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--- |
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license: cc-by-4.0 |
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task_categories: |
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- robotics |
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language: |
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- en |
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tags: |
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- AMASS |
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- Retarget |
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- Robotics |
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- Humanoid |
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pretty_name: Retargeted AMASS for Robotics |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Retargeted AMASS for Robotics |
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## Project Overview |
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This project aims to retarget motion data from the AMASS dataset to various robot models and open-source the retargeted data to facilitate research and applications in robotics and human-robot interaction. AMASS (Archive of Motion Capture as Surface Shapes) is a high-quality human motion capture dataset, and the SMPL-X model is a powerful tool for generating realistic human motion data. |
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By adapting the motion data from AMASS to different robot models, we hope to provide a more diverse and accessible motion dataset for robot training and human-robot interaction. |
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## Dataset Content |
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This open-source project includes the following: |
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1. **Retargeted Motions**: Motion files retargeted from AMASS to various robot models. |
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- **Unitree G1**: |
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<iframe src="//player.bilibili.com/player.html?bvid=BV1zd6iYkEZ2&page=1&high_quality=1&danmaku=0" allowfullscreen="allowfullscreen" width="100%" height="500" scrolling="no" frameborder="0" sandbox="allow-top-navigation allow-same-origin allow-forms allow-scripts"></iframe> |
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The retargeted motions for the Unitree G1 robot are generated based on the official open-source model provided by Unitree. |
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https://github.com/unitreerobotics/unitree_ros/blob/master/robots/g1_description/g1_29dof_rev_1_0.xml |
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The joint positions comply with the constraints defined in the XML file. |
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data shape：[-1,36] |
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0:3 root world position |
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3:7 root quaternion rotation, order: xyzw |
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7:36 joint positions |
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joint order: |
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```txt |
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left_hip_pitch_joint |
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left_hip_roll_joint |
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left_hip_yaw_joint |
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left_knee_joint |
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left_ankle_pitch_joint |
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left_ankle_roll_joint |
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right_hip_pitch_joint |
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right_hip_roll_joint |
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right_hip_yaw_joint |
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right_knee_joint |
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right_ankle_pitch_joint |
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right_ankle_roll_joint |
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waist_yaw_joint |
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waist_roll_joint |
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waist_pitch_joint |
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left_shoulder_pitch_joint |
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left_shoulder_roll_joint |
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left_shoulder_yaw_joint |
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left_elbow_joint |
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left_wrist_roll_joint |
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left_wrist_pitch_joint |
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left_wrist_yaw_joint |
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right_shoulder_pitch_joint |
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right_shoulder_roll_joint |
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right_shoulder_yaw_joint |
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right_elbow_joint |
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right_wrist_roll_joint |
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right_wrist_pitch_joint |
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right_wrist_yaw_joint |
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``` |
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- **Others**: Future Updates |
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2. **Usage Examples**: Code examples on how to use the retargeted data. |
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./g1/visualize.py |
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3. **License Files**: Original license information for each sub-dataset within AMASS. |
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## License |
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The retargeted data in this project is derived from the AMASS dataset and therefore adheres to the original license terms of AMASS. Each sub-dataset within AMASS may have different licenses, so please ensure compliance with the following requirements when using the data: |
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- **Propagate Original Licenses**: When using or distributing the retargeted data, you must include and comply with the original licenses of the sub-datasets within AMASS. |
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- **Attribution Requirements**: Properly cite this work and the original authors and sources of the AMASS dataset and its sub-datasets. |
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For detailed license information, please refer to the `LICENSE` file in this project. |
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## Acknowledgments |
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This project is built on the AMASS dataset and the SMPL-X model. Special thanks to the research team at the Max Planck Institute for Intelligent Systems for providing this valuable resource. |
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## Citation |
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If you use the data or code from this project, please cite this work and relevant papers for AMASS and SMPL-X: |
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```bibtex |
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@misc{Retargeted_AMASS_R, |
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title={Retargeted AMASS for Robotics}, |
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author={Kun Zhao}, |
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url={https://huggingface.co/datasets/fleaven/Retargeted_AMASS_for_robotics} |
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} |
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@inproceedings{AMASS2019, |
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title={AMASS: Archive of Motion Capture as Surface Shapes}, |
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author={Mahmood, Naureen and Ghorbani, Nima and Troje, Nikolaus F. and Pons-Moll, Gerard and Black, Michael J.}, |
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booktitle={International Conference on Computer Vision (ICCV)}, |
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year={2019} |
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} |
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@inproceedings{SMPL-X2019, |
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title={Expressive Body Capture: 3D Hands, Face, and Body from a Single Image}, |
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author={Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.}, |
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booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, |
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year={2019} |
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} |
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``` |
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## Contact |
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For any questions or suggestions, please contact: |
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- **Kun Zhao**: [email protected] |
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For more information, follow my Xiaohongshu and Bilibili: |
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https://www.xiaohongshu.com/user/profile/60cdc5360000000001007e33 |
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https://space.bilibili.com/678369952 |
