README.md

---
license: gpl-3.0
pipeline_tag: robotics
---


![](doc/img/logo/logo8.png)

---

# Rofunc: The Full Process Python Package for Robot Learning from Demonstration and Robot Manipulation

> **Repository address: [https://github.com/Skylark0924/Rofunc](https://github.com/Skylark0924/Rofunc)** <br>
> **Documentation: [https://rofunc.readthedocs.io/](https://rofunc.readthedocs.io/)**


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    <tr>
        <td><img src="doc/img/task_gif/CURIQbSoftHandSynergyGraspSpatulaRofuncRLPPO.gif"></td>
        <td><img src="doc/img/task_gif/CURIQbSoftHandSynergyGraspPower_drillRofuncRLPPO.gif"></td>
        <td><img src="doc/img/task_gif/CURIQbSoftHandSynergyGraspPhillips_Screw_DriverRofuncRLPPO.gif"></td>
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    <tr>
        <td><img src="doc/img/task_gif/HumanoidFlipRofuncRLAMP.gif"></td>
        <td><img src="doc/img/task_gif/HumanoidDanceRofuncRLAMP.gif"></td>
        <td><img src="doc/img/task_gif/HumanoidRunRofuncRLAMP.gif"></td>
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        <td><img src="doc/img/task_gif/BiShadowHandLiftUnderarmRofuncRLPPO.gif"></td>
        <td><img src="doc/img/task_gif/BiShadowHandDoorOpenOutwardRofuncRLPPO.gif"></td>
        <td><img src="doc/img/task_gif/BiShadowHandSwingCupRofuncRLPPO.gif"></td>
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Rofunc package focuses on the **Imitation Learning (IL), Reinforcement Learning (RL) and Learning from Demonstration (LfD)** for **(Humanoid) Robot Manipulation**. It provides valuable and convenient python functions, including
_demonstration collection, data pre-processing, LfD algorithms, planning, and control methods_. We also provide an
`IsaacGym` and `OmniIsaacGym` based robot simulator for evaluation. This package aims to advance the field by building a full-process
toolkit and validation platform that simplifies and standardizes the process of demonstration data collection,
processing, learning, and its deployment on robots.

## Citation

If you use rofunc in a scientific publication, we would appreciate citations to the following paper:

```
@software{liu2023rofunc, 
          title = {Rofunc: The Full Process Python Package for Robot Learning from Demonstration and Robot Manipulation},
          author = {Liu, Junjia and Dong, Zhipeng and Li, Chenzui and Li, Zhihao and Yu, Minghao and Delehelle, Donatien and Chen, Fei},
          year = {2023},
          publisher = {Zenodo},
          doi = {10.5281/zenodo.10016946},
          url = {https://doi.org/10.5281/zenodo.10016946},
          dimensions = {true},
          google_scholar_id = {0EnyYjriUFMC},
}
```
> [!WARNING]
> **If our code is found to be used in a published paper without proper citation, we reserve the right to address this issue formally by contacting the editor to report potential academic misconduct!**
> 
> **如果我们的代码被发现用于已发表的论文而没有被恰当引用，我们保留通过正式联系编辑报告潜在学术不端行为的权利。**