@inproceedings{870f41f7ec554e26ba275d7501b7f92c,
title = "MSTC∗: Multi-robot Coverage Path Planning under Physical Constraints",
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.",
author = "Jingtao Tang and Chun Sun and Xinyu Zhang",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 IEEE International Conference on Robotics and Automation, ICRA 2021 ; Conference date: 30-05-2021 Through 05-06-2021",
year = "2021",
doi = "10.1109/ICRA48506.2021.9561371",
language = "英语",
series = "Proceedings - IEEE International Conference on Robotics and Automation",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2518--2524",
booktitle = "2021 IEEE International Conference on Robotics and Automation, ICRA 2021",
address = "美国",
}