Many robotics tasks require an ability to determine quickly the nature of the terrain surrounding the robot. In cross country navigation in particular, the robot needs to know where the vegetation is and where the hard obstacles are. I have developed a general system which has successfully allowed real-time terrain typing in the NavLab II autonomous vehicle. This system and training paradigm are based on standard neural network technology and allow the robot to learn arbitrary non-linear mappings from color and texture space to terrain space.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Neural Networks for Real-Time Terrain Typing


    Contributors:
    I. L. Davis (author)

    Publication date :

    1995


    Size :

    16 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




    Terrain Typing for Real Robots

    Davis, I. / Kelly, A. / Stentz, A. et al. | British Library Conference Proceedings | 1995


    Terrain typing for real robots

    Davis, I.L. / Kelly, A. / Stentz, A. et al. | IEEE | 1995


    Modeling Terrestrial Mobile Networks in Real Terrain

    Joensson, C. / Groenkvist, J. / Sterner, U. et al. | British Library Conference Proceedings | 1999


    Terrain contour matching with recurrent neural networks

    Lee, Seongheon / Bang, Hyochoong | IEEE | 2018


    Terrain fusion real-time ray tracing optimization

    DROSDECK JONATHAN ANDREW | European Patent Office | 2024

    Free access