Abstract: In order to solve the problem of warehouse mobile robot path planning with high efficiency and real time in the process of picking operation, an effective method was proposed. First of all, according to the demand of order picking, a flexible storage space model was made and the task of order picking was described. Secondly, according to the characteristics of the batch picking task, the mathematical model of the Traveling Salesman Problem (TSP) was established. Once again, an improved adaptive genetic algorithm was proposed to solve the TSP. Finally, under the premise of considering the cost of the path turning angle, an improved A*algorithm combined with the improved adaptive genetic algorithm was used to solve the problem of batch picking path planning. The simulation results show that the method which meets the requirement of batch picking path planning of warehouse mobile robot is of faster convergence speed, less average path length and less algorithm running time.

Key words:  mobile robot, batch picking, path planning, traveling salesman problem (TSP), genetic algorithm, A* algorithm