Improving Multisensor Positioning of Land Vehicles with Integrated Visual Odometry for Next-Generation Self-Driving Cars
المؤلفون المشاركون
Noureldin, Aboelmaged
Rahman, Muhammed Tahsin
Karamat, Tashfeen
Givigi, Sidney
المصدر
Journal of Advanced Transportation
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-05-02
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
For their complete realization, autonomous vehicles (AVs) fundamentally rely on the Global Navigation Satellite System (GNSS) to provide positioning and navigation information.
However, in area such as urban cores, parking lots, and under dense foliage, which are all commonly frequented by AVs, GNSS signals suffer from blockage, interference, and multipath.
These effects cause high levels of errors and long durations of service discontinuity that mar the performance of current systems.
The prevalence of vision and low-cost inertial sensors provides an attractive opportunity to further increase the positioning and navigation accuracy in such GNSS-challenged environments.
This paper presents enhancements to existing multisensor integration systems utilizing the inertial navigation system (INS) to aid in Visual Odometry (VO) outlier feature rejection.
A scheme called Aided Visual Odometry (AVO) is developed and integrated with a high performance mechanization architecture utilizing vehicle motion and orientation sensors.
The resulting solution exhibits improved state covariance convergence and navigation accuracy, while reducing computational complexity.
Experimental verification of the proposed solution is illustrated through three real road trajectories, over two different land vehicles, and using two low-cost inertial measurement units (IMUs).
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Rahman, Muhammed Tahsin& Karamat, Tashfeen& Givigi, Sidney& Noureldin, Aboelmaged. 2018. Improving Multisensor Positioning of Land Vehicles with Integrated Visual Odometry for Next-Generation Self-Driving Cars. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1181541
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Rahman, Muhammed Tahsin…[et al.]. Improving Multisensor Positioning of Land Vehicles with Integrated Visual Odometry for Next-Generation Self-Driving Cars. Journal of Advanced Transportation No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1181541
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Rahman, Muhammed Tahsin& Karamat, Tashfeen& Givigi, Sidney& Noureldin, Aboelmaged. Improving Multisensor Positioning of Land Vehicles with Integrated Visual Odometry for Next-Generation Self-Driving Cars. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1181541
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1181541
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر