Demand is growing for unmanned air vehicles (UAVs) with greater autonomy, including the ability to navigate without GPS information, such as indoors. In this work, a novel visual odometry algorithm is developed and flight tested. It uses sequential pairs of red, green, blue, depth (RGBD) camera images to estimate the UAV’s change in position (delta pose), which can be used to aid a navigation filter. Unlike existing related techniques, it uses a novel perturbation approach to estimate the uncertainty of the odometry measurement dynamically in real time, a technique that is applicable to a wide range of sensor preprocessing tasks aimed at generating navigation-relevant measurements. Real-time estimates of the delta pose and its covariance allow these estimates to be efficiently fused with other sensors in a navigation filter. Indoor flight testing was performed with motion capture, which demonstrated that the odometry and covariance estimates are accurate when appropriately scaled. Flights also demonstrated the algorithm used in a navigation filter to improve a velocity estimate, which represents a significant improvement over the state of the art for RGBD odometry.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Real-Time Visual Odometry Covariance Estimation for Unmanned Air Vehicle Navigation


    Contributors:

    Published in:

    Publication date :

    2019-02-27


    Size :

    17 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    AUTONOMOUS NAVIGATION USING VISUAL ODOMETRY

    LIAO MIAO / LI MING / HONG SOONHAC | European Patent Office | 2017

    Free access

    Stereo Visual Inertial Odometry for Unmanned Aerial Vehicle Autonomous Flight

    Liu, Quanpan / Wang, Zhengjie / Wang, Huan | Springer Verlag | 2019


    WHEEL ODOMETRY AIDED VISUAL-INERTIAL ODOMETRY FOR LAND VEHICLE NAVIGATION IN WINTER URBAN ENVIRONMENTS

    Huang, Cheng / Jiang, Yang / O Keefe, Kyle | British Library Conference Proceedings | 2020


    Communicationless navigation through robust visual odometry

    Van Hamme, David / Veelaert, Peter / Philips, Wilfried | IEEE | 2012


    Reliability of visual inertial odometry on an unmanned aerial vehicle

    Setati Tiro / Maweni Thabisa / Botha Natasha | DOAJ | 2023

    Free access