改进精英蚁群算法在未知环境下的移动机器人路径规划  

Improved Elite Ant Colony Algorithm for Mobile Robot Path Planning in Complex Environment

作　　者：胡丹[1] 黄辉[1] 潘梦莎 

机构地区：[1]台州科技职业学院,浙江台州318020

出　　处：《工业控制计算机》2022年第11期119-122,125,共5页Industrial Control Computer

基　　金：浙江省教育厅一般科研项目(Y202044685)。

摘　　要：针对传统精英蚁群算法在移动机器人路径规划中易陷入局部最优的问题,通过改进最优路径信息素增加系数e的取值提升算法性能,使其跟随迭代周期的改变而不断自适应变化。首先利用栅格法对机器人感知的环境进行空间环境建模,明确移动规则;接着构建最优路径信息素增加系数e的数学模型并进行验证;最后对比不同规模地图环境的仿真实验,发现改进后的精英蚁群算法在寻找最优路径时有更好的收敛性、更快的运算速度、更优的平滑性。Aiming at the problem that traditional elite ant colony algorithm is prone to fall into local optimum in the path planning of mobile robot,the algorithm performance is improved by improving the value of the pheromone increasing coefficient e of the optimal path,so that it can adapt to the change of iteration cycle continuously.Firstly,the raster method is used to model the spatial environment perceived by the robot and define the movement rules.Then,the mathematical model of the optimal path pheromone increasing coefficient e is constructed and verified.Finally,by comparing the simulation experiments of different scale map environments,it is found that the improved elite ant colony algorithm has better convergence,faster operation speed and better smoothness in finding the optimal path.

关 键 词：移动机器人 改进精英蚁群算法 路径规划 参数优化 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP18[自动化与计算机技术—控制科学与工程]