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- README_zh.md +75 -0
README.md
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<p align="center"><a href="README.md">English</a> | <a href="README_zh.md">中文</a></p>
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## 📥 Download
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| Checkpoint | Benchmarks |
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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).
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<p align="center"><a href="README.md">English</a> | <a href="README_zh.md">中文</a></p>
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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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[📄 Paper](https://arxiv.org/abs/2609.32779) · [🌐 Project Page](https://zexinfeng-cn.github.io/works/copper-policy/) · [💻 Code](https://github.com/Mark4551124015/Copper-Policy)
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## 📦 Included checkpoints
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```text
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libero/
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├── policy.pt
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└── policy.json
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robotwin/
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├── policy.pt
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└── policy.json
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release_manifest.json
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SHA256SUMS
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LICENSE
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```
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- **LIBERO:** one checkpoint shared by LIBERO and LIBERO-Plus; 2 RGB views, 7-dimensional actions and 8-dimensional proprioception.
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- **RoboTwin:** one checkpoint shared by clean and randomized evaluations; 3 RGB views, 14-dimensional actions and proprioception.
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- 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.
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- `policy.json` describes each checkpoint; `SHA256SUMS` provides checksums. These custom PyTorch checkpoints are loaded using the Copper-Policy code repository.
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## 📥 Download
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| Checkpoint | Benchmarks |
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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).
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## ⚙️ Inference
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The code repository provides four evaluation launchers:
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```bash
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uv run --frozen --all-extras --no-sync bash test_libero.sh --all-tasks
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uv run --frozen --all-extras --no-sync bash test_libero_plus.sh --all-tasks
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uv run --frozen --all-extras --no-sync bash test_robotwin_clean.sh --all-tasks
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uv run --frozen --all-extras --no-sync bash test_robotwin_rand.sh --all-tasks
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```
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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.**
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<details>
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<summary><b>Note: LIBERO language mapping</b></summary>
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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.
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</details>
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## 📊 Reported results
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| LIBERO | LIBERO-Plus | RoboTwin clean | RoboTwin randomized |
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| :---: | :---: | :---: | :---: |
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| 97.25% | 80.85% | 70.84% | 12.98% |
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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.
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## 📚 Citation
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```bibtex
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@misc{feng2026copperpolicyfocusrepresentationrobust,
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title={Copper-Policy: Focus on the Representation for Robust Robot Manipulation},
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author={Zexin Feng and Yixu Feng and Lingyu Xiao and Shang Su and Kexin Zheng and Chang Xu and Mengkai Shi and Shuo Feng and Xintao Yan},
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year={2026},
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eprint={2609.32779},
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archivePrefix={arXiv},
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primaryClass={cs.RO},
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url={https://arxiv.org/abs/2609.32779}
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}
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```
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## 🙏 Acknowledgements and license
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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.
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Released under [Apache 2.0](LICENSE). External encoders and simulator assets retain their respective licenses.
