Done -... +Check the implementations of `_drag()`, `_groundEffect()`, and `_downwash()` in class [`Aviary`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/Aviary.py) for more detail -### Downwash Model -WIP - - - - -## Simpler Environments for Swarm Applications -WIP - - - - -### PointMassSwarmEnv -A multi-agent environment with simplifed dynamics, using point-mass models (WIP) +## Control +Class [`Control`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/Control.py) contains implementations of controllers that can be used to command the quadcopters, for example +``` +>>> ctrl = [Control(env, control_type=ControlType.PID) for i in range(num_drones)] # Initialize "num_drones" controllers +>>> ... +>>> for i in range(num_drones): # Compute control for each drone +>>> action[str(i)], _, _ = ctrl[i].computeControlFromState( \ # Write the action in a dictionary +>>> control_timestep=env.TIMESTEP, \ +>>> state=obs[str(j)]["state"], \ +>>> target_pos=TARGET_POS) +``` -### VelocitySwarmEnv -A multi-agent environment without dynamics, where velocities can be arbitrarily set (WIP) +## Logger +Class [`Logger`](https://github.com/JacopoPan/gym-pybullet-drones/blob/master/gym_pybullet_drones/envs/Control.py) contains helper functions to save an plot the simulation data, for example +``` +>>> logger = Logger(duration_sec=T, simulation_freq_hz=freq, num_drones=num_drones) # Initialize the logger +>>> ... +>>> for i in range(NUM_DRONES): # Log information for each drone +>>> logger.log(drone=i, \ +>>> timestamp=K/env.SIM_FREQ, \ +>>> state= obs[str(i)]["state"], \ +>>> control=np.hstack([ TARGET_POS, np.zeros(9) ])) +>>> ... +>>> logger.save() # Save data to file +>>> logger.plot() # Plot data +``` @@ -217,8 +242,8 @@ A multi-agent environment without dynamics, where velocities can be arbitrarily If you wish, please refer to this work as ``` @MISC{gym-pybullet-drones2020, - author = {Panerati, Jacopo and Zhou, SiQi and Zheng, Hehui and Xu, James and Prorok, Amanda and Schoellig, Angela P.}, - title = {A PyBullet-based Gym environment to simulate and learn nano-quadcopter control}, + author = {Panerati, Jacopo and Zheng, Hehui and Zhou, SiQi and Xu, James and Prorok, Amanda and Schoellig, Angela P.}, + title = {Learning to Fly: a Gym environment based on PyBullet to simulate and learn the control of multiple nano-quadcopters}, howpublished = {\url{https://github.com/JacopoPan/gym-pybullet-drones}}, year = {2020} } diff --git a/examples/compare.py b/examples/compare.py new file mode 100644 index 000000000..8150f38b2 --- /dev/null +++ b/examples/compare.py @@ -0,0 +1,84 @@ +import os +import time +from datetime import datetime +import pdb +import math +import numpy as np +import pybullet as p +import pickle +import matplotlib.pyplot as plt + +from utils import * +from gym_pybullet_drones.envs.Aviary import DroneModel, Physics, Aviary +from gym_pybullet_drones.envs.Logger import Logger +from gym_pybullet_drones.envs.Control import ControlType, Control + +GUI = False +RECORD_VIDEO = False +TRACE_FILE = "example_trace.pkl" +PHYSICS = Physics.PYB + +if __name__ == "__main__": + + #### Load a trace and control reference from a .pkl file ########################################### + with open(os.path.dirname(os.path.abspath(__file__))+"/../files/"+TRACE_FILE, 'rb') as in_file: + TRACE_TIMESTAMPS, TRACE_DATA, TRACE_CTRL_REFERENCE, _, _, _ = pickle.load(in_file) + + + #TRACE_CTRL_REFERENCE = np.array(TRACE_CTRL_REFERENCE); TRACE_DATA = np.array(TRACE_DATA) + + + + #### Compute trace's parameters #################################################################### + DURATION_SEC = int(TRACE_TIMESTAMPS[-1]); SIMULATION_FREQ_HZ = int(len(TRACE_TIMESTAMPS)/TRACE_TIMESTAMPS[-1]) + + #### Initialize the simulation ##################################################################### + env = Aviary(drone_model=DroneModel.CF2X, initial_xyzs=np.array([0,0,.1]).reshape(1,3), physics=PHYSICS, \ + normalized_spaces=False, freq=SIMULATION_FREQ_HZ, gui=GUI, obstacles=False, record=RECORD_VIDEO) + INITIAL_STATE = env.reset(); action = np.zeros(4); pos_err = 9999. + + #### Assuming TRACE_FILE starts at position [0,0,0] and the sim starts at [0,0,INITIAL_STATE[2]] ### + TRACE_CTRL_REFERENCE[:,2] = INITIAL_STATE[2] + + #### Initialize the logger ######################################################################### + logger = Logger(duration_sec=DURATION_SEC, simulation_freq_hz=SIMULATION_FREQ_HZ, num_drones=2) + + #### Initialize the controller ##################################################################### + ctrl = Control(env, control_type=ControlType.PID) + + #### Run the comparison ############################################################################ + START = time.time() + for i in range(DURATION_SEC*env.SIM_FREQ): + + #### Step the simulation ########################################################################### + obs, reward, done, info = env.step(action) + + #### Compute the next action using the set points from the trace file ############################## + action, pos_err, yaw_err = ctrl.computeControlFromState(control_timestep=env.TIMESTEP, state=obs, \ + target_pos=TRACE_CTRL_REFERENCE[i,0:3], target_vel=TRACE_CTRL_REFERENCE[i,3:6]) + + + #### Re-arrange the trace for consistency with the logger ######################################### + trace_obs = np.hstack([TRACE_DATA[i,0:3], np.zeros(4), TRACE_DATA[i,6:9], TRACE_DATA[i,3:6], TRACE_DATA[i,9:12], TRACE_DATA[i,12:16]]) + + #### Log the trace ################################################################################# + logger.log(drone=0, timestamp=TRACE_TIMESTAMPS[i], state=trace_obs, control=np.hstack([TRACE_CTRL_REFERENCE[i,:], np.zeros(6)])) + + #### Log the simulation ############################################################################ + logger.log(drone=1, timestamp=i/env.SIM_FREQ, state=obs, control=np.hstack([TRACE_CTRL_REFERENCE[i,:], np.zeros(6)])) + + #### Printout ###################################################################################### + env.render() + + #### Sync the simulation ########################################################################### + if GUI: sync(i, START, env.TIMESTEP) + + #### Close the environment ######################################################################### + env.close() + + #### Save the simulation results ################################################################### + logger.save() + + #### Plot the simulation results ################################################################### + logger.plot(pwm=True) + diff --git a/examples/fly.py b/examples/fly.py new file mode 100644 index 000000000..583d57d84 --- /dev/null +++ b/examples/fly.py @@ -0,0 +1,81 @@ +import os +import time +from datetime import datetime +import pdb +import math +import numpy as np +import pybullet as p +import pickle +import matplotlib.pyplot as plt + +from utils import * +from gym_pybullet_drones.envs.Aviary import DroneModel, Physics, Aviary +from gym_pybullet_drones.envs.Logger import Logger +from gym_pybullet_drones.envs.Control import ControlType, Control + +DRONE = DroneModel.CF2X +NUM_DRONES = 3 +GUI = True +PHYSICS = Physics.PYB +RECORD_VIDEO = False +SIMULATION_FREQ_HZ = 240 +CONTROL_FREQ_HZ = 48 +DURATION_SEC = 10 + +if __name__ == "__main__": + + #### Initialize the simulation ##################################################################### + H = .5; R = .5; INIT_XYZS = np.array([ [R*np.cos((i/NUM_DRONES)*2*np.pi+np.pi/2), R*np.sin((i/NUM_DRONES)*2*np.pi+np.pi/2)-R, H] for i in range(NUM_DRONES) ]) + env = Aviary(drone_model=DRONE, num_drones=NUM_DRONES, initial_xyzs=INIT_XYZS, physics=PHYSICS, visibility_radius=10, \ + normalized_spaces=False, freq=SIMULATION_FREQ_HZ, gui=GUI, obstacles=True, record=RECORD_VIDEO); env.reset() + + #### Initialize a circular trajectory ############################################################## + PERIOD = 10; NUM_WP = CONTROL_FREQ_HZ*PERIOD; TARGET_POS = np.zeros((NUM_WP,3)) + for i in range(NUM_WP): TARGET_POS[i,:] = R*np.cos((i/NUM_WP)*(2*np.pi)+np.pi/2)+INIT_XYZS[0,0], R*np.sin((i/NUM_WP)*(2*np.pi)+np.pi/2)-R+INIT_XYZS[0,1], INIT_XYZS[0,2] + wp_counters = [ int(i*NUM_WP/NUM_DRONES) for i in range(NUM_DRONES) ] + + #### Initialize the logger ######################################################################### + logger = Logger(duration_sec=DURATION_SEC, simulation_freq_hz=SIMULATION_FREQ_HZ, num_drones=NUM_DRONES) + + #### Initialize the controllers #################################################################### + ctrl = [Control(env, control_type=ControlType.PID) for i in range(NUM_DRONES)] + + #### Run the simulation ############################################################################ + CTRL_EVERY_N_STEPS= int(np.floor(env.SIM_FREQ/CONTROL_FREQ_HZ)) + action = { str(i): np.array([0,0,0,0]) for i in range(NUM_DRONES) } if NUM_DRONES>1 else np.array([0,0,0,0]) + START = time.time() + for i in range(DURATION_SEC*env.SIM_FREQ): + + #### Step the simulation ########################################################################### + obs, reward, done, info = env.step(action) + + #### Transform 1-drone obs into the Dict format of multiple drones to simplify the code ############ + if NUM_DRONES==1: obs = {"0": {"state": obs}} + + #### Compute control at the desired frequency @@@@@################################################# + if i%CTRL_EVERY_N_STEPS==0: + + #### Compute control for the current waypoint ###################################################### + for j in range(NUM_DRONES): action[str(j)], _, _ = ctrl[j].computeControlFromState(control_timestep=CTRL_EVERY_N_STEPS*env.TIMESTEP, \ + state=obs[str(j)]["state"], target_pos=TARGET_POS[wp_counters[j],:]) + + #### Go to the next waypoint and loop ############################################################## + for j in range(NUM_DRONES): wp_counters[j] = wp_counters[j] + 1 if wp_counters[j]<(NUM_WP-1) else 0 + + #### Log the simulation ############################################################################ + for j in range(NUM_DRONES): logger.log(drone=j, timestamp=i/env.SIM_FREQ, state= obs[str(j)]["state"], control=np.hstack([ TARGET_POS[wp_counters[j],:], np.zeros(9) ])) + + #### Printout ###################################################################################### + env.render() + + #### Sync the simulation ########################################################################### + if GUI: sync(i, START, env.TIMESTEP) + + #### Close the environment ######################################################################### + env.close() + + #### Save the simulation results ################################################################### + logger.save() + + #### Plot the simulation results ################################################################### + logger.plot() diff --git a/examples/sa_learning.py b/examples/learn.py similarity index 55% rename from examples/sa_learning.py rename to examples/learn.py index 2811ea7fd..56eaeec25 100644 --- a/examples/sa_learning.py +++ b/examples/learn.py @@ -16,40 +16,35 @@ from ray.rllib.agents import ppo from utils import * -from gym_pybullet_drones.envs.SingleDroneEnv import SingleDroneEnv +from gym_pybullet_drones.envs.Aviary import Aviary RLLIB = False if __name__ == "__main__": - #################################################################################################### - #### Check out the environment's spaces ############################################################ - #################################################################################################### - env = gym.make("single-drone-v0") - print("Action space:", env.action_space) - print("Observation space:", env.observation_space) + #### Check the environment's spaces ################################################################ + env = gym.make("the-aviary-v1") + print("[INFO] Action space:", env.action_space) + print("[INFO] Observation space:", env.observation_space) check_env(env, warn=True, skip_render_check=True) - #################################################################################################### #### Train the model ############################################################################### - #################################################################################################### if not RLLIB: model = A2C(MlpPolicy, env, verbose=1) model.learn(total_timesteps=500000) else: config = ppo.DEFAULT_CONFIG.copy() config["num_workers"] = 0 - agent = ppo.PPOTrainer(config, env="single-drone-v0") + agent = ppo.PPOTrainer(config, env="the-aviary-v1") for i in range(100): results = agent.train() - print("{:d}: episode_reward max {:f} min {:f} mean {:f}".format(i, results["episode_reward_max"], results["episode_reward_min"], results["episode_reward_mean"])) + print("[INFO] {:d}: episode_reward max {:f} min {:f} mean {:f}".format(i, \ + results["episode_reward_max"], results["episode_reward_min"], results["episode_reward_mean"])) policy = agent.get_policy() print(policy.model.base_model.summary()) - #################################################################################################### #### Show (and record a video of) the model's performance ########################################## - #################################################################################################### - env = SingleDroneEnv(normalized_spaces=True, gui=True, record=True) + env = Aviary(normalized_spaces=True, gui=True, record=True) obs = env.reset() start = time.time() for i in range(10*env.SIM_FREQ): diff --git a/examples/physics.py b/examples/physics.py new file mode 100644 index 000000000..a1412c43d --- /dev/null +++ b/examples/physics.py @@ -0,0 +1,77 @@ +import os +import time +import pdb +import math +import numpy as np +import pybullet as p + +from utils import * +from gym_pybullet_drones.envs.Aviary import DroneModel, Aviary + +DURATION_SEC = 60 +NUM_RESETS = 0 + +if __name__ == "__main__": + + #### Initialize the simulation ##################################################################### + env = Aviary(drone_model=DroneModel.CF2X, initial_xyzs=np.array([-.7, -.5, .3]).reshape(1,3), \ + initial_rpys=np.array([0, -30*(np.pi/180), 0]).reshape(1,3), gui=True, obstacles=True); env.reset() + + #### Get PyBullet's and drone's ids ################################################################ + PYB_CLIENT = env.getPyBulletClient(); DRONE_IDS = env.getDroneIds() + + #### Make the drone weightless ##################################################################### + p.setGravity(0, 0, 0, physicsClientId=PYB_CLIENT) + + #### Run the simulation ############################################################################ + START = time.time() + for i in range(DURATION_SEC*env.SIM_FREQ): + + #### Apply x-axis force to the base ################################################################ + # p.applyExternalForce(DRONE_IDS[0], linkIndex=-1, forceObj=[1e-4,0.,0,], posObj=[0.,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) + # p.applyExternalForce(DRONE_IDS[0], linkIndex=-1, forceObj=[1e-4,0.,0,], posObj=[0.,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) + + #### Apply y-axis force to the base ################################################################ + # p.applyExternalForce(DRONE_IDS[0], linkIndex=-1, forceObj=[0.,1e-4,0.], posObj=[0.,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) + # p.applyExternalForce(DRONE_IDS[0], linkIndex=-1, forceObj=[0.,1e-4,0.], posObj=[0.,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) + + #### Apply z-axis force to the base ################################################################ + # p.applyExternalForce(DRONE_IDS[0], linkIndex=-1, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) + # p.applyExternalForce(DRONE_IDS[0], linkIndex=-1, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) + #### To propeller 0 ################################################################################ + # p.applyExternalForce(DRONE_IDS[0], linkIndex=0, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) + p.applyExternalForce(DRONE_IDS[0], linkIndex=0, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) + #### To the center of mass ######################################################################### + # p.applyExternalForce(DRONE_IDS[0], linkIndex=4, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) + # p.applyExternalForce(DRONE_IDS[0], linkIndex=4, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) + + #### Apply x-axis torque to the base ############################################################### + # p.applyExternalTorque(DRONE_IDS[0], linkIndex=-1, torqueObj=[5e-6,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) + # p.applyExternalTorque(DRONE_IDS[0], linkIndex=-1, torqueObj=[5e-6,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) + + #### Apply y-axis torque to the base ############################################################### + # p.applyExternalTorque(DRONE_IDS[0], linkIndex=-1, torqueObj=[0.,5e-6,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) + # p.applyExternalTorque(DRONE_IDS[0], linkIndex=-1, torqueObj=[0.,5e-6,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) + + #### Apply z-axis torque to the base ############################################################### + # p.applyExternalTorque(DRONE_IDS[0], linkIndex=-1, torqueObj=[0.,0.,5e-6], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) + # p.applyExternalTorque(DRONE_IDS[0], linkIndex=-1, torqueObj=[0.,0.,5e-6], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) + #### To propeller 0 ################################################################################ + # p.applyExternalTorque(DRONE_IDS[0], linkIndex=0, torqueObj=[0.,0.,5e-6], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) + # p.applyExternalTorque(DRONE_IDS[0], linkIndex=0, torqueObj=[0.,0.,5e-6], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) + #### To the center of mass ######################################################################### + # p.applyExternalTorque(DRONE_IDS[0], linkIndex=4, torqueObj=[0.,0.,5e-6], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) + p.applyExternalTorque(DRONE_IDS[0], linkIndex=4, torqueObj=[0.,0.,5e-6], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) + + #### Draw base frame ############################################################################### + env._showDroneFrame(0) + + #### Step, printout the state, and sync the simulation ############################################# + p.stepSimulation(physicsClientId=PYB_CLIENT); env.render(); sync(i, START, env.TIMESTEP) + + #### Reset ######################################################################################### + if i>1 and i%((DURATION_SEC/(NUM_RESETS+1))*env.SIM_FREQ)==0: env.reset() + + #### Close the environment ######################################################################### + env.close() + diff --git a/examples/sa_flight.py b/examples/sa_flight.py deleted file mode 100644 index 243b76fbc..000000000 --- a/examples/sa_flight.py +++ /dev/null @@ -1,120 +0,0 @@ -import os -import time -from datetime import datetime -import pdb -import math -import numpy as np -import pybullet as p -import pickle -import matplotlib.pyplot as plt - -from utils import * -from gym_pybullet_drones.envs.SingleDroneEnv import DroneModel, SingleDroneEnv -from gym_pybullet_drones.control.SingleDroneControl import ControlType, SingleDroneControl - -DRONE = DroneModel.CF2X -GUI = True -AERO_EFFECTS = False -RECORD_VIDEO = True -SAVE_TO_FILE = True -SIMULATION_FREQ_HZ = 240 -CONTROL_FREQ_HZ = 48 -DURATION_SEC = 15 -NUM_RESTARTS = 0 - -if __name__ == "__main__": - - #################################################################################################### - #### Alternatively, initialize a 1m by 1m, 41-waypoint trajectory ################################## - #################################################################################################### - height = .4 - zeros = np.zeros(20); ones = -1*np.ones(20); zero2one = np.array([-x/20-0.05 for x in range(20)]); one2zero = np.flip(zero2one) - waypoints = (np.vstack([np.hstack([0,zero2one,ones,one2zero,zeros]), np.hstack([0,zeros,zero2one,ones,one2zero]),height*np.ones(81)])).transpose() - wp_counter = 0; current_wp = waypoints[wp_counter] - - #################################################################################################### - #### Initialize the simulation ##################################################################### - #################################################################################################### - start = time.time() - start_xyz = [0,0,.35] if DRONE == DroneModel.HB else [0,0,.025] - env = SingleDroneEnv(drone_model=DRONE, initial_xyz=start_xyz, pybullet=True, aero_effects=AERO_EFFECTS, normalized_spaces=False, freq=SIMULATION_FREQ_HZ, gui=GUI, obstacles=True, record=RECORD_VIDEO) - initial_state = env.reset() - action = np.zeros(4); pos_err = 9999. - control_every_n_steps = int(np.floor(env.SIM_FREQ/CONTROL_FREQ_HZ)) - simulation_data = np.zeros((DURATION_SEC*SIMULATION_FREQ_HZ,16)) - simulation_control_reference = np.zeros((DURATION_SEC*SIMULATION_FREQ_HZ,12)) - simulation_timestamps = np.zeros((DURATION_SEC*SIMULATION_FREQ_HZ,1)) - #################################################################################################### - #### Setup the controller ########################################################################## - #################################################################################################### - ctrl = SingleDroneControl(env, control_type=ControlType.PID) - for i in range(DURATION_SEC*env.SIM_FREQ): - - #################################################################################################### - #### Step the simulation ########################################################################## - #################################################################################################### - state, reward, done, info = env.step(action) - - #################################################################################################### - #### Alternatively, navigate the waypoints in the waypoint list #################################### - #################################################################################################### - if i%control_every_n_steps==0: - target_rpy=np.array([0,0,-45])*env.DEG2RAD - action, pos_err, yaw_err = ctrl.computeControl(control_timestep=control_every_n_steps*env.TIMESTEP, cur_pos=state[0:3], cur_quat_rpy=state[3:7], cur_vel=state[10:13], cur_ang_vel=state[13:16], \ - target_pos=current_wp) # Waypoints - # target_pos=np.array([-.5, -1., .8])) # XYZ transfer - # target_pos=np.array([0., 0., 0.5]), target_rpy=target_rpy) # Hover and yaw - #################################################################################################### - #### Go to the next waypoint ####################################################################### - #################################################################################################### - if np.linalg.norm(pos_err) < 0.05 and np.linalg.norm(state[10:13])<0.1: - wp_counter = 0 if wp_counter==(len(waypoints)-1) else wp_counter+1 - current_wp = waypoints[wp_counter] - - #################################################################################################### - #### Log the simulation ############################################################################ - #################################################################################################### - simulation_timestamps[i] = i/env.SIM_FREQ - simulation_data[i,:] = np.hstack([state[0:3], state[10:13], state[7:10], state[13:20]]) - simulation_control_reference[i,:] = np.hstack([current_wp, np.zeros(3), target_rpy, np.zeros(3)]) - - #################################################################################################### - #### Printout and sync ############################################################################# - #################################################################################################### - env.render() - if GUI: sync(i, start, env.TIMESTEP) - - #################################################################################################### - #### Reset the simulation ########################################################################## - #################################################################################################### - if i>1 and i%((DURATION_SEC/(NUM_RESTARTS+1))*env.SIM_FREQ)==0: initial_state = env.reset(); wp_counter = 0 - - #################################################################################################### - #### Close the environment ######################################################################### - #################################################################################################### - env.close() - - #################################################################################################### - #### Save the simulation results ################################################################### - #################################################################################################### - if SAVE_TO_FILE: - with open(os.path.dirname(os.path.abspath(__file__))+"/../files/saves/save-flight-"+datetime.now().strftime("%m.%d.%Y_%H.%M.%S")+".npy", 'wb') as out_file: - np.save(out_file, simulation_timestamps); np.save(out_file, simulation_data); np.save(out_file, simulation_control_reference) - - #################################################################################################### - #### Plot the simulation results ################################################################### - #################################################################################################### - min_last_step = simulation_data.shape[0] - simulation_plot_data = simulation_data[:min_last_step,:] - fig, axs = plt.subplots(8,2) - t = np.arange(0, DURATION_SEC, 1/SIMULATION_FREQ_HZ) - labels = ['X', 'Y', 'Z', 'VX', 'VY', 'VZ', 'R', 'P', 'Yaw', 'WR', 'WP', 'WY', 'RPM1', 'RPM2', 'RPM3', 'RPM4'] - for i in range(16): - axs[i%8,i//8].plot(t, simulation_plot_data[:,i], '--r', label='sim.') - axs[i%8,i//8].set_xlabel('time') - axs[i%8,i//8].set_ylabel(labels[i]) - axs[i%8,i//8].grid(True) - axs[i%8,i//8].legend(loc='upper right', frameon=True) - fig.subplots_adjust(left=0.06, bottom=0.05, right=0.99, top=0.98, wspace=0.15, hspace=0.0) - plt.show() - diff --git a/examples/sa_trace.py b/examples/sa_trace.py deleted file