Autonomous driving in off-road environments requires an exceptionally capable sensor system, particularly given that the unstructured environment does not provide many of the cues available in on-road environments. This paper presents a complex vision system, which is able to provide the two basic sensorial capabilities needed by autonomous vehicle navigation in extreme environments: obstacle detection and path detection. A variable-width-baseline (up to 1.5 m) single-frame stereo system is used for pitch estimation and obstacle detection, whereas a decision-network approach is used to detect the drivable path by a monocular vision system. The system has been field tested on the TerraMax vehicle, which is one of the only five vehicles to complete the 2005 Defense Advanced Research Projects Agency (DARPA) Grand Challenge course.


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    Titel :

    Off-road path and obstacle detection using decision networks and stereo vision


    Beteiligte:
    Caraffi, C. (Autor:in) / Cattani, S. (Autor:in) / Grisleri, P. (Autor:in)


    Erscheinungsdatum :

    2007


    Format / Umfang :

    12 Seiten, 34 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




    Off-Road Path and Obstacle Detection Using Decision Networks and Stereo Vision

    Caraffi, C. / Cattani, S. / Grisleri, P. | IEEE | 2007



    Obstacle Detection with Stereo Vision for Off-Road Vehicle Navigation

    Broggi, A. / Caraffi, C. / Fedriga, R.I. et al. | IEEE | 2005


    Evaluation of stereo vision obstacle detection algorithms for off-road autonomous navigation

    Rankin, Arturo / Huertas, Andres / Matthies, Larry | NTRS | 2005


    Contrast-invariant Obstacle Detection System using Color Stereo Vision

    Cabani, Iyadh / Toulminet, Gwenaelle / Bensrhair, Abdelaziz | IEEE | 2008