- This project is to learn to create a custom environment in webots to test out a quadruped robot environment for reinforcement learning.
- It is a 3D version of the 2D env Bipedal walker.
- I chose to use stable baselines for this project as the goal of this project was simply to create a robot environment that is easily accessible for others.
- SAC was chosen out of DDPG, SAC and PPO as it yields better results based on what i written and tested in my other github project for bipedal walker.
- Install webots in your system and use the spot model (protos) in the protos folder.
- Install stable-baselines3 in your python environment. https://github.com/DLR-RM/stable-baselines3
- Install open ai gym in your python environment. https://gym.openai.com/docs/
To run the program, Open worlds/test_spot4.wbt in webots.
If there are any issues with running the world, please change the controller being used by spot referred to below. There are 2 controllers in this world.
- spot_controller - To test out if the controllers are running correctly in your system.
- rl_controller - To run the spot robot using the trained model of RL controller.
- 970 Graphics card or higher
In the future i'd probably pair up a camera with yolov5 for feature selection then pass those features to the RL algorithm to train to walk.