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Sensors 2018, 18(9), 2952; https://doi.org/10.3390/s18092952

An Autonomous Vehicle Navigation System Based on Inertial and Visual Sensors

1
College of Automation, Harbin Engineering University, Harbin 150001, China
2
Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB T2N1N4, Canada
3
Beijing Institute of Control and Electronic Technology, Beijing 100032, China
*
Author to whom correspondence should be addressed.
Received: 1 August 2018 / Revised: 2 September 2018 / Accepted: 3 September 2018 / Published: 5 September 2018
(This article belongs to the Section Physical Sensors)
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Abstract

The strapdown inertial navigation system (SINS) is widely used in autonomous vehicles. However, the random drift error of gyroscope leads to serious accumulated navigation errors during long continuous operation of SINS alone. In this paper, we propose to combine the Inertial Measurement Unit (IMU) data with the line feature parameters from a camera to improve the navigation accuracy. The proposed method can also maintain the autonomy of the navigation system. Experimental results show that the proposed inertial-visual navigation system can mitigate the SINS drift and improve the accuracy, stability, and reliability of the navigation system. View Full-Text
Keywords: autonomous vehicle; strapdown inertial navigation system; inertial-visual fusion method; Kalman Filter autonomous vehicle; strapdown inertial navigation system; inertial-visual fusion method; Kalman Filter
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Guang, X.; Gao, Y.; Leung, H.; Liu, P.; Li, G. An Autonomous Vehicle Navigation System Based on Inertial and Visual Sensors. Sensors 2018, 18, 2952.

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