Hybrid Path Planning Strategy Based on Improved Particle Swarm Optimisation Algorithm Combined with DWA for Unmanned Surface Vehicles

被引:5
作者
Li, Jing [1 ]
Wan, Lili [1 ]
Huang, Zhen [1 ]
Chen, Yan [2 ]
Tang, Huiying [3 ]
机构
[1] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China
[2] Wuhan Polytech Univ, Sch Mech Engn, Wuhan 430048, Peoples R China
[3] Wuhan Donghu Univ, Sch Mech & Elect Engn, Wuhan 430212, Peoples R China
关键词
unmanned surface vehicle; path planning; PSO; DWA; COLREGS;
D O I
10.3390/jmse12081268
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Path planning is one of the core issues in the autonomous navigation of an Unmanned Surface Vehicle (USV), as the accuracy of the results directly affects the safety of the USV. Hence, this paper proposes a USV path planning algorithm that integrates an improved Particle Swarm Optimisation (PSO) algorithm with a Dynamic Window Approach (DWA). Firstly, in order to advance the solution accuracy and convergence speed of the PSO algorithm, a nonlinear decreasing inertia weight and adaptive learning factors are introduced. Secondly, in order to solve the problem of long path and path non-smoothness, the fitness function of PSO is modified to consider both path length and path smoothness. Finally, the International Regulations for Preventing Collisions at Sea (COLREGS) are utilised to achieve dynamic obstacle avoidance while complying with maritime practices. Numerical cases verify that the path planned via the proposed algorithm is shorter and smoother, guaranteeing the safety of USV navigation while complying with the COLREGS.
引用
收藏
页数:16
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