M. Sabry, Abdulla Al-Kaff, A. Hussein, Slim Abdennadher
{"title":"地面车辆单目视觉里程计","authors":"M. Sabry, Abdulla Al-Kaff, A. Hussein, Slim Abdennadher","doi":"10.1109/ITSC.2019.8917391","DOIUrl":null,"url":null,"abstract":"Technology advances in the field of Intelligent Transportation Systems are rapidly increasing to obtain higher autonomy levels, and improve the robustness and reliability of autonomous driving. One of the challenges related to autonomous vehicles is the localization systems especially in GPS-denied environments. This paper presents an enhancement in the monocular visual odometry by exploring the use of one external sensor (encoder); in order to obtain the vehicle speed with computer vision techniques to provide a reliable and real time localization system. The proposed algorithm has been validated by performing real experiments, and the obtained results show the improvement in accuracy comparing to existing stereo visual odometry algorithm, with lower error in translation and rotation of the path points.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"55 1","pages":"3587-3592"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Ground Vehicle Monocular Visual Odometry\",\"authors\":\"M. Sabry, Abdulla Al-Kaff, A. Hussein, Slim Abdennadher\",\"doi\":\"10.1109/ITSC.2019.8917391\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Technology advances in the field of Intelligent Transportation Systems are rapidly increasing to obtain higher autonomy levels, and improve the robustness and reliability of autonomous driving. One of the challenges related to autonomous vehicles is the localization systems especially in GPS-denied environments. This paper presents an enhancement in the monocular visual odometry by exploring the use of one external sensor (encoder); in order to obtain the vehicle speed with computer vision techniques to provide a reliable and real time localization system. The proposed algorithm has been validated by performing real experiments, and the obtained results show the improvement in accuracy comparing to existing stereo visual odometry algorithm, with lower error in translation and rotation of the path points.\",\"PeriodicalId\":6717,\"journal\":{\"name\":\"2019 IEEE Intelligent Transportation Systems Conference (ITSC)\",\"volume\":\"55 1\",\"pages\":\"3587-3592\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Intelligent Transportation Systems Conference (ITSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2019.8917391\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2019.8917391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Technology advances in the field of Intelligent Transportation Systems are rapidly increasing to obtain higher autonomy levels, and improve the robustness and reliability of autonomous driving. One of the challenges related to autonomous vehicles is the localization systems especially in GPS-denied environments. This paper presents an enhancement in the monocular visual odometry by exploring the use of one external sensor (encoder); in order to obtain the vehicle speed with computer vision techniques to provide a reliable and real time localization system. The proposed algorithm has been validated by performing real experiments, and the obtained results show the improvement in accuracy comparing to existing stereo visual odometry algorithm, with lower error in translation and rotation of the path points.
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