Robots Autónomos

Fecha límite: viernes 10 de junio

Enviar un correo a domingo.gallardo@ua.es con un fichero ZIP adjunto con la documentación y el código fuente de las prácticas:

• Práctica 1a: Modelo de movimiento con partículas
• Práctica 1b: Localización 1-D (robot moviéndose por pasillo) con filtro de Kalman
• Práctica 2: Mapa de ocupación con Player/Stage

• Introduction
• Lecture Notes
• Scipy
• Introducción a Python, Numpy y Matplotlib, Ejemplos python
• Simulaciones físicas en Visual Python

References

• Thrun, Burgard, Fox. Probabilistic Robotics. MIT Press, 2005. Cap. 5

• Lecture Notes

References

• Thrun, Burgard, Fox. Probabilistic Robotics. MIT Press, 2005. Cap. 1,2,6.
• Papoulis, Pillai. Probability, Random Variables and Stochastic Process. McGraw-Hill, 2002. Cap. 4,5,6.

• Lecture Notes
• Lab (MATLAB code)

References

• Thrun, Burgard, Fox. Probabilistic Robotics. MIT Press, 2005. Cap. 7,10.
• Greg Welch and Gary Bishop. An Introduction to the Kalman Filter. University of North Carolina at Chapel Hill, Department of Computer Science. TR 95-041, July 2006.
• Hugh Durrant-Whyte and Tim Bailey. Simultaneous Localisation and Mapping (SLAM): Part I The Essential Algorithms. Robotics and Automation Magazine, June, 2006.
• Tim Bailey and Hugh Durrant-Whyte. Simultaneous Localisation and Mapping (SLAM): Part II State of the Art. Robotics and Automation Magazine, September, 2006.
• Morten Rufus Blas and Søren Riisgaard, SLAM for dummies (Proyecto de fin de asignatura del curso del MIT Cognitive Robotics)

• Lecture Notes
• Player/Stage
• Lab

References

• Thrun, Burgard, Fox. Probabilistic Robotics. MIT Press, 2005. Cap. 4, 8, 9.
• Visual object tracking in 3D with color based particle filter (pdf)
  P.Barrera, J.M.Cañas, V.Matellán. Int. Journal of Information Technology, Vol 2, Num 1, pp 61-65, 2005. ISSN: 1305-2403

• Lecture Notes

References

• Código FastSlam en java. http://www.oursland.net
• Datos para el código anterior. Más datos. Cortesía de Alan Oursland.
• Thrun, Burgard, Fox. Probabilistic Robotics. MIT Press, 2005. Cap. 13.
• S. Thrun, M. Montemerlo, D. Koller, B. Wegbreit, J. Nieto and E. Nebot. FastSLAM: An efficient solution to the simultaneous localization and mapping problem with unknown data association. 2004. Journal of Machine Learning Research.

• Lecture Notes

References

• Alessandro Farinelli, Luca Iocchi, Daniele Nardi. Multirobot Systems: A Classification Focused on Coordination. IEEE Transactions on Systems, Man, and Cybernetics, Oct 2004
• Jakob Fredslund, Maja J Mataric. A General Algorithm for Robot Formations Using Local Sensing and Minimal Communication. In IEEE Transactions on Robotics and Automation, Special Issue on Multi Robot Systems, 18(5):837-846, October 2002
• W. Burgard, M. Moors, C. Stachniss, F. Schneider. Coordinated Multi-Robot Exploration. IEEE Transactions on Robotics 21(3), 2005
• Andreas Kolling, Stefano Carpin. Multirobot Cooperation for Surveillance of Multiple Moving Targets ? A New Behavioral Approach. IEEE International Conference on Robotics and Automation, 2006