Abstract
This paper describes the optimization of an Integrator control block within the proposed navigation control system for a mobile robot. The control blocks that the integrator will combine are two Fuzzy Inference Systems (FIS) in charge of tracking and reaction respectively. The integrator block is call Weighted Fussy Inference System (WFIS), and assigns weights to the responses on each behavior block, to combine them into a single response.
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References
Aceves, A., Aguilar, J.: A Simplified Version of Mamdani’s Fuzzy Controller The Natural Logic Controller. IEEE Transactions on Fuzzy Systems 14(1), 16–30 (2006)
Aguilar, L., Melin, P., Castillo, O.: Intelligent Control of a stepping motor drive using a hybrid neuro-fuzzy ANFIS approach. Applied Soft Computing 3(3), 209–219 (2003)
Astudillo, L., Castillo, O.T., Aguilar, L.: Intelligent Control of an Autonomous Mobile Robot Using Type-2 Fuzzy Logic. Engineering Letters 13(2), 93–97 (2006)
Bell, M., Toriu, T., Nakajima, S.: Image-Based Robot Map Building and Path Planning with an Omnidirectional Camera Using Self-Organising Maps. International Journal of Innovative Computing, Information and Control, 3845–3852 (2011)
Castillo, O., Melin, P.: New fuzzy-fractal-genetic method for automated mathematical Modeling and Simulation of Robotic Dynamic Systems. IEEE, International Conference on Fuzzy Systems, vol. 2, 1182–118 (1998)
Castillo, O., Melin, P.: New fuzzy-fractal-genetic method for automated mathematical Modeling and Simulation of Robotic Dynamic Systems. In: IEEE, International Conference on Fuzzy Systems, vol. 2, pp. 1182–1118 (1998)
Coupland, S.: Type-2 Fuzzy Control of a Mobile Robot. PhD Transfer Report. De Montfort University, UK (2003)
Cupertino, F., Giordano, V., Naso, D., Delfine, L.: Fuzzy control of a mobile robot. IEEE Robotics & Automation Magazine, 74–81 (2006)
Fate, M.: Robust Voltage Control of Electrical Manipulators in Task-Space. International Journal of Innovative Computing, Information and Control, 2691–2700 (2010)
Ishikawa, S.: A Method of Indoor Mobile Robot Navigation by Fuzzy Control. In: Proc. Int. Conf. Intell. Robot. Syst., Osaka, Japan, pp. 1013–1018 (1991)
Klir, J.G., Yuan, B.: Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers by Lotfi A. Zadeh. In: Advances in Fuzzy Systems: Application and Theory, vol. 6. World Scientific Publishing Company (1996)
Kim, C., Lee, K.: Robust Control of Robot Manipulators Using Dynamic Compensators under Parametric Uncertainty. International Journal of Innovative Computing, Information and Control, 4129–4137 (2011)
Leyden, M., Toal, D., Flanagan, C.: A Fuzzy Logic Based Navigation System for a Mobile Robot. In: Proceedings of Automatisierungs Symposium (1999)
Mamdani, E.: Applications of fuzzy logic to approximate reasoning using linguistic synthesis. In: Proc. 6th Int. Symp. on Multiple Value Logic, pp. 196–202. Utah State University (1976)
Melendez, A., Castillo, O., Soria, J.: Reactive and Tracking Control of a Mobile Robot in a Distributed Environment Using Fuzzy Logic. In: IEEE International Conference on FUZZ, pp. 1–5 (2010)
Melendez, A., Castillo, O., Melin, P.: Evolutionary Optimization of the Fuzzy Controllers in a Navigation System for a Mobile Robot. International Journal of Innovative Computing, Information and Control, International Journal (in press)
Meléndez, A., Castillo, O., Soria, J.: Reactive Control of a Mobile Robot in a Distributed Environment Using Fuzzy Logic. In: Fuzzy Information Processing Society, NAFIPS 2008. Annual Meeting of the North American, vol. (19-22), pp. 1–5 (2008)
Melin, P., Castillo, O.: Intelligent Systems with Interval Type-2 Fuzzy Logic. International Journal of Innovative Computing, Information and Control, 771–784 (2008)
Melin, P., Castillo, O.: Intelligent control of aircraft dynamic systems with a new hybrid neuro-fuzzy fractal approach. Information Sciences 142(1-4), 161–175 (2002)
Melin, P., Castillo, O.: Adaptive Intelligent control of aircraft systems with a hybrid approach combining neural networks, fuzzy logic and fractal theory. Applied Soft Computing 3(4), 353–262 (2003)
Pishkenari, H.N., Mahboobi, S.H., Meghdari, A.: On the Optimum Design of Fuzzy Logic Controller for Trajectory Tracking Using Evolutionary Algorithms. In: Cybernetics and Intelligent Systems, 2004 IEEE Conference on Publication Date: 1-3, vol. 1, pp. 660–665 (2004)
Payton, D.W., Rosenblatt, J.K., Keirsey, D.M.: Plan guided reaction. IEEE Transactions on Systems, Man and Cybernetics 20(6), 1370–1382 (1990)
Shafiei, S., Soltanpour, M.: Neural Network Sliding-Mode-PID Controller Design for Electrically Driven Robot Manipulators. International Journal of Innovative Computing, Information and Control, 511–524 (2011)
Shafiei, S., Soltanpour, M.: Robust Task-Space Control of Robot Manipulators under Imperfect Transformation of Control Space. International Journal of Innovative Computing, Information and Control, 3949–3960 (2009)
Thomson, A., Baltes, J.: A path following system for autonomous robots with minimal computing power. University of Auckland, Private Bag 92019, Auckland, New Zealand, Technical Report (2001)
Mobile robotics toolbox for Matlab 5 (2001), http://www.uamt.feec.vutbr.cz/robotics/simulations/amrt/simrobot_en.html
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Meléndez, A., Castillo, O. (2013). Evolutionary Optimization of the Fuzzy Integrator in a Navigation System for a Mobile Robot. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Recent Advances on Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33021-6_2
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DOI: https://doi.org/10.1007/978-3-642-33021-6_2
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