This paper proposes a novel method for corresponding visual measurements to map points in a visual-inertial navigation system. The algorithm is based on the minimization of the photometric error on sparse locations of the image region, and realizes a gain in robustness that comes from the elimination of the need of feature-extraction for correspondence. The system is compared to a standard approach based on feature extraction, within a visual-inertial EKF formulation. High-fidelity simulation results show the proposed method improves the horizontal RMS error by means of increasing the number of features corresponded by the algorithm.


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    Titel :

    Direct feature correspondence in vision-aided inertial navigation for unmanned aerial vehicles


    Beteiligte:


    Erscheinungsdatum :

    01.06.2017


    Format / Umfang :

    1532187 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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