| --- |
| license: apache-2.0 |
| language: |
| - en |
| library_name: pytorch |
| model_name: Copper-Policy |
| tags: |
| - robotics |
| - robot-manipulation |
| - world-action-model |
| - libero |
| - libero-plus |
| - robotwin |
| - arxiv:2609.32779 |
| --- |
| |
| <h1 align="center"><img src="assets/copper.png" width="32" height="32" align="absmiddle" style="display: inline-block; vertical-align: middle;" alt="Copper-Policy logo"> Copper-Policy</h1> |
|
|
| <h3 align="center">Focus on the Representation for Robust Robot Manipulation</h3> |
|
|
| <p align="center"><b>Zexin Feng · Yixu Feng · Lingyu Xiao · Shang Su · Kexin Zheng<br>Chang Xu · Mengkai Shi · Shuo Feng · Xintao Yan</b></p> |
|
|
| <p align="center">The University of Hong Kong · The University of Sydney · Tsinghua University · DenseAI</p> |
|
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| <p align="center"><a href="https://huggingface.co/Mark455/Copper-Policy/blob/main/README.md">English</a> | <a href="https://huggingface.co/Mark455/Copper-Policy/blob/main/README_zh.md">中文</a></p> |
|
|
| Official inference checkpoints for **Copper-Policy: Focus on the Representation for Robust Robot Manipulation**. |
|
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| Copper-Policy combines a compact world representation with spatial visual features for robot manipulation. This release contains two approximately 2B-parameter policies. |
|
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| <p align="center"><a href="https://arxiv.org/abs/2609.32779">📄 Paper</a> · <a href="https://zexinfeng-cn.github.io/works/copper-policy/">🌐 Project Page</a> · <a href="https://github.com/Mark4551124015/Copper-Policy">💻 Code</a></p> |
|
|
| ## 📦 Included checkpoints |
|
|
| ```text |
| libero/ |
| ├── policy.pt |
| └── policy.json |
| robotwin/ |
| ├── policy.pt |
| └── policy.json |
| release_manifest.json |
| SHA256SUMS |
| LICENSE |
| ``` |
|
|
| - **LIBERO:** one checkpoint shared by LIBERO and LIBERO-Plus; 2 RGB views, 7-dimensional actions and 8-dimensional proprioception. |
| - **RoboTwin:** one checkpoint shared by clean and randomized evaluations; 3 RGB views, 14-dimensional actions and proprioception. |
| - Both checkpoints predict an action horizon of **32**. Normalization statistics and the configuration needed for inference are included in `policy.pt`; no separate dataset-statistics file is required. |
| - `policy.json` describes each checkpoint; `SHA256SUMS` provides checksums. These custom PyTorch checkpoints are loaded using the Copper-Policy code repository. |
|
|
| ## 📥 Download |
|
|
| <div align="center"> |
|
|
| | Checkpoint | Benchmarks | |
| | --- | --- | |
| | `libero/policy.pt` | LIBERO / LIBERO-Plus | |
| | `robotwin/policy.pt` | RoboTwin clean / randomized | |
|
|
| </div> |
|
|
| Each checkpoint is approximately **4.06 GB**. Both together require approximately **8.12 GB**. |
|
|
| ```bash |
| # Run in the Copper-Policy code repository |
| uv run --frozen --all-extras --no-sync hf download Mark455/Copper-Policy \ |
| libero/policy.pt robotwin/policy.pt \ |
| --local-dir pretrained_weights/copper_policy |
| ``` |
|
|
| To download only one model, keep only its file path in the command. |
|
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| For installation and inference, see the [code repository](https://github.com/Mark4551124015/Copper-Policy). |
|
|
| ## ⚙️ Inference |
|
|
| The code repository provides four evaluation launchers: |
|
|
| ```bash |
| uv run --frozen --all-extras --no-sync bash test_libero.sh --all-tasks |
| uv run --frozen --all-extras --no-sync bash test_libero_plus.sh --all-tasks |
| uv run --frozen --all-extras --no-sync bash test_robotwin_clean.sh --all-tasks |
| uv run --frozen --all-extras --no-sync bash test_robotwin_rand.sh --all-tasks |
| ``` |
|
|
| Default inference uses **10 denoising steps**, with **10 replan steps for LIBERO / LIBERO-Plus** and **24 for RoboTwin**. Compilation and rollout videos are enabled. Download the V-JEPA 2.1, DINOv2 and Wan T5 encoder presets using `python -m tools.download_weights all --yes` through the repository's uv environment. No separate Wan transformer initialization weights are needed. |
|
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| Follow the [code repository](https://github.com/Mark4551124015/Copper-Policy) for installation and simulator assets; adapt PyTorch/CUDA to your hardware and driver. **Training code — coming soon.** |
|
|
| <details> |
| <summary><b>Note: LIBERO language mapping</b></summary> |
|
|
| LIBERO training instructions sometimes differ from benchmark prompts. The code maps exact plaintext benchmark prompts to training instructions. LIBERO-Plus language perturbations are not mapped; unmatched prompts retain the benchmark text. |
|
|
| </details> |
|
|
| ## 📊 Reported results |
|
|
| <div align="center"> |
|
|
| | LIBERO | LIBERO-Plus | RoboTwin clean | RoboTwin randomized | |
| | :---: | :---: | :---: | :---: | |
| | 97.25% | 80.85% | 70.84% | 12.98% | |
|
|
| </div> |
|
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| These are results reported in the [paper and project page](https://zexinfeng-cn.github.io/works/copper-policy/). Individual evaluation runs record their own measured scores. |
|
|
| ## 📚 Citation |
|
|
| ```bibtex |
| @article{feng2026copper, |
| title={Copper-Policy: Focus on the Representation for Robust Robot Manipulation}, |
| author={Feng, Zexin and Feng, Yixu and Xiao, Lingyu and Su, Shang and Zheng, Kexin and Xu, Chang and Shi, Mengkai and Feng, Shuo and Yan, Xintao}, |
| journal={arXiv preprint arXiv:2609.32779}, |
| year={2026} |
| } |
| ``` |
|
|
| ## 🙏 Acknowledgements and license |
|
|
| Our implementation builds on [FastWAM](https://github.com/yuantianyuan01/FastWAM) and [LingBot-VA](https://github.com/robbyant/lingbot-va). Dataset conversion uses our [lerobot-tools](https://github.com/Mark4551124015/lerobot-tools). Codex helped organize the open-source code. |
|
|
| Released under [Apache 2.0](LICENSE). External encoders and simulator assets retain their respective licenses. |
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|
