This paper compares model-based and artificial neural network approaches to computer vision based road following. Representative techniques of each approach, dynamic vision and radial basis function networks, were implemented in C/C++ on the same outdoor mobile robot using a commercially available workstation. Their performance was evaluated using the rules of the 1995 3rd Annual International Unmanned Ground Robotics Competition. Both methods were able to navigate a simple course; however, the model-based method performed more consistently and was found to have several practical advantages.


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    Titel :

    Implementation and comparison of two computer vision based road following approaches


    Weitere Titelangaben:

    Implementierung und Vergleich von zwei computervisionbasierten Straßenfolgeverfahren


    Beteiligte:
    Murphy, R. (Autor:in) / Hoff, W. (Autor:in) / Hoffmann, J. (Autor:in) / Blitch, J. (Autor:in) / Hawkins, D. (Autor:in) / Gough, V. (Autor:in) / Krosley, R. (Autor:in)


    Erscheinungsdatum :

    1995


    Format / Umfang :

    8 Seiten, 2 Bilder, 12 Quellen


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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