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An enhanced A* method incorporating an encrypted memory database for ASV efficient local path planning

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Title: An enhanced A* method incorporating an encrypted memory database for ASV efficient local path planning
Authors: Yuanshuo Liu, Defeng Wu, Zheng You
Source: Mathematical Biosciences and Engineering, Vol 21, Iss 2, Pp 2302-2322 (2024)
Publisher Information: American Institute of Mathematical Sciences (AIMS), 2024.
Publication Year: 2024
Subject Terms: 0209 industrial biotechnology, memory database, improved heuristic function, QA1-939, 0211 other engineering and technologies, autonomous surface vehicle (asv), 02 engineering and technology, enhanced a* algorithm, path planning, TP248.13-248.65, Mathematics, Biotechnology
Description: For the autonomous surface vehicle (ASV) planning problem, an enhanced A* method incorporating encrypted memory database for ASV efficient local path planning is proposed. Considering the current various path planning problems mostly use methods with high time complexity, such as neural networks, we select the A* algorithm with low time complexity as the basis. To speed up the path planning rate and further improve the real-time and realistic algorithm, this paper modifies the heuristic function of the A* algorithm by combining the motion mode of ASV. In response to the problem that the target point is far from the detection, we improve the target point design mechanism and create a new temporary target point within the detection range. In addition, the algorithm incorporates a memory database, which can record commonly used waters or retain the environmental path of navigated waters as a priori information. When the same waters are reencountered, the memory database information can be read directly to complete the navigation. Moreover, the memory database is encrypted to prevent information leakage. Finally, a simulation environment is built to verify the effectiveness of the proposed algorithm by comparison with some existing algorithms.
Document Type: Article
ISSN: 1551-0018
DOI: 10.3934/mbe.2024101
Access URL: https://pubmed.ncbi.nlm.nih.gov/38454684
https://doaj.org/article/cb2c6d0da113437680569466f36fbd0a
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  Data: An enhanced A* method incorporating an encrypted memory database for ASV efficient local path planning
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  Data: <searchLink fieldCode="AR" term="%22Yuanshuo+Liu%22">Yuanshuo Liu</searchLink><br /><searchLink fieldCode="AR" term="%22Defeng+Wu%22">Defeng Wu</searchLink><br /><searchLink fieldCode="AR" term="%22Zheng+You%22">Zheng You</searchLink>
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  Data: Mathematical Biosciences and Engineering, Vol 21, Iss 2, Pp 2302-2322 (2024)
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  Data: American Institute of Mathematical Sciences (AIMS), 2024.
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  Data: For the autonomous surface vehicle (ASV) planning problem, an enhanced A* method incorporating encrypted memory database for ASV efficient local path planning is proposed. Considering the current various path planning problems mostly use methods with high time complexity, such as neural networks, we select the A* algorithm with low time complexity as the basis. To speed up the path planning rate and further improve the real-time and realistic algorithm, this paper modifies the heuristic function of the A* algorithm by combining the motion mode of ASV. In response to the problem that the target point is far from the detection, we improve the target point design mechanism and create a new temporary target point within the detection range. In addition, the algorithm incorporates a memory database, which can record commonly used waters or retain the environmental path of navigated waters as a priori information. When the same waters are reencountered, the memory database information can be read directly to complete the navigation. Moreover, the memory database is encrypted to prevent information leakage. Finally, a simulation environment is built to verify the effectiveness of the proposed algorithm by comparison with some existing algorithms.
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        Value: 10.3934/mbe.2024101
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      – SubjectFull: 0209 industrial biotechnology
        Type: general
      – SubjectFull: memory database
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      – SubjectFull: improved heuristic function
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      – SubjectFull: enhanced a* algorithm
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      – SubjectFull: path planning
        Type: general
      – SubjectFull: TP248.13-248.65
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      – SubjectFull: Mathematics
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      – SubjectFull: Biotechnology
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      – TitleFull: An enhanced A* method incorporating an encrypted memory database for ASV efficient local path planning
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            NameFull: Zheng You
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              Y: 2024
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