OpenAI Gym interface for Universal Robots with ROS Gazebo based on openai_ros
- Reinforcement Learning with Soft-Actor-Critic (SAC) with the implementation from TF2RL with 2 action spaces: task-space (end-effector Cartesian space) and joint-space.
- Start the simulation environment based on ur3
roslaunch ur3_gazebo ur3e_cubes_example.launch
- Execute the learning session:
For task-space example:
rosrun ur_rl tf2rl_sac.py -e 0
For task-space example:
rosrun ur_rl tf2rl_sac.py -e 1