地形
计算机科学
机器人
运动规划
工作量
网格
路径(计算)
螺旋(铁路)
集合(抽象数据类型)
数学优化
势场
算法
模拟
实时计算
分布式计算
人工智能
工程类
数学
计算机网络
地理
操作系统
地图学
地球物理学
程序设计语言
机械工程
地质学
几何学
作者
Jingtao Tang,Chunwen Sun,Xinyu Zhang
标识
DOI:10.48550/arxiv.2108.04632
摘要
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.
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