The design of a robotic vehicle requires a unique knowledge of the world in which the vehicle is to operate. This paper investigates the potential of a knowledge acquisition system for such a vehicle, based on a scanning laser radar sensor system that can provide 3-D surface descriptions of the surveyed terrain simultaneously with an active reflectance image of the scene. The advantages and disadvantages of this sensor are explored along with algorithms for efficiently extracting the type of knowledge required to control a robotic vehicle. Specifically the output of this knowledge acquisition system must consist of the location and extent of the road, the presence, size and location of any obstacles, and the location of road intersections, all in real time. Based on this knowledge of the scene, a desired local path can be planned for the robotic vehicle.


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    Title :

    Knowledge Acquisition For Autonomous Navigation


    Contributors:

    Conference:

    Applications of Artificial Intelligence III ; 1986 ; Orlando,United States


    Published in:

    Publication date :

    1986-03-26





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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