mode 100644 index 05f9799cf..000000000 --- a/examples/sa_trace.py +++ /dev/null @@ -1,104 +0,0 @@ -import os -import time -from datetime import datetime -import pdb -import math -import numpy as np -import pybullet as p -import pickle -import matplotlib.pyplot as plt - -from utils import * -from gym_pybullet_drones.envs.SingleDroneEnv import DroneModel, SingleDroneEnv -from gym_pybullet_drones.control.SingleDroneControl import ControlType, SingleDroneControl - -GUI = False -RECORD_VIDEO = False -SAVE_TO_FILE = True -TRACE_FILE = "trace.pkl" - -if __name__ == "__main__": - - #################################################################################################### - #### Load a trace and control reference from a .pkl file ########################################### - #################################################################################################### - with open(os.path.dirname(os.path.abspath(__file__))+"/../files/traces/"+TRACE_FILE, 'rb') as in_file: - trace_timestamps, trace_data, trace_control_reference, _, trace_error, trace_rmse = pickle.load(in_file) - SIMULATION_FREQ_HZ = int(len(trace_timestamps)/trace_timestamps[-1]) - DURATION_SEC = int(trace_timestamps[-1]) - trace_control_reference = np.array(trace_control_reference) - - #################################################################################################### - #### Initialize the simulation ##################################################################### - #################################################################################################### - start = time.time() - env = SingleDroneEnv(drone_model=DroneModel.CF2X, initial_xyz=[0,0,.1], pybullet=True, aero_effects=False, normalized_spaces=False, freq=SIMULATION_FREQ_HZ, gui=GUI, obstacles=False, record=RECORD_VIDEO) - initial_state = env.reset() - action = np.zeros(4); pos_err = 9999. - trace_control_reference[:,2] = initial_state[2] # assuming TRACE_FILE starts at position (0,0,0) while the sim starts at (0,0,initial_state[2]) - simulation_data = np.zeros((DURATION_SEC*SIMULATION_FREQ_HZ,16)) - simulation_control_reference = np.zeros((DURATION_SEC*SIMULATION_FREQ_HZ,12)) - simulation_timestamps = np.zeros((DURATION_SEC*SIMULATION_FREQ_HZ,1)) - #################################################################################################### - #### Setup the controller ########################################################################## - #################################################################################################### - ctrl = SingleDroneControl(env, control_type=ControlType.PID) - for i in range(DURATION_SEC*env.SIM_FREQ): - - #################################################################################################### - #### Step the simulation ########################################################################## - #################################################################################################### - state, reward, done, info = env.step(action) - - #################################################################################################### - #### Compute the next action using the set points from the trace file ############################## - #################################################################################################### - action, pos_err, yaw_err = ctrl.computeControl(control_timestep=env.TIMESTEP, cur_pos=state[0:3], cur_quat_rpy=state[3:7], cur_vel=state[10:13], cur_ang_vel=state[13:16], \ - target_pos=trace_control_reference[i,0:3], target_rpy=np.array([0,0,0]), target_vel=trace_control_reference[i,3:6]) - - #################################################################################################### - #### Log the simulation ############################################################################ - #################################################################################################### - simulation_timestamps[i] = i/env.SIM_FREQ - simulation_data[i,:] = np.hstack([state[0:3], state[10:13], state[7:10], state[13:20]]) - simulation_control_reference[i,:] = np.hstack([trace_control_reference[i,:], np.zeros(3), np.zeros(3)]) - - #################################################################################################### - #### Printout and sync ############################################################################# - #################################################################################################### - env.render() - if GUI: sync(i, start, env.TIMESTEP) - - #################################################################################################### - #### Close the environment ######################################################################### - #################################################################################################### - env.close() - - #################################################################################################### - #### Save the simulation results ################################################################### - #################################################################################################### - if SAVE_TO_FILE: - with open(os.path.dirname(os.path.abspath(__file__))+"/../files/saves/save-trace-comparison-"+datetime.now().strftime("%m.%d.%Y_%H.