Mobile Robot Global Path Planning Based on Improved Augment Ant Colony Algorithm

被引：15
|
作者：
Gao, Meijuan [1 ,2 ]
Xu, Jin [2 ]
Tian, Jingwen [1 ,2 ]
机构：
[1] Beijing Union Univ, Beijing, Peoples R China
[2] Beijing Univ Chem Technol, Beijing, Peoples R China
来源：
SECOND INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING: WGEC 2008, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/WGEC.2008.39
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
To overcome the defects of precocity and the time for initial population building is too long in traditional augment ant colony algorithm for mobile robot global path planning, an improved augment ant colony algorithm is presented in this paper. The operations of crossover and mutation of genetic algorithm (GA) are used in augment ant colony optimization, and the heuristic probability function is added to the process of the initial population building. The process flow of improved ant colony algorithm is given and the simulation experiment is done under the VC++ 6.0 environment. Experimental results show that the algorithm has much higher capacity of global optimization than traditional augment ant colony algorithm.
引用
收藏
页码：273 / +
页数：2
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