Skip to main content

Advertisement

Log in

Multi-objective dynamic optimization with genetic algorithms for automatic parking

Soft Computing Aims and scope Submit manuscript

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. This problem is solved by means of a bio-inspired approach in which the vehicle controller does not need to know the car kinematics and dynamic, neither does it call for a priori knowledge of the environment map. The key point in the proposed approach is the definition of performance indices that for automatic parking happen to be functions of the strategic orientations to be injected, in real time, to the car-like robot controller. This solution leads to a dynamic multi-objective optimization problem, which is extremely hard to be dealt analytically. A genetic algorithm is therefore applied, thanks to which we obtain a very simple and efficient solution.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  1. Deb K (2001) Multi-objective optimization using evolutionary algorithms. Wiley, New York

    MATH  Google Scholar 

  2. Fonseca CM, Fleming PJ (1993) Genetic algorithms for multiobjective optimization: formulation, discussion and generalization. In: Proceedings of the 5th International Conference on genetic algorithms, Morgan Kaufmann, San Francisco, pp. 416–423

  3. Coello CA, Van Veldhuizen DA, Laumont GB (2003) Evolutionary algorithms for solving multi-objective problems. Kluwer, New York

    MATH  Google Scholar 

  4. Coello CA (2003) Special issue on evolutionary multiobjective optimization. IEEE Trans Evol Comput 7(2):97–99

    Article  Google Scholar 

  5. Maravall D, De Lope J (2003) 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. Physica-Verlag, Springer, Berlin Heidelberg New York, pp. 263–292

    Google Scholar 

  6. De Lope J, Maravall D (2005) A biomimetic approach to the stability of biped robots. In: Armada M, González P (eds) Climbing and walking robots. Springer, Berlin Heidelberg New York, pp. 593–600

    Chapter  Google Scholar 

  7. De Lope J, Maravall D (2003) 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. Physica-Verlag, Springer, Berlin Heidelberg New York, pp. 103–139

    Google Scholar 

  8. Maravall D, De Lope J (2002) Integration of artificial potential field theory and sensory-based search in autonomous navigation. In: Proceedings of the 15th IFAC World Congress, International federation of automatic control

  9. Maravall D, De Lope J, Patricio MA (2004) Competitive goal coordination in automatic parking. In: 1st European workshop on evolutionary algorithms in stochastic and dynamic environments, EVOSTOC-2004. LNCS 3005, Springer, Berlin Heidelberg New york, pp. 537–548

  10. Zadeh L (1965) Fuzzy sets. Inform Control 8:338–353

    Article  MATH  MathSciNet  Google Scholar 

  11. Zadeh L (1968) Fuzzy algorithms. Inform Control 12:94–102

    Article  MATH  MathSciNet  Google Scholar 

  12. Sugeno M, Nishida M (1985) Fuzzy control of a model car. Fuzzy Sets Syst 16:100–110

    Google Scholar 

  13. Sugeno M, Murofushi T (1989) Fuzzy algorithm control of a model car by oral instructions. Fuzzy Sets Syst 32:207–219

    Article  MathSciNet  Google Scholar 

  14. Sugeno M, Murakami K (1985) An experimental study of fuzzy parking control using a model car. In: Sugeno M (eds) Industrial applications of fuzzy control. North-Holland, Amsterdom, pp. 125–135

    Google Scholar 

  15. Tanaka K (1995) Design of model-based controllers using Lyapunov’s stability approach and its applications to trajectory stabilization of a model car. In: Nguyeng HT et al (eds) Theoretical Aspects of Fuzzy Control. Wiley, New York, pp. 31–50

    Google Scholar 

  16. Laugier C, Fraichard Th, Garnier Ph, Paromtchik IE, Scheuer A (1999) Sensor-based control architecture for a car-like vehicle. Auton Robots 6(2):165–185

    Article  Google Scholar 

  17. Petti S, Fraichard Th (2005) Safe motion planning in dynamic environments. In: Proceedings of the IEEE-RSJ International Conference on intelligent robots and systems, Edmonton, Canada

  18. Chipperfield A, Fleming P, Pohlheim H, Fonseca C (1994) Genetic algorithm toolbox for matlab, Department of Automatic Control and Systems Engineering, University of Sheffield

  19. Khatib O (1986) Real-time obstacle avoidance for manipulators and mobile robots. Int J Robot Res 5(1):90–98

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Darío Maravall.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Maravall, D., de Lope, J. Multi-objective dynamic optimization with genetic algorithms for automatic parking. Soft Comput 11, 249–257 (2007). https://doi.org/10.1007/s00500-006-0066-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-006-0066-6

Keywords

Navigation