---
license: cc-by-4.0
task_categories:
- robotics
- reinforcement-learning
language:
- en
tags:
- AMASS
- Retarget
- Robotics
- Humanoid
size_categories:
- 10K<n<100K
---
# Retargeted AMASS for Robotics

## Project Overview

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.

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.

## Dataset Content

This open-source project includes the following:
1. **Retargeted Motions**: Motion files retargeted from AMASS to various robot models.
   - **bxirobotics elf2**: 

     The retargeted motions for the bxirobotics elf2 robot are generated based on the official open-source model: 

     https://github.com/bxirobotics/robot_models/tree/main/elf2_dof25

     The joint positions is not limited, you should limit them during use.

     data shape：[-1,32]

     ​		0:3 	root world position

     ​		3:7	 root quaternion rotation, order: xyzw

     ​		7:32   joint positions

     joint order:

     ```txt
        l_hip_z_joint, 
        l_hip_x_joint, 
        l_hip_y_joint, 
        l_knee_y_joint, 
        l_ankle_y_joint, 
        l_ankle_x_joint, 
        r_hip_z_joint, 
        r_hip_x_joint, 
        r_hip_y_joint, 
        r_knee_y_joint, 
        r_ankle_y_joint, 
        r_ankle_x_joint,  
        waist_z_joint, 
        waist_x_joint, 
        waist_y_joint, 
        l_shld_y_joint, 
        l_shld_x_joint, 
        l_shld_z_joint, 
        l_elb_y_joint, 
        l_elb_z_joint, 
        r_shld_y_joint, 
        r_shld_x_joint, 
        r_shld_z_joint, 
        r_elb_y_joint, 
        r_elb_z_joint
     ```

     

2. **Usage Examples**: Code examples and tutorials on how to use the retargeted data.

   ./visualize.py

   

3. **License Files**: Original license information for each sub-dataset within AMASS.

   

## License

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:
- **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.
- **Attribution Requirements**: Properly cite this work and the original authors and sources of the AMASS dataset and its sub-datasets.

For detailed license information, please refer to the `LICENSE` file in this project.



## Acknowledgments

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.

## Citation

If you use the data or code from this project, please cite this work and relevant papers for AMASS and SMPL-X:
```bibtex
@misc{Retargeted_AMASS_R,
  title={Retargeted AMASS for Robotics},
  author={Kun Zhao},
  url={https://huggingface.co/datasets/fleaven/Retargeted_AMASS_for_robotics}
}

@inproceedings{AMASS2019,
  title={AMASS: Archive of Motion Capture as Surface Shapes},
  author={Mahmood, Naureen and Ghorbani, Nima and Troje, Nikolaus F. and Pons-Moll, Gerard and Black, Michael J.},
  booktitle={International Conference on Computer Vision (ICCV)},
  year={2019}
}

@inproceedings{SMPL-X2019,
  title={Expressive Body Capture: 3D Hands, Face, and Body from a Single Image},
  author={Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2019}
}
```

## Contact

For any questions or suggestions, please contact:
- **Kun Zhao**: fleaven@hotmail.com