Tema 1 Introducción

Tema 2 Arquitecturas

Tema 3 Mecánica

Tema 4 Sensores

Tema 5 Localización

Artículo introducción a filtro de kalman

Filtro de Kalman. Formulación

Ejemplo filtro Kalman en Matlab

Bibliografía

• Capítulo 1 de Stochastic models, estimation and control. Vol1. by Meter S. Maybeck, Academic Press 1979.
• An Introduction to the Kalman Filter. Greg Welch and Gary Bishop. TR 95-041 .Department of Computer Science. University of North Carolina at Chapel Hill. Chapel Hill, NC 27599-3175.
• S. Thrun. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel, editors, Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, 2002.
• Real-time Obstacle Avoidance for Fast Mobile Robots. (http://www.eecs.umich.edu/~johannb/paper10.pdf) J. Borenstein, Y. Koren IEEE Transactions on Systems, Man, and Cybernetics, Vol. 19, No. 5, Sept./Oct., pp. 1179-1187. 1989.
• Experimental comparison of localization methods. (http://www.ai.sri.com/~konolige/papers/comparison.pdf). Gutmann, J-S, W.Burgard, D. Fox, and K. Konolige, International Conference on Intelligent Robots and Systems, Victoria, B.C. (October 1998).
• Intelligence Without Representation. (http://www.ai.mit.edu/people/brooks/papers/representation.pdf). Rodney A. Brooks, Artificial Intelligence Journal (47), 1991, pp. 139-159.
• A Robust Layered Control System for a Mobile Robot. (http://www.ai.mit.edu/people/brooks/papers/AIM-864.pdf). IEEE Journal Robotics and Automation(2), 1, pp. 14-23, 1986.
• Transparencias de la asignatura.  http://www.eis.uva.es/~eduzal/doctorado/robotica.html

Comentarios o sugerencias: Eduardo Zalama Casanova
                                                   E-mail: eduzal@eis.uva.es