| --- |
| license: apache-2.0 |
| tags: |
| - robotics |
| - reinforcement-learning |
| - humanoid |
| --- |
| |
| # FADA Oracle PPO Checkpoints |
|
|
| Oracle PPO expert checkpoints for **FADA: Few-Shot Domain Adaptation via Dynamics Alignment for |
| Humanoid Control** (arXiv:2606.28476), used as the `--expert-checkpoint` input to the DAgger |
| distillation step of the FADA pipeline. |
|
|
| - Code: https://github.com/lecar-lab/FADA |
| - Paper: https://arxiv.org/abs/2606.28476 |
| - Project page: https://lecar-lab.github.io/FADA-humanoid/ |
|
|
| ## Contents |
|
|
| - `t1/`: Booster T1 (23-DoF) oracle PPO training run, every intermediate checkpoint saved every |
| 100 iterations (`model_00000.pt` ... `model_24999.pt`, 251 files). |
| - `g1/`: Unitree G1 (29-DoF) oracle PPO training run, every intermediate checkpoint saved every |
| 100 iterations (`model_00000.pt` ... `model_24999.pt`, 251 files). |
|
|
| The full intermediate history is included, not just the final checkpoint: FADA's DAgger training |
| reward-samples 20 checkpoints from across the oracle run for its weak-policy ("suboptimal-data") |
| source, so `--expert-checkpoint` must point into a directory holding every intermediate |
| `model_*.pt`. See the code repository's README for the exact usage and how to opt out of that |
| source (`--suboptimal-data-ratio 0`), which only requires the single final checkpoint. |
|
|
| ## Security note |
|
|
| A `.pt` checkpoint is executable content. The FADA codebase loads these with torch's restricted |
| `weights_only=True` reader, which raises rather than executing an untrusted pickle stream. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{xie2026fada, |
| title = {FADA: Few-Shot Domain Adaptation via Dynamics Alignment for Humanoid Control}, |
| author = {Xie, Angchen and Sobanbabu, Nikhil and Shikhare, Ishayu and Wang, Alan |
| and Simchowitz, Max and Shi, Guanya}, |
| journal = {arXiv preprint arXiv:2606.28476}, |
| year = {2026}, |
| doi = {10.48550/arXiv.2606.28476} |
| } |
| ``` |
|
|
