In Global Navigation Satellite System (GNSS)-denied environments, image registration has emerged as a prominent approach to utilize visual information for estimating the position of Unmanned Aerial Vehicles (UAVs). However, traditional image-registration-based localization methods encounter limitations, such as strong dependence on the prior initial position information. In this paper, we propose a systematic method for UAV geo-localization. In particular, an efficient range–visual–inertial odometry (RVIO) is proposed to provide local tracking, which utilizes measurements from a 1D Laser Range Finder (LRF) to suppress scale drift in the odometry. To overcome the differences in seasons, lighting conditions, and other factors between satellite and UAV images, we propose an image-registration-based geo-localization method in a coarse-to-fine manner that utilizes the powerful representation ability of Convolutional Neural Networks (CNNs). Furthermore, to ensure the accuracy of global optimization, we propose an adaptive weight assignment method based on the evaluation of the quality of image-registration-based localization. The proposed method is extensively evaluated in both synthetic and real-world environments. The results demonstrate that the proposed method achieves global drift-free estimation, enabling UAVs to accurately localize themselves in GNSS-denied environments.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Range–Visual–Inertial Odometry with Coarse-to-Fine Image Registration Fusion for UAV Localization


    Beteiligte:
    Yun Hao (Autor:in) / Mengfan He (Autor:in) / Yuzhen Liu (Autor:in) / Jiacheng Liu (Autor:in) / Ziyang Meng (Autor:in)


    Erscheinungsdatum :

    2023




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt





    Radar aided visual inertial odometry initialization

    NIESEN URS | Europäisches Patentamt | 2020

    Freier Zugriff

    RADAR AIDED VISUAL INERTIAL ODOMETRY INITIALIZATION

    NIESEN URS | Europäisches Patentamt | 2019

    Freier Zugriff

    AIRCRAFT-BASED VISUAL-INERTIAL ODOMETRY WITH RANGE MEASUREMENT FOR DRIFT REDUCTION

    HEWITT ROBERT A / IZRAELEVITZ JACOB / RUFFATTO DONALD F et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    Uncertainty-Aware Attention Guided Sensor Fusion For Monocular Visual Inertial Odometry

    Shinde, Kashmira | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2020

    Freier Zugriff