微型机与应用2016，Vol.35Issue(21)：16-19,23,5.DOI:10.19358/j.issn.1674-7720.2016.21.005
基于K-Means与SVM结合的栅格分区路径规划方法
Path planning method based on K-Means and SVM combination grid partition
摘要
Abstract
In the global path planning of intelligent cleaning robot, the grid method is used to model the working environment of the robot.This paper introduced K-means clustering algorithm and Support Vector Machine (SVM) algorithm, using a combination of K-means clustering algorithm and SVM method for clustering with different constraint conditions.In the gird map containing complex obstacles, raster map can effectively reduce partition.Using ant colony algorithm to simulate the partitioned grid map path planning.It can effectively improve the ant colony algorithm in path planning of raster map of overall efficiency.关键词
栅格地图/K-Means聚类/支持向量机(SVM)/蚁群算法Key words
grid map/K-Means clustering/Support Vector Machine (SVM)/ant colony algorithm分类
计算机与自动化引用本文复制引用
张堂凯,罗杰,李龙俊..基于K-Means与SVM结合的栅格分区路径规划方法[J].微型机与应用,2016,35(21):16-19,23,5.基金项目
国家自然科学基金(61203028) （61203028）
