Advertisement

Behavior-based control system of a mobile robot for the visual inspection of ventilation ducts

  • W. Panfil
  • P. Przystałka
  • M. Adamczyk

Abstract

The paper deals with the implementation of a behavior-based control and learning controller for autonomous inspection robots. The presented control architecture is designed to be used in the mobile robot (Amigo) for the visual inspection of ventilation systems. The main aim of the authors’ study is to propose a behavior-based controller with neural network-based coordination methods. Preliminary results are promising for further development of the proposed solution. The method has several advantages when compared with other competitive and/or co-operative approaches due to its robustness and modularity.

Keywords

Mobile Robot Autonomous Underwater Vehicle Linear Speed Mobile Robot Navigation Virtual Robot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Adamczyk M.: “Mechanical carrier of a mobile robot for inspecting ventilation ducts” In the current proceedings of the 7th International Conference “MECHATRONICS 2007”.Google Scholar
  2. [2]
    Adamczyk M., Bzymek A., Przystał ka P, Timofiejczuk A.: “Environment detection and recognition system of a mobile robot for inspecting ventilation ducts.” In the current proceedings of the 7th International Conference “MECHATRONICS 2007”.Google Scholar
  3. [3]
    A. D’Amico, Ippoliti G., Longhi S.: “A Multiple Models Approach for Adaptation and Learning in Mobile Robots Control” Journal of Intelligent and Robotic Systems, Vol. 47, pp. 3–31, (September 2006).CrossRefGoogle Scholar
  4. [4]
    Arkin, R. C. 1989 Neuroscience in motion: the application of schema theory to mobile robotics. In Visuomotor coordination: amphibians, comparisons, models and robots (ed. J.-P. Ewert & M. A. Arbib), pp. 649–671. New York: Plenum.Google Scholar
  5. [5]
    Brooks, R. A., “A Robust Layered Control System for a Mobile Robot.” IEEE Journal of Robotics and Automation, Vol. RA-2, No. 1, 1986, pp. 14–23.Google Scholar
  6. [6]
    Carreras M., Yuh J., Batlle J., Pere Ridao: “A behavior-based scheme using reinforcement learning for autonomous underwater vehicles.” Oceanic Engineering, IEEE Journal, April 2005, Vol. 30, pp. 416–427.CrossRefGoogle Scholar
  7. [7]
    Moczulski W., Adamczyk M., Przystałka P., Timofiejczuk A.: „Mobile robot for inspecting ventilation ducts” In the current proceedings of the 7th International Conference “MECHATRONICS 2007”.Google Scholar
  8. [8]
    Rusu P., Petriu E.M., Whalen T.E., Cornell A.: Spoelder, H.J.W.: “Behavior-based neuro-fuzzy controller for mobile robot navigation” Instrumentation and Measurement, IEEE Transactions on Vol. 52, Aug. 2003 pp.1335–1340.CrossRefGoogle Scholar
  9. [9]
    Scheutz M., Andronache V.: “Architectural mechanisms for dynamic changes of behavior selection strategies in behavior-based systems” Systems, Man and Cybernetics, Part B, Dec. 2004, Vol. 34, pp. 2377–2395.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • W. Panfil
    • 1
  • P. Przystałka
    • 1
  • M. Adamczyk
    • 1
  1. 1.Department of Fundamentals of Machinery DesignSilesian University of TechnologyGliwicePoland

Personalised recommendations