Abstract
Path planning of Unmanned Underwater Vehicle (UUV) is of considerable significance for the underwater navigation, the objective of the path planning is to find an optimal collision-free and the shortest trajectory from the start to the destination. In this paper, a new improved particle swarm optimization (IPSO) was proposed to process the global path planning in a static underwater environment for UUV. Firstly, the path planning principle for UUV was established, in which three cost functions, path length, exclusion potential field between the UUV and obstacle, and attraction potential field between UUV and destination, were considered and developed as an optimization objective. Then, on the basis of analysis traditional particle swarm optimization (PSO), the time-varying acceleration coefficients and slowly varying function were employed to improve performance of PSO, time-varying acceleration coefficients was utilized to balance the local optimum and global optimum, and slowly varying function was introduced into the updating formula of PSO to expand search space and maintain particle diversity. Finally, numerical simulations verify that, the proposed approach can fulfill path planning problems for UUN successfully.
Highlights
With the popularity and wide application of UUV (Unmanned Underwater Vehicle) in the ocean engineering and military operation fields, UUV as an indispensable intelligent navigation vehicle has attracted many attentions [1,2,3,4]
Path planning problem can be classified into two categories: local path planning (LPP) and global path planning (GPP) [11,12]
In improved particle swarm optimization (IPSO), time-varying acceleration coefficients and slowly varying function were employed, time-varying acceleration coefficients is utilized to balance the local optimum and global optimum, and slowly varying function is introduced into the updating formula of particle swarm optimization (PSO) to expand search space and maintain particle diversity
Summary
With the popularity and wide application of UUV (Unmanned Underwater Vehicle) in the ocean engineering and military operation fields, UUV as an indispensable intelligent navigation vehicle has attracted many attentions [1,2,3,4]. In dealing with the LPP problem, some approaches have been applied, such as artificial potential field method [13], fuzzy logic algorithm [14], and the rolling windows method [15] Those methods always exists some significant problems such as high computational cost, ineffective in path planning when the underwater space is large, and even deadlock phenomenon. Several improved PSO algorithms, such as PSOlinearly inertia weight, PSO-fuzzy inertia weight and PSO-nonlinear inertia weight, had been proposed [8,19] At present those methods have obtained with a certain performance improvement, but convergence and scarce exploration was the frequent problems in the application process.
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