# Overview

<p align="center">
  <img width="95.0%" src="../images/mimicgen.gif">
</p>

This repository contains the official release of data generation code, simulation environments, and datasets for the [CoRL 2023](https://www.corl2023.org/) paper "MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations". 

Website: [https://mimicgen.github.io](https://mimicgen.github.io)

Paper: [https://arxiv.org/abs/2310.17596](https://arxiv.org/abs/2310.17596)

Documentation: [https://mimicgen.github.io/docs/introduction/overview.html](https://mimicgen.github.io/docs/introduction/overview.html)

<div class="admonition note">
<p class="admonition-title">Note</p>

For business inquiries, please submit this form: [NVIDIA Research Licensing](https://www.nvidia.com/en-us/research/inquiries/).

</div>

## Useful Documentation Links

Some helpful suggestions on useful documentation pages to view next:

- [Getting Started](https://mimicgen.github.io/docs/tutorials/getting_started.html)
- [Launching Several Data Generation Runs](https://mimicgen.github.io/docs/tutorials/launching_several.html)
- [Reproducing Published Experiments and Results](https://mimicgen.github.io/docs/tutorials/reproducing_experiments.html)
- [Data Generation for Custom Environments](https://mimicgen.github.io/docs/tutorials/datagen_custom.html)
- [Overview of MimicGen Codebase](https://mimicgen.github.io/docs/modules/overview.html)

## Troubleshooting

Please see the [troubleshooting](https://mimicgen.github.io/docs/miscellaneous/troubleshooting.html) section for common fixes, or submit an issue on our github page.

## License

The code is released under the [NVIDIA Source Code License](https://github.com/NVlabs/mimicgen/blob/main/LICENSE) and the datasets are released under [CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/).

## Citation

Please cite [the MimicGen paper](https://arxiv.org/abs/2310.17596) if you use this code in your work:

```bibtex
@inproceedings{mandlekar2023mimicgen,
    title={MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations},
    author={Mandlekar, Ajay and Nasiriany, Soroush and Wen, Bowen and Akinola, Iretiayo and Narang, Yashraj and Fan, Linxi and Zhu, Yuke and Fox, Dieter},
    booktitle={7th Annual Conference on Robot Learning},
    year={2023}
}
```