Unmanned ground vehicles (UGV), traversing open terrain, require the capability of identifying non-geometric barriers or impediments to navigation, such as soft soil, fine sand, mud, snow, compliant vegetation, washboard, and ruts. Given the ever changing nature of these terrain characteristics, for an UVG to be able to consistently navigate such barriers, it must have the ability to learn from and to adapt to changes in these environmental conditions. As part of ongoing research co-operation with the Defense Research Establishment Suffield (DRES), Scientific Instrumentation Ltd. (SIL) has developed a Terrain Simulator that allows for the investigation of terrain perception and of learning techniques.


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    Titel :

    Perception for learned trafficability models


    Beteiligte:

    Kongress:

    Unmanned Ground Vehicle Technology IV ; 2002 ; Orlando,FL,United States


    Erschienen in:

    Erscheinungsdatum :

    17.07.2002





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Perception for learned trafficability models [4715-20]

    Broten, G. S. / Digney, B. L. / SPIE | British Library Conference Proceedings | 2002



    Trafficability of organic terrain

    Ashdown, K. / Radforth, N.W. | Engineering Index Backfile | 1966


    Forecasting trafficability of soils

    Engineering Index Backfile | 1963