A significant challenge in the employment of UAV platforms for indoor inspection and maintenance operations lies in the problem of finding a portable and cost-effective way to accurately localize aerial vehicles in GNSS-denied environments. Focusing on the visual-based positioning paradigm, we outline a pose estimation procedure whose accuracy is achieved by leveraging the potential offered by a dense and size-heterogeneous map of tags. The proposed indoor UAVs localization rests on i) hierarchical tag selection, ii) outlier removal, and iii) multi-tag estimation averaging, to facilitate visual-inertial reconciliation. We assess the performance of the outlined positioning system through ad-hoc experimental tests that highlight the localization accuracy improvement as compared with other existing state-of-the-art solutions.


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    Titel :

    Streamlined Indoor UAVs Localization Using a Dense and Size-Heterogeneous Tags Map


    Beteiligte:


    Erscheinungsdatum :

    04.06.2024


    Format / Umfang :

    1030130 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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