Details of Research Outputs

TitleA Bio-inspired Simultaneous Surface and Underwater Risk Assessment Method Based on Stereo Vision for USVs in Nearshore Clean Waters
Author (Name in English or Pinyin)
Date Issued2022
Source PublicationIEEE Robotics and Automation Letters
ISSN23773766
Volume8Issue:1Pages:360-367
AbstractEnsuring safety of unmanned surface vehicles (USVs) during nearshore field operations is challenging as they face unknown risks of collision with surface and underwater obstacles. To address this problem, we propose a bio-inspired collision risk-assessment method for ensuring safe USVs operation in nearshore clean waters. Collision risks are typically unknown due to the imprecision of underwater measurements for the water-air boundary light refraction, and disturbances caused by wave-induced USV motion. To tackle these two causes of imprecision, our collision risk-assessment method employs one single stereo camera and an IMU. We use visual information from the stereo camera to model the light rays at the water-air interface, rectify the underwater measurements, and monitor for surface obstacles, and IMU data to model wave disturbances via time-frequency analysis. We verify the performance of this new method in both the indoor and outdoor experiments, which demonstrates that it achieves a 65.44% improvement in the depth accuracy at the water-air interface compared with raw depth measurements, and provides a range of safety levels for guiding USV operations. This new collision risk-assessment method significantly expands the USVs working areas while ensuring safety during field exploration. Additionally, the simplicity of the sensor setup and thus minimal cost of this method underscore its utility for supporting USV-based various explorations in clear waters.
KeywordField robots marine robotics risk assessment USVs safety visual perception
DOI10.1109/LRA.2022.3145045
Indexed BySCIE
language英语
Funding ProjectNSFC [U1813217, U1613226]; Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS),; Shenzhen Science and Technology Innovation Commission,China [KQJSCX20180330165912672]
WOS Research AreaRobotics
WOS SubjectRobotics
WOS IDWOS:000896647000015
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Original Document TypeArticle
Firstlevel Discipline计算机科学技术
Education discipline科技类
Published range国外学术期刊
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Data SourceWOS
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttps://irepository.cuhk.edu.cn/handle/3EPUXD0A/3266
CollectionSchool of Science and Engineering
Shenzhen Institute of Artificial Intelligence and Robotics for Society
Corresponding AuthorJi, Xiaoqiang; Qian, Huihuan Alex
Affiliation
1.school of science and engineering, The Chinese University of Hong Kong, Shenzhen, Shenzhen, China, 518172 (e-mail: 217019024@link.cuhk.edu.cn)
2.Electronic Information Engineering, The Chinese University of Hong Kong, Shenzhen, Shen Zhen, China, 518172 (e-mail: 117010166@link.cuhk.edu.cn)
3.School of Science and Engineering, Chinese University of Hong Kong, Shenzhen, Shenzhen, China, 518172 (e-mail: nanxiao@link.cuhk.edu.cn)
4.SSE, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China, 518172 (e-mail: jixiaoqiang@cuhk.edu.cn)
5.Shenzhen Institute of Artificial Intelligence and Robotics for Society, The Chinese University of Hong Kong, Shenzhen, Shenzhen, China, 518172 (e-mail: hhqian@cuhk.edu.cn)
First Author AffilicationSchool of Science and Engineering
Corresponding Author AffilicationShenzhen Institute of Artificial Intelligence and Robotics for Society
Recommended Citation
GB/T 7714
Xue, Kaiwen,Liu, Jiawei,Xiao, Nanet al. A Bio-inspired Simultaneous Surface and Underwater Risk Assessment Method Based on Stereo Vision for USVs in Nearshore Clean Waters[J]. IEEE Robotics and Automation Letters,2022,8(1):360-367.
APA Xue, Kaiwen, Liu, Jiawei, Xiao, Nan, Ji, Xiaoqiang, & Qian, Huihuan Alex. (2022). A Bio-inspired Simultaneous Surface and Underwater Risk Assessment Method Based on Stereo Vision for USVs in Nearshore Clean Waters. IEEE Robotics and Automation Letters, 8(1), 360-367.
MLA Xue, Kaiwen,et al."A Bio-inspired Simultaneous Surface and Underwater Risk Assessment Method Based on Stereo Vision for USVs in Nearshore Clean Waters".IEEE Robotics and Automation Letters 8.1(2022):360-367.
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