Adaptive Neuro-Fuzzy Controler With Genetic Training For Mobile Robot Control

Olumide Obe, Ioan Dumitrache

Abstract


In this paper, we investigate the use of adaptive techniques in the optimization of navigation of Khepera mobile robot in an unstructured and dynamic environment. We optimize the performance of our simplified fuzzy controller using neural network that utilizes genetic algorithm learning. The adaptation of the system involves the tuning of the control rules thereby trimming the control actions, and adjusting the fuzzy controller output gain. We realised an improved performance in our adaptive neuro-fuzzy controller with genetic training for various implemented behaviours on the robot.


Keywords


Khepera, fuzzy controller, neuro-fuzzy controller, navigation, genetic algorithm

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References


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DOI: https://doi.org/10.15837/ijccc.2012.1.1429



Copyright (c) 2017 Olumide Obe, Ioan Dumitrache

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