mlsanityData to 7 Oct 2026

MSTC*:Multi-robot Coverage Path Planning under Physical Constraints

arXiv 2108.04632 ↗First posted 10 Aug 2021cs.ROcited by 9

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Abstract (arXiv)

For large-scale tasks, coverage path planning (CPP) can benefit greatly from multiple robots. In this paper, we present an efficient algorithm MSTC* for multi-robot coverage path planning (mCPP) based on spiral spanning tree coverage (Spiral-STC). Our algorithm incorporates strict physical constraints like terrain traversability and material load capacity. We compare our algorithm against the state-of-the-art in mCPP for regular grid maps and real field terrains in simulation environments. The experimental results show that our method significantly outperforms existing spiral-STC based mCPP methods. Our algorithm can find a set of well-balanced workload distributions for all robots and therefore, achieve the overall minimum time to complete the coverage.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Aug 2021.

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Citing papers per year: 2022: 1; 2023: 2; 2024: 3; 2025: 0; 2026: 3.

9 papers.