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Aquatic Environment Establishment and USV Path Planning Simulation Analysis using the ROS Framework.

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Τίτλος: Aquatic Environment Establishment and USV Path Planning Simulation Analysis using the ROS Framework.
Συγγραφείς: Xu, Zhenyu1 (AUTHOR) 45844363@qq.com, Li, Ning2 (AUTHOR) 20251016@hziee.edu.cn, Tian, Hao2 (AUTHOR) 20251005@hdu.edu.cn, Xu, Jing3 (AUTHOR) xujing@hdu.edu.cn
Πηγή: International Journal of Pattern Recognition & Artificial Intelligence. Sep2026, p1. 21p. 12 Illustrations.
Θεματικοί όροι: *Heuristic, Robotic path planning, Computer simulation, Autonomous vehicles, Maritime safety, Wind pressure, Robotics software
Περίληψη: Comprehensive, accurate, and timely cognition of the navigation situation is a prerequisite to make safe, efficient, and scientific decisions for Unmanned Surface Vehicles (USVs). The autonomous path planning problem for USVs operating in complex aquatic environments was addressed. A hybrid path planning algorithm integrating A* and Dynamic Window Approach (DWA) is proposed, and its performance under diverse environmental conditions is systematically validated through simulation experiments. A virtual aquatic environment was constructed to conduct path planning simulations under three distinct scenarios: still water without wind, constant wind conditions, and variable wind speeds, thereby comprehensively evaluating the algorithm’s adaptability, safety, and optimization capability. The results demonstrate that within a certain wind speed range, the optimization capability of the hybrid path planning algorithm significantly strengthens as the experimental aquatic environment scales up, leading to further enhancement of USV navigation safety. Under constant wind disturbance of 5 m/s, the USV successfully navigates to the target point while maintaining a safety distance exceeding 0.5 m from obstacles throughout the voyage, exhibiting robust anti-interference capability and planning stability. Quantitative analysis of simulation results under varying wind conditions was performed using an evaluation function. By optimizing this evaluation function based on an improved DWA motion model, the navigation path length is reduced by 4.12% and navigation time decreases by 7.66%, while simultaneously increasing the safe clearance between the USV and obstacles. These improvements substantially enhance both path optimality and navigation safety of the USVs. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Pattern Recognition & Artificial Intelligence is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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IllustrationInfo
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  Data: Aquatic Environment Establishment and USV Path Planning Simulation Analysis using the ROS Framework.
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  Data: <searchLink fieldCode="AR" term="%22Xu%2C+Zhenyu%22">Xu, Zhenyu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 45844363@qq.com</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Ning%22">Li, Ning</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> 20251016@hziee.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Tian%2C+Hao%22">Tian, Hao</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> 20251005@hdu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Xu%2C+Jing%22">Xu, Jing</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> xujing@hdu.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Pattern+Recognition+%26+Artificial+Intelligence%22">International Journal of Pattern Recognition & Artificial Intelligence</searchLink>. Sep2026, p1. 21p. 12 Illustrations.
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  Data: *<searchLink fieldCode="DE" term="%22Heuristic%22">Heuristic</searchLink><br /><searchLink fieldCode="DE" term="%22Robotic+path+planning%22">Robotic path planning</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Autonomous+vehicles%22">Autonomous vehicles</searchLink><br /><searchLink fieldCode="DE" term="%22Maritime+safety%22">Maritime safety</searchLink><br /><searchLink fieldCode="DE" term="%22Wind+pressure%22">Wind pressure</searchLink><br /><searchLink fieldCode="DE" term="%22Robotics+software%22">Robotics software</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Comprehensive, accurate, and timely cognition of the navigation situation is a prerequisite to make safe, efficient, and scientific decisions for Unmanned Surface Vehicles (USVs). The autonomous path planning problem for USVs operating in complex aquatic environments was addressed. A hybrid path planning algorithm integrating A* and Dynamic Window Approach (DWA) is proposed, and its performance under diverse environmental conditions is systematically validated through simulation experiments. A virtual aquatic environment was constructed to conduct path planning simulations under three distinct scenarios: still water without wind, constant wind conditions, and variable wind speeds, thereby comprehensively evaluating the algorithm’s adaptability, safety, and optimization capability. The results demonstrate that within a certain wind speed range, the optimization capability of the hybrid path planning algorithm significantly strengthens as the experimental aquatic environment scales up, leading to further enhancement of USV navigation safety. Under constant wind disturbance of 5 m/s, the USV successfully navigates to the target point while maintaining a safety distance exceeding 0.5 m from obstacles throughout the voyage, exhibiting robust anti-interference capability and planning stability. Quantitative analysis of simulation results under varying wind conditions was performed using an evaluation function. By optimizing this evaluation function based on an improved DWA motion model, the navigation path length is reduced by 4.12% and navigation time decreases by 7.66%, while simultaneously increasing the safe clearance between the USV and obstacles. These improvements substantially enhance both path optimality and navigation safety of the USVs. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Pattern Recognition & Artificial Intelligence is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1142/s021800142659038x
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 1
    Subjects:
      – SubjectFull: Heuristic
        Type: general
      – SubjectFull: Robotic path planning
        Type: general
      – SubjectFull: Computer simulation
        Type: general
      – SubjectFull: Autonomous vehicles
        Type: general
      – SubjectFull: Maritime safety
        Type: general
      – SubjectFull: Wind pressure
        Type: general
      – SubjectFull: Robotics software
        Type: general
    Titles:
      – TitleFull: Aquatic Environment Establishment and USV Path Planning Simulation Analysis using the ROS Framework.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Xu, Zhenyu
      – PersonEntity:
          Name:
            NameFull: Li, Ning
      – PersonEntity:
          Name:
            NameFull: Tian, Hao
      – PersonEntity:
          Name:
            NameFull: Xu, Jing
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 09
              Text: Sep2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 02180014
          Titles:
            – TitleFull: International Journal of Pattern Recognition & Artificial Intelligence
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