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A Basal Ganglia Inspired Soft Switching Approach to the Motion Control of a Car-Like Autonomous Vehicle

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7888)

Abstract

This paper presents a new brain-inspired, switching control approach for a car-like autonomous vehicle using a basal ganglia (BG) model as an action selection mechanism. The problem domain has challenging nonholonomic and state constraints which imply no single stabilizing controller solution is possible by time-invariant smooth state feedback. To allow the BG make the correct controller selection from a family of candidate motion controllers, a fuzzy logic-based salience model using reference and tracking error only is developed, and applied in a soft switching control mechanism. To demonstrate the effectiveness of our approach for motion tracking control, we show effective control for a circular trajectory tracking application. The performance and advantages of the proposed fuzzy salience model and the BG-based soft switching control scheme against a traditional single control method are compared.

Keywords

Brain-inspired computing basal ganglia cognitive computation autonomous vehicles motion control soft switching multiple controller systems action selection fuzzy logic 

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References

  1. 1.
    Yang, E., Hussain, A., Gurney, K.: Neurobiologically-inspired soft switching control of autonomous vehicles. In: Zhang, H., Hussain, A., Liu, D., Wang, Z. (eds.) BICS 2012. LNCS, vol. 7366, pp. 82–91. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  2. 2.
    Hussain, A., Abdullah, R., Yang, E., Gurney, K.: An intelligent multiple-controller framework for the integrated control of autonomous vehicles. In: Zhang, H., Hussain, A., Liu, D., Wang, Z. (eds.) BICS 2012. LNCS, vol. 7366, pp. 92–101. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    Giulio, R., James, U., Graham, B., Durrant-Whyte, H.: Radar-based perception for autonomous outdoor vehicles. Journal of Field Robotics 28(6), 894–913 (2011)CrossRefGoogle Scholar
  4. 4.
    Huntsberger, T.: Biologically inspired autonomous rover control. Autonomous Robots 11, 341–346 (2001)zbMATHCrossRefGoogle Scholar
  5. 5.
    Abdullah, R., Hussain, A., Warwick, K., Zayed, A.: Autonomous intelligent cruise control using a novel multiple-controller framework incorporating fuzzy-logic-based switching and tuning. Neurocomputing 71, 2727–2741 (2008)CrossRefGoogle Scholar
  6. 6.
    Gurney, K., Hussain, A., Chambers, J., Abdullah, R.: Controlled and automatic processing in animals and machines with application to autonomous vehicle control. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds.) ICANN 2009, Part I. LNCS, vol. 5768, pp. 198–207. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  7. 7.
    Kolmanovsky, I., McClamroch, N.H.: Developments in nonholonomic control problems. IEEE Control Systems Magazine 15(6), 20–36 (1995)CrossRefGoogle Scholar
  8. 8.
    Yang, E., Gu, D., Mita, T., Huo, H.: Nonlinear tracking control of a car-like mobile robot via dynamic feedback linearization. In: Proc. Control 2004, Bath, UK (2004)Google Scholar
  9. 9.
    Sastry, S.: Nonlinear Systems-Analysis, Stability, and Control. Springer-Verlag New York, Inc. (1999)Google Scholar
  10. 10.
    Gurney, K., Prescott, T., Redgrave, P.: A computational model of action selection in the basal ganglia. I. a new functional anatomy. Bio. Cybern. 84, 401–410 (2001)zbMATHCrossRefGoogle Scholar
  11. 11.
    Gurney, K., Prescott, T., Redgrave, P.: A computational model of action selection in the basal ganglia. II. analysis and simulation of behaviour. Bio. Cybern. 84, 411–423 (2001)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Division of Computing Science and MathematicsUniversity of StirlingStirlingUK
  2. 2.Department of PsychologyUniversity of SheffieldSheffieldUK

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