Warehouse Multi-Robot Picking Task Planning Based on Strong Reproduction Genetic Algorithm
In order to reduce the travel path of intelligent warehouse picking robot,a multi robot picking task planning method based on strong propagation genetic algorithm is proposed.The hybrid control of multi robot system and the operation process of intelligent warehouse are introduced,and the grid environment model of intelligent warehouse is established.In order to reduce the length of robot travel path,an optimization model of picking task planning is established.The reproductive ability of chromo-somes is defined in genetic algorithm.According to the reproductive ability,chromosomes are divided into traditional group and reinforcement group;The traditional population uses the traditional operation mode to maintain its strong reproductive ability;The methods of strong breeding crossover and mutation were put forward,so as to forcibly improve the reproductive ability of the population.Strong propagation genetic algorithm is applied to intelligent warehouse picking task planning.The robot path length of traditional genetic algorithm task planning is 63.0103,and the path length of strong propagation genetic algorithm task plan-ning is 55.9496,which is 11.21％less than that of traditional algorithm,and the convergence speed of strong propagation ge-netic algorithm is higher than that of traditional genetic algorithm.The simulation results verify the superiority of strong propaga-tion genetic algorithm in picking task planning of intelligent warehouse.
万方数据
维普