%M.%S")+".npy", 'wb') as out_file: - np.save(out_file, simulation_timestamps); np.save(out_file, simulation_data); np.save(out_file, simulation_control_reference) - - #################################################################################################### - #### Plot the simulation results ################################################################### - #################################################################################################### - min_last_step = min(trace_data.shape[0],simulation_data.shape[0]) - simulation_plot_data = simulation_data[:min_last_step,:] - trace_plot_data = trace_data[:min_last_step,:] - fig, axs = plt.subplots(8,2) - t = np.arange(0, DURATION_SEC, 1/SIMULATION_FREQ_HZ) - labels = ['X', 'Y', 'Z', 'VX', 'VY', 'VZ', 'R', 'P', 'Yaw', 'WR', 'WP', 'WY', 'PWM1', 'PWM2', 'PWM3', 'PWM4'] - for i in range(16): - axs[i%8,i//8].plot(t, trace_plot_data[:,i], '-b', label='trace') - if i > 11: # Comparison to CF2's PWM instead of RPM is specific to file trace.pkl - simulation_plot_data[:,i] = (simulation_plot_data[:,i] - 4070.3) / 0.2685 - axs[i%8,i//8].plot(t, simulation_plot_data[:,i], '--r', label='sim.') - axs[i%8,i//8].set_xlabel('time') - axs[i%8,i//8].set_ylabel(labels[i]) - axs[i%8,i//8].grid(True) - axs[i%8,i//8].legend(loc='upper right', frameon=True) - fig.subplots_adjust(left=0.06, bottom=0.05, right=0.99, top=0.98, wspace=0.15, hspace=0.0) - plt.show() - diff --git a/examples/test_physics.py b/examples/test_physics.py deleted file mode 100644 index 05877ae9b..000000000 --- a/examples/test_physics.py +++ /dev/null @@ -1,101 +0,0 @@ -import os -import time -import pdb -import math -import numpy as np -import pybullet as p - -from utils import * -from gym_pybullet_drones.envs.SingleDroneEnv import DroneModel, SingleDroneEnv - -DURATION_SEC = 60 -NUM_RESTARTS = 0 - -if __name__ == "__main__": - start = time.time() - env = SingleDroneEnv(drone_model=DroneModel.CF2X, initial_xyz=[-.7,-.5,.3], initial_rpy=[0,-30*(np.pi/180),0], gui=True, record=False, obstacles=True) - env.reset() - PYB_CLIENT = env.getPyBulletClient() - DRONE_ID = env.getDroneId() - - #################################################################################################### - #### Make the drone weightless ##################################################################### - #################################################################################################### - p.setGravity(0, 0, 0, physicsClientId=PYB_CLIENT) - for i in range(DURATION_SEC*env.SIM_FREQ): - - #################################################################################################### - #### Apply x-axis force to the base ################################################################ - #################################################################################################### - # p.applyExternalForce(DRONE_ID, linkIndex=-1, forceObj=[1e-4,0.,0,], posObj=[0.,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) - # p.applyExternalForce(DRONE_ID, linkIndex=-1, forceObj=[1e-4,0.,0,], posObj=[0.,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) - - #################################################################################################### - #### Apply y-axis force to the base ################################################################ - #################################################################################################### - # p.applyExternalForce(DRONE_ID, linkIndex=-1, forceObj=[0.,1e-4,0.], posObj=[0.,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) - # p.applyExternalForce(DRONE_ID, linkIndex=-1, forceObj=[0.,1e-4,0.], posObj=[0.,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) - - #################################################################################################### - #### Apply z-axis force to the base ################################################################ - #################################################################################################### - # p.applyExternalForce(DRONE_ID, linkIndex=-1, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) - # p.applyExternalForce(DRONE_ID, linkIndex=-1, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) - #################################################################################################### - #### To propeller 0 ################################################################################ - #################################################################################################### - # p.applyExternalForce(DRONE_ID, linkIndex=0, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) - p.applyExternalForce(DRONE_ID, linkIndex=0, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) - #################################################################################################### - #### To the center of mass ######################################################################### - #################################################################################################### - # p.applyExternalForce(DRONE_ID, linkIndex=4, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) - # p.applyExternalForce(DRONE_ID, linkIndex=4, forceObj=[0.,0.,1e-4], posObj=[0.,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) - - #################################################################################################### - #### Apply