Cheng-Pei Tsai, C. Chuang, Ming-Chih Lu, Wei-Yen Wang, S. Su, Shyang-Lih Chang
{"title":"Machine-vision based obstacle avoidance system for robot system","authors":"Cheng-Pei Tsai, C. Chuang, Ming-Chih Lu, Wei-Yen Wang, S. Su, Shyang-Lih Chang","doi":"10.1109/ICSSE.2013.6614673","DOIUrl":null,"url":null,"abstract":"In this paper, we proposed a machine-vision based obstacle avoidance system for robot system by using single camera, it could accomplished an obstacle avoidance and path planning. The structure of this system is using a camera and two laser projectors fixed on same base. When robot get into a unknown environment, it will stop and capture an image, the system use several simple image process steps to recognize the obstacle. The system will rotate the base to project the laser points on obstacle, the distance measurement results calculated by IBDMS method, when the system calculated the distance between obstacle and robot, it could planned the path to achieve the autonomous patrol.","PeriodicalId":124317,"journal":{"name":"2013 International Conference on System Science and Engineering (ICSSE)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE.2013.6614673","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper, we proposed a machine-vision based obstacle avoidance system for robot system by using single camera, it could accomplished an obstacle avoidance and path planning. The structure of this system is using a camera and two laser projectors fixed on same base. When robot get into a unknown environment, it will stop and capture an image, the system use several simple image process steps to recognize the obstacle. The system will rotate the base to project the laser points on obstacle, the distance measurement results calculated by IBDMS method, when the system calculated the distance between obstacle and robot, it could planned the path to achieve the autonomous patrol.