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.

Full text not available from this repository. (Request a copy)

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:	27 Sep 2011 12:31
URI:	http://usir.salford.ac.uk/id/eprint/922

Actions (login required)

Edit record (repository staff only)