An Optimized Hybrid Ant Colony Algorithm for Robot Path Planning
Aiming at the disadvantages of the potential ant colony algorithm that the efficiency of random search path at the initial time is low and is easy to fall into the local optimal,A new optimized hybrid ant colony algorithm is proposed.Firstly,The algorithm uses the target gravitational force generated by the artificial potential field to construct a heuristic factor.The heuristic factor is combined with the initial heuristic factor of the ant colony algorithm to construct the comprehensive heuristic information to improve the search efficiency.Then,The pheromone in the ant colony algorithm is updated by wolves distribution rules to avoid getting into the local optimal;At Last,the planning path is optimized by path optimization algorithm which makes it more suitable for robot execution.Experiments show that the optimized hybrid ant colony algorithm can quickly and efficiently plan the optimal path.
path planning ant colony algorithm artificial potential field wolves distribution rules path optimization algorithm
Yi Zhang Jie Liu Yan Liu Xiaoquan Xu
Chongqing University of Posts and Telecommunications Intelligent System and Robotics Laboratory, Chongqing 400065, China
国内会议
哈尔滨
英文
639-648
2017-10-01（万方平台首次上网日期，不代表论文的发表时间）