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Implementation and Analysis of Tightly Integrated INS/Stereo VO for Land Vehicle Navigation

Published online by Cambridge University Press:  23 August 2017

Fei Liu ,
Yashar Balazadegan Sarvrood  and
Yang Gao
Fei Liu*
Affiliation:
(University of Calgary, Calgary, Canada)
Yashar Balazadegan Sarvrood
Affiliation:
(University of Calgary, Calgary, Canada)
Yang Gao
Affiliation:
(University of Calgary, Calgary, Canada)
*
(E-mail: liu19@ucalgary.ca)
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Abstract

Tight integration of inertial sensors and stereo visual odometry to bridge Global Navigation Satellite System (GNSS) signal outages in challenging environments has drawn increasing attention. However, the details of how feature pixel coordinates from visual odometry can be directly used to limit the quick drift of inertial sensors in a tight integration implementation have rarely been provided in previous works. For instance, a key challenge in tight integration of inertial and stereo visual datasets is how to correct inertial sensor errors using the pixel measurements from visual odometry, however this has not been clearly demonstrated in existing literature. As a result, this would also affect the proper implementation of the integration algorithms and their performance assessment. This work develops and implements the tight integration of an Inertial Measurement Unit (IMU) and stereo cameras in a local-level frame. The results of the integrated solutions are also provided and analysed. Land vehicle testing results show that not only the position accuracy is improved, but also better azimuth and velocity estimation can be achieved, when compared to stand-alone INS or stereo visual odometry solutions.

Keywords

Stereo VOInertial Navigation SystemExtended Kalman filterTight integration
Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 1 , January 2018 , pp. 83 - 99
Copyright
Copyright © The Royal Institute of Navigation 2017 

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