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Developing Comprehensive State Estimators for Robot Soccer
Thorsten Schmitt, Robert Hanek, and Michael Beetz
TU München, Institut für Informatik, 80290 München, Germanyschmittt@in.tum.de
hanek@in.tum.de
beetzm@in.tum.de
http://www9.in.tum.de/agilo
Abstract. This paper sketches and discusses design options for complex probabilistic state estimators and investigates their interactions and their impact on performance. We consider, as an example, the estimation of game states in autonomous robot soccer. We show that many factors other than the choice of algorithms determine the performance of the estimation systems. We propose empirical investigations and learning as necessary tools for the development of successful state estimation systems.
LNAI 3020, p. 397 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2004