Complete Coverage Path Planning for Industrial Mobile Robots

Abstract

Due to the increase in labor costs and the popularization of intelligent factories, there are more and more mobile robots replacing human resources in large places such as factories, shopping malls, and hospitals. However, these places have a large number of obstacles composed of special materials such as glass and grids. The map constructed by the existing technology is flawed, so using the traditional complete coverage algorithm in the obstacle area will also be planned out of the path, burying security risks. Aiming at the problems in the existing methods, this paper proposes a complete coverage path planning algorithm for custom regions based on the idea of the cellular decomposition method. Convex quadrilaterals are selected as a subregion. The baseline offset method is used to calculate the waypoints. The greedy algorithm is used to calculate the connection cost of all sub-regions. The lowest-cost cleaning sequence and the order of waypoints in the sub-regions are selected, and all waypoints are summarized. The target points are published based on the ROS (Robot Operating System) navigation stack to complete the complete coverage path planning. This method effectively standardizes the operation area of the robot, optimizes the number of turns in the cell, and reduces the time cost. The mobile robot experiments in the factory show that the method has high security and coverage.