Intelligent mobile robot navigation using a neuro-fuzzy approach
by Somia Brahimi; Ouahiba Azouaoui; Malik Loudini
International Journal of Computer Aided Engineering and Technology (IJCAET), Vol. 11, No. 6, 2019

Abstract: This paper introduces an intelligent navigation system allowing a car-like robot to attain its destination autonomously, intelligently and safely. Based on a neuro-fuzzy (FNN) approach, the applied technique permits the robot to avoid all encountered obstacles and seek for its target's location in a local manner referring to the concepts of learning and adaptation. It uses two fuzzy Artmap neural networks, a reinforcement trial and error neural network and a Mamdani fuzzy logic controller (FLC). Experimental results in the Generator of modules (GenoM) robotics architecture, in an unknown environment, shows the FNN effectiveness for the autonomous mobile robot Robucar.

Online publication date: Mon, 30-Sep-2019

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