Institutional Repository of Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
| 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
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| Source Publication | IEEE TRANSACTIONS ON CYBERNETICS
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| ISSN | 2168-2267 |
| 2019-12-01 | |
| Volume | 49Issue:12Pages:4167-4179 |
| Corresponding Author | Yin, Yingjie(yingjie.yin@ia.ac.cn) |
| Abstract | In 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. |
| Keyword | Aerial refueling landmark detection monocular vision multitask parallel deep convolution neural network (MPDCNN) position measurement |
| DOI | 10.1109/TCYB.2018.2859422 |
| WOS Keyword | POSE ESTIMATION ; LOCALIZATION ; ALGORITHMS ; STRATEGY ; BOOM |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National 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 Organization | National Natural Science Foundation of China ; National High Technology Research and Development Program of China (863 Program) |
| WOS Research Area | Automation & Control Systems ; Computer Science |
| WOS Subject | Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
| WOS ID | WOS:000485687200010 |
| Publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://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 Author | Yin, Yingjie |
| Affiliation | 1.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 Affilication | Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China |
| Corresponding Author Affilication | Chinese 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. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Robust Landmark Dete（2687KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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