Hierarchical formation control technology for multiple autonomous underwater vehicles

IF 2.7 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IET Smart Grid Pub Date : 2025-01-24 DOI:10.1049/stg2.12209
Shibo Fan, Jie Jiao, Pengfeng Lin, Qingzuo Meng
{"title":"Hierarchical formation control technology for multiple autonomous underwater vehicles","authors":"Shibo Fan,&nbsp;Jie Jiao,&nbsp;Pengfeng Lin,&nbsp;Qingzuo Meng","doi":"10.1049/stg2.12209","DOIUrl":null,"url":null,"abstract":"<p>The employment of multiple AUVs is to perform missions while maintaining a geometric formation designated. In this paper, communication mechanism based on blackboard is introduced to support cooperation between AUVs, messages are typed according to artificial intelligence. The hierarchical formation control algorithm is proposed, including designing level, generating level, behavioural level, evaluating level. Several formation patterns are designed according to different tasks and requirements. Orderly-Quaternion sets and control matrix are defined for the design of accurate formation geometry. Behaviours of following subgoals and avoiding obstacles enable AUVs team move forward to destination by keeping ideal pattern. Formation length rate and formation maintaining rate are utilised for AUVs team to evaluate the effect of formation. Finally, the presented approach is verified by a simulation of a swarm of AUVs moving through a constrained environment.</p>","PeriodicalId":36490,"journal":{"name":"IET Smart Grid","volume":"8 1","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/stg2.12209","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Smart Grid","FirstCategoryId":"1085","ListUrlMain":"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/stg2.12209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

The employment of multiple AUVs is to perform missions while maintaining a geometric formation designated. In this paper, communication mechanism based on blackboard is introduced to support cooperation between AUVs, messages are typed according to artificial intelligence. The hierarchical formation control algorithm is proposed, including designing level, generating level, behavioural level, evaluating level. Several formation patterns are designed according to different tasks and requirements. Orderly-Quaternion sets and control matrix are defined for the design of accurate formation geometry. Behaviours of following subgoals and avoiding obstacles enable AUVs team move forward to destination by keeping ideal pattern. Formation length rate and formation maintaining rate are utilised for AUVs team to evaluate the effect of formation. Finally, the presented approach is verified by a simulation of a swarm of AUVs moving through a constrained environment.

Abstract Image

Abstract Image

Abstract Image

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
多自主潜水器的分层编队控制技术
使用多个auv是为了执行任务,同时保持指定的几何编队。本文引入了基于黑板的通信机制,支持水下机器人之间的协作,并根据人工智能进行消息输入。提出了分层编队控制算法,包括设计关卡、生成关卡、行为关卡、评价关卡。根据不同的任务和要求,设计了几种编队模式。定义了有序四元数集和控制矩阵,用于精确的地层几何设计。跟随子目标和避开障碍物的行为使auv团队能够保持理想模式向目的地前进。水下机器人团队利用地层长度速率和地层保持速率来评估地层效果。最后,通过对一群auv在受限环境中移动的仿真验证了所提出的方法。
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 去求助
来源期刊
IET Smart Grid
IET Smart Grid Computer Science-Computer Networks and Communications
CiteScore
6.70
自引率
4.30%
发文量
41
审稿时长
29 weeks
期刊最新文献
Optimal Planning for Public Charging Infrastructure by Behaviour-Based Electric Vehicle Charging Demand Simulations and Geographic Information System Robust Operation Method for Renewable-Integrated Port-Ship System With Ship-Participated Grid-Forming Control Multi-Energy Sharing Framework and Coordinated Operation Technologies in Integrated Energy Systems: A Review Multi-Microgrids Optimal Scheduling Incorporating CO2 and Peer-to-Peer Energy Trading Considering Demand Response and Electric Vehicle Loads Using Adaptive Robust Optimisation Optimal Hardening Model for Reliable and Resilient Cyber–Physical Power Systems
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1