Unified robot environment framework supporting multiple tensor and simulation backends
Project description
UniEnv
Framework unifying robot environments and data APIs. UniEnv provides an universal interface for robot actors, sensors, environments, and data.
Tensor library cross-backend Support
UniEnv supports multiple tensor backends with zero-copy translation layers through the DLPack protocol, and allows you to use the same abstract compute backend interface to write custom data transformation layers, environment wrappers and other utilities. This is powered by the XBArray package.
Universal Robot Environment Interface
UniEnv supports diverse simulation environments and real robots, built on top of the abstract environment / world interface. This allows you to reuse code across different sim and real robots.
Universal Robot Data Interface
UniEnv provides a universal data interface for accessing robot data through the abstract BatchBase interface. We also provide a utility ReplayBuffer for saving data from various environments with diverse data format support, including hdf5, memory-mapped torch tensors, and others.
Installation
Install the package with pip
pip install unienv
You can install optional dependencies such as gymnasium (for Gymnasium-compatible environments), dev, or video by running
pip install unienv[gymnasium,video]
Cite
If you use UniEnv in your research, please cite it as follows:
@software{cao_unienv,
author = {Cao, Yunhao AND Fang, Kuan},
title = {{UniEnv: Unifying Robot Environments and Data APIs}},
year = {2025},
month = oct,
url = {https://github.com/UniEnvOrg/UniEnv},
license = {MIT}
}
Acknowledgements
The idea of this project is inspired by Gymnasium and its predecessor OpenAI Gym. This library is impossible without the great work of DataAPIs Consortium and their work on the Array API Standard. The zero-copy translation layers are powered by the DLPack project.
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