x-axis torque to the base ############################################################### - #################################################################################################### - # p.applyExternalTorque(DRONE_ID, linkIndex=-1, torqueObj=[5e-6,0.,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) - # p.applyExternalTorque(DRONE_ID, linkIndex=-1, torqueObj=[5e-6,0.,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) - - #################################################################################################### - #### Apply y-axis torque to the base ############################################################### - #################################################################################################### - # p.applyExternalTorque(DRONE_ID, linkIndex=-1, torqueObj=[0.,5e-6,0.], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) - # p.applyExternalTorque(DRONE_ID, linkIndex=-1, torqueObj=[0.,5e-6,0.], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) - - #################################################################################################### - #### Apply z-axis torque to the base ############################################################### - #################################################################################################### - # p.applyExternalTorque(DRONE_ID, linkIndex=-1, torqueObj=[0.,0.,5e-6], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) - # p.applyExternalTorque(DRONE_ID, linkIndex=-1, torqueObj=[0.,0.,5e-6], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) - #################################################################################################### - #### To propeller 0 ################################################################################ - #################################################################################################### - # p.applyExternalTorque(DRONE_ID, linkIndex=0, torqueObj=[0.,0.,5e-6], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) - # p.applyExternalTorque(DRONE_ID, linkIndex=0, torqueObj=[0.,0.,5e-6], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) - #################################################################################################### - #### To the center of mass ######################################################################### - #################################################################################################### - # p.applyExternalTorque(DRONE_ID, linkIndex=4, torqueObj=[0.,0.,5e-6], flags=p.WORLD_FRAME, physicsClientId=PYB_CLIENT) - p.applyExternalTorque(DRONE_ID, linkIndex=4, torqueObj=[0.,0.,5e-6], flags=p.LINK_FRAME, physicsClientId=PYB_CLIENT) - - #################################################################################################### - #### Draw base frame ############################################################################### - #################################################################################################### - env._showDroneFrame() - - #################################################################################################### - #### Printout, step, and sync ###################################################################### - #################################################################################################### - env.render() - p.stepSimulation(physicsClientId=PYB_CLIENT) - sync(i, start, env.TIMESTEP) - - #################################################################################################### - #### Reset ######################################################################################### - #################################################################################################### - if i>1 and i%((DURATION_SEC/(NUM_RESTARTS+1))*env.SIM_FREQ)==0: env.reset() - - env.close() - diff --git a/examples/utils.py b/examples/utils.py index c68ebee43..270ece7be 100644 --- a/examples/utils.py +++ b/examples/utils.py @@ -4,11 +4,11 @@ #### Sync the stepped simulation with the wall-clock ############################################### #################################################################################################### #### Arguments ##################################################################################### -#### - i (Integer) current step of the simulation ######################### -#### - start_time (Timestamp) timestamp of the simulation start ###################### -#### - timestep (Float) desired, wall-clock timestep to render the simulation ## +#### - i (int) current simulation iteration ########################### +#### - start_time (timestamp) timestamp of the simulation start ###################### +#### - timestep (float) desired, wall-clock step of the simulation's rendering # #################################################################################################### def sync(i, start_time, timestep): - elapsed = time.time()-start_time - if elapsed < i*(timestep): time.sleep(i*(timestep)-elapsed) + elapsed = time.time() - start_time + if elapsed<(i*timestep): time.sleep(timestep*i - elapsed) diff --git a/files/traces/trace.pkl b/files/example_trace.pkl similarity index 100% rename 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