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README.md
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---
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license: mit
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tags:
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- robotics
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- diffusion-policy
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- imitation-learning
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- manipulation
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---
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# UMI-on-Air - Pre-trained Checkpoints
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Pre-trained diffusion policy checkpoints for **UMI-on-Air: Embodiment-Aware Guidance for Embodiment-Agnostic Visuomotor Policies**.
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📄 **Paper:** [UMI-on-Air (PDF)](https://umi-on-air.github.io/static/umi-on-air.pdf) | [arXiv](https://arxiv.org/abs/2510.02614)
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🌐 **Project Website:** [umi-on-air.github.io](https://umi-on-air.github.io/)
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💻 **Code:** [GitHub](https://github.com/LeCAR-Lab/UMI-on-Air)
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## Checkpoints Included
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| Task | Description |
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|------|-------------|
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| `umi_cabinet` | Cabinet door opening task |
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| `umi_peg` | Peg insertion task |
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| `umi_pick` | Object picking task |
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| `umi_valve` | Valve turning task |
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## Usage
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```bash
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# Download and extract
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wget https://huggingface.co/LeCAR-Lab/umi-on-air_checkpoints/resolve/main/checkpoints.tar.gz
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tar -xzf checkpoints.tar.gz
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```
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Each checkpoint folder contains:
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- `checkpoints/latest.ckpt` - Model weights
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- `normalizer.pkl` - Data normalization parameters
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- `.hydra/config.yaml` - Training configuration
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## Citation
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If you use these checkpoints, please cite our work:
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```bibtex
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@misc{gupta2025umionairembodimentawareguidanceembodimentagnostic,
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title={UMI-on-Air: Embodiment-Aware Guidance for Embodiment-Agnostic Visuomotor Policies},
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author={Harsh Gupta and Xiaofeng Guo and Huy Ha and Chuer Pan and Muqing Cao and Dongjae Lee and Sebastian Sherer and Shuran Song and Guanya Shi},
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year={2025},
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eprint={2510.02614},
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archivePrefix={arXiv},
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primaryClass={cs.RO},
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url={https://arxiv.org/abs/2510.02614},
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}
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```
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