SIA OpenIR  > 空间自动化技术研究室
基于视觉方法的输电线断股检测与机器人行为规划
Alternative TitleVision Based Transmission Line Broken Strand Detection and Robot Behaviour Planning
宋屹峰; 王洪光; 李贞辉; 姜勇
Department空间自动化技术研究室
Source Publication机器人
ISSN1002-0446
2015
Volume37Issue:2Pages:204-211, 223
Indexed ByEI ; CSCD
EI Accession number20152300924823
CSCD IDCSCD:5414399
Contribution Rank1
Funding Organization国家自然科学基金资助项目(61179049) ; 辽宁省自然科学基金资助项目(2013020054)
Keyword电力机器人 断股检测 行为规划 支持向量机
Abstract输电线维护机器人用于代替人工完成危险作业,准确的故障检测与合理的行为规划对于作业效果至关重要.针对以上需求,采用视觉方法,提出了一种基于图像特征分类的输电线断股检测方法.该方法提取边缘梯度向量作为图像特征,采用支持向量机方法进行分类运算完成线路断股检测.在断股检测的基础上,利用断股检测信息与机器人传感器测得的信息构建机器人状态向量.根据当前状态向量,结合机器人断股补修作业流程,提出了面向捋线与压接复杂作业的机器人断股补修作业行为规划方法.利用实验室模拟线路开展实验,验证了提出的输电线断股检测及行为规划方法的有效性.
Other AbstractPower line maintenance robots are used to replace workers due to the dangerous maintenance operation, and the robot maintenance effect is much related with accurate fault detection and rational behavior planning. With those requirements in mind, a visual method is presented to detect the broken strand fault based on the classification of an image feature. In the visual detection method, image edge gradient histogram is firstly extracted as the image feature, and broken strand detection can be accomplished by the classification of the image feature with support vector machine (SVM) method. On this basis, several robot state vectors are established by combining the broken strand detection result and the information of robot sensors. Based on the current state vector and robotic broken strand repair process, a behavior planning method for broken strand repair is proposed toward complex operations of broken strand return and clamps installation. Experiments are carried out in the laboratory, and results demonstrate the effectiveness of the proposed broken strand detection method and the behavior planning method.
Language中文
Citation statistics
Cited Times:6[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/16189
Collection空间自动化技术研究室
Affiliation1.中国科学院沈阳自动化研究所机器人学国家重点实验室
2.中国科学院大学
Recommended Citation
GB/T 7714
宋屹峰,王洪光,李贞辉,等. 基于视觉方法的输电线断股检测与机器人行为规划[J]. 机器人,2015,37(2):204-211, 223.
APA 宋屹峰,王洪光,李贞辉,&姜勇.(2015).基于视觉方法的输电线断股检测与机器人行为规划.机器人,37(2),204-211, 223.
MLA 宋屹峰,et al."基于视觉方法的输电线断股检测与机器人行为规划".机器人 37.2(2015):204-211, 223.
Files in This Item: Download All
File Name/Size DocType Version Access License
基于视觉方法的输电线断股检测与机器人行为(1080KB)期刊论文出版稿开放获取ODC PDDLView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[宋屹峰]'s Articles
[王洪光]'s Articles
[李贞辉]'s Articles
Baidu academic
Similar articles in Baidu academic
[宋屹峰]'s Articles
[王洪光]'s Articles
[李贞辉]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[宋屹峰]'s Articles
[王洪光]'s Articles
[李贞辉]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 基于视觉方法的输电线断股检测与机器人行为规划.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.