# Acknowledgements

**robosuite** is built on the [MuJoCo engine](http://www.mujoco.org/) with the Python interfaces provided by [mujoco](https://github.com/deepmind/mujoco). We would like to thank members of the [Stanford People, AI, & Robots (PAIR) Group](http://pair.stanford.edu/) and [UT Robot Perception and Learning Lab](http://rpl.cs.utexas.edu/) for their support and feedback to this project. In particular, the following people have made their contributions in different stages of this project:

- [Jiren Zhu](https://github.com/jirenz), [Joan Creus-Costa](https://github.com/jcreus) (robosuite v0.3)
- [Jim (Linxi) Fan](http://jimfan.me/), [Zihua Liu](https://www.linkedin.com/in/zihua-liu/), [Orien Zeng](https://www.linkedin.com/in/orien-zeng-054589b6/), [Anchit Gupta](https://www.linkedin.com/in/anchitgupta/) ([Surreal](http://surreal.stanford.edu/) experiments)
- [Michelle Lee](http://stanford.edu/~mishlee/), [Rachel Gardner](https://www.linkedin.com/in/rachel0/) (controller implementations)
- [Danfei Xu](https://cs.stanford.edu/~danfei/) (placement initializer)
- [Andrew Kondrich](http://www.andrewkondrich.com/), [Jonathan Booher](https://web.stanford.edu/~jaustinb/) (domain randomization)
- [Albert Tung](https://www.linkedin.com/in/albert-tung3/) (demonstration collection)
- [Divyansh Jha](https://github.com/divyanshj16), [Fei Xia](http://fxia.me/) (robosuite v1.3 renderers)

We wholeheartedly welcome the community to contribute to our project through issues and pull requests. New contributors will be added to the list above.