{"title":"使用单摄像头和测地线方向道路标志的地面车辆视觉定位","authors":"R. Bikmaev, A. Polukarov, R. N. Sadekov","doi":"10.23919/icins43215.2020.9133769","DOIUrl":null,"url":null,"abstract":"The work explores the on-board navigation system of the moving object, which includes a camera, odometer and steering sensor. The navigation algorithm is based on the method of visual odometry compensated by the data of recognized road signs. Recognition of road signs is carried out on the basis of a roll-out neural network. The algorithm is tested on natural data.","PeriodicalId":127936,"journal":{"name":"2020 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Visual Localization of a Ground Vehicle Using a Monocamera and Geodesic-Bound Road Signs\",\"authors\":\"R. Bikmaev, A. Polukarov, R. N. Sadekov\",\"doi\":\"10.23919/icins43215.2020.9133769\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The work explores the on-board navigation system of the moving object, which includes a camera, odometer and steering sensor. The navigation algorithm is based on the method of visual odometry compensated by the data of recognized road signs. Recognition of road signs is carried out on the basis of a roll-out neural network. The algorithm is tested on natural data.\",\"PeriodicalId\":127936,\"journal\":{\"name\":\"2020 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/icins43215.2020.9133769\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/icins43215.2020.9133769","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Visual Localization of a Ground Vehicle Using a Monocamera and Geodesic-Bound Road Signs
The work explores the on-board navigation system of the moving object, which includes a camera, odometer and steering sensor. The navigation algorithm is based on the method of visual odometry compensated by the data of recognized road signs. Recognition of road signs is carried out on the basis of a roll-out neural network. The algorithm is tested on natural data.