Adaptive integrated positioning algorithm of VIO/UWB based on robust estimation

被引：0
|
作者：
Li X. [1 ,2 ]
Li J. [1 ]
Wang A. [1 ]
Luo H. [1 ]
Yang Z. [1 ]
Li K. [1 ]
机构：
[1] Institute of Geospatial Information, Information Engineering University, Zhengzhou
[2] Troops 61618, Beijing
来源：
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | 2023年 / 31卷 / 11期
关键词：
adaptive; multi-sensor fusion; robust; ultra-wideband; visual-inertial odometry;
D O I：
10.13695/j.cnki.12-1222/o3.2023.11.004
中图分类号：
学科分类号：
摘要：
In the indoor environment positioning where the global navigation satellite system (GNSS) signal is rejected, the positioning error of visual-inertial odometry (VIO) inevitably accumulates under adverse conditions such as long-term movement or no loop closure, and the positioning accuracy of ultra-wideband (UWB) is difficult to guarantee due to the influence of non-line-of-sight (NLOS). Therefore, an UWB aided visual-inertial adaptive integrated positioning algorithm based on the robust estimation is proposed. Firstly, the optimization framework of UWB and VIO is constructed, and the global constraints on VIO are applied by using the UWB positioning results. Secondly, robust estimation is added in the back-end optimization stage to adjust the weight values between sensors in real time to suppress the influence of NLOS of UWB. Finally, experiments are carried out in EuRoc dataset and real-world scenarios. Experimental results in real-world scenarios show that the positioning accuracy of the combination algorithm is improved by 75.05% compared to VINS_Mono under non-occlusion conditions, and the positioning accuracy of the combination algorithm based on robust estimation is improved by 37.53% compared to the combination algorithm without robust estimation under occlusion conditions. © 2023 Editorial Department of Journal of Chinese Inertial Technology. All rights reserved.
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页码：1083 / 1091
页数：8
相关论文
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