This paper presents a vehicle navigation system that is capable of achieving sub-meter GPS-denied navigation accuracy in large-scale urban environments, using pre-mapped visual landmarks. Our navigation system tightly couples IMU data with local feature track measurements, and fuses each observation of a pre-mapped visual landmark as a single global measurement. This approach propagates precise 3D global pose estimates for longer periods. Our mapping pipeline leverages a dual-layer architecture to construct high-quality pre-mapped visual landmarks in real time. Experimental results demonstrate that our approach provides sub-meter GPS-denied navigation solutions in large-scale urban scenarios.


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    Titel :

    Sub-meter vehicle navigation using efficient pre-mapped visual landmarks


    Beteiligte:
    Chiu, Han-Pang (Autor:in) / Sizintsev, Mikhail (Autor:in) / Zhou, Xun S. (Autor:in) / Miller, Philip (Autor:in) / Samarasekera, Supun (Autor:in) / Kumar, Rakesh (Autor:in)


    Erscheinungsdatum :

    01.11.2016


    Format / Umfang :

    2590672 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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