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Improving Multisensor Positioning of Land Vehicles with Integrated Visual Odometry for Next-Generation Self-Driving Cars
Joint Authors
Noureldin, Aboelmaged
Rahman, Muhammed Tahsin
Karamat, Tashfeen
Givigi, Sidney
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-05-02
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract 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).
American Psychological Association (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
Modern Language Association (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
American Medical Association (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
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181541