仓储物流机器人拣选路径规划仿真研究

发布时间：2018-01-24 09:13

本文关键词： 仓储物流机器人拣选作业路径规划旅行商问题遗传算法 A*算法　出处：《中北大学》2017年硕士论文　论文类型：学位论文

【摘要】：在电子商务的背景下,仓储物流配送具有“品种多、批量小、批次多、周期短”的特点。随着电子商务的快速发展、顾客对消费体验重视程度的提高以及人力成本的上升,传统的仓储物流技术已经越来越难以适应物流配送的需要,以人工智能技术为支撑的仓储物流机器人技术开始被应用到仓储物流领域,而如何为仓储物流机器人在仓库中进行高效实时的拣选路径规划是迫切需要解决的问题。针对如何实现多仓储物流机器人在拣选作业的过程中进行高效实时的路径规划问题,本文提出一套完整的解决方案。首先,根据仓库以及仓储物流机器人移动的特点建立一个灵活的仓库模型并利用修正的A*算法实现单机器人单拣选点的路径规划。其次,根据批量拣选作业任务的特点,建立了以路径总长度最小为优化目标的旅行商问题的数学模型,然后提出改进的自适应遗传算法解决旅行商问题并与修正A*算法相结合实现单机器人批量拣选的路径规划。再次,在考虑单仓储物流机器人转向时间、货物拣选时间以及多仓储物流机器人的位置冲突等待时间的前提条件下,引入时间代价对A*算法作进一步改进以实现多仓储物流机器人批量拣选路径规划。最后,根据本文提出算法,利用.Net可视化编程技术,建立了一个完整的仓储物流机器人拣选路径规划仿真系统以用来验证本文所提出算法的有效性,并分析了在是否考虑机器人避障的条件下不同机器人数量对多仓储物流机器人批量拣选作业任务完成的时间、平均路径长度以及路径冲突协调的影响。
[Abstract]:Under the background of electronic commerce, warehousing logistics distribution has the characteristics of "variety, small batch, many batches, short cycle". With the rapid development of electronic commerce. With the increase of customer's attention to consumption experience and the increase of manpower cost, the traditional warehousing logistics technology has become more and more difficult to meet the needs of logistics distribution. The technology of warehouse logistics robot supported by artificial intelligence technology has been applied to the field of warehousing logistics. It is urgent to solve the problem of how to carry out efficient and real-time routing planning for warehousing logistics robot in warehouse, aiming at how to realize the efficient and real-time path of multi-warehouse logistics robot in the process of sorting. Path planning. This paper proposes a complete set of solutions. First of all. According to the characteristics of warehouse and warehouse logistics robot mobile, a flexible warehouse model is established, and a modified A* algorithm is used to realize the path planning of single robot picking point. According to the characteristics of batch sorting task, a mathematical model of traveling salesman problem with the minimum path length as the optimization objective is established. Then an improved adaptive genetic algorithm is proposed to solve the traveling salesman problem and combined with the modified A * algorithm to realize the path planning of single robot batch picking. Thirdly, the turning time of single warehouse logistics robot is considered. The cargo picking time and the location conflict waiting time of the multi-warehousing logistics robot are under the premise of the waiting time. Time cost is introduced to further improve the A* algorithm in order to realize bulk routing planning of multi-warehouse logistics robot. Finally, according to the algorithm proposed in this paper, using .Net visual programming technology. A complete routing path planning simulation system for warehouse logistics robot is established to verify the effectiveness of the proposed algorithm. The effects of different number of robots on the completion time, average path length and path conflict coordination of multi-warehouse logistics robots are analyzed.
【学位授予单位】：中北大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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