A novel robotic visual perception framework for underwater operation

doi:10.1631/FITEE.2100366

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进机器人控制团队

	A novel robotic visual perception framework for underwater operation
	Lu, Yue 4; Chen, Xingyu 3; Wu, Zhengxing 4; Yu, Junzhi 2,4; Wen, Li 1
刊名	FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
	2022-05-31
页码	18
关键词	Underwater operation Robotic perception Visual restoration Video object detection
ISSN号	2095-9184
DOI	10.1631/FITEE.2100366
通讯作者	Yu, Junzhi(junzhi.yu@ia.ac.cn)
英文摘要	Underwater 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 .
资助项目	National 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]
WOS关键词	OBJECT DETECTION ; QUALITY ; IMAGES
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	ZHEJIANG UNIV PRESS
WOS记录号	WOS:000803783300001
资助机构	National Natural Science Foundation of China ; S&T Program of Hebei Province, China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/49485]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者	Yu, Junzhi
作者单位	1.Beihang Univ, Sch Mech Engn & Automat, Beijing 100191, Peoples R China 2.Peking Univ, Coll Engn, Dept Adv Mfg & Robot, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China 3.Kuaishou Technol, Ytech, Beijing 100085, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 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.