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Structured Light Vision Based Pipeline Tracking and 3D Reconstruction Method for Underwater Vehicle

文献类型：期刊论文

作者Fan, Junfeng1; Ou, Yaming1,2; Li, Xuan3; Zhou, Chao1; Hou, Zengguang4
刊名IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
出版日期2024-02-01
卷号9期号:2页码:3372-3383
关键词Pipelines Underwater vehicles Inspection Three-dimensional displays Sensors Synthetic aperture sonar Magnetic sensors Underwater vehicle structured light vision underwater pipeline underwater 3D reconstruction
ISSN号2379-8858
DOI10.1109/TIV.2023.3340737
通讯作者Ou, Yaming(ouyaming2021@ia.ac.cn) ; Li, Xuan(lix05@pcl.ac.cn)
英文摘要The inspection of underwater pipeline by underwater vehicles is of great significance to ensure safe transportation. However, most of underwater pipeline inspection methods have disadvantages such as low precision, low resolution and less information, and cannot realize the fine three-dimensional (3D) reconstruction of underwater pipelines. In order to address these problems, an underwater pipeline tracking and 3D reconstruction method for underwater vehicle based on structured light vision (SLV) is proposed. Firstly, a dual-line laser SLV is developed, and a new underwater pipeline positioning method is proposed, which can simultaneously obtain the lateral deviation, height deviation and heading deviation of underwater vehicle and underwater pipeline under weak light water environment. Then, by combining laser stripe image feature points, refracted underwater SLV model and Doppler Velocity Log (DVL) information, underwater pipeline tracking and dense 3D reconstruction are realized. Finally, by integrating the self-designed underwater SLV sensor with the underwater vehicle BlueROV, an underwater pipeline tracking and 3D reconstruction system is developed. A series of planar and spatial pipeline tracking and 3D reconstruction experiments demonstrate the effectiveness of the proposed method.
WOS关键词CALIBRATION ; SENSOR ; SYSTEM
资助项目Beijing Natural Science Foundation
WOS研究方向Computer Science ; Engineering ; Transportation
语种英语
WOS记录号WOS:001215322100042
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构Beijing Natural Science Foundation
源URL[http://ir.ia.ac.cn/handle/173211/59046]  
专题复杂系统管理与控制国家重点实验室_水下机器人
通讯作者Ou, Yaming; Li, Xuan
作者单位1.Chinese Acad Sci, Inst Automat, Lab Cognit & Decis Intelligence Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.Peng Cheng Lab, Shenzhen 518000, Peoples R China
4.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Fan, Junfeng,Ou, Yaming,Li, Xuan,et al. Structured Light Vision Based Pipeline Tracking and 3D Reconstruction Method for Underwater Vehicle[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2024,9(2):3372-3383.
APA Fan, Junfeng,Ou, Yaming,Li, Xuan,Zhou, Chao,&Hou, Zengguang.(2024).Structured Light Vision Based Pipeline Tracking and 3D Reconstruction Method for Underwater Vehicle.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,9(2),3372-3383.
MLA Fan, Junfeng,et al."Structured Light Vision Based Pipeline Tracking and 3D Reconstruction Method for Underwater Vehicle".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 9.2(2024):3372-3383.

入库方式： OAI收割

来源：自动化研究所

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