Environment Perception Technologies for Power Transmission Line Inspection Robots

doi:10.1155/2021/5559231

	Environment Perception Technologies for Power Transmission Line Inspection Robots
	Chen, Minghao1,2 ; Tian, Yunong1,2 ; Xing, Shiyu 1,2; Li, Zhishuo 1,2; Li, En1,2 ; Liang, Zize1,2 ; Guo, Rui 3
发表期刊	JOURNAL OF SENSORS
ISSN	1687-725X
	2021-03-31
卷号	2021 页码:16
通讯作者	Li, En(en.li@ia.ac.cn)
摘要	With the fast development of the power system, traditional manual inspection methods of a power transmission line (PTL) cannot supply the demand for high quality and dependability for power grid maintenance. Consequently, the automatic PTL inspection technology becomes one of the key research focuses. For the purpose of summarizing related studies on environment perception and control technologies of PTL inspection, technologies of three-dimensional (3D) reconstruction, object detection, and visual servo of PTL inspection are reviewed, respectively. Firstly, 3D reconstruction of PTL inspection is reviewed and analyzed, especially for the technology of LiDAR-based reconstruction of power lines. Secondly, the technology of typical object detection, including pylons, insulators, and power line accessories, is classified as traditional and deep learning-based methods. After that, their merits and demerits are considered. Thirdly, the progress and issues of visual servo control of inspection robots are also concisely addressed. For improving the automation degree of PTL robots, current problems of key techniques, such as multisensor fusion and the establishment of datasets, are discussed and the prospect of inspection robots is presented.
DOI	10.1155/2021/5559231
关键词[WOS]	SCALE ; UAV
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018YFB1307400] ; National Natural Science Foundation of China[61873267]
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China
WOS研究方向	Engineering ; Instruments & Instrumentation
WOS类目	Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS记录号	WOS:000640265900004
出版者	HINDAWI LTD
七大方向——子方向分类	机器人感知与决策
引用统计	被引频次：10[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/44549
专题	复杂系统认知与决策实验室_先进机器人
通讯作者	Li, En
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, 19 A Yuquan Rd, Beijing 100049, Peoples R China 3.State Grid Shandong Elect Power Co, 150 Jinger Rd, Jinan 250001, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Chen, Minghao,Tian, Yunong,Xing, Shiyu,et al. Environment Perception Technologies for Power Transmission Line Inspection Robots[J]. JOURNAL OF SENSORS,2021,2021:16.
APA	Chen, Minghao.,Tian, Yunong.,Xing, Shiyu.,Li, Zhishuo.,Li, En.,...&Guo, Rui.(2021).Environment Perception Technologies for Power Transmission Line Inspection Robots.JOURNAL OF SENSORS,2021,16.
MLA	Chen, Minghao,et al."Environment Perception Technologies for Power Transmission Line Inspection Robots".JOURNAL OF SENSORS 2021(2021):16.