栅格环境下机器人路径的复合启发蚁群规划  

Robot Path Planning Based on Composite Heuristic Information Ant Colony Algorithm Under Grid Environment

作　　者：龙珊珊[1] 高倩 高曼曼 LONG Shan-shan;GAO Qian;GAO Man-man(Shijiazhuang Institute of Technology,Hebei Shijiazhuang 050000,China)

机构地区：[1]石家庄理工职业学院,河北石家庄050000

出　　处：《机械设计与制造》2022年第9期295-299,共5页Machinery Design & Manufacture

基　　金：河北省教育厅资助项目(QN2021408)。

摘　　要：为了减小机器人的工作路径长度、提高路径规划的效率,提出了基于复合启发信息蚁群算法的栅格环境下路径规划方法。介绍了栅格模型建立方法和传统蚁群算法原理,分析了传统蚁群算法的缺陷。以待选栅格矢量与目标栅格矢量间夹角为基础,提出了两种启发信息。经分析,启发信息1具有更大的搜索范围,启发信息2具有更强的搜索方向性。将启发信息1和启发信息2以动态变化的方式融入到蚁群算法中,得到了复合启发信息蚁群算法。在(30×30)规模的栅格环境中进行仿真验证,复合启发信息蚁群算法的路径长度、迭代次数均小于传统蚁群算法和文献[11]参数优化蚁群算法,以上结果证明复合启发信息蚁群算法规划的路径质量更好、规划效率更高。In order to reduce the working path length of robot and improve the efficiency of path planning,this paper proposes a path planning method based on composite heuristic information ant colony algorithm in grid environment.The grid model build⁃ing method and the principle of traditional ant colony algorithm are introduced,and analyzes the defects of traditional ant colo⁃ny algorithm.Based on the angle between the selected grid vector and the target grid vector,two kinds of heuristic information are proposed.After analysis,heuristic information 1 has a larger search scope,and heuristic information 2 has a stronger search direction.Heuristic information 1 and heuristic information 2 are integrated into the ant colony algorithm in a dynamic way,and the compound heuristic information ant colony algorithm is obtained.The simulation clarifying at(30×30)scale simulation environment is executed.The simulation results show that the path length and the number of iterations of the composite heuristic information ant colony algorithm are less than those of the traditional ant colony algorithm and the parameter optimization ant colony algorithm in reference[11].The above results show that the composite heuristic information ant colony algorithm has better path quality and higher planning efficiency.

关 键 词：路径规划 栅格环境 复合启发信息 蚁群算法 动态融入 

分 类 号：TH16[机械工程—机械制造及自动化] TP301[自动化与计算机技术—计算机系统结构]