基于改进智能算法的机器人路径规划  

Robot Path Planning Based on Improved Intelligent Algorithm

作　　者：姜子棋 闫帅 周航[1] 薛钰婷 蔡方儿 JIANG Ziqi;YAN Shuai;ZHOU Hang;XUE Yuting;CAI Fanger(College of civil aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China;Beijing Institute of Computer Technology and Applications,Beijing 100854,China)

机构地区：[1]南京航空航天大学民航学院,南京211106 [2]北京计算机技术及应用研究所,北京100854

出　　处：《武汉理工大学学报（交通科学与工程版）》2023年第4期629-633,共5页Journal of Wuhan University of Technology（Transportation Science & Engineering）

摘　　要：文中提出一种改进蚁群算法求解路径规划问题.建立路径距离与转弯总角度的多目标函数,提高规划路径的平滑性和安全性.设计改进启发函数,引入障碍排除机制,提高优质节点的启发性.考虑优质孙节点与目标点距离,提高蚁群算法的全局搜索能力.引入防死锁机制,并记录临时不可选点,避免蚂蚁重复陷入障碍包围.采用改进节点信息素更新规则,提高算法的运行效率.通过不同密度随机障碍实验,证明提出改进蚁群算法的正确性和优越性.结果表明:对比蚁群算法,改进算法在路径长度、转弯总角度上分别提高11.14%和54.26%.An improved ant colony algorithm was proposed to solve the path planning problem.The multi-objective function of path distance and total turning angle was established to improve the smoothness and safety of the planned path.Secondly,the heuristic function was designed and improved,and the obstacle elimination mechanism was introduced to improve the heuristic of high-quality nodes.Considering the distance between high-quality grandson nodes and target points,the global search ability of ant colony algorithm was improved.Anti-deadlock mechanism was introduced,and temporary non-optional points were recorded to prevent ants from falling into obstacles repeatedly.Improved pheromone updating rules were adopted to improve the efficiency of the algorithm.Finally,the correctness and superiority of the improved ant colony algorithm were proved by random obstacle experiments with different densities.The results show that compared with the ant colony algorithm,the improved algorithm improves the path length and the total turning angle by 11.14%and 54.26%respectively.

关 键 词：障碍排除 防死锁 目标距离 节点信息素 蚁群算法 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]