Coverage path planning is a major application for mobile robots, which requires robots to move along a planned path to cover the entire map. For large-scale tasks, coverage path planning benefits greatly from multiple robots. In this paper, we describe Turn-minimizing Multirobot Spanning Tree Coverage Star(TMSTC*), an improved multirobot coverage path planning (mCPP) algorithm based on the MSTC*. Our algorithm partitions the map into minimum bricks as tree's branches and thereby transforms the problem into finding the maximum independent set of bipartite graph. We then connect bricks with greedy strategy to form a tree, aiming to reduce the number of turns of corresponding circumnavigating coverage path. Our experimental results show that our approach enables multiple robots to make fewer turns and thus complete terrain coverage tasks faster than other popular algorithms.
翻译:覆盖路径规划是移动机器人的一个主要应用程序, 它要求机器人在计划路径上移动以覆盖整个地图。 对于大型任务, 覆盖路径规划会大大受益于多个机器人。 在本文中, 我们描述以 MSTC * 为基础改进多机器人覆盖路径规划。 我们的算法将地图分割成最小砖块作为树枝, 从而将问题转化成找到最大的独立双叶图集。 然后我们将砖块与贪婪策略连接到树上, 目的是减少相应的环绕覆盖路径的旋转次数。 我们的实验结果表明, 我们的方法可以让多机器人进行更少的旋转, 从而完成比其他常用算法更快的地形覆盖任务 。