Competitive Goal Coordination in Automatic Parking

  • Darío Maravall
  • Javier de Lope
  • Miguel Ángel Patricio
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3005)

Abstract

This paper addresses the problem of automatic parking by a back-wheel drive vehicle, using a biomimetic model based on direct coupling between vehicle perceptions and actions. The proposed automatic parking solution leads to a dynamic multiobjective optimization problem that cannot be dealt with analytically. A genetic algorithm is therefore used. The paper ends with a discussion of the results of computer simulations.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Maravall, D., de Lope, J.: A Bio-Inspired Robotic Mechanism for Autonomous Locomotion in Unconventional Environments. In: Zhou, C., Maravall, D., Ruan, D. (eds.) Autonomous Robotic Systems: Soft Computing and Hard Computing Methodologies and Applications, pp. 263–292. Physica, Heidelberg (2003)Google Scholar
  2. 2.
    Maravall, D., de Lope, J.: A Reinforcement Learning Method for Dynamic Obstacle Avoidance in Robotic Mechanisms. In: Ruan, D., D’Hondt, P., Kerre, E.E. (eds.) Computational Intelligent Systems for Applied Research, pp. 485–494. World Scientific, Singapore (2002)Google Scholar
  3. 3.
    de Lope, J., Maravall, D.: Integration of Reactive Utilitarian Navigation and Topological Modeling. In: Zhou, C., Maravall, D., Ruan, D. (eds.) Autonomous Robotic Systems: Soft Computing and Hard Computing Methodologies and Applications, pp. 103–139. Physica, Heidelberg (2003)Google Scholar
  4. 4.
    Maravall, D., de Lope, J.: Integration of Potential Field Theory and Sensory-based Search in Autonomous Navigation. In: 15th IFAC World Congress, International Federation of Automatic Control, Barcelona (2002)Google Scholar
  5. 5.
    Laumond, J.-P., Jacobs, P.E., Taix, M., Murray, R.M.: A motion planner for nonholonomic mobile robots. IEEE Trans. on Robotics and Automation 10(5), 577–593 (1996)CrossRefGoogle Scholar
  6. 6.
    Paromtchik, I.E., Laugier, C.: Motion generation and control for parking an autonomous vehicle. In: Proc. IEEE Int. Conf. on Robotics and Automation, Minneapolis, pp. 3117–3122 (1996)Google Scholar
  7. 7.
    Kong, S.G., Kosko, B.: Comparison of fuzzy and neural track backer-upper control systems. In: Kosko, B. (ed.) Neural Networks and Fuzzy Systems, pp. 339–361. Prentice-Hall, Englewood Cliffs (1992)Google Scholar
  8. 8.
    Gu, D., Hu, H.: Neural predictive control for a car-like mobile robot. Robotics and Autonomous Systems 39, 73–86 (2002)CrossRefGoogle Scholar
  9. 9.
    Hitchings, M., Vlacic, L., Kecman, V.: Fuzzy control. In: Vlacic, L., Parent, M., Harashima, F. (eds.) Intelligent Vehicle Technologies, pp. 289–331. Butterworth&Heinemann, Oxford (2001)CrossRefGoogle Scholar
  10. 10.
    Cordón, O., Herrera, F., Hoffmann, F., Magdalena, L.: Genetic Fuzzy Systems. World Scientific, Singapore (2001)MATHGoogle Scholar
  11. 11.
    Chipperfield, A., Fleming, P., Pohlheim, H., Fonseca, C.: Genetic Algorithm Toolbox for Matlab, Department of Automatic Control and Systems Engineering, University of Sheffield (1994)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Darío Maravall
    • 1
  • Javier de Lope
    • 1
  • Miguel Ángel Patricio
    • 2
  1. 1.Department of Artificial Intelligence Faculty of Computer ScienceUniversidad Politécnica de MadridMadridSpain
  2. 2.Department of Computer ScienceUniversidad Carlos III de Madrid 

Personalised recommendations