Knowledge Commons of Institute of Automation,CAS
Environment Perception Technologies for Power Transmission Line Inspection Robots | |
Chen, Minghao1,2; Tian, Yunong1,2; Xing, Shiyu1,2; Li, Zhishuo1,2; Li, En1,2; Liang, Zize1,2; Guo, Rui3 | |
发表期刊 | JOURNAL OF SENSORS |
ISSN | 1687-725X |
2021-03-31 | |
卷号 | 2021页码:16 |
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 |
国重实验室规划方向分类 | 人-机-算法混合与协同决策 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
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. |
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二作论文1-陈铭浩:Environmen(2248KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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