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A Hierarchical Region-Based Approach for Efficient Multi-Robot Exploration

17 March 2025
Di Meng
Tianhao Zhao
Chaoyu Xue
Jun Wu
Qiuguo Zhu
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Abstract

Multi-robot autonomous exploration in an unknown environment is an important application inthis http URLexploration methods only use information around frontier points or viewpoints, ignoring spatial information of unknown areas. Moreover, finding the exact optimal solution for multi-robot task allocation is NP-hard, resulting in significant computational time consumption. To address these issues, we present a hierarchical multi-robot exploration framework using a new modeling method called RegionGraph. The proposed approach makes two main contributions: 1) A new modeling method for unexplored areas that preserves their spatial information across the entire space in a weighted graph called RegionGraph. 2) A hierarchical multi-robot exploration framework that decomposes the global exploration task into smaller subtasks, reducing the frequency of global planning and enabling asynchronous exploration. The proposed method is validated through both simulation and real-world experiments, demonstrating a 20% improvement in efficiency compared to existing methods.

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@article{meng2025_2503.12876,
  title={ A Hierarchical Region-Based Approach for Efficient Multi-Robot Exploration },
  author={ Di Meng and Tianhao Zhao and Chaoyu Xue and Jun Wu and Qiuguo Zhu },
  journal={arXiv preprint arXiv:2503.12876},
  year={ 2025 }
}
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