基于蚁群算法和冲突消除的多机器人移动路径优化研究  

Research on multi-robot moving path optimizationbased on ant colony algorithm and conflict elimination

作　　者：吕英杰 Lv Yingjie(Haier School,Qingdao Technical College,Shandong Qingdao,266555,China)

机构地区：[1]青岛职业技术学院海尔学院,山东青岛266555

出　　处：《机械设计与制造工程》2023年第12期55-61,共7页Machine Design and Manufacturing Engineering

基　　金：青岛职业技术学院科研重点课题(2020YYZD08);山东省教育教学改革研究项目(20SJG120)。

摘　　要：针对多机器人路径冲突问题,提出一种基于蚁群算法和冲突消除的路径优化方法。首先在构建栅格地图的前提下,构建多机器人运动的目标函数和约束条件,利用蚁群算法对目标函数进行求解,针对经典蚁群算法初始位置随机性强、“死锁”和迭代次数多的问题,分别提出路径指引函数、虚拟障碍标记以及加入阈值参数和权值参数,得到单个机器人的最优路径;其次提出多机器人移动冲突消除策略,解决路径冲突问题。试验结果表明,经改进的蚁群算法求解得到的路径和总耗时都最短,且不存在“死锁”问题;运用冲突消除策略,避免了多机器人移动中的路径冲突,解决了多机器人运动中的碰撞问题。Aiming at the problem of multi-robot path conflict,a path optimization method based on ant colony algorithm and conflict elimination is proposed.On the premise of constructing grid map,the first step is to construct the objective function and constraints of multi-robot motion,and then utilizes ant colony algorithm to solve the objective function.Aiming at the problems of strong randomness of the initial position,"deadlock"and many iterations of the classical ant colony algorithm,the path guidance function and virtual obstacle marker are proposed respectively,and threshold parameters and weight parameters are added,thus the optimal path of a single robot is obtained.The second step is to propose a multi-robot moving conflict elimination strategy to solve the path conflict problem.The test results show that the improved ant colony algorithm has the shortest path and least total time,and there is no"deadlock"problem.Using the conflict elimination strategy,the path conflict in multi-robot motion is avoided,and the collision problem in multi-robot motion is solved.

关 键 词：目标函数 多机器人 轨迹规划 蚁群算法 冲突消除 

分 类 号：TP399[自动化与计算机技术—计算机应用技术] TH69[自动化与计算机技术—计算机科学与技术]