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Robust Landmark Detection and Position Measurement Based on Monocular Vision for Autonomous Aerial Refueling of UAVs
Sun, Siyang1,2; Yin, Yingjie1,2; Wang, Xingang1,2; Xu, De1,2
Source PublicationIEEE TRANSACTIONS ON CYBERNETICS
ISSN2168-2267
2019-12-01
Volume49Issue:12Pages:4167-4179
Corresponding AuthorYin, Yingjie(yingjie.yin@ia.ac.cn)
AbstractIn this paper, a position measurement system, including drogue's landmark detection and position computation for autonomous aerial refueling of unmanned aerial vehicles, is proposed. A multitask parallel deep convolution neural network (MPDCNN) is designed to detect the landmarks of the drogue target. In MPDCNN, two parallel convolution networks are used, and a fusion mechanism is proposed to accomplish the effective fusion of the drogue's two salient parts' landmark detection. Considering the drogue target's geometric constraints, a position measurement method based on monocular vision is proposed. An effective fusion strategy, which fuses the measurement results of drogue's different parts, is proposed to achieve robust position measurement. The error of landmark detection with the proposed method is 3.9%, and it is obviously lower than the errors of other methods. Experimental results on the two KUKA robots platform verify the effectiveness and robustness of the proposed position measurement system for aerial refueling.
KeywordAerial refueling landmark detection monocular vision multitask parallel deep convolution neural network (MPDCNN) position measurement
DOI10.1109/TCYB.2018.2859422
WOS KeywordPOSE ESTIMATION ; LOCALIZATION ; ALGORITHMS ; STRATEGY ; BOOM
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61573349] ; National Natural Science Foundation of China[61421004] ; National Natural Science Foundation of China[61703398] ; National High Technology Research and Development Program of China (863 Program)[2015AA042308]
Funding OrganizationNational Natural Science Foundation of China ; National High Technology Research and Development Program of China (863 Program)
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000485687200010
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21699
Collection精密感知与控制研究中心_精密感知与控制
Corresponding AuthorYin, Yingjie
Affiliation1.Chinese Acad Sci, Res Ctr Precis Sensing & Control, Inst Automat, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Sun, Siyang,Yin, Yingjie,Wang, Xingang,et al. Robust Landmark Detection and Position Measurement Based on Monocular Vision for Autonomous Aerial Refueling of UAVs[J]. IEEE TRANSACTIONS ON CYBERNETICS,2019,49(12):4167-4179.
APA Sun, Siyang,Yin, Yingjie,Wang, Xingang,&Xu, De.(2019).Robust Landmark Detection and Position Measurement Based on Monocular Vision for Autonomous Aerial Refueling of UAVs.IEEE TRANSACTIONS ON CYBERNETICS,49(12),4167-4179.
MLA Sun, Siyang,et al."Robust Landmark Detection and Position Measurement Based on Monocular Vision for Autonomous Aerial Refueling of UAVs".IEEE TRANSACTIONS ON CYBERNETICS 49.12(2019):4167-4179.
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