全球导航卫星系统应用
计算机科学
计算机视觉
人工智能
约束(计算机辅助设计)
滤波器(信号处理)
惯性导航系统
滑动窗口协议
运动学
全球导航卫星系统增强
惯性参考系
控制理论(社会学)
窗口(计算)
工程类
物理
全球定位系统
电信
机械工程
控制(管理)
经典力学
量子力学
操作系统
作者
Xiaohong Huang,Cui Yang,Miaowen Wen
出处
期刊:IEEE Transactions on Robotics
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:: 1-17
标识
DOI:10.1109/tro.2024.3365008
摘要
In this paper, we present a novel method by using a sliding window filter (SWF) for real-time kinematic (RTK)-visual-inertial navigation. Unlike other recent works that retain only the states of visual keyframes to reduce computational complexity, we additionally retain the GNSS states (i.e., position, orientation, and velocity of the body and inertial biases at the time of capturing GNSS measurements) in the SWF to construct more appropriate constraints between measurements and states. In order to make the method run as a real-time system, especially when the SWF contains numerous GNSS states, we propose a parallel elimination strategy in a predefined elimination ordering, which can solve the Gauss-Newton problem and simultaneously obtain the covariance for ambiguity resolution (AR). We reveal when and how the system improves the AR performance. Moreover, we analyze the observability of the system under different conditions. We also conduct experiments in the real world and compare the results with the state-of-the-arts. Experimental results show that the proposed method is able to achieve a higher and stabler fixed rate in GNSS challenging environments, and has better positioning performance with or without measurements of a base station. We have decided to publish the code of our work for the community 1 .
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