This paper describes a novel obstacle detection system for autonomous robots in agricultural field environments that uses a novelty detector to inform stereo matching. Stereo vision alone erroneously detects obstacles in environments with ambiguous appearance and ground plane such as in broad-acre crop fields with harvested crop residue. The novelty detector estimates the probability density in image descriptor space and incorporates image-space positional understanding to identify potential regions for obstacle detection using dense stereo matching. The results demonstrate that the system is able to detect obstacles typical to a farm at day and night. This system was successfully used as the sole means of obstacle detection for an autonomous robot performing a long term two hour coverage task travelling 8.5 km.


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    Title :

    Novelty-based visual obstacle detection in agriculture


    Contributors:
    Ross, Patrick (author) / English, Andrew (author) / Ball, David (author) / Upcroft, Ben (author) / Wyeth, Gordon (author) / Corke, Peter (author)


    Publication date :

    2014-05-01


    Size :

    922306 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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