Relative visual-inertial odometry for fixed-wing aircraft in GPS-denied environments
Relative visual-inertial odometry for fixed-wing aircraft in GPS-denied environments
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DOI：
10.1109/plans.2018.8373454
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发表时间：
2018-04
期刊：
影响因子：
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通讯作者：
Gary Ellingson;K. Brink;T. McLain
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文献类型：
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作者：
Gary Ellingson;K. Brink;T. McLain
本文介绍了一种类似里程计的前端估计器，用于使用单目相机进行 GPS 拒绝的固定翼飞行。这一发展是使固定翼飞机能够使用称为相对导航的新颖方法的关键组成部分。相对导航允许单个车辆优雅地适应间歇性 GPS 或地理注册图像更新。它还可以为众多车辆提供通信和计算上可行的协作式、基于批处理的导航方法。本文提出了一种适合固定翼飞行特性和传感要求的视觉里程计估计器。我们提出了对多状态约束卡尔曼滤波器的修改，它不是在单个惯性/全局框架中运行过滤器，而是定期将导航框架重置为新的本地原点。车辆基于最新的关键帧运行，并在关键帧更新时产生位姿（里程计）和协方差输出的边缘化变化。这允许前端以 IMU 速率运行，以适应引导和控制输入，同时与后端共享边缘化关键帧到关键帧里程计估计，图形优化的速率比传统批量导航方案低得多。还介绍了在滤波器的高保真仿真中测试所提出的方法的结果。
This paper introduces an odometry-like front-end estimator for GPS-denied fixed-wing flight using a monocular camera. This development is a critical component for enabling fixed-wing aircraft to use a novel methodology called relative navigation. Relative navigation allows a single vehicle to gracefully accommodate intermittent GPS or geo-registered image updates. It can also enable communication and a computationally feasible cooperative, batch-based navigation approach for numerous vehicles. This paper presents a visual-odometry estimator that is appropriate for fixed-wing flight characteristics and sensing requirements. We propose a modification to the multi-state-constraint Kalman filter which, instead of running the filter in a single inertial/global frame, regularly resets the navigation frame to a new local origin. The vehicle operates based on the most recent keyframe and produces a marginalized change in pose (odometry) and covariance output whenever the keyframe is updated. This allows the front end to operate at the IMU rate to accommodate guidance and control inputs while sharing marginalized keyframe-to-keyframe odometry estimates with a back-end, graph optimization at a much lower rate than traditional batch navigation schemes. Results from testing the proposed method in a high-fidelity simulation of the filter is also presented.