Collaborative Path Planning Algorithm for Multiple AGVs

Abstract

Aiming at the problem of material distribution in industrial production workshops, this paper proposes a multi AGVs collaborative path planning method based on genetic algorithm (GA) to improve its logistics management level and production efficiency. The improvement of the algorithm is to “explore” as many paths as possible. It uses information entropy to measure the diversity of the group and the constraints within the space to set the rewards and punishments. According to the set cooperation mechanism, it reduces the standby state of the robot without tasks, balances the workload of each robot, and finally realizes the goal of shortening the system running time on the basis of ensuring the safe operation of the system. The advantages and disadvantages of the algorithm are measured by the number of iterations and rewards when the algorithm tends to be stable. The effectiveness of the optimization algorithm is finally proved.