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SPEAR: A Simulator for Photorealistic Embodied AI Research

Interactive simulators are becoming powerful tools for training embodied agents, but existing simulators suffer from limited content diversity, physical interactivity, and visual fidelity. We address these limitations by introducing SPEAR: A Simulator for Photorealistic Embodied AI Research. To create our simulator, we worked closely with a team of professional artists for over a year to construct 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each of our environments features detailed geometry, photorealistic materials, and a unique floor plan and object layout designed by a professional artist, i.e., we do not rely on remixing existing layouts to create additional content. Our environments are implemented as Unreal Engine assets, and we provide an OpenAI Gym interface for interacting with the environments via Python.

The code and assets in this repository are released under an MIT License and a CC0 License respectively.

Citation

If you find SPEAR useful in your research, please cite this repository as follows:

@misc{spear,
    author       = {Mike Roberts AND Rachith Prakash AND Renhan Wang AND Quentin Leboutet AND
                    Stephan R. Richter AND Stefan Leutenegger AND Rui Tang AND Matthias
                    M{\"u}ller AND German Ros AND Vladlen Koltun},
    title        = {{SPEAR}: {A} Simulator for Photorealistic Embodied AI Research},
    howpublished = {\url{http://github.com/spear-sim/spear}}
}

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