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arXiv · 2407.02473

Open Scene Graphs for Open World Object-Goal Navigation

Joel Loo·Zhanxin Wu·David Hsu
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Abstract

How can we build robots for open-world semantic navigation tasks, like searching for target objects in novel scenes? While foundation models have the rich knowledge and generalisation needed for these tasks, a suitable scene representation is needed to connect them into a complete robot system. We address this with Open Scene Graphs (OSGs), a topo-semantic representation that retains and organises open-set scene information for these models, and has a structure that can be configured for different environment types. We integrate foundation models and OSGs into the OpenSearch system for Open World Object-Goal Navigation, which is capable of searching for open-set objects specified in natural language, while generalising zero-shot across diverse environments and embodiments. Our OSGs enhance reasoning with Large Language Models (LLM), enabling robust object-goal navigation outperforming existing LLM approaches. Through simulation and real-world experiments, we validate OpenSearch's generalisation across varied environments, robots and novel instructions.

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Joel Loo, Zhanxin Wu, David Hsu. 2024-07-02. Open Scene Graphs for Open World Object-Goal Navigation. https://arxiv.org/abs/2407.02473

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