This is a Pytorch implementation of the paper Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning
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- python2.7
- ROS Kinetic
- mpi4py
- Stage
- PyTorch
Please use the stage_ros-add_pose_and_crash package instead of the default package provided by ROS.
mkdir -p catkin_ws/src cp stage_ros-add_pose_and_crash catkin_ws/src cd catkin_ws catkin_make source devel/setup.bash To train Stage1, modify the hyper-parameters in ppo_stage1.py as you like, and running the following command:
rosrun stage_ros_add_pose_and_crash stageros -g worlds/stage1.world mpiexec -np 24 python ppo_stage1.py To train Stage2, modify the hyper-parameters in ppo_stage2.py as you like, and running the following command:
rosrun stage_ros_add_pose_and_crash stageros -g worlds/stage2.world mpiexec -np 44 python ppo_stage2.py rosrun stage_ros_add_pose_and_crash stageros worlds/circle.world mpiexec -np 50 python circle_test.py I am not the author of the paper and not in their group either. You may contact Jia Pan (jpan@cs.hku.hk) for the paper related issues. If you find it useful and use it in your project, please consider citing:
@misc{Tianyu2018, author = {Tianyu Liu}, title = {Robot Collision Avoidance via Deep Reinforcement Learning}, year = {2018}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/Acmece/rl-collision-avoidance.git}}, commit = {7bc682403cb9a327377481be1f110debc16babbd} }