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.