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[NeurIPS 2024] SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation

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SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation

SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation
Hang Yin*, Xiuwei Xu* $^\dagger$, Zhenyu Wu, Jie Zhou, Jiwen Lu$^\ddagger$

* Equal contribution $\dagger$ Project leader $\ddagger$ Corresponding author

We propose a zero-shot object-goal navigation framework by constructing an online 3D scene graph to prompt LLMs. Our method can be directly applied to different kinds of scenes and categories without training.

News

  • [2024/09/26]: SG-Nav is accepted to NeurIPS 2024!

Demo

Scene1:

demo

Scene2:

demo

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Method

Method Pipeline: overview

Getting Started

For environment setup and dataset preparation, please follow:

For evaluation, please follow:

Code Structure

TODO.

Citation

@article{yin2024sgnav, 
      title={SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation}, 
      author={Hang Yin and Xiuwei Xu and Zhenyu Wu and Jie Zhou and Jiwen Lu},
      journal={arXiv preprint arXiv},
      year={2024}
}

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[NeurIPS 2024] SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation

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