Reactive navigation for autonomous guided vehicle using neuro-fuzzy techniques

Jin Cao; Xiaoqun Liao; Ernest L. Hall

doi:10.1117/12.360289

26 August 1999 Reactive navigation for autonomous guided vehicle using neuro-fuzzy techniques

Jin Cao, Xiaoqun Liao, Ernest L. Hall

Proceedings Volume 3837, Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision; (1999) https://doi.org/10.1117/12.360289
Event: Photonics East '99, 1999, Boston, MA, United States

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.

Citation Download Citation

Jin Cao, Xiaoqun Liao, and 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); https://doi.org/10.1117/12.360289

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