A monocular vision-based perception approach for unmanned aerial vehicle close proximity transmission tower inspection
文献类型：期刊论文
| 作者 | Bian, Jiang ; Huie, Xiaolong; Zhao, Xiaoguang; Tan, Min; Hui, Xiaolong
|
| 刊名 | INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
 |
| 出版日期 | 2019-01-09 |
| 卷号 | 16期号:1页码:20 |
| 关键词 | Close proximity inspection of transmission tower tower localization UAV self-positioning monocular vision |
| ISSN号 | 1729-8814 |
| DOI | 10.1177/1729881418820227 |
| 通讯作者 | Bian, Jiang(bianjiang2015@ia.ac.cn) |
| 英文摘要 | Employing 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. |
| WOS关键词 | POWER-LINE INSPECTION ; PLACE RECOGNITION ; SEGMENT DETECTOR ; REPRESENTATION ; SURVEILLANCE ; MAINTENANCE ; UAV |
| 资助项目 | National Natural Science Foundation of China[61271432] ; National Natural Science Foundation of China[61673378] ; National Natural Science Foundation of China[61421004] |
| WOS研究方向 | Robotics |
| 语种 | 英语 |
| WOS记录号 | WOS:000455723400001 |
| 出版者 | SAGE PUBLICATIONS INC |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/25323]  |
| 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 | Bian, Jiang |
| 作者单位 | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China |
| 推荐引用方式 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,&Hui, Xiaolong.(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. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。