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2012 (Vol. 4, Issue: 15)
Article Information:

A Novel Mobile Robot Navigation System Using Neuro-Fuzzy Rule-Based Optimization Technique

Ayman AbuBaker
Corresponding Author:  Ayman AbuBaker 

Key words:  Fuzzy logic, mobile robot, neural network, rule-based optimization, , ,
Vol. 4 , (15): 2577-2583
Submitted Accepted Published
April 04, 2012 May 22, 2012 August 01, 2012

A new novel approach to control the autonomous mobile robot that moved along a collision free trajectory until it reaches its target is proposed in this study. The approach taken here utilizes a hybrid neuro-fuzzy method where the neural network effectively chooses the optimum number of activation rules in order to reduce computational time for real-time applications. Initially, a classical fuzzy logic controller has been constructed for the path planning problem. The inference engine required 625 if-then rules for its implementation. Then the neural network is implemented to choose the optimum number of the activation rules based on the input crisp values. Simulation experiments were conducted to test the performance of the developed controller and the results proved that the approach to be practical for real time applications. The proposed neuro-fuzzy optimization controller is evaluated subjectively and objectively with other fuzzy approaches and also the processing time is taken in consideration.
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  Cite this Reference:
Ayman AbuBaker, 2012. A Novel Mobile Robot Navigation System Using Neuro-Fuzzy Rule-Based Optimization Technique.  Research Journal of Applied Sciences, Engineering and Technology, 4(15): 2577-2583.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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