Year: 2021
Type: preprint
Abstract: 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.
Source: arXiv (Cornell University)
Authors: Tang, Jingtao, Sun, Chun, Zhang, Xinyu
Institution: East China Normal University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3191452671