In various examples, one or more deep neural networks (DNNs) are executed to regress on control points of a curve, and the control points may be used to perform a curve fitting operation—e.g., Bezier curve fitting—to identify landmark locations and geometries in an environment. The outputs of the DNN(s) may thus indicate the two-dimensional (2D) image-space and/or three-dimensional (3D) world-space control point locations, and post-processing techniques—such as clustering and temporal smoothing—may be executed to determine landmark locations and poses with precision and in real-time. As a result, reconstructed curves corresponding to the landmarks—e.g., lane line, road boundary line, crosswalk, pole, text, etc.—may be used by a vehicle to perform one or more operations for navigating an environment.


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    Titel :

    LANDMARK DETECTION USING CURVE FITTING FOR AUTONOMOUS DRIVING APPLICATIONS


    Beteiligte:
    PARK MINWOO (Autor:in) / YANG YILIN (Autor:in) / LIN XIAOLIN (Autor:in) / BAJPAYEE ABHISHEK (Autor:in) / SEO HAE-JONG (Autor:in) / YUAN ERIC JONATHAN (Autor:in) / CHEN XUDONG (Autor:in)

    Erscheinungsdatum :

    2023-07-06


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G06V / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion




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    Raj, Sugandh / Dreyer, Matthew / Gururajan, Srikanth | AIAA | 2018


    Autonomous landmark tracking orbit determination strategy

    Miller, J. K. / Cheng, Y. | NTRS | 2003