Autonomous off-road navigation of robotic ground vehicles has important applications on Earth and in space exploration. Progress in this domain has been retarded by the limited lookahead range of 3-D sensors and by the difficulty of preprogramming systems to understand the traversability of the wide variety of terrain they can encounter.


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    Titel :

    Learning for autonomous navigation


    Beteiligte:
    Angelova, Anelia (Autor:in) / Howard, Andrew (Autor:in) / Matthies, Larry (Autor:in) / Tang, Benyang (Autor:in) / Turmon, Michael (Autor:in) / Mjolsness, Eric (Autor:in)

    Kongress:

    Neural Information Processing Systems ; 2005 ; Vancouver, British Columbia, Canada


    Erscheinungsdatum :

    01.12.2005


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch




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