26 August 1999 Reactive navigation for autonomous guided vehicle using neuro-fuzzy techniques
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Abstract
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 navigate 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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Jin Cao, Jin Cao, Xiaoqun Liao, Xiaoqun Liao, Ernest L. Hall, Ernest L. Hall, } "Reactive navigation for autonomous guided vehicle using neuro-fuzzy techniques", Proc. SPIE 3837, Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision, (26 August 1999); doi: 10.1117/12.360289; https://doi.org/10.1117/12.360289
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