This course covers the mathematical foundations and state-of-the-art implementations of algorithms for vision-based navigation of autonomous vehicles (e.g., mobile robots, self-driving cars, drones). It provides students with a rigorous but pragmatic overview of differential geometry and optimization on manifolds and knowledge of the fundamentals of 2-view and multi-view geometric vision for real-time motion estimation, calibration, localization, and mapping. The theoretical foundations are complemented with hands-on labs based on state-of-the-art mini racecar and drone platforms. It culminates in a critical review of recent advances in the field and a team project aimed at advancing the state of the art.


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    Titel :

    Visual Navigation for Autonomous Vehicles (VNAV)


    Beteiligte:

    Medientyp :

    Sonstige


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    VNAV vs. Glideslope

    Bergner, S. E. | British Library Online Contents | 2001


    A Cognitive Engineering Analysis of the Vertical Navigation (VNAV) Function

    Sherry, Lance / Feary, Michael / Polson, Peter et al. | NTRS | 2001




    Visual Navigation System for Autonomous Land Vehicles

    A. M. Waxman / J. LeMoigne / L. S. Davis et al. | NTIS | 1985