CASIA OpenIR
A monocular vision-based perception approach for unmanned aerial vehicle close proximity transmission tower inspection
Bian, Jiang; Huie, Xiaolong; Zhao, Xiaoguang; Tan, Min
Source PublicationINTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
ISSN1729-8814
2019-01-09
Volume16Issue:1Pages:20
Corresponding AuthorBian, Jiang(bianjiang2015@ia.ac.cn)
AbstractEmploying unmanned aerial vehicles to conduct close proximity inspection of transmission tower is becoming increasingly common. This article aims to solve the two key problems of close proximity navigation-localizing tower and simultaneously estimating the unmanned aerial vehicle positions. To this end, we propose a novel monocular vision-based environmental perception approach and implement it in a hierarchical embedded unmanned aerial vehicle system. The proposed framework comprises tower localization and an improved point-line-based simultaneous localization and mapping framework consisting of feature matching, frame tracking, local mapping, loop closure, and nonlinear optimization. To enhance frame association, the prominent line feature of tower is heuristically extracted and matched followed by the intersections of lines are processed as the point feature. Then, the bundle adjustment optimization leverages the intersections of lines and the point-to-line distance to improve the accuracy of unmanned aerial vehicle localization. For tower localization, a transmission tower data set is created and a concise deep learning-based neural network is designed to perform real-time and accurate tower detection. Then, it is in combination with a keyframe-based semi-dense mapping to locate the tower with a clear line-shaped structure in 3-D space. Additionally, two reasonable paths are planned for the refined inspection. In experiments, the whole unmanned aerial vehicle system developed on Robot Operating System framework is evaluated along the paths both in a synthetic scene and in a real-world inspection environment. The final results show that the accuracy of unmanned aerial vehicle localization is improved, and the tower reconstruction is fast and clear. Based on our approach, the safe and autonomous unmanned aerial vehicle close proximity inspection of transmission tower can be realized.
KeywordClose proximity inspection of transmission tower tower localization UAV self-positioning monocular vision
DOI10.1177/1729881418820227
WOS KeywordPOWER-LINE INSPECTION ; PLACE RECOGNITION ; SEGMENT DETECTOR ; REPRESENTATION ; SURVEILLANCE ; MAINTENANCE ; UAV
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61271432] ; National Natural Science Foundation of China[61673378] ; National Natural Science Foundation of China[61421004]
Funding OrganizationNational Natural Science Foundation of China
WOS Research AreaRobotics
WOS SubjectRobotics
WOS IDWOS:000455723400001
PublisherSAGE PUBLICATIONS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/25324
Collection中国科学院自动化研究所
Corresponding AuthorBian, Jiang
AffiliationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, 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
Bian, Jiang,Huie, Xiaolong,Zhao, Xiaoguang,et al. A monocular vision-based perception approach for unmanned aerial vehicle close proximity transmission tower inspection[J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,2019,16(1):20.
APA Bian, Jiang,Huie, Xiaolong,Zhao, Xiaoguang,&Tan, Min.(2019).A monocular vision-based perception approach for unmanned aerial vehicle close proximity transmission tower inspection.INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,16(1),20.
MLA Bian, Jiang,et al."A monocular vision-based perception approach for unmanned aerial vehicle close proximity transmission tower inspection".INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 16.1(2019):20.
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