仓库多机器人拣选任务的强繁殖遗传算法规划  

Warehouse Multi-Robot Picking Task Planning Based on Strong Reproduction Genetic Algorithm

作　　者：高林国[1] 于薇[1] 占华林 GAO Linguo;YU Wei;ZHAN Hualin(Jiangxi Arts&Ceramics Technology Institute,Jiangxi Jingdezhen 333000,China;Jiangxi Science and Technology Normal University,Jiangxi Nanchang 330013,China)

机构地区：[1]江西陶瓷工艺美术职业技术学院,江西景德镇333000 [2]江西科技师范大学,江西南昌330013

出　　处：《机械设计与制造》2024年第12期222-226,共5页Machinery Design & Manufacture

基　　金：江西省教育厅科学技术研究项目(2019JX081)。

摘　　要：为了减小智能仓库拣选机器人的行驶路径,提出了基于强繁殖遗传算法的多机器人拣选任务规划方法。介绍了多机器人系统的混合式控制与智能仓库运行流程,建立了智能仓库的栅格环境模型。以减小机器人行驶路径长度为目标,建立了拣选任务规划的优化模型。在遗传算法中定义了染色体的繁殖能力,根据繁殖能力将染色体分为传统群和加强群;传统群使用传统提出操作方式,维持其较强的繁殖能力;提出了强繁殖交叉和变异方式,从而强制提高加强群的繁殖能力。将强繁殖遗传算法应用于智能仓库拣选任务规划,传统遗传算法任务规划的机器人路径长度为63.0103,强繁殖遗传算法任务规划的路径长度为55.9496,比传统算法减少了11.21%,且强繁殖遗传算法的收敛速度高于传统遗传算法。仿真结果验证了强繁殖遗传算法在智能仓库拣选任务规划中的优越性。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 chromosomes 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 planning is 55.9496,which is 11.21%less than that of traditional algorithm,and the convergence speed of strong propagation genetic algorithm is higher than that of traditional genetic algorithm.The simulation results verify the superiority of strong propagation genetic algorithm in picking task planning of intelligent warehouse.

关 键 词：智能仓库 任务规划 强繁殖遗传算法 加强群 繁殖能力 

分 类 号：TH16[机械工程—机械制造及自动化] TP242[自动化与计算机技术—检测技术与自动化装置]