An embedded interval type-2 neuro-fuzzy controller for mobile robot navigation

This paper describes intelligent navigation using an embedded interval type-2 neuro-fuzzy controller. Weightless neural network (WNNs) strategy is used because fast learning, easy hardware implementation and well suited to microcontroller-based-real-time systems. The WNNs utilizes previous sensor data and analyzes the situation of the current environment and classifies geometric feature such as U-shape, corridor and left or right corner. The behavior of mobile robot is implemented by means of interval type-2 fuzzy control rules can be generated directly from the WNNs classifier. This functionality is demonstrated on a mobile robot using modular platform and containing several microcontrollers implies the implementation of a robust architecture. The proposed architecture implemented using low cost range sensor and low cost microprocessor. The experiment results show, using that technique the source code is efficient. The mobile robot can recognize the current environment and to be able successfully avoid obstacle in real time and achieve smother motion compare than logic function and fuzzy type-1 controller.

[1]  Dante Augusto Couto Barone,et al.  Hardware implementation of RAM neural networks , 1996, Pattern Recognit. Lett..

[2]  Richard Mitchell,et al.  Neural Network Control of a Simple Mobile Robot , 1998, Concepts for Neural Networks.

[3]  Toshio Fukuda,et al.  An intelligent robotic system based on a fuzzy approach , 1999, Proc. IEEE.

[4]  Jerry M. Mendel,et al.  Type-2 fuzzy sets made simple , 2002, IEEE Trans. Fuzzy Syst..

[5]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Ching-Hung Lee,et al.  TYPE-2 FUZZY NEURAL NETWORK SYSTEMS AND LEARNING , 2002 .

[7]  E. do Valle Simoes,et al.  High speed neural control for robot navigation , 1996, 1996 IEEE International Conference on Systems, Man and Cybernetics. Information Intelligence and Systems (Cat. No.96CH35929).

[8]  Siti Zaiton Mohd Hashim,et al.  An Embedded Fuzzy Type-2 Controller Based Sensor Behavior for Mobile Robot , 2008, 2008 Eighth International Conference on Intelligent Systems Design and Applications.

[9]  Hani Hagras,et al.  Embedded Interval Type-2 Neuro-Fuzzy Speed Controller for Marine Diesel Engines , 2006 .

[10]  Yan Zhou,et al.  Neural network control for a fire-fighting robot , 1998, Softw. Concepts Tools.

[11]  Jerry M. Mendel,et al.  Interval type-2 fuzzy logic systems , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[12]  Chi-Hsu Wang,et al.  Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN) , 2003, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[13]  Alessandro Saffiotti,et al.  The uses of fuzzy logic in autonomous robot navigation , 1997, Soft Comput..

[14]  Jerry M. Mendel,et al.  Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems , 2002, IEEE Trans. Fuzzy Syst..

[15]  Hani Hagras,et al.  A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots , 2004, IEEE Transactions on Fuzzy Systems.

[16]  Pisit Phokharatkul,et al.  Mobile robot control using type-2 fuzzy logic system , 2004, IEEE Conference on Robotics, Automation and Mechatronics, 2004..

[17]  Hani Hagras,et al.  Using Uncertainty Bounds in the Design of an Embedded Real-Time Type-2 Neuro-Fuzzy Speed Controller for Marine Diesel Engines , 2006, 2006 IEEE International Conference on Fuzzy Systems.

[18]  Jim Austin.  A review of RAM based neural networks , 1994, Proceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems.

[19]  Siti Zaiton Mohd Hashim,et al.  Environmental Recognition Using RAM-Network Based Type-2 Fuzzy Neural for Navigation of Mobile Robot , 2009, 2009 International Conference on Computer and Automation Engineering.

[20]  Dongrui Wu,et al.  A type-2 fuzzy logic controller for the liquid-level process , 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

[21]  Adel M. Alimi,et al.  Motion Planning in Dynamic and Unknown Environment Using an Interval Type-2 TSK Fuzzy Logic Controller , 2007, 2007 IEEE International Fuzzy Systems Conference.