Efficient tracking of ocean eddies using unmanned underwater vehicles

IF 4.4 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Hanbin Zhang , Dalei Song , Jiangli Cao , Wenshan Yu , Wenchuan Zang
{"title":"Efficient tracking of ocean eddies using unmanned underwater vehicles","authors":"Hanbin Zhang ,&nbsp;Dalei Song ,&nbsp;Jiangli Cao ,&nbsp;Wenshan Yu ,&nbsp;Wenchuan Zang","doi":"10.1016/j.apm.2025.116392","DOIUrl":null,"url":null,"abstract":"<div><div>Unmanned underwater vehicles deployed in formations for eddy measurement enhance spatial resolution and temporal continuity. However, coordinating unmanned underwater vehicle swarms presents significant challenges in accurately solving the optimization problem of maintaining high-coverage observation formations, subject to time-varying constraints imposed by dynamic eddy migration and turbulent environmental disturbances. This work proposes a hybrid framework for unmanned underwater vehicle swarm tracking of dynamic ocean eddies. The Lyapunov Guidance Vector Field generates stable guidance commands via rotational vector fields to maintain an equilateral formation, while Policy Optimization with Collaborative Adaptation optimizes real-time corrections for vortex migration and turbulence. A bidirectional collaborative mechanism facilitates parameter adaptation between modules, while Lyapunov-based constraints bound correction ranges to suppress high-frequency oscillations. Simulations and physical experiments demonstrate the effectiveness of the proposed method, achieving a spatial-temporal uniformity improvement of approximately 32.5% in static tracking scenarios and 36.5% in dynamic tracking scenarios compared to traditional methods. This work enhances unmanned underwater vehicle navigation control, improving eddy observation quality. Incorporating artificial intelligence increases automation in swarm planning, providing an effective solution for ocean eddy observation and improving oceanographic observation accuracy.</div></div>","PeriodicalId":50980,"journal":{"name":"Applied Mathematical Modelling","volume":"150 ","pages":"Article 116392"},"PeriodicalIF":4.4000,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematical Modelling","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0307904X25004664","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Unmanned underwater vehicles deployed in formations for eddy measurement enhance spatial resolution and temporal continuity. However, coordinating unmanned underwater vehicle swarms presents significant challenges in accurately solving the optimization problem of maintaining high-coverage observation formations, subject to time-varying constraints imposed by dynamic eddy migration and turbulent environmental disturbances. This work proposes a hybrid framework for unmanned underwater vehicle swarm tracking of dynamic ocean eddies. The Lyapunov Guidance Vector Field generates stable guidance commands via rotational vector fields to maintain an equilateral formation, while Policy Optimization with Collaborative Adaptation optimizes real-time corrections for vortex migration and turbulence. A bidirectional collaborative mechanism facilitates parameter adaptation between modules, while Lyapunov-based constraints bound correction ranges to suppress high-frequency oscillations. Simulations and physical experiments demonstrate the effectiveness of the proposed method, achieving a spatial-temporal uniformity improvement of approximately 32.5% in static tracking scenarios and 36.5% in dynamic tracking scenarios compared to traditional methods. This work enhances unmanned underwater vehicle navigation control, improving eddy observation quality. Incorporating artificial intelligence increases automation in swarm planning, providing an effective solution for ocean eddy observation and improving oceanographic observation accuracy.
使用无人水下航行器有效跟踪海洋涡流
无人水下航行器部署在编队中进行涡流测量,提高了空间分辨率和时间连续性。然而,由于动态涡动迁移和湍流环境扰动的时变约束,协调无人潜航器群在准确解决维持高覆盖观测编队的优化问题方面面临着重大挑战。本文提出了一种用于动态海洋涡流中无人潜航器群跟踪的混合框架。Lyapunov制导矢量场通过旋转矢量场生成稳定的制导命令,以保持等边编队,而具有协同自适应的策略优化可以优化对涡旋迁移和湍流的实时修正。双向协作机制促进了模块之间的参数自适应,而基于lyapunov的约束约束约束了校正范围以抑制高频振荡。仿真和物理实验证明了该方法的有效性,与传统方法相比,静态跟踪场景下的时空均匀性提高了约32.5%,动态跟踪场景下的时空均匀性提高了36.5%。提高了无人潜航器的导航控制能力,提高了涡流观测质量。人工智能的结合提高了群规划的自动化程度,为海洋涡旋观测提供了有效的解决方案,提高了海洋观测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Applied Mathematical Modelling
Applied Mathematical Modelling 数学-工程:综合
CiteScore
9.80
自引率
8.00%
发文量
508
审稿时长
43 days
期刊介绍: Applied Mathematical Modelling focuses on research related to the mathematical modelling of engineering and environmental processes, manufacturing, and industrial systems. A significant emerging area of research activity involves multiphysics processes, and contributions in this area are particularly encouraged. This influential publication covers a wide spectrum of subjects including heat transfer, fluid mechanics, CFD, and transport phenomena; solid mechanics and mechanics of metals; electromagnets and MHD; reliability modelling and system optimization; finite volume, finite element, and boundary element procedures; modelling of inventory, industrial, manufacturing and logistics systems for viable decision making; civil engineering systems and structures; mineral and energy resources; relevant software engineering issues associated with CAD and CAE; and materials and metallurgical engineering. Applied Mathematical Modelling is primarily interested in papers developing increased insights into real-world problems through novel mathematical modelling, novel applications or a combination of these. Papers employing existing numerical techniques must demonstrate sufficient novelty in the solution of practical problems. Papers on fuzzy logic in decision-making or purely financial mathematics are normally not considered. Research on fractional differential equations, bifurcation, and numerical methods needs to include practical examples. Population dynamics must solve realistic scenarios. Papers in the area of logistics and business modelling should demonstrate meaningful managerial insight. Submissions with no real-world application will not be considered.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信