| --- |
| license: apache-2.0 |
| tags: [lerobot, so101, mujoco, ppo, distillation, sim2real] |
| --- |
| |
| # SO101 MuJoCo sim2real: PPO teacher -> vision student |
|
|
| Checkpoints from `lerobot.rl.so101_mujoco`. Code, configs and full instructions: |
| [github.com/suuu-u/Learn_SO101](https://github.com/suuu-u/Learn_SO101). |
|
|
| Download them to `outputs/so101_mujoco/` of the lerobot checkout, where the configs expect them: |
|
|
| ```bash |
| hf download suuu3/so101_mujoco_sim2real --local-dir outputs/so101_mujoco |
| ``` |
|
|
| | File | Kind | Description | |
| |---|---|---| |
| | `teacher_realscene.pt` | PPO teacher (privileged state: cube pose, contacts, ...) | Trained on the real-scene-matched MuJoCo scene (`ppo_realscene/config.yaml`), best checkpoint = iteration 7600, rolling success rate ~0.54 | |
| | `student_realcam.pt` | Vision student (front + wrist cameras + 18-dim joint state), **used for deployment** | DAgger distillation from `teacher_realscene.pt` (`distill_realcam/config.yaml`), best checkpoint = iteration 200, rolling success rate ~0.48 | |
|
|
| Success rates are rolling training statistics under domain randomization, not a separate evaluation. |
| The released weights were trained in stages; training from scratch with these configs may give slightly different results. |
|
|
| `ppo_realscene/` and `distill_realcam/` contain the training `config.yaml` and `metrics.jsonl`. |
|
|
| ```bash |
| # Evaluate in simulation / deploy (from the lerobot checkout) |
| python -m lerobot.rl.so101_mujoco.eval --checkpoint outputs/so101_mujoco/student_realcam.pt |
| python -m lerobot.rl.so101_mujoco.deploy --headless true --n_episodes 50 |
| ``` |
|
|
