| Issue |
MATEC Web Conf.
Volume 309, 2020
2019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
|
|
|---|---|---|
| Article Number | 03006 | |
| Number of page(s) | 9 | |
| Section | Smart Algorithms and Recognition | |
| DOI | https://doi.org/10.1051/matecconf/202030903006 | |
| Published online | 04 March 2020 | |
VO and GPS integrated navigation algorithm based on plane constraint
1 College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2 Key Laboratory of Nuclear Technology Application and Radiation Protection in Astronautics (Nanjing University of Aeronautics and Astronautics), Ministry of Industry and Information Technology, Nanjing 211106, China
* Corresponding author: autonavinuaa@163.com
In view of the deficiencies of GPS in the urban environment, such as signal occlusion, multipath and Non-LOS, this paper proposes a solution that using a low-cost monocular camera instead of inertial navigation system to combine with GPS. Firstly, considering that the actual road conditions of the vehicle are mostly plane and in order to reduce the computational resources of visual odometer (VO), this paper establishes a VO solving model based on plane constraint; then the VO&GPS loose coupling model is proposed. The position error and yaw angle error of the two sensors are taken as input, and the errors are filtered by the adaptive Kalman filter. Experiments show that the positioning effect of VO&GPS loose coupling system is better than that of single GPS, and it can suppress the drift of VO, which can meet the positioning requirements when satellite signals are interfered in a short time.
Key words: Monocular VO / GPS / Integrated navigation / Adaptive Kalman filtering
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.