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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

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


    Contributors:
    Caraffi, C. (author) / Cattani, S. (author) / Grisleri, P. (author)


    Publication date :

    2007-12-01


    Size :

    1389345 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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

    Caraffi, C. / Cattani, S. / Grisleri, P. | Tema Archive | 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


    Genetic approach for obstacle detection using linear stereo vision

    Ruichek, Y. / Issa, H. / Postaire, J.-G. | IEEE | 2000