Dunyang Geng, Changsheng Ai, Lei Zheng, Zhengguang Qi, Zhiquan Feng, Jiebing Yan
{"title":"基于双目摄像机的车道定位与导航技术研究","authors":"Dunyang Geng, Changsheng Ai, Lei Zheng, Zhengguang Qi, Zhiquan Feng, Jiebing Yan","doi":"10.1145/3501409.3501435","DOIUrl":null,"url":null,"abstract":"Aiming at the problem that the traditional single sensor of AGV cannot meet the indoor and outdoor operating conditions and the cost of multi-sensor is too high, this paper studies a navigation method for lane detection and positioning based on binocular camera. Based on the analysis of lane line equation coefficient variation, several dynamic filtering noise reduction methods are compared. The results show that the lane line detection method based on feature can accurately extract the lane line in multi-scenario. The variance of Kalman filter method is at least one order of magnitude lower than that of other filtering methods, which can effectively improve the stability of the system. According to the lane line equation, a relatively stable body posture deviation is obtained. The extracted yaw angle is less than 1 degree and the lateral deviation is less than 4 cm, which provides a basis for AGV vehicle control","PeriodicalId":191106,"journal":{"name":"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Lane Location and Navigation Technology Based on Binocular Camera\",\"authors\":\"Dunyang Geng, Changsheng Ai, Lei Zheng, Zhengguang Qi, Zhiquan Feng, Jiebing Yan\",\"doi\":\"10.1145/3501409.3501435\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the problem that the traditional single sensor of AGV cannot meet the indoor and outdoor operating conditions and the cost of multi-sensor is too high, this paper studies a navigation method for lane detection and positioning based on binocular camera. Based on the analysis of lane line equation coefficient variation, several dynamic filtering noise reduction methods are compared. The results show that the lane line detection method based on feature can accurately extract the lane line in multi-scenario. The variance of Kalman filter method is at least one order of magnitude lower than that of other filtering methods, which can effectively improve the stability of the system. According to the lane line equation, a relatively stable body posture deviation is obtained. The extracted yaw angle is less than 1 degree and the lateral deviation is less than 4 cm, which provides a basis for AGV vehicle control\",\"PeriodicalId\":191106,\"journal\":{\"name\":\"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering\",\"volume\":\"94 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3501409.3501435\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3501409.3501435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Lane Location and Navigation Technology Based on Binocular Camera
Aiming at the problem that the traditional single sensor of AGV cannot meet the indoor and outdoor operating conditions and the cost of multi-sensor is too high, this paper studies a navigation method for lane detection and positioning based on binocular camera. Based on the analysis of lane line equation coefficient variation, several dynamic filtering noise reduction methods are compared. The results show that the lane line detection method based on feature can accurately extract the lane line in multi-scenario. The variance of Kalman filter method is at least one order of magnitude lower than that of other filtering methods, which can effectively improve the stability of the system. According to the lane line equation, a relatively stable body posture deviation is obtained. The extracted yaw angle is less than 1 degree and the lateral deviation is less than 4 cm, which provides a basis for AGV vehicle control