Open Scene Graphs for Open World Object-Goal Navigation
<|reference_start|>Open Scene Graphs for Open World Object-Goal Navigation: 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.<|reference_end|>
@article{loo2024open,
    title={Open Scene Graphs for Open World Object-Goal Navigation},
    author={Joel Loo, Zhanxin Wu, David Hsu},
    journal={arXiv preprint arXiv:2407.02473},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.02473},
    primaryClass={cs.RO}
}