Simultaneous Optimization of Task Allocation and Route Planning for Multiple Mobile Robots

Multiple automated guided vehicles are used for automatic transportation. It is necessary to generate a conflict-free routing and task assignment that can avoid the collisions and interference among AGVs without congestion. This paper presents a simultaneous optimization method to determine the task assignment and the conflict-free route that can minimize the total transportation time. We propose the following two task allocation methods: one is an empirical method based on the Manhattan distance between AGV and the starting and ending nodes of tasks. The second one is a simultaneous optimization method for task allocation and path planning using a genetic algorithm. Computational experiments are conducted to show the effectiveness of the proposed method in terms of the reduction of the total traveling distance and the reduction of computation time with less computational effort.