Improved ant colony algorithm of path planning for mobile robot

被引：0
|
作者：
Zhao, Juan-Ping [1 ,2 ]
Gao, Xian-Wen [1 ]
Fu, Xiu-Hui [2 ,3 ]
Liu, Jin-Gang [1 ,4 ]
机构：
[1] College of Information Science and Engineering, Northeastern University, Shenyang Liaoning 110004, China
[2] College of Information Engineering, Shenyang University of Chemical Technology, Shenyang Liaoning 110142, China
[3] Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang Liaoning 110015, China
[4] Shenyang Xinghua Aero-Electric Appliances Company of Limited Liability, Shenyang Liaoning 100080, China
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2011年 / 28卷 / 04期
关键词：
Evolutionary algorithms - Mobile robots - Robot programming - Ant colony optimization;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
An improved ant colony optimization algorithm-a differential evolution chaos ant colony optimization (DEACO) algorithm is proposed to plan the optimal collision-free path for a mobile robot in a complicated static environment. It utilizes differential evolution algorithm to update the pheromone, and appends the chaos disturbance factor in the updating process to avoid the possible stagnation phenomenon. Finally, a new evaluation criterion is employed to enhance the escaping capability of algorithm, avoid the path-locked situations and improve the efficiency in planning the optimal path. Simulation results indicate that an optimal and safe path which the robot moves on can be rapidly obtained even in a complicated geographical environment. The results are very satisfactory.
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页码：457 / 461
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