A computer-implemented method comprises receiving an image captured by a camera on an unmanned aerial vehicle (UAV). The image depicts an environment below the UAV. A feature mask associated with the image is generated via a machine learning model that is trained to identify and semantically label pixels representing the environment depicted in the image. One or more reference tiles associated with the environment are retrieved. The reference tiles are associated with particular geographic locations and specify semantically labeled pixels representing the geographic locations. The semantically labeled pixels of the feature mask are correlated with the semantically labeled pixels of at least one of the one or more reference tiles to determine the geographic location of the UAV in the environment.


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    Title :

    Method for Semantic Localization of an Unmanned Aerial Vehicle


    Contributors:
    SHOEB ALI (author) / KAKLIGIAN KYLE (author) / JOURDAN DAMIEN (author) / ZHONG MICHAEL (author) / XU KE (author) / GABOR JEREMIE (author)

    Publication date :

    2023-10-05


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06V / B64C AEROPLANES , Flugzeuge / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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