基于改进蚁群算法的机器人路径规划设计

Robot Path Planning Design Based on Improved Ant Colony Algorithm

蚁群算法是由于其良好的反馈信息、优秀的分布式计算和强鲁棒性等优点,在移动机器人的路径规划中受到了较多应用,同时该算法也存在着收敛速度较慢的问题。本文介绍了一种改进的蚁群算法,对于机器人移动环境进行建模分析,在原有蚁群算法的基础上,对于刺激概率和信息素的规则进行了优化调整。改进后算法提升了收敛速度,扩大了搜索区域,通过仿真的结果表明,改进算法具有更好的规划特性。

Ant colony algorithm is widely used in path planning of mobile robots because of its good feedback information,excellent distributed computing and strong robustness.At the same time,the algorithm also has the problem of slow convergence.This paper introduces an improved ant colony algorithm to model and analyze the mobile environment of robots.On the basis of the original ant colony algorithm,the rules of stimulus probability and pheromone are optimized and adjusted.The improved algorithm improves the convergence speed and expands the search area.The simulation results show that the improved algorithm has better planning characteristics.