自动化学报2007，Vol.33Issue(3)：279-285,7.
基于ACS算法的移动机器人实时全局最优路径规划
Ant Colony System Algorithm for Real-Time Globally Optimal Path Planning of Mobile Robots
摘要
Abstract
A novel method for the real-time globally optimal path planning of mobile robots is proposed based on the ant colony system (ACS) algorithm. This method includes three steps: the first step is utilizing the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is utilizing the Dijkstra algorithm to find a sub-optimal collision-free path,and the third step is utilizing the ACS algorithm to optimize the location of the sub-optimal path so as to generate the globally optimal path. The result of computer simulation experiment shows that the proposed method is effective and can be used in the real-time path planning of mobile robots. It has been verified that the proposed method has better performance in convergence speed, solution variation, dynamic convergence behavior, and computational efficiency than the path planning method based on the genetic algorithm with elitist model.关键词
Mobile robot/globally optimal path planning/ACS algorithm/MAKLINK graph/Dijkstra algorithmKey words
Mobile robot/globally optimal path planning/ACS algorithm/MAKLINK graph/Dijkstra algorithm分类
信息技术与安全科学引用本文复制引用
谭冠政,贺欢,SLOMAN Aaron..基于ACS算法的移动机器人实时全局最优路径规划[J].自动化学报,2007,33(3):279-285,7.基金项目
Supported by National Natural Science Foundation of P. R. China (50275150) and National Research Foundation for the Doctoral Program of Higher Education of P. R. China (20040533035) （50275150）
