A hierarchical type-2 fuzzy logic control architecture 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 of 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. In this paper, we present a novel reactive control architecture for autonomous mobile robots that is based on type-2 FLC to implement the basic navigation behaviors and the coordination between these behaviors to produce a type-2 hierarchical FLC. In our experiments, we implemented this type-2 architecture in different types of mobile robots navigating in indoor and outdoor unstructured and challenging environments. The type-2-based control system dealt with the uncertainties facing mobile robots in unstructured environments and resulted in a very good performance that outperformed the type-1-based control system while achieving a significant rule reduction compared to the type-1 system.

[1]  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).

[2]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[3]  Andrea Bonarini,et al.  Anytime Learning and Adaptation of Structured Fuzzy Behaviors , 1997, Adapt. Behav..

[4]  J. Mendel.  Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions , 2001 .

[5]  Edward Tunstel,et al.  Behavior Hierarchy for Autonomous Mobile Robots: Fuzzy-Behavior Modulation and Evolution , 1997, Intell. Autom. Soft Comput..

[6]  José M. Molina López,et al.  Genetic learning of fuzzy reactive controllers , 1998, Robotics Auton. Syst..

[7]  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..

[8]  Chuen-Chien Lee,et al.  Fuzzy logic in control systems: fuzzy logic controller. II , 1990, IEEE Trans. Syst. Man Cybern..

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

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

[11]  M. Maeda,et al.  Fuzzy drive control of an autonomous mobile robot , 1991 .

[12]  HANI HAGRAS,et al.  Outdoor mobile robot learning and adaptation , 2001, IEEE Robotics Autom. Mag..

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

[14]  A. Garcia-Cerezo,et al.  Fuzzy modelling operator navigation behaviors , 1997, Proceedings of 6th International Fuzzy Systems Conference.

[15]  Chuen-Chien Lee.  FUZZY LOGIC CONTROL SYSTEMS: FUZZY LOGIC CONTROLLER - PART I , 1990 .

[16]  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).

[17]  C C Lee,et al.  FUZZY LOGIC IN CONTROL SYSTEM FUZZY LOGIC CONTROLLER-PART II , 1990 .

[18]  Li-Xin Wang,et al.  Analysis and design of hierarchical fuzzy systems , 1999, IEEE Trans. Fuzzy Syst..

[19]  Robert Ivor John,et al.  Type 2 Fuzzy Sets: An Appraisal of Theory and Applications , 1998, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

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

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

[23]  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..

[24]  Hani Hagras,et al.  for Prototyping Outdoor Mobile Robots Operating in Unstructured Environments Online Learning Techniques for Prototyping Outdoor Mobile Robots Operating in Unstructured , 2001 .

[25]  K. Wu.  Fuzzy interval control of mobile robots , 1996 .

[26]  Jerry M. Mendel,et al.  Connection admission control in ATM networks using survey-based type-2 fuzzy logic systems , 2000, IEEE Trans. Syst. Man Cybern. Part C.

[27]  A. Safiotti,et al.  Fuzzy logic in autonomous robotics: behavior coordination , 1997, Proceedings of 6th International Fuzzy Systems Conference.