摘要
针对移动机器人在路径规划中使用蚁群算法存在的算法前期效率低、函数收敛速度慢等问题,结合人工势场法提出一种融合算法.首先,根据传统蚁群算法数学模型,分析各个参数的作用,通过栅格地图建模,在MATLB中仿真分析出最优参数,记录各项数据.其次,通过引入中间点和目标相对距离的方法改进经典人工势场法的无法到达终点和局部锁死无法移动的问题.最后,结合两者算法特点,将改进的人工势场法和传统蚁群算法融合,在移动机器人路径规划初期,使得改进后的人工势场法发挥主要作用,后期随着信息素浓度增高,发挥蚁群算法的主要作用.通过仿真分析,验证蚁群算法和改进人工势场法后的融合算法各项结果要优于传统蚁群算法.
Aiming at the problems of low efficiency and slow convergence of function in the early stage of using ant colony algorithm in path planning of mobile robots,a fusion algorithm is proposed based on the artificial potential field method.Firstly,according to the mathematical model of traditional ant colony algorithm,the function of each parameter is analyzed.Through grid map modeling,the optimal parameters are simulated and analyzed in MATLAB,and the data are recorded.Secondly,the relative distance between the intermediate point and the target is introduced to improve the problems of the classical artificial potential field method that can not reach the end point and can not be moved due to local locking.Finally,combined with the characteristics of the two algorithms,the improved artificial potential field method and the traditional ant colony algorithm are fused.At the initial stage of path planning for mobile robots,the improved artificial potential field method plays a major role,and at the later stage,as the pheromone concentration increases,the ant colony algorithm plays a major role.Through simulation analysis,it is verified that the results of the fusion algorithm after the ant colony algorithm and the improved artificial potential field method are better than the traditional ant colony algorithm.
作者
任志伟
胡平
闫方
曲富柱
REN Zhiwei;HU Ping;Yan Fang;QU Fuzhu(School of Information Engineering,Henan Institute of Science and Technology,Xinxiang 453003,China)
出处
《河南科技学院学报（自然科学版）》
2023年第4期52-63,共12页
Journal of Henan Institute of Science and Technology(Natural Science Edition)
基金
国家自然科学基金项目(32207009)。
关键词
路径规划
蚁群算法
改进人工势场法
融合算法
path planning
ant colony
improved artificial potential field method
fusion algorithm
