A Multi-Robot Balanced Coverage Path Planning Strategy for Patrol Missions

Abstract

This paper presents a multi-robot balanced coverage path planning (MCPP) strategy for patrol missions. In the entire path-based multi-robot path assignment problem, conventional studies allow path redundancy and divide the path itself according to the number of robots. However, more collisions between robots can happen due to path redundancy. Therefore, a strategy of equally assigning a path to each robot is proposed without path redundancy. First, given a map, a graph for robot movement is constructed. A problem similar to the traveling salesman problem is solved in the graph. As a result, an entire path is generated. Subsequently, unique paths are extracted from the whole path and combined according to the number of robots. Since the combined paths are not evenly divided, the paths are compensated in a way that minimizes the maximum length of ones. Simulations were performed by varying the number of robots. Through performance comparison, it showed that the paths were divided well using the proposed approach.