Mobile Robot Path Planning based on Parameter Optimization Ant Colony Algorithm

被引：12
|
作者：
Wang Zhangqi [1 ]
Zhu Xiaoguang [1 ]
Han Qingyao [1 ]
机构：
[1] N China Elect Power Univ, Sch Mech Engn, Baoding 071003, Peoples R China
来源：
CEIS 2011 | 2011年 / 15卷
关键词：
Ant colony algorithm; Mobile Robot; Path planning; Genetic algorithm;
D O I：
10.1016/j.proeng.2011.08.515
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The basic ant colony algorithm for mobile robot path planning exists many problems, such as lack of stability, algorithm premature convergence, more difficult to find optimal solution for complex problems and so on. This paper proposes improvement measures. Apply genetic algorithm to optimization and configuration parameters of the basic ant colony algorithm. Simulation results show that the improved optimal path length significantly less than the basic ant colony algorithm and volatility is smaller, stability significantly improves. The stability of improved ant colony algorithm is superior to the basic ant colony algorithm, verify the effectiveness of the improvement measures. (c) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]
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页数：4
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