Version 1
: Received: 31 May 2024 / Approved: 31 May 2024 / Online: 31 May 2024 (10:50:49 CEST)
How to cite:
Cheng, X.; Wang, Y. Research on Visual/Ins Integrated Navigation Technology Based on FGO. Preprints2024, 2024052127. https://doi.org/10.20944/preprints202405.2127.v1
Cheng, X.; Wang, Y. Research on Visual/Ins Integrated Navigation Technology Based on FGO. Preprints 2024, 2024052127. https://doi.org/10.20944/preprints202405.2127.v1
Cheng, X.; Wang, Y. Research on Visual/Ins Integrated Navigation Technology Based on FGO. Preprints2024, 2024052127. https://doi.org/10.20944/preprints202405.2127.v1
APA Style
Cheng, X., & Wang, Y. (2024). Research on Visual/Ins Integrated Navigation Technology Based on FGO. Preprints. https://doi.org/10.20944/preprints202405.2127.v1
Chicago/Turabian Style
Cheng, X. and Yu Wang. 2024 "Research on Visual/Ins Integrated Navigation Technology Based on FGO" Preprints. https://doi.org/10.20944/preprints202405.2127.v1
Abstract
In order to make full use of the complementarity of existing navigation systems to improve the navigation and positioning accuracy, this paper investigates the visual/INS integrated navigation system based on the factor graph optimization (FGO) algorithm. In the traditional visual/INS integrated navigation system, there is often the problem of image blurring due to the rapid change of light and shadow captured by the vision sensor and the attitude change of the carrier, which leads to the decrease of the positioning accuracy of the combined navigation system. Therefore, this paper firstly introduces Retinex algorithm and BID algorithm to carry out the design of image de-blurring method; then implements the visual/INS integrated navigation algorithm based on the factor graph optimization method; finally, the experimental scheme is designed, comparative experiments are carried out, and the researched method is verified by using the public dataset. The experimental results show that the combined navigation algorithm realized in this paper has high accuracy, and its positioning accuracy is improved by 40% compared with visual positioning.
Copyright:
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.