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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    Title :

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


    Contributors:


    Publication date :

    2017-06-01


    Size :

    1532187 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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