Neural Networks and Fuzzy Logic navigation approach for a bi-steerable mobile robot

Author

Azouaoui, O. ; Ouadah, N. ; Mansour, I. ; Semani, A.

Author_Institution

Centre de Dev. des Technol. Av. (CDTA), Algiers, Algeria

fYear

2011

fDate

23-26 Nov. 2011

Firstpage

44

Lastpage

49

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.

Keywords

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; Artificial neural networks; Collision avoidance; Fuzzy logic; Navigation; Robot kinematics; Vehicles; Mobile robots; fuzzy logic; neural networks; obstacle avoidance;

fLanguage

English

Publisher

ieee

Conference_Titel

Ubiquitous Robots and Ambient Intelligence (URAI), 2011 8th International Conference on

Conference_Location

Incheon

Print_ISBN

978-1-4577-0722-3

Type

conf

DOI

10.1109/URAI.2011.6145930

Filename

6145930