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Water-MBSL: Underwater Movable Binocular Structured Light-Based High-Precision Dense Reconstruction Framework | |
Ou, Yaming1,2; Fan, Junfeng1![]() ![]() ![]() ![]() | |
发表期刊 | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
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ISSN | 1551-3203 |
2023-12-29 | |
页码 | 13 |
通讯作者 | Fan, Junfeng() ; Zhou, Chao() |
摘要 | Structured light systems are widely used in underwater dense reconstruction due to their excellent accuracy. However, the current related methods mainly focus on fixed positions. The reconstruction performance in motion is insufficient. Therefore, we propose an underwater movable binocular structured light (MBSL) based high-precision dense reconstruction framework, named WaterMBSL, to realize the robot reconstruction while moving. Specifically, an onboard binocular structured light system based on mirror-galvanometer is developed first. Then, a simplified underwater point cloud acquisition algorithm is presented to quickly obtain 3-D information of the scene. Besides, a new underwater motion compensation algorithm combining inertial measurement unit and uniform velocity model is proposed. Moreover, the generalized-ICP point cloud registration algorithm is introduced to achieve accurate motion estimation. Finally, an underwater movable reconstruction platform is developed by integrating the self-designed structured light system with the underwater robot BlueROV for validating the performance of our proposed Water-MBSL. Experimental results show that satisfactory motion reconstruction performance can be obtained. |
关键词 | Motion reconstruction structured light underwater 3-D reconstruction underwater exploration |
DOI | 10.1109/TII.2023.3342899 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Beijing Natural Science Foundation |
项目资助者 | Beijing Natural Science Foundation |
WOS研究方向 | Automation & Control Systems ; Computer Science ; Engineering |
WOS类目 | Automation & Control Systems ; Computer Science, Interdisciplinary Applications ; Engineering, Industrial |
WOS记录号 | WOS:001137388200001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/54857 |
专题 | 多模态人工智能系统全国重点实验室 复杂系统认知与决策实验室 |
通讯作者 | Fan, Junfeng; Zhou, Chao |
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 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Ou, Yaming,Fan, Junfeng,Zhou, Chao,et al. Water-MBSL: Underwater Movable Binocular Structured Light-Based High-Precision Dense Reconstruction Framework[J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,2023:13. |
APA | Ou, Yaming,Fan, Junfeng,Zhou, Chao,Cheng, Long,&Tan, Min.(2023).Water-MBSL: Underwater Movable Binocular Structured Light-Based High-Precision Dense Reconstruction Framework.IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS,13. |
MLA | Ou, Yaming,et al."Water-MBSL: Underwater Movable Binocular Structured Light-Based High-Precision Dense Reconstruction Framework".IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2023):13. |
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