USV path planning based on quantum-behaved particle swarm optimization

被引：0
|
作者：
Jin J.-H. [1 ]
Sun J. [2 ]
Zhang A.-T. [1 ]
Zhang B. [1 ]
机构：
[1] China Ship Scientific Research Center, Wuxi
[2] School of IOT Engineering, Jiangnan University, Wuxi
来源：
Chuan Bo Li Xue/Journal of Ship Mechanics | 2020年 / 24卷 / 03期
关键词：
Path planning; Potential field model; Quantum-behaved particle swarm optimization (QPSO); Unmanned surface vehicles;
D O I：
10.3969/j.issn.1007-7294.2020.03.009
中图分类号：
学科分类号：
摘要：
In order to overcome the problems of low efficiency, slow convergence or being prone to be trapped into the local minima encountered by the existing algorithms of USV path planning, the quantum-behaved particle swarm optimization algorithm possessing a strong global search ability is proposed to solve the USV path planning problem. The proposed method also integrates the basic idea of potential field model for the purpose of further improvement of the algorithmic performance. Simulation results show that the method has the advantages of high searching efficiency, fast convergence speed and good stability, which can well be suitable for USV path planning in different environments. © 2020, Editorial Board of Journal of Ship Mechanics. All right reserved.
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收藏
页码：352 / 361
页数：9
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