CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
A novel robotic visual perception framework for underwater operation
Lu, Yue1; Chen, Xingyu2; Wu, Zhengxing1; Yu, Junzhi1,3; Wen, Li4
Source PublicationFRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
ISSN2095-9184
2022-05-31
Pages18
Corresponding AuthorYu, Junzhi(junzhi.yu@ia.ac.cn)
AbstractUnderwater robotic operation usually requires visual perception (e.g., object detection and tracking), but underwater scenes have poor visual quality and represent a special domain which can affect the accuracy of visual perception. In addition, detection continuity and stability are important for robotic perception, but the commonly used static accuracy based evaluation (i.e., average precision) is insufficient to reflect detector performance across time. In response to these two problems, we present a design for a novel robotic visual perception framework. First, we generally investigate the relationship between a quality-diverse data domain and visual restoration in detection performance. As a result, although domain quality has an ignorable effect on within-domain detection accuracy, visual restoration is beneficial to detection in real sea scenarios by reducing the domain shift. Moreover, non-reference assessments are proposed for detection continuity and stability based on object tracklets. Further, online tracklet refinement is developed to improve the temporal performance of detectors. Finally, combined with visual restoration, an accurate and stable underwater robotic visual perception framework is established. Small-overlap suppression is proposed to extend video object detection (VID) methods to a single-object tracking task, leading to the flexibility to switch between detection and tracking. Extensive experiments were conducted on the ImageNet VID dataset and real-world robotic tasks to verify the correctness of our analysis and the superiority of our proposed approaches. The codes are available at .
KeywordUnderwater operation Robotic perception Visual restoration Video object detection
DOI10.1631/FITEE.2100366
WOS KeywordOBJECT DETECTION ; QUALITY ; IMAGES
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61633004] ; National Natural Science Foundation of China[61725305] ; National Natural Science Foundation of China[62073196] ; S&T Program of Hebei Province, China[F2020203037]
Funding OrganizationNational Natural Science Foundation of China ; S&T Program of Hebei Province, China
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Engineering, Electrical & Electronic
WOS IDWOS:000803783300001
PublisherZHEJIANG UNIV PRESS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/49486
Collection复杂系统管理与控制国家重点实验室_先进机器人
复杂系统管理与控制国家重点实验室
复杂系统管理与控制国家重点实验室_水下机器人
Corresponding AuthorYu, Junzhi
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Kuaishou Technol, Ytech, Beijing 100085, Peoples R China
3.Peking Univ, Coll Engn, Dept Adv Mfg & Robot, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
4.Beihang Univ, Sch Mech Engn & Automat, Beijing 100191, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Lu, Yue,Chen, Xingyu,Wu, Zhengxing,et al. A novel robotic visual perception framework for underwater operation[J]. FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING,2022:18.
APA Lu, Yue,Chen, Xingyu,Wu, Zhengxing,Yu, Junzhi,&Wen, Li.(2022).A novel robotic visual perception framework for underwater operation.FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING,18.
MLA Lu, Yue,et al."A novel robotic visual perception framework for underwater operation".FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING (2022):18.
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