基于改进混沌蚁群算法的变电站巡检自动引导车路径规划  

Path Planning of Substation Inspection Automated Guided Vehicle Based on Improved Chaotic Ant Colony Algorithm

作　　者：刘云飞 周光远 刘聪 刘闯 刘婧珂 曾杰 鲁彦 杨友 LIU Yunfei;ZHOU Guangyuan;LIU Cong;LIU Chuang;LIU Jingke;ZENG Jie;LU Yan;YANG You(Jingmen Power Supply Company,State Grid Hubei Electric Power Co.,Ltd.,Jingmen 448000,China)

机构地区：[1]国网湖北省电力有限公司荆门供电公司,湖北荆门448000

出　　处：《吉林电力》2024年第5期27-32,52,共7页Jilin Electric Power

摘　　要：针对巡检自动引导车(Automated Guided Vehicle,AGV)在变电站复杂环境中的路径规划问题,提出了一种基于改进混沌蚁群算法的路径规划方式。传统蚁群算法在路径规划过程中存在寻找路径过长、收敛速度过慢和转弯次数过多等问题,因此将混沌理论与蚁群算法相结合,利用混沌算法来优化蚁群算法的初始参数,使该算法具有更快的收敛速度和更强的鲁棒性。同时,针对传统混沌算法不均匀分布和单侧领域内寻优的问题,改进了混沌算法的遍历公式与映射方式,增强了寻优效果。将基于改进混沌蚁群算法的路径规划方法与传统蚁群算法进行对比分析,结果表明改进混沌蚁群算法具有更高的搜索效率和更优质的解。Aiming at the path planning problem of inspection AGV in complex substation environment,a path planning method based on improved chaotic ant colony algorithm is proposed in this paper.Traditional ant colony algorithm has some problems in the process of path planning,including long search path,slow convergence speed and too many turns,so the chaos theory is combined with ant colony algorithm,and the initial parameters of ant colony algorithm are optimized by chaos algorithm to make the algorithm have faster convergence speed and stronger robustness.And chaos theory is used to optimize the initial parameters of ant colony algorithm.At the same time,aiming at the problems of non-uniform distribution and unilateral domain optimization of traditional chaotic algorithm,the ergodic formula and mapping mode of the chaotic algorithm is improved to enhance the optimization effect in this paper.The path planning method based on improved chaos ant colony algorithm is compared and analyzed with that based on traditional ant colony algorithm,and the results show that improved chaos ant colony algorithm has higher searching efficiency and better solution.

关 键 词：变电站 巡检AGV 蚁群算法 路径规划 混沌理论 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TM63[自动化与计算机技术—控制科学与工程]