Abstract
This paper describes the intelligent automated guided vehicle (AGV) control system. The AGV used in this paper is a virtual vehicle simulated using computer. The purpose of the control system is to control the simulated AGV for moving along the given path towards the goal. Some obstacles can be placed on or near the path to increase the difficulties of the control system. The intelligent AGV should trace the path by avoiding these obstacles. In some situations, it is inevitable to avoid the obstacles without reversing. In this paper, we look into the use of fuzzy automaton for controlling the AGV. In order to better avoid the obstacles, reverse strategy has been implemented to the fuzzy automaton controller. Another alternative to incorporate the human expertise and observations is to use a hybrid intelligent controller using fuzzy and case base reasoning to implement the reverse strategy. This paper presents the comparison results for the three intelligent AGV systems used to avoid obstacles.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Mamdami, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Human-Computer Studies 7, 1–13 (1975)
Wong, K.W., Gedeon, T.D., Koczy, L.: Fuzzy Signature and Cognitive Modelling for Complex Decision Model. In: Castillo, O., Melin, P., Montiel Ross, O., Sepúlveda Cruz, R., Pedrycz, W., Kacprzyk, J. (eds.) Theoretical Advances and Applications of Fuzzy Logic and Soft Computing. Advances in Soft Computing Series, vol. 42, pp. 380–389. Springer, Heidelberg (2007)
Cselényi, J., Kovács, S., Pap, L., Kóczy, L.T.: New Concepts in the Fuzzy Logic Controlled Path Tracking Strategy of the Differential Steered AGVs. In: 5th International Workshop on Robotics in Alpe-Adria-Danube Region, RAAD 1996, pp. 587–592 (1996)
Kovács, S.: Similarity based Control Strategy Reconfiguration by Fuzzy Reasoning and Fuzzy Automata. In: Proceedings of the IECON 2000, IEEE International Conference on Industrial Electronics, Control and Instrumentation, pp. 542–547 (2000)
Kato, S., Wong, K.W.: The Automated Guided Vehicle Using Fuzzy Control and CBR Techniques. In: Proceedings of SCIS & ISIS 2008, pp. 1788–1792 (2008)
Kato, S., Wong, K.W.: Fuzzy and Case Based Reasoning Obstacle Avoidance Techniques for Games and Robots. IEEE Transactions on Computational Intelligence and AI in Games (submitted)
Wong, K.W., Tikk, D., Gedeon, T.D., Kóczy, L.T.: Fuzzy rule interpolation for multidimensional input spaces with applications: A case study. IEEE Trans of Fuzzy Systems 13(6), 809–819 (2005)
Aamodt, A., Plaza, E.: Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. Artificial Intelligence Communications 7(1), 39–59 (1994)
Kovács, S., Kóczy, L.T.: Application of an approximate fuzzy logic controller in an AGV steering system, path tracking and collision avoidance strategy. In: Fuzzy Set Theory and Applications, Tatra Mountains Mathematical Publications. Mathematical Institute Slovak Academy of Sciences, Bratislava, Slovakia, vol. 16, pp. 456–467 (1999)
Kovács, S.: Fuzzy Rule Interpolation in Practice. In: Proceedings of the Joint 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2006), Tokyo Institute of Technology, Tokyo, Japan, p. 6 (2006) (invited talk)
Johanyak, Z.C., Tikk, D., Kovács, S., Wong, K.W.: Fuzzy Rule Interpolation Matlab Toolbox - FRI Toolbox. In: Proceedings of IEEE International Conference on Fuzzy Systems 2006, Vancouver, Canada, pp. 1427–1433 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kato, S., Wong, K.W. (2009). Intelligent Automated Guided Vehicle with Reverse Strategy: A Comparison Study. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02490-0_78
Download citation
DOI: https://doi.org/10.1007/978-3-642-02490-0_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02489-4
Online ISBN: 978-3-642-02490-0
eBook Packages: Computer ScienceComputer Science (R0)