For some time, I have been working on a basic reinforcement learning playground designed to enable experimentatio with simple systems in the ROS 2 environment and Gazebo.
Currently, you can try it with a cart-pole example. The repository includes both reinforcement learning nodes and model-based control, with full calculations provided in a Jupyter notebook. The project also comes with a devcontainer, making it easy to set up.
You can find the code here: GitHub - Wiktor-99/reinforcement_learning_playground
