Data-driven fuzzy logic control method for improved USV path planning

The parameters of the path planning algorithm for unmanned surface vehicles (USVs) usually rely on manual settings, which makes it difficult for the algorithm to achieve the optimal solution when considering multiple factors in path planning. This paper proposes a data-driven method to improve the U...

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Vydané v:	The Journal of supercomputing Ročník 81; číslo 7; s. 844
Hlavní autori:	Wang, Feng, Wang, Chenglong, Wang, Yuanhui, Chemori, Ahmed, Zhang, Xiaoyue, Zhang, Kun, Zhang, Yuxuan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer Nature B.V 09.05.2025 Springer Verlag
Predmet:	Algorithms Automatic Automatic Control Engineering Computer Science Control algorithms Control methods Datasets Engineering Sciences Fuzzy control Fuzzy logic Kinematics Neural networks Parameters Path planning Robotics Surface vehicles Unmanned vehicles Velocity Fuzzy logic control Path planning Data-driven Neural network Dynamic Window Approach Unmanned Surface Vehicles (USVs)
ISSN:	1573-0484, 0920-8542, 1573-0484
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