较大场景下的路径规划研究  

Study on path planning in larger scenarios

作　　者：古宗宝 肖红军[1] GU Zong-Bao;XIAO Hong-jun(Automation School of Foshan University,Foshan 528225,China)

机构地区：[1]佛山科学技术学院,广东佛山528225

出　　处：《山东工业技术》2021年第2期62-68,共7页Journal of Shandong Industrial Technology

摘　　要：随着工业制造自动化技术的不断发展,自动导引运输车(Automated Guided Vehicle,AGV)因其简洁性、安全性、自动化程度高等特点在各领域得到了充分的运用,路径规划作为其中一个重要的环节,广受海内外学者的关注。本文针对常用路径规划算法如A*算法、遗传算法、蚁群算法[1]等,在较大地图上耗时较久的问题,提出了一种基于地图分割的A*算法,并通过仿真实验验证了其有效性和优化性。With the continuous development of industrial manufacturing automation technology,Automated Guided Vehicle(AGV) has been fully used in various fields because of its features of simplicity,safety and high degree of automation.As one of the important links,path planning has been widely paid attention by scholars at home and abroad.In order to solve the problem that common path planning algorithms such as A* algorithm,genetic algorithm and ant colony algorithm [1] take A long time on large maps,this paper proposes A map segmentation based A* algorithm,and its effectiveness and optimization are verified through simulation experiments.

关 键 词：AGV 路径规划 地图分割 A*算法 

分 类 号：TP241.3[自动化与计算机技术—检测技术与自动化装置]