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Vision-based autonomous navigation approach for unmanned aerial vehicle transmission-line inspection
Hui, Xiaolong; Bian, Jiang; Zhao, Xiaoguang; Tan, Min
Source PublicationINTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
2018-01-21
Volume15Issue:1Pages:1-15
SubtypeArticle
AbstractThis article presents an autonomous navigation approach based on a transmission tower for unmanned aerial vehicle (UAV) power line inspection. For this complex vision task, a perspective navigation model, which plays an important role in the description and analysis of the flight strategy, is introduced. Based on the proposed navigation model, valuable cues are excavated from a perspective image, which enhances the capability of the perception of three-dimensional direction and simultaneously improves the safety of intelligent inspection. Specifically, for robust and continuous localization of the transmission tower, a developed detecting-tracking visual strategycomprised tower detection based on a faster region-based convolutional neural network and tower tracking by kernelized correlation filtersis presented. Further, segmentation by fully convolutional networks is applied to the extraction of transmission lines, from which the vanishing point (VP), an important basis for determining the flight heading, can be obtained. For more robust navigation, the designed scheme addresses the scenario of a nonexistent VP. Finally, the proposed navigation approach and constructed UAV platform were evaluated in a practical environment and achieved satisfactory results. To the best of our knowledge, this article marks the first time that a navigation approach based on a transmission tower is proposed and implemented.
KeywordUnmanned Aerial Vehicle Intelligent Inspection Three-dimensional (3-d) Perception Visual Navigation
WOS HeadingsScience & Technology ; Technology
DOI10.1177/1729881417752821
WOS KeywordVANISHING-POINT DETECTION ; FALSE DETECTION CONTROL ; SEGMENT DETECTOR ; FILTERS ; UAV
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61673378 ; 61421004)
WOS Research AreaRobotics
WOS SubjectRobotics
WOS IDWOS:000422921400001
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20906
Collection复杂系统管理与控制国家重点实验室_先进机器人
Corresponding AuthorHui, Xiaolong
AffiliationUniv Chinese Acad Sci, Inst Automat, Chinese Acad Sci, 95 ZhongGuanCun East Rd, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Hui, Xiaolong,Bian, Jiang,Zhao, Xiaoguang,et al. Vision-based autonomous navigation approach for unmanned aerial vehicle transmission-line inspection[J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,2018,15(1):1-15.
APA Hui, Xiaolong,Bian, Jiang,Zhao, Xiaoguang,&Tan, Min.(2018).Vision-based autonomous navigation approach for unmanned aerial vehicle transmission-line inspection.INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,15(1),1-15.
MLA Hui, Xiaolong,et al."Vision-based autonomous navigation approach for unmanned aerial vehicle transmission-line inspection".INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 15.1(2018):1-15.
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