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货到人拣选系统多阶段可穿行多AGV路径规划
引用本文:李腾,丁佩佩,刘金芳.货到人拣选系统多阶段可穿行多AGV路径规划[J].系统仿真学报,2022,34(7):1512-1523.
作者姓名:李腾  丁佩佩  刘金芳
作者单位:1.哈尔滨商业大学 管理学院,黑龙江 哈尔滨 1500282.岭南师范学院 计算机与智能教育学院,广东 湛江 524048
基金项目:国家科技支撑计划(2018YFB1402500);黑龙江省自然科学基金(LH2021G014);湛江市科技计划(2021B01045)
摘    要:针对货到人拣选系统大规模多AGV(automated guided vehicle)路径规划中由于转弯和避障导致行驶时间增长的问题,考虑空载AGV可穿行货架建立以任务完成时间最短为目标的路径规划模型,并通过改进A*算法对该问题进行求解。对AGV运行阶段进行划分,在A*算法中引入转弯惩罚值减少转弯次数,利用避障等待时间设置避障优先级。仿真实例结果表明考虑转弯和避障的可穿行货架路径规划方法能够降低任务完成时间和行走路径长度,在提高拣选系统作业效率方面具有参考价值。

关 键 词:货到人拣选系统  多AGV路径规划  可穿行  转弯  避障策略  A*算法  
收稿时间:2021-10-19

Multi-Stage Multi-AGV Path Planning with Walk under Shelves for Robotic Mobile Fulfillment Systems
Teng Li,Peipei Ding,Jinfang Liu.Multi-Stage Multi-AGV Path Planning with Walk under Shelves for Robotic Mobile Fulfillment Systems[J].Journal of System Simulation,2022,34(7):1512-1523.
Authors:Teng Li  Peipei Ding  Jinfang Liu
Institution:1.Management School, Harbin University of Commerce, Harbin 150028, China2.School of Computer and AI Education, LingNan Normal University, Zhanjiang 524048, China
Abstract:Aiming at the problem of increasing travel time due to turning and obstacle avoidance in robotic mobile fulfillment systems(RMFS) with large-scale multi-AGV path planning, a path planning model with the shortest task completion time is established. A path planning model considering no-load AGV that can pass through the shelf is proposed, and the model is solved by an improving A* algorithm. The AGV operation stage is divided, an turning penalty value is introduced into the A* algorithm to reduce the turning times, and the obstacle avoidance priority with the obstacle avoidance waiting time is set. The simulation results show that the new path planning method considering turning and obstacle avoidance can reduce task completion time and travel path length, and improve order picking efficiency of the warehouse of a distribution center.
Keywords:RMFS (robotic mobile fulfillment systems)  multi-AGVs path planning  walk under shelves  turning time  obstacle avoidance strategy  A* algorithm  
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