Mobile robot path planning based on the wolf ant colony hybrid algorithm

被引：0

作者：

Zhang Y. ^{[1
]}

Quan H. ^{[1
]}

Wen J. ^{[1
]}

机构：

[1] Research Center of Information Accessibility Project and Robotics, Chongqing University of Posts and Telecommunications, Chongqing

来源：

Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2020年 / 48卷 / 01期

关键词：

Ant colony algorithm; Mobile robot; Path planning; The wolf algorithm; Visual area search;

D O I：

10.13245/j.hust.200123

中图分类号：

学科分类号：

摘要：

To solve the problem of mobile robot path planning, an adaptive elite ant colony hybrid algorithm based on the unique wolf search mechanism is proposed.Firstly, the visual area search mechanism of wolf is introduced in the elite ant colony algorithm and the adaptive enhancement function is designed to improve the ability of the ant colony to find the path in the elite ant colony algorithm search mechanism.Secondly, to eliminate the stagnation phenomenon in the hybrid algorithm, the wolf escape strategy and constructs a pheromone optimization mechanism are introduced, which is used to improve the global search ability of the hybrid algorithm, help the path-seeking individual to break through the current path stagnation problem and avoid the algorithm falling into local optimum.Finally, through the simulation analysis and the physical experiment test, a targeted comparison experiment was carried out.The results show that the hybrid algorithm has better convergence speed and efficient path finding ability in path planning under various environments. © 2020, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.

引用

页码：127 / 132

页数：5

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