by T Schmitt, R Hanek and M Beetz
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.
Reference:
Developing Comprehensive State Estimators for Robot Soccer (T Schmitt, R Hanek and M Beetz), In RoboCup International Symposium 2003, 2003.
Bibtex Entry:
@inproceedings{schmitt_developing_2003,
author = {T Schmitt and R Hanek and M Beetz},
title = {Developing Comprehensive State Estimators for Robot Soccer},
booktitle = {{RoboCup} International Symposium 2003},
year = {2003},
series = {Padova},
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.},
}