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基于遗传算法的C烟厂AGV路径规划研究

发布时间:2018-07-31 18:04
【摘要】:随着国内经济的迅速增长,企业规模不断扩大,生产效率的不断提高,土地资源短缺的限制,物流自动化已成为国内众多企业关注的热点。AGV作为现代物流系统中重点的组织成部分,其应用也越来越广泛,AGV比较贵重,如果使用不合理,会造成严重的浪费,AGV的路径问题一直是研究的重点。本文以AGV小车为研究对象,对其进行路径规划,以提高其运行使用效率。论文首先提出了研究背景及意义,概述了AGV路径规划国内外研究发展现状,并对相关理论进行了阐述,对AGV路径规划算法进行了研究分析,通过对各种算法的优缺点简单对比,最终选择遗传算法作为AGV路径规划的求解算法。其次,以单AGV为研究对象,在运行环境条件已知的情况下,以最短路为目标建立数学模型,运用遗传算法对AGV进行路径规划,并借助MATLAB编程进行仿真,通过仿真结果对算法的可行性进行了分析。再次,在单AGV路径规划研究的基础上,用停车等待或避开占用路径寻找次短路的方法,对多AGV进行路径规划研究,为多台AGV规划出无碰撞、协调的路径。还对AGV小车的任务分配、车辆管理进行约束,制定了优先级的标准,并参照交通规则法制定适当约束AGV小车的交通规则法,对利用规则无法规避的冲突问题,提出了解决问题的策略,从而保证多AGV能在系统中协调运行。最后,对C烟厂辅料库的现状进行分析,将路径规划方法与实际相结合,通过产能及需求分析计算出所需要AGV小车的台数,并按照前面设计的规划方法及算法对多AGV进行路径规划,并以某一时刻为例,为系统内每台小车选择路径,以分析各AGV小车在运行过程中可能出现的碰撞问题,如何利用已制定的规划策略规则对碰撞问题进行检测,如何规避碰撞问题,从而实现多AGV的路径规划。通过本文对AGV路径规划的研究思路,尤其是对遗传算法及MATLAB软件的应用,并结合实例将设计的规划方法应用于实际,为C烟厂辅料库输送系统中AGV的路径规划提供了一种可行性的方法,对移动机器人的路径规划具有较好的实用参考价值。
[Abstract]:With the rapid growth of domestic economy, the scale of enterprises is expanding, the efficiency of production has been improved, and the shortage of land resources has been restricted. Logistics automation has become the focus of attention of many domestic enterprises. AGV, as a key organization in modern logistics system, is becoming more and more widely used, and its application is more and more valuable. If it is not reasonable to use, The path problem which will cause serious waste of AGV is always the focus of research. In this paper, AGV trolley is taken as the research object, and its path planning is carried out to improve its running efficiency. Firstly, the paper puts forward the research background and significance, summarizes the current research and development of AGV path planning at home and abroad, and expounds the relevant theories, and analyzes the algorithm of AGV path planning, and simply compares the advantages and disadvantages of various algorithms. Finally, genetic algorithm is chosen as the solution algorithm of AGV path planning. Secondly, taking the single AGV as the research object, taking the shortest path as the target, the mathematical model is established under the condition of known running environment, and the path planning of AGV is carried out by using genetic algorithm, and the simulation is carried out by MATLAB programming. The feasibility of the algorithm is analyzed by simulation results. Thirdly, on the basis of the research of single AGV path planning, using the method of parking waiting or avoiding the occupation path to find the secondary short circuit, the path planning of multiple AGV is carried out, and the collision-free and coordinated path is planned for multiple AGV. In addition, the task assignment and vehicle management of AGV vehicle are restricted, and the priority criterion is established. According to the traffic rules method, the traffic rules that restrict the AGV car are formulated, and the conflicts that can not be avoided by using the rules are solved. A solution to the problem is proposed to ensure the coordinated operation of multiple AGV in the system. Finally, the status quo of C cigarette factory auxiliary material storehouse is analyzed, the path planning method is combined with practice, and the number of AGV vehicles needed is calculated by capacity and demand analysis. According to the planning method and algorithm designed before, the path planning of multiple AGV is carried out, and taking a certain time as an example, the path is selected for each vehicle in the system, in order to analyze the collision problem that may occur in the running process of each AGV car. How to detect the collision problem by using the planning policy rules, how to avoid the collision problem, and how to realize the path planning of multiple AGV. Through the research of AGV path planning, especially the application of genetic algorithm and MATLAB software, the design method is applied to practice. It provides a feasible method for the path planning of AGV in the transportation system of auxiliary material storehouse in C cigarette factory, and has a good practical reference value for the path planning of mobile robot.
【学位授予单位】:昆明理工大学
【学位级别】:硕士
【学位授予年份】:2015
【分类号】:TP18

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