Lightweight hybrid visual-inertial odometry with closed-form zero velocity update

查看全文 作　　者：QIU [1,2]Xiaochen;ZHANG [1,2]Hai;FU [3]Wenxing

机构地区：[1]School of Automation Science and Electrical Engineering,Beihang University,Beijing 100191,China;[2]Science and Technology on Aircraft Control Laboratory,Beijing 100191,China;[3]Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory,Beijing 100074,China

出　　处：《Chinese Journal of Aeronautics》索引2020年第33卷第12期,共16页

基　　金：supported by the National Key Research and Development Program of China(Nos.2016YFB0502004,2017YFC0821102)。 摘　　要：Visual-Inertial Odometry(VIO) fuses measurements from camera and Inertial Measurement Unit(IMU) to achieve accumulative performance that is better than using individual sensors.Hybrid VIO is an extended Kalman filter-based solution which augments features with long tracking length into the state vector of Multi-State Constraint Kalman Filter(MSCKF). In this paper, a novel hybrid VIO is proposed, which focuses on utilizing low-cost sensors while also considering both the computational efficiency and positioning precision. The proposed algorithm introduces several novel contributions. Firstly, by deducing an analytical error transition equation, onedimensional inverse depth parametrization is utilized to parametrize the augmented feature state.This modification is shown to significantly improve the computational efficiency and numerical robustness, as a result achieving higher precision. Secondly, for better handling of the static scene,a novel closed-form Zero velocity UPda Te(ZUPT) method is proposed. ZUPT is modeled as a measurement update for the filter rather than forbidding propagation roughly, which has the advantage of correcting the overall state through correlation in the filter covariance matrix. Furthermore, online spatial and temporal calibration is also incorporated. Experiments are conducted on both public dataset and real data. The results demonstrate the effectiveness of the proposed solution by showing that its performance is better than the baseline and the state-of-the-art algorithms in terms of both efficiency and precision. A related software is open-sourced to benefit the community. 关键词：Inverse depth parametrization Kalman filter Online calibration Visual-inertial odometry Zero velocity update

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Lightweight hybrid visual-inertial odometry with closed-form zero velocity update

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