摘要
Map exploration in unknown environments is the key to various robotics applications (e.g., 3D reconstruction, search and rescue). However, finding the optimal path to maximize the environmental coverage is NP-hard. To overcome this problem, this research proposes a dynamic generalized cost-benefit (DGCB) algorithm to explore unknown environments via utilizing submodularity and tree-Structured routing. Moreover, the theoretical guarantees at each time step are proved via submodularity. The experiments show that the proposed method outperforms benchmark methods (e.g., FUEL, GCB, GCB-MST).
原文 | ???core.languages.en_GB??? |
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頁(從 - 到) | 5062-5069 |
頁數 | 8 |
期刊 | IEEE Robotics and Automation Letters |
卷 | 9 |
發行號 | 6 |
DOIs | |
出版狀態 | 已出版 - 1 6月 2024 |