@inproceedings{ee964a3dd3284557b94346ec33c8e9d6,
title = "A Robust Integrated Navigation System for Unmanned Ground Vehicle Based on IMU/GNSS/Vision/Geomagnetic Fusion",
abstract = "Aiming at the problem of GNSS signal failure of unmanned ground vehicles in urban environments, a robust integrated navigation system based on IMU/GNSS/vision/geomagnetic combination is designed, which can generate full-dimension navigation information under the framework of factor graph (FG). Different from the traditional FG model which takes IMU measurement as the core, this paper designs a complete navigation information fusion algorithm and covariance matrix based on visual odometry. To improve the accuracy and reliability of navigation information, this paper introduces offline maps. Given the different dimensions measured in the process of attitude information optimization and the particularity of the rotation matrix, this paper designed an attitude update process based on visual feature points to realize the fusion of IMU, geomagnetic, and feature points. Long endurance road test in a typical urban environment shows that the horizontal positioning accuracy is 4.38m (RMSE), and course accuracy is 0.849r (RMSE).",
keywords = "FG, integrated navigation, multi-sensors fusion, optimism algorithm, visual odometry",
author = "Pengxiang Yang and Chaoming Yang and Zhenhui Fan and Kai Shen and Chunbo Mei and Yicheng Zhou",
note = "Publisher Copyright: {\textcopyright} 2024 The Authors.; 3rd International Conference on Mechatronics and Automation Technology, ICMAT 2024 ; Conference date: 25-10-2024 Through 26-10-2024",
year = "2024",
doi = "10.3233/ATDE241290",
language = "English",
series = "Advances in Transdisciplinary Engineering",
publisher = "IOS Press BV",
pages = "563--572",
editor = "Jinyang Xu",
booktitle = "Mechatronics and Automation Technology - Proceedings of the 3rd International Conference, ICMAT 2024",
address = "Netherlands",
}