README.md

A repository that contains example json files that can be used for different applications of the LeRobot code base.

Current available configs:

  - RL :
    - env_config.json: Environment config for a real robot setup using a gamepad for teleoperation and an SO10* arm as the main agent. Using `gym_manipulator.py`, one can use this config to teleoperate the robot and record a dataset for reinforcement learning.
    - train_config.json: Training config for the HIL-SERL implementation in LeRobot on the real robot using the similar environment configuration to the `env_config.json` in the same directory. 
    - gym_hil:
      - env_config.json: Environment config for simulation using the `gym_hil` environment. 
      - train_config.json: Training config for the HIL-SERL implementation in LeRobot for simulated environments.
  - Sim IL:
    - env_config.json: Environment config for simulation using the `gym_hil` environment. You can use this configuration to collect a dataset in simulation that can be used for imitation learning or reinforcement learning. 
    - eval_config.json: Evaluation config for models trained on datasets collected from `gym_hil` environment.
  - Reward Classifier:
    - config.json: Main configuration for training a reward classifier.