摘要
针对机器人进行避障路径规划时存在收敛速度差、规划路径长、迭代次数多以及规划时间长的问题,提出基于改进蚁群算法的巡检机器人避障路径规划方法。首先使用栅格法划分巡检机器人工作环境,通过对像素矩阵等指标的分析,构建栅格地图模型;基于人工势场法提出蚁群路径规划算法,使蚁群适应子空间的搜索;最后在模型中利用该算法,寻找该模型的最佳路径。实验结果表明,运用该方法进行路径规划时,收敛速度高、规划路径短、迭代次数少以及规划时间短。
Aiming at the problems of poor convergence speed,long planning path,large number of iterations and long planning time when using current methods for obstacle avoidance path planning of robot,a method designed for obstacle avoidance path planning for inspection robot based on improved ant colony algorithm is proposed.First,a grid method is used to divide the working environment of the inspection robot,and a grid map model is constructed through the analysis of the pixel matrix and other indicators;an ant colony path planning algorithm based on the artificial potential field method is proposed to adapt the ant colony to the subspace search;finally,the algorithm is used in the model to find the best path of the model.Experimental results show that this method for path planning has high convergence speed,short planned path,fewer iterations and shorter planning time.
作者
李鹏
闵小翠
王建华
LI Peng;MIN Xiaocui;WANG Jianhua(Guangzhou Huali Science and Technology Vocational College,Guangzhou 511325,China)
出处
《机械与电子》
2022年第2期71-74,80,共5页
Machinery & Electronics
基金
广东省高职院校高水平专业群(GSPZYQ2020082)
广东省大学生科技创新培育专项资金项目(pdjh2020b1410)。
关键词
蚁群算法
巡检机器人
避障路径
人工势场
ant colony algorithm
inspection robot
obstacle avoidance path
artificial potential field
