In this paper we predict the amount of slip an exploration rover would experience using stereo imagery by learning from previous examples of traversing similar terrain. To do that, the information of terrain appearance and geometry regarding some location is correlated to the slip measured by the rover while this location is being traversed. This relationship is learned from previous experience, so slip can be predicted later at a distance from visual information only.


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    Titel :

    Learning to predict slip for ground robots


    Beteiligte:
    Angelova, Anelia (Autor:in) / Matthies, Larry (Autor:in) / Helmick, Daniel (Autor:in) / Sibley, Gabe (Autor:in) / Perona, Pietro (Autor:in)

    Erscheinungsdatum :

    2006-01-01


    Medientyp :

    Preprint


    Format :

    Keine Angabe


    Sprache :

    Englisch




    Learning to predict slip for ground robots

    Angelova, A. / Matthies, L. / Helmick, D. et al. | Tema Archiv | 2006


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