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Lookup NU author(s): Dr Zheming Zuo
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 by the authors.Unmanned surface vehicles (USVs) often operate in real-world environments with long voyage distances and complex routes. The use of a single-grid map model presents challenges, such as the high computational costs for high-resolution maps and loss of environmental information for low-resolution maps. This article proposes an environmental modeling method using a hybrid map that combines topology units and grids. The approach involves calibrating key nodes based on the watershed skeleton line, constructing a topology map using these nodes, decomposing the original map into unit maps, converting each unit map into a grid map, and creating a hybrid map environment model that comprises topology maps, unit map sets, and grid map sets. Then, the article introduces an improved genetic algorithm, called Genetic Algorithm with Feedback (FGA), to address path planning in hybrid maps. Experimental results demonstrate that FGA has better computational efficiency than other algorithms in similar experimental environments. In hybrid maps, path planning with FGA reduces the path lengths and time consumption, and the paths are more logical, smooth, and continuous. These findings contribute to enhancing the quality of path planning and the practical value of USVs.
Author(s): Gao H, Zhang T, Zuo Z, Guo X, Long Y, Qiu D, Liu S
Publication type: Article
Publication status: Published
Journal: Journal of Marine Science and Engineering
Year: 2024
Volume: 12
Issue: 6
Online publication date: 03/06/2024
Acceptance date: 31/05/2024
Date deposited: 15/07/2024
ISSN (electronic): 2077-1312
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
URL: https://doi.org/10.3390/jmse12060939
DOI: 10.3390/jmse12060939
Data Access Statement: The raw data supporting the conclusions of this article will be made available by the authors on request
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