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README_zh.md
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<p align="center"><a href="README.md">English</a> | <a href="README_zh.md">中文</a></p>
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## 📥 模型下载
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| 权重 | 测评环境 |
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只下载一个模型时,在命令中保留对应的文件路径即可。
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安装与推理说明见[代码仓库](https://github.com/Mark4551124015/Copper-Policy)。
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<p align="center"><a href="README.md">English</a> | <a href="README_zh.md">中文</a></p>
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**Copper-Policy: Focus on the Representation for Robust Robot Manipulation** 的官方推理权重。
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Copper-Policy 将紧凑的世界表征与空间视觉特征结合,用于机器人操作。本仓库提供两份约 2B 参数的策略模型。
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[📄 论文](https://arxiv.org/abs/2609.32779) · [🌐 项目主页](https://zexinfeng-cn.github.io/works/copper-policy/) · [💻 代码](https://github.com/Mark4551124015/Copper-Policy)
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## 📦 发布的模型
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```text
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libero/
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├── policy.pt
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└── policy.json
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robotwin/
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├── policy.pt
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└── policy.json
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release_manifest.json
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SHA256SUMS
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LICENSE
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```
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- **LIBERO:** LIBERO 与 LIBERO-Plus 共用一份权重;输入 2 个 RGB 视角,动作维度为 7,本体状态维度为 8。
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- **RoboTwin:** clean 与 randomized 共用一份权重;输入 3 个 RGB 视角,动作及本体状态维度均为 14。
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- 两份模型的动作预测长度均为 **32**。`policy.pt` 已包含归一化统计与推理所需配置,无需单独下载数据集统计文件。
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- `policy.json` 提供模型信息,`SHA256SUMS` 提供校验值。这些自定义 PyTorch checkpoint 请使用 Copper-Policy 代码仓库加载。
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## 📥 模型下载
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| 权重 | 测评环境 |
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只下载一个模型时,在命令中保留对应的文件路径即可。
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安装与推理说明见[代码仓库](https://github.com/Mark4551124015/Copper-Policy)。
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## ⚙️ 推理
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代码仓库提供四个测评入口:
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```bash
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uv run --frozen --all-extras --no-sync bash test_libero.sh --all-tasks
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uv run --frozen --all-extras --no-sync bash test_libero_plus.sh --all-tasks
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uv run --frozen --all-extras --no-sync bash test_robotwin_clean.sh --all-tasks
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uv run --frozen --all-extras --no-sync bash test_robotwin_rand.sh --all-tasks
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```
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默认使用 **10 个去噪步**;**LIBERO / LIBERO-Plus 的 replan steps 为 10**,**RoboTwin 为 24**。默认开启编译与视频保存。在仓库的 uv 环境中使用 `python -m tools.download_weights all --yes` 下载 V-JEPA 2.1、DINOv2 与 Wan T5 编码器预设。无需额外的 Wan transformer 初始化权重。
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安装与模拟器资源请参考[代码仓库](https://github.com/Mark4551124015/Copper-Policy),按自己的硬件和驱动适配 PyTorch/CUDA。**训练代码 coming soon。**
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<details>
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<summary><b>Note:LIBERO 语言映射</b></summary>
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LIBERO 训练数据的指令有时与 benchmark 提供的文本不同。代码通过明文到明文的精确查表映射回训练指令。LIBERO-Plus 的 language 扰动不做映射;找不到映射时保留 benchmark 原始文本。
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</details>
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## 📊 论文报告结果
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| LIBERO | LIBERO-Plus | RoboTwin clean | RoboTwin randomized |
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| :---: | :---: | :---: | :---: |
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| 97.25% | 80.85% | 70.84% | 12.98% |
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以上为[论文与项目主页](https://zexinfeng-cn.github.io/works/copper-policy/)报告的结果,每次测评会记录该次实际运行的分数。
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## 📚 引用
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```bibtex
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@misc{feng2026copperpolicyfocusrepresentationrobust,
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title={Copper-Policy: Focus on the Representation for Robust Robot Manipulation},
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author={Zexin Feng and Yixu Feng and Lingyu Xiao and Shang Su and Kexin Zheng and Chang Xu and Mengkai Shi and Shuo Feng and Xintao Yan},
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year={2026},
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eprint={2609.32779},
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archivePrefix={arXiv},
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primaryClass={cs.RO},
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url={https://arxiv.org/abs/2609.32779}
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}
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```
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## 🙏 致谢与许可证
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实现基于 [FastWAM](https://github.com/yuantianyuan01/FastWAM) 与 [LingBot-VA](https://github.com/robbyant/lingbot-va)。数据转换使用我们自己的 [lerobot-tools](https://github.com/Mark4551124015/lerobot-tools)。Codex 协助整理了开源代码。
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权重以 [Apache 2.0](LICENSE) 发布,外部编码器和模拟器资源遵循各自的许可证。
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