{"title":"Obstacle Recognition and Localization Based on the Monocular Vision for Double Split Transmission Lines Inspection Robot","authors":"Caishi Hu, Gongping Wu, Heng Cao, Xiaohui Xiao","doi":"10.1109/CISP.2009.5303695","DOIUrl":null,"url":null,"abstract":"Obstacle recognition and location is one of the key techniques for the autonomous transmission line inspection robot. Considering the structure of 220kV double split transmission line, a method of obstacle recognition and location based on the monocular vision is proposed. First of all, capture the image located ahead of the inspection robot with camera, and recognize such obstacles as spacer, counterweight, etc in the image. Then build the geometric model of ranging using the position relation of obstacle’s location center and camera, and calibrate the camera’s intrinsic parameters. At last, put the parameters obtained by calibration into ranging formula to perform the ranging tests. The tests indicate that the method can recognize and locate the obstacles effectively.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"115 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Congress on Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2009.5303695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Obstacle recognition and location is one of the key techniques for the autonomous transmission line inspection robot. Considering the structure of 220kV double split transmission line, a method of obstacle recognition and location based on the monocular vision is proposed. First of all, capture the image located ahead of the inspection robot with camera, and recognize such obstacles as spacer, counterweight, etc in the image. Then build the geometric model of ranging using the position relation of obstacle’s location center and camera, and calibrate the camera’s intrinsic parameters. At last, put the parameters obtained by calibration into ranging formula to perform the ranging tests. The tests indicate that the method can recognize and locate the obstacles effectively.
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