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 |
|---|---|
| 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: | Schools > School of Computing, Science and Engineering Schools > School of Computing, Science and Engineering > Salford Innovation 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 Aug 2021 22:04 |
| URI: | https://usir.salford.ac.uk/id/eprint/922 |
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