考虑环境复杂度的机器人路径双向蚁群规划  

Robot Path Planning Based on Bi-Direction Searching Ant Colony Algorithm Considering Environment Complexity

作　　者：任云晖[1] 贾仙鱼 REN Yun-hui;JIA Xian-yu(Jianghai Polytechnic College,Jiangsu Yangzhou 225101,China;Yangzhou University,Jiangsu Yangzhou 225000,China)

机构地区：[1]江海职业技术学院,江苏扬州225101 [2]扬州大学,江苏扬州225000

出　　处：《机械设计与制造》2023年第6期263-267,共5页Machinery Design & Manufacture

基　　金：2014年江苏省现代教育技术研究十二五规划课题(2014-R-31675)。

摘　　要：为了减少机器人的路径长度、提高路径平滑性,提出了基于配对双向新型蚁群算法的路径规划方法。介绍了栅格环境模型的建立方法;给出了基于改进K-means的环境复杂度聚类方法,实现了以复杂度为标准的环境分区;将环境复杂度作为新型启发信息引入到蚁群算法中,引导蚂蚁选择简单环境区域。借鉴蚂蚁的双向搜索思想,提出了配对双向搜索的新型蚁群算法,并将该算法应用于栅格环境的路径规划。经仿真验证可以看出,与传统蚁群算法、文献[12]算法比,配对双向新型蚁群算法的路径长度最短、拐点数量最少、收敛时迭代次数最少,验证了这里算法在路径规划中的优越性。In order to reduce the path length of robot and improve the path smoothness,a path planning method based on paired bidirectional new ant colony algorithm is proposed.The establishment method of grid environment model is introduced;An environment complexity clustering method based on improved K-means is proposed,and the environment partition based on complexity is realized.The environment complexity is introduced into ant colony algorithm as a new heuristic information to guide ants to select simple environment areas.Based on the idea of two-way search of ants,a new paired two-way search ant colony algorithm is proposed and applied to path planning in grid environment.The simulation results show that compared with the traditional ant colony algorithm and the algorithm in reference[12],the paired two-way new ant colony algorithm has the shortest path length,the least number of inflection points and the least number of iterations during convergence,which verifies the superiority of this algorithm in path planning.

关 键 词：机器人 路径规划 环境复杂度 新型启发信息 配对双向搜索 

分 类 号：TH16[机械工程—机械制造及自动化] TP242[自动化与计算机技术—检测技术与自动化装置]