Evolving Type-2 Fuzzy Logic Controllers for Autonomous Mobile Robots

Autonomous mobile robots navigating in changing and dynamic unstructured environments like the outdoor environments need to cope with large amounts of uncertainties that are inherent in natural environments. The traditional type-1 Fuzzy Logic Controller (FLC) using precise type-1 fuzzy sets cannot fully handle such uncertainties. A type-2 FLC using type-2 fuzzy sets can handle such uncertainties to produce a better performance. However, manually designing the type-2 Membership Functions (MFs) for an interval type-2 FLC is a difficult task. This paper will present a Genetic Algorithm (GA) based architecture to evolve the type-2 MFs of interval type-2 FLCs used for mobile robots. The GA based system converges after a small number of iterations to type-2 MFs which gave very good performance. We have performed various experiments in which the evolved type-2 FLC dealt with the uncertainties and resulted in a very good performance that has outperformed its type-1 counterpart as well as the manually designed type-2 FLC.

[1]  Dongrui Wu,et al.  Type-2 FLS Modeling Capability Analysis , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

[2]  Abdollah Homaifar,et al.  Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms , 1995, IEEE Trans. Fuzzy Syst..

[3]  Ebrahim H. Mamdani.  Responses to Elkan (E.H. Mamdani) , 1994, IEEE Expert.

[4]  N. N. Karnik,et al.  Introduction to type-2 fuzzy logic systems , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[5]  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.

[6]  Jerry M. Mendel,et al.  Type-2 fuzzy logic systems , 1999, IEEE Trans. Fuzzy Syst..

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

[8]  Francisco Herrera,et al.  Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases , 2002, Advances in Fuzzy Systems - Applications and Theory.

[9]  Jorge Posada,et al.  A Type-2 Fuzzy Controller for Tracking Mobile Objects in the Context of Robotic Soccer Games , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

[10]  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).

[11]  Lawrence. Davis,et al.  Handbook Of Genetic Algorithms , 1990 .

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

[13]  W. TanW.,et al.  Uncertain Rule-Based Fuzzy Logic Systems , 2007 .

[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]  J.Ma Troya Linero,et al.  Evolutionary design of fuzzy logic controllers using strongly-typed GP , 1999 .

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

[17]  George J. Klir,et al.  Fuzzy sets, uncertainty and information , 1988 .

[18]  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).

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

[20]  Jerry M. Mendel,et al.  Uncertainty versus choice in rule-based fuzzy logic systems , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[21]  Frank Hoffmann,et al.  Evolutionary design of a fuzzy knowledge base for a mobile robot , 1997, Int. J. Approx. Reason..

[22]  Hani Hagras,et al.  Learning and adaptation of an intelligent mobile robot navigator operating in unstructured environment based on a novel online Fuzzy-Genetic system , 2004, Fuzzy Sets Syst..

[23]  Woei Wan Tan,et al.  On-line Learning Rules for Type-2 Fuzzy Controller , 2006, 2006 IEEE International Conference on Fuzzy Systems.

[24]  H. Ishibuchi.  Genetic fuzzy systems: evolutionary tuning and learning of fuzzy knowledge bases , 2004 .