Mobile Robot Path Planning using an Improved Ant Colony Algorithm in Uncertain Environments

被引：1
|
作者：
Cui, Shigang [1 ]
Wang, Hui [1 ]
Li, Jigong [1 ]
机构：
[1] Tianjin Univ Technol & Educ, Tianjin Key Lab Informat Sensing & Intelligent Co, Tianjin, Peoples R China
来源：
2013 THIRD INTERNATIONAL CONFERENCE ON INSTRUMENTATION & MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC) | 2013年
关键词：
path planning; ant colony algorithm; heuristic factor;
D O I：
10.1109/IMCCC.2013.49
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
As a swarm intelligence, ant colony algorithm (ACA) is widely used to solve the path planning problem. But ACA applied to the path planning has some disadvantages such as fall into local optimization easily and low convergence. In order to overcome these defects, we improved the ant colony algorithm by changing heuristic factor. The experiment results indicate that the improved algorithm performs better original algorithm.
引用
收藏
页码：200 / 203
页数：4
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