Technical University of Munich

@inproceedings{beetz_agilo_2002-1,
 author = {M Beetz and S Buck and R Hanek and A Hofhauser and T Schmitt},
 title = {{AGILO} {RoboCuppers} 2002: Applying Cooperative Game State Estimation
	Experience-based Learning, and Plan-based Control to Autonomous Robot
	Soccer},
 booktitle = {{RoboCup} International Symposium 2002},
 year = {2002},
 series = {Lecture Notes in Computer Science},
 abstract = {This paper describes the computational model underlying the {AGILO}
	autonomous robot soccer team and its implementation. The most salient
	aspects of the {AGILO} control software are that it includes (1)
	a cooperative probabilistic game state estimator working with a simple
	off-the-shelf camera system; (2) a situated action selection module
	that makes amble use of experience-based learning and produces coherent
	team behavior even if inter-robot communication is perturbed; and
	(3) a playbook executor that can perform preprogrammed complex soccer
	plays in appropriate situations by employing plan-based control techniques.
	The use of such sophisticated state estimation and control techniques
	characterizes the {AGILO} software. The paper discusses the computational
	techniques and necessary extensions based on experimental data from
	the 2001 robot soccer world championship.},
}