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.
Highlights
The successful use of automated vehicles will have a great impact on human live [1]
The Inertial Measurement Unit (IMU), Global Position System (GPS) receiver, and power system are in the vehicle trunk
The IMU is fixed on the vehicle via a steel plate which is parallel with the under panel of the vehicle
Summary
The successful use of automated vehicles will have a great impact on human live [1]. It will bring more convenient and easier driving experiences for human. Integrated IMU with Global Navigation Satellite System (GNSS) is a widely used approach to improve the accuracy of SINS [10,11,12]. Vivacqua et al propose the low-cost sensors approach for accurate vehicle localization and autonomous driving that uses a camera and SINS [18]. In these applications, the visual sensor is only used for the lanes detection and the visual information is not fused for navigation. It uses point feature extraction to improve the accuracy of the navigation system during driving These studies are all about moving vehicles. Experimental results show that the proposed inertial-visual integrated navigation system can improve the accuracy and reliability of the navigation system
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