A Novel Unmanned Surface Vehicle Path-Planning Algorithm Based on A and Artificial Potential Field in Ocean Currents

Ocean currents make it difficult for unmanned surface vehicles (USVs) to keep a safe distance from obstacles. Effective path planning should adequately consider the effect of ocean currents on USVs. This paper proposes an improved A* algorithm based on an artificial potential field (APF) for USV pat...

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Vydané v:Journal of marine science and engineering Ročník 12; číslo 2; s. 285
Hlavní autori: Yang, Chaopeng, Pan, Jiacai, Wei, Kai, Lu, Mengjie, Jia, Shihao
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.02.2024
Predmet:
Algorithms
Barriers
Computing time
Cost function
Curves
Distance
Efficiency
Energy consumption
Genetic algorithms
improved A algorithm
Literature reviews
Ocean
Ocean currents
Optimization
Path planning
Planning
potential field force
Potential fields
Surface vehicles
Unmanned vehicles
USV path planning
Vehicles
ISSN:2077-1312, 2077-1312
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Shrnutí:Ocean currents make it difficult for unmanned surface vehicles (USVs) to keep a safe distance from obstacles. Effective path planning should adequately consider the effect of ocean currents on USVs. This paper proposes an improved A* algorithm based on an artificial potential field (APF) for USV path planning in a current environment. There are three main improvements to the A* algorithm. Firstly, the proposed algorithm ignores unnecessary perilous nodes to decrease calculation. Secondly, an adaptive guidance angle is developed to guide the search in the most appropriate direction to reduce the computing time. Thirdly, the potential field force function is introduced into the cost function to ensure that the path designed for the USV always maintains a safe distance from obstacles under the influence of ocean currents. Furthermore, the Bezier curve is adapted to smooth the path. The experimental results show that the USV path-planning algorithm proposed in this paper, which synthesizes the APF and A* algorithms, runs 22.5% faster on average than the traditional A* algorithm. Additionally, the path developed by the proposed A* algorithm effectively keeps appropriate and different distances from obstacles by considering different ocean currents.
Bibliografia:ObjectType-Article-1
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ISSN:2077-1312
2077-1312
DOI:10.3390/jmse12020285