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Intelligent adaptive mobile robot navigation

Djouani, K, Oussalah, M, Pontnau, J and Nefti-Meziani, S 2001, 'Intelligent adaptive mobile robot navigation' , Journal of Intelligent and Robotic Systems, 30 (4) , pp. 311-329.

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Abstract

This paper deals with the application of a neuro-fuzzy inference system to a mobile robot navigation in an unknown, or partially unknown environment. The final aim of the robot is to reach some pre-defined goal. For this purpose, a sort of a co-operation between three main sub-modules is performed. These sub-modules consist in three elementary robot tasks: following a wall, avoiding an obstacle and running towards the goal. Each module acts as a Sugeno–Takagi fuzzy controller where the inputs are the different sensor information and the output corresponds to the orientation of the robot. The rule-base is generated by the controller after some learning process based on a neural architecture close to that used by Wang and Menger. This leads to adaptive neuro-fuzzy inference systems (ANFIS) (one for each module). The adaptive navigation system (ANFIS), based on integrated reactive-cognitive parts, learns and generates the required knowledge for achieving the desired task. However, the generated rule-base suffers from redundancy and abundance of data, most of which are less useful. This makes the assignment of a linguistic label to the associated variable difficult and sometimes counter-intuitive. Consequently, a simplification phase allowing elimination of redundancy is required. For this purpose, an algorithm based on the class of fuzzy c-means algorithm introduced by Bezdek and we have developed an inclusion structure. Experimental results confirm the meaningfulness of the elaborated methodology when dealing with navigation of a mobile robot in unknown, or partially unknown environment.

Item Type: Article
Uncontrolled Keywords: neuro-fuzzy, fuzzy c-means, navigation, mobile robotics
Themes: Subjects / Themes > T Technology > TK Electrical engineering. Electronics Nuclear engineering
Subjects / Themes > Q Science > QA Mathematics > QA075 Electronic computers. Computer science > QA076 Computer software
Subjects outside of the University Themes
Schools: Colleges and Schools > College of Science & Technology
Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering
Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > CASE Control & Systems Engineering Research Centre
Journal or Publication Title: Journal of Intelligent and Robotic Systems
Publisher: Springer Netherlands
Refereed: Yes
ISSN: 09210296
Depositing User: H Kenna
Date Deposited: 06 Jan 2009 16:12
Last Modified: 20 Aug 2013 16:51
URI: http://usir.salford.ac.uk/id/eprint/922

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