Paper Info
Title
Neural Networks and Fuzzy Logic navigation approach for a bi-steerable mobile robot
Abstract
This paper presents an implementation of an intelligent navigation approach on a bi-steerable mobile robot Robucar. This approach is based on Neural Networks (NN) and Fuzzy Logic (FL) paradigms to provide Robucar with capability to acquire the obstacle avoidance, target localization, decision-making and action behaviors after learning and adaptation. To develop this approach, three (NN) and a FL controller to achieve the desired task are used. Experimental results are presented showing the effectiveness of the overall navigation control system.
Year
DOI
Venue
2011
10.1109/URAI.2011.6145930
Ubiquitous Robots and Ambient Intelligence
Keywords
Field
DocType
collision avoidance,decision making,fuzzy control,learning systems,mobile robots,neurocontrollers,action behaviors,bisteerable mobile robot Robucar,decision-making,fuzzy logic controller,intelligent navigation approach,learning,navigation control system,neural networks,obstacle avoidance,target localization,Mobile robots,fuzzy logic,neural networks,obstacle avoidance
Obstacle avoidance,Control theory,Fuzzy logic,Control engineering,Artificial intelligence,Mobile robot navigation,Engineering,Fuzzy control system,Control system,Artificial neural network,Mobile robot
Conference
ISBN
Citations 
PageRank 
978-1-4577-0722-3
0
0.34
References 
Authors
6
4
Name
Order
Citations
PageRank
Ouahiba Azouaoui1367.12
Noureddine Ouadah2233.80
Ibrahim Mansour321.10
Semani, A.400.34