  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.
