With the rapid development of computer vision, visual odometry (VO) and visual simultaneous localization and mapping (vSLAM) have been widely used in unmanned aerial vehicles. However, VO suffers from drifts and VSLAM requires loop closure to improve localization accuracy. In this paper, we propose to combine a visual-inertial odometry with a 2D georeferenced map to achieve high precision localization performance in UAVs. Firstly, the georeferenced map is preprocessed to build a visual landmark database. Then a micro inertial measurement unit (MIMU) and a downward facing camera are fused to form a visual inertial odometry (VIO), which estimates relative motion between camera frames. To cure the VIO drifts, we further register the features tracked by the VIO with the 2D georeferenced map. While most conventional methods perform one-shot geo-registration or use 3D maps, we propose to use a 2D geo-referenced map and track the registered features in multiple frames to improve localization accuracy. Finally, a factor graph is built to fuse the relative motion from VIO with the geo-registration information to obtain consecutive and accurate localization results. We valid the proposed algorithm with real flight experiments and the results show significant localization accuracy improvements.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Improving UAV Localization Accuracy by Tracking Visual Features in a Georeferenced Map


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Wu, Meiping (editor) / Niu, Yifeng (editor) / Gu, Mancang (editor) / Cheng, Jin (editor) / Mao, Dengke (author) / He, Xiaofeng (author) / Mao, Jun (author) / Zhang, Lilian (author) / Qu, Hao (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021



    Publication date :

    2022-03-18


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Maritime Tracking with Georeferenced Multi-Camera Fusion

    Helgesen, Øystein Kaarstad / Stahl, Annette / Brekke, Edmund Førland | BASE | 2023

    Free access

    Estimating the reliability of georeferenced lane markings for map-aided localization

    Welte, Anthony / Xu, Philippe / Bonnifait, Philippe et al. | IEEE | 2019


    Georeferenced trajectory estimation system

    ZLOT ROBERT / EADE ETHAN DUFF / HANSEN PETER et al. | European Patent Office | 2022

    Free access


    Information System: Georeferenced Database

    Brovelli, Maria / Negretti, Marco / Biagi, Ludovico | Springer Verlag | 2017