Abstract
A rule selection scheme of evolutionary algorithm is proposed to design fuzzy path planner for shooting ability in robot soccer. The fuzzy logic is good for the system that works with ambiguous information. Evolutionary algorithm is employed to deal with difficulty and tediousness in deriving fuzzy control rules. Generic evolutionary algorithm, however, evaluate and select chromosomes which may include inferior genes, and generate solutions with uncertainty. To ameliorate this problem, we propose a recombinant rule selection method for gene level selection, which grades genes at the same position in the chromosomes and recombine new parent for next generation. The method was evaluated with application of designing the fuzzy path planner, where each fuzzy rule was encoded as a gene. Simulation and experimental results showed the effectiveness and the applicability of the proposed method.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Dubins, L.E.: On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents. Amer. J. Math. 79, 497–516 (1957)
Kim, J.-H., et al.: A cooperative multi-agent system and its real time application to robot soccer. In: IEEE Proc. Int. Conf. Robot. Automat. Albuquerque, NM, pp. 638–643 (1997)
Shen, W.-M., et al.: Building integrated mobile robots for soccer competition. In: IEEE Proc. Int. Conf. Robot. Automat. vol. 3, Leuven, Belgium, May 1998, pp. 2613–2618 (1998)
Jung, M.-J., et al.: Fuzzy rule extraction for shooting action controller of soccer robot. In: IEEE Proc. Int. Conf. Fuzzy Syst., vol. 1, pp. 556–561 (1999)
Kim, D.-H., et al.: Vector field based path planning and Petri-net based role selection mechanism with Q-learning for the soccer robot system. Intell. Automat. Soft Comput 6(1), 75–87 (2000)
Han, W.-G., et al.: GA based on-line path planning of mobile robots playing soccer games. In: Proc. IEEE 40th Midwest Symp. Circuit Syst., Sacramento, CA, Sep. 1998, pp. 522–525 (1998)
Kim, J.-H., et al.: Path planning and role selection mechanism for soccer robots. In: Proc. IEEE Int. Conf. Robot. Automat. vol. 4. Leuven, Belgium, pp. 3216–3221 (1998)
Hoffmann, F.: Evolutionary Algorithms for Fuzzy Control System Design. Proceedings of the IEEE 89(9), 1318–1333 (2001)
Kang, S.-J., et al.: Evolutionary design of fuzzy rule base for nonlinear system modeling and control. IEEE Transactions on Fuzzy Systems 8(1), 37–45 (2000)
Park, D.-H., Kandel, A.: Genetic-Based New Fuzzy Resoning Models with Application to Fuzzy Control. IEEE Transactions on Sys., Man, and Cybernetics 24(1), 39–47 (1994)
Schwefel, H.-P.: Numerical Optimization of Computer Models. John Wiley, Chichester (1981)
Goldberg, D.E.: Genetic Alogrithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading (1989)
Wang, L.-X.: A Course in Fuzzy Systems and Control. Prentice Hall, Englewood Cliffs (1997)
Kim, J.-H. (ed.): Robotics and Autonomous Systems (Special Issue: First Micro-Robot World Cup Soccer Tournament, MiroSot) 21(2) (1997)
Yang, J.-M., Kim, J.-H.: Sliding Mode Control for Trajectory Tracking of Nonholonomic Wheeled Mobile Robots. IEEE Transactions on Robotics and Automation 15(3), 578–587 (1999)
Kim, J.-H., et al.: Soccer Robotics (Springer Tracts in Advanced Robotics). Springer, Heidelberg (2004)
Jung, M.-J., et al.: Fuzzy rule extraction for shooting action controller of soccer robot. In: Fuzzy Systems Conference Proceedings, vol. 1, pp. 556–561 (1999)
Lee, M.-S., Jung, M.-J., Kim, J.-H.: Evolutionary programming-based fuzzy logic path planner and follower for mobile robots. In: Proceedings of the 2000 Congress on Evolutionary Computation, vol. 1, pp. 139–144 (2000)
Kim, Y.-J., Kim, J.-H., Kim, D.-S.: Evolutionary Programming-Based Uni-vector Field Navigation Method for Fast Mobile Robots. IEEE Trans. on Systems Man and Cybernetics - Part B - Cybernetics 31(3), 450–458 (2001)
Mizumoto, M.: Fuzzy controls by fuzzy sington-type resoning method. In: Proc. of the Fifth IFSA world congress, Seoul, Korea, pp. 945–948 (1993)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Park, JH., Stonier, D., Kim, JH., Ahn, BH., Jeon, MG. (2007). Recombinant Rule Selection in Evolutionary Algorithm for Fuzzy Path Planner of Robot Soccer. In: Freksa, C., Kohlhase, M., Schill, K. (eds) KI 2006: Advances in Artificial Intelligence. KI 2006. Lecture Notes in Computer Science(), vol 4314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69912-5_24
Download citation
DOI: https://doi.org/10.1007/978-3-540-69912-5_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69911-8
Online ISBN: 978-3-540-69912-5
eBook Packages: Computer ScienceComputer Science (R0)