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首页> 外文期刊>The Journal of Navigation >Minimum Sigma Set SR-UKF for Quadrifocal Tensor-based Binocular Stereo Vision-IMU Tightly-coupled System
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Minimum Sigma Set SR-UKF for Quadrifocal Tensor-based Binocular Stereo Vision-IMU Tightly-coupled System

机译：基于四向张量的双目立体视觉-IMU紧耦合系统的最小Sigma Set SR-UKF

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摘要

This paper presents a binocular vision-IMU (Inertial Measurement Unit) tightly-coupled structure based on a Minimum sigma set Square-Root Unscented Kalman Filter (M-SRUKF) for real time navigation applications. Though the M-SRUKF has only half the sigma points of the SRUKF, it has the same accuracy as the SRUKF when applied to the binocular vision-IMU tightly-coupled system. As the Kalman filter flow is a kind of square-root system, the stability of the system can be guaranteed. The measurement model and the outlier rejection model of this tightly-coupled system not only utilises the epipolar constraint and the trifocal tensor geometry constraint between the consecutive two image pairs, but also uses the quadrifocal tensor geometry among four views. The structure of the binocular vision-IMU tightly-coupled system is in the form of an error state, and the time updates of the state and the state covariance are directly estimated without using Unscented Transformation (UT). Experiments are carried out based on an outdoor land vehicle open source dataset and an indoor Micro Aerial Vehicle (MAV) open source dataset. Results clearly show the effectiveness of the proposed new mechanisation.
机译：本文提出了一种基于最小sigma集平方根无味卡尔曼滤波器（M-SRUKF）的双目视觉IMU（惯性测量单元）紧密耦合结构，用于实时导航应用。尽管M-SRUKF仅具有SRUKF的sigma点的一半，但将其应用于双目视觉-IMU紧密耦合系统时，其精度与SRUKF相同。由于卡尔曼滤波流是平方根系统，因此可以保证系统的稳定性。该紧密耦合系统的测量模型和离群值剔除模型不仅利用连续两对图像之间的对极约束和三焦点张量几何约束，而且还利用四视图中的四叉张量几何。双目视觉-IMU紧密耦合系统的结构为错误状态，无需使用无味变换（UT）即可直接估算状态的时间更新和状态协方差。实验基于室外陆地车辆开源数据集和室内微型飞行器（MAV）开源数据集进行。结果清楚地表明了所提议的新机械化的有效性。

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