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Structured Light-Based Underwater Collision-Free Navigation and Dense Mapping System for Refined Exploration in Unknown Dark Environments

文献类型：期刊论文

作者Ou, Yaming1,2; Fan, Junfeng1; Zhou, Chao1; Kang, Song1; Zhang, Zhuoliang1; Hou, Zeng-Guang3; Tan, Min1
刊名IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
出版日期2024-03-18
页码14
关键词Refined exploration structured light vision underwater collision-free navigation underwater dense mapping
ISSN号2168-2216
DOI10.1109/TSMC.2024.3370917
通讯作者Fan, Junfeng(junfeng.fan@ia.ac.cn) ; Zhou, Chao(chao.zhou@ia.ac.cn)
英文摘要Underwater collision-free navigation and dense reconstruction are essential for marine refined exploration. However, existing passive vision-based methods are difficult to apply in low-light and weak-feature underwater environments. In this article, a more adaptable three-dimensional (3-D) dense mapping robotic system based on self-designed scanning binocular structured light (BSL), named ROV-Scanner, is developed to address this challenge. First, the measurement principle based on the refraction model ensures its high accuracy. Second, an underwater 3-D dense mapping algorithm fusing the Doppler velocity log (DVL), inertial measurement unit (IMU), and pressure sensor multifrequency information is proposed to realize dense mapping during robot motion. Then, an air-water two-stage extrinsic calibration algorithm is proposed. In particular, the extrinsic parameters between DVL and camera are innovatively calibrated using BSL, enhancing robustness. Furthermore, for the first time, a framework of BSL-based collision-free navigation is presented to guarantee the safe movement of the system in unknown environments. Experimental results show that our system can simultaneously achieve autonomous collision-free navigation and dense mapping in dark underwater environments, which has great potential for application in marine refined exploration.
WOS关键词CAMERA
资助项目National Natural Science Foundation of China
WOS研究方向Automation & Control Systems ; Computer Science
语种英语
WOS记录号WOS:001189480800001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/58032]  
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
3.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		 Ou, Yaming,Fan, Junfeng,Zhou, Chao,et al. Structured Light-Based Underwater Collision-Free Navigation and Dense Mapping System for Refined Exploration in Unknown Dark Environments[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2024:14.
APA Ou, Yaming.,Fan, Junfeng.,Zhou, Chao.,Kang, Song.,Zhang, Zhuoliang.,...&Tan, Min.(2024).Structured Light-Based Underwater Collision-Free Navigation and Dense Mapping System for Refined Exploration in Unknown Dark Environments.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,14.
MLA Ou, Yaming,et al."Structured Light-Based Underwater Collision-Free Navigation and Dense Mapping System for Refined Exploration in Unknown Dark Environments".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2024):14.

入库方式： OAI收割

来源：自动化研究所

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