Reinforcement Learning

I am super new to simulators. I will need to implement a reinforcement learning algorithm on a robot so I wanted to learn Gazebo. Is there a comprehensive tutorial for using Gazebo with reinforcement. Any resource to get me on my way will be truly appreciated.

Check out OpenAI gym: 2019-tfm-ignacio-arranz/ at master · RoboticsLabURJC/2019-tfm-ignacio-arranz · GitHub . Just be aware that it uses “Gazebo Classic” (the older Gazebo) simulator, which is however more suitable for RL because it fully supports resetting the environment with a single service call (AFAIK the new Gazebo always struggled with this).

There’s also which uses the new Gazebo, but I don’t think it’s actively maintained anymore. As to the reset capability, I only see one issue with a particular system crashing after reset. Things should be working if you don’t use that system. @peci1, if you know of specific problems with reset, please let us know.

I am using my Own robot and my own environment. I want to use Reinforment learning Algorithm to develop a path plan for a Pick and place robot.

I dont really know how to develop an Enviroment in Gazebo. That’s why i tried using OPEN_AI Ros package, but it doesn’t work for Python 3. I am getting a lot of error

I have also created a Moveit package for my Robot

Do you know how to integrate RL in Gazebo to train the robot?

Cofig: WSL2 in Windows 11, Ubuntu 20.04.6, Ros Noetic

Try this GitHub - ammar-n-abbas/sim2real-ur-gym-gazebo: Universal Robot Environment for OpenAI Gymnasium and ROS Gazebo Interface. It is a “Sim2Real Implementation: Gymnasium-Gazebo UREnv for Deep Reinforcement Learning With Reach, Grasp, and Pick&Place Environment with Collision Avoidance (Object or Human)”.