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OmniGibson: a platform for accelerating Embodied AI research built upon NVIDIA's Omniverse engine. Join our Discord for support: https://discord.gg/bccR5vGFEx

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StanfordVL/OmniGibson

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OmniGibson


Latest Updates

  • [08/04/23] v0.2.0: More assets! 600 pre-sampled tasks, 7 new scenes, and many new objects πŸ“ˆ [release notes]

  • [04/10/22] v0.1.0: Significantly improved stability, performance, and ease of installation πŸ”§ [release notes]


OmniGibson is a platform for accelerating Embodied AI research built upon NVIDIA's Omniverse platform, featuring:

  • πŸ“Έ Photorealistic Visuals and πŸ“ Physical Realism
  • 🌊 Fluid and πŸ‘• Soft Body Support
  • πŸ”οΈ Large-Scale, High-Quality Scenes and 🎾 Objects
  • 🌑️ Dynamic Kinematic and Semantic Object States
  • πŸ€– Mobile Manipulator Robots with Modular βš™οΈ Controllers
  • 🌎 OpenAI Gym Interface

Check out OmniGibson's documentation to get started!

Citation

If you use OmniGibson or its assets and models, please cite:

@inproceedings{
li2022behavior,
title={{BEHAVIOR}-1K: A Benchmark for Embodied {AI} with 1,000 Everyday Activities and Realistic Simulation},
author={Chengshu Li and Ruohan Zhang and Josiah Wong and Cem Gokmen and Sanjana Srivastava and Roberto Mart{\'\i}n-Mart{\'\i}n and Chen Wang and Gabrael Levine and Michael Lingelbach and Jiankai Sun and Mona Anvari and Minjune Hwang and Manasi Sharma and Arman Aydin and Dhruva Bansal and Samuel Hunter and Kyu-Young Kim and Alan Lou and Caleb R Matthews and Ivan Villa-Renteria and Jerry Huayang Tang and Claire Tang and Fei Xia and Silvio Savarese and Hyowon Gweon and Karen Liu and Jiajun Wu and Li Fei-Fei},
booktitle={6th Annual Conference on Robot Learning},
year={2022},
url={https://openreview.net/forum?id=_8DoIe8G3t}
}