A neuro-fuzzy control method for navigation of an autonomous guided vehicle robot is described. Robot navigation is defined as the guiding of a mobile robot to a desired destination or along a desired path in an environment characterized by as terrain and a set of distinct objects, such as obstacles and landmarks. The autonomous navigation ability and road following precision are mainly influenced by its control strategy and real-time control performance. Neural network and fuzzy logic control techniques can improve real-time control performance for mobile robot due to its high robustness and error-tolerance ability. For a mobile robot to navigate automatically and rapidly, an important factor is to identify and classify mobile robots' currently perceptual environment. In this paper, a new approach of the current perceptual environment feature identification and classification, which are based on the analysis of the classifying neural network and the neuro-fuzzy algorithm, is presented. The significance of this work lies in the development of a new method for mobile robot navigation.


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    Title :

    Reactive navigation for autonomous guided vehicle using neuro-fuzzy techniques


    Contributors:
    Cao, J. (author) / Liao, X. (author) / Hall, E. (author)


    Publication date :

    1999


    Size :

    10 Seiten, 12 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





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