{"title":"基于墙-地板边界线的平板电脑AGV自主运行控制系统","authors":"Anar Zorig, Atsushi Haginiwa, Hiroyuki Sato","doi":"10.1109/CIVTS.2014.7009486","DOIUrl":null,"url":null,"abstract":"In our research, we have studied the autonomous running control system of the automatic guided vehicles (AGV) used in the manufacturing facilities using the tablet PC. The moving direction of automatic vehicle is controlled by the results of image processing methods on captured images of the tablet PC. In the image processing step, after detecting edges we obtain wall-floor boundaries by analyzing those edges. By applying the least square method on the wall-floor boundaries, we calculate the moving direction of the AGV. To improve the accuracy of the moving direction, we divide the edge detection image into grid cells and remove all edges in cells with sparse edges. Furthermore, we divided all boundary points into vertical subdivisions, estimated unusual small boundaries and discarded them. As a result of our research, the running distance of the AGV was improved from 10 meters to the whole length of the testing course. The distance of testing course is 100 meters long.","PeriodicalId":283766,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Autonomous running control system of an AGV by a tablet PC based on the wall-floor boundary line\",\"authors\":\"Anar Zorig, Atsushi Haginiwa, Hiroyuki Sato\",\"doi\":\"10.1109/CIVTS.2014.7009486\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In our research, we have studied the autonomous running control system of the automatic guided vehicles (AGV) used in the manufacturing facilities using the tablet PC. The moving direction of automatic vehicle is controlled by the results of image processing methods on captured images of the tablet PC. In the image processing step, after detecting edges we obtain wall-floor boundaries by analyzing those edges. By applying the least square method on the wall-floor boundaries, we calculate the moving direction of the AGV. To improve the accuracy of the moving direction, we divide the edge detection image into grid cells and remove all edges in cells with sparse edges. Furthermore, we divided all boundary points into vertical subdivisions, estimated unusual small boundaries and discarded them. As a result of our research, the running distance of the AGV was improved from 10 meters to the whole length of the testing course. The distance of testing course is 100 meters long.\",\"PeriodicalId\":283766,\"journal\":{\"name\":\"2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIVTS.2014.7009486\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIVTS.2014.7009486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Autonomous running control system of an AGV by a tablet PC based on the wall-floor boundary line
In our research, we have studied the autonomous running control system of the automatic guided vehicles (AGV) used in the manufacturing facilities using the tablet PC. The moving direction of automatic vehicle is controlled by the results of image processing methods on captured images of the tablet PC. In the image processing step, after detecting edges we obtain wall-floor boundaries by analyzing those edges. By applying the least square method on the wall-floor boundaries, we calculate the moving direction of the AGV. To improve the accuracy of the moving direction, we divide the edge detection image into grid cells and remove all edges in cells with sparse edges. Furthermore, we divided all boundary points into vertical subdivisions, estimated unusual small boundaries and discarded them. As a result of our research, the running distance of the AGV was improved from 10 meters to the whole length of the testing course. The distance of testing course is 100 meters long.