| 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. | |