蚁群算法引导人工势场法的机器人路径规划  

The robot path planning of ant colony optimization based on artificial potential field

作　　者：廉博洋 林明星[1,2,3] Lian Boyang;Lin Mingxing(School of Mechanical Engineering,Shandong University,Shandong Jinan,250061,China;Key Laboratory of High-efficiency and Clean Mechanical Manufacture of Ministry of Education,Shandong Jinan,250061,China;National Demonstration Center for Experimental Mechanical Engineering Education,Shandong Jinan,250061,China)

机构地区：[1]山东大学机械工程学院,山东济南250061 [2]高效洁净机械制造教育部重点实验室,山东济南250061 [3]机械工程国家级实验教学示范中心,山东济南250061

出　　处：《机械设计与制造工程》2024年第8期67-71,共5页Machine Design and Manufacturing Engineering

基　　金：山东省自然科学基金(ZR2020ME267);山东省重点研发计划(重大科技创新工程)(2019JZZY020703)。

摘　　要：提出了一种将改进蚁群算法和人工势场法相融合的算法。使用改进蚁群算法规划出一条全局最优路径,在全局最优路径的引导下采用人工势场法进行局部路径规划,规划出机器人的实时最优路径。仿真实验证明,所提算法规划出的路径不仅具有全局最优路径的信息,同时还具备规避未知障碍物和动态障碍物的能力。In this paper,a fusion algorithm combining the improved ant colony optimization and artificial potential field is proposed.A global optimal path is planned by the improved ant colony optimization.Under the guidance of the global optimal path,the artificial potential field is used for local path planning,so as to realize the real-time optimal path planning of the robot.Finally,the simulation experiments are carried out and the results show that the path planned by the proposed algorithm not only has the information of the global optimal path,but also has the ability to avoid unknown obstacles and dynamic obstacles.

关 键 词：蚁群算法 人工势场法 路径规划 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]