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Image Understanding and Knowledge-Based Systems

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AGILO RoboCuppers 2002: Applying Cooperative Game State Estimation Experience-based Learning, and Plan-based Control to Autonomous Robot Soccer (bibtex)
AGILO RoboCuppers 2002: Applying Cooperative Game State Estimation Experience-based Learning, and Plan-based Control to Autonomous Robot Soccer (bibtex)
by M Beetz, S Buck, R Hanek, A Hofhauser and T Schmitt
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.
Reference:
AGILO RoboCuppers 2002: Applying Cooperative Game State Estimation Experience-based Learning, and Plan-based Control to Autonomous Robot Soccer (M Beetz, S Buck, R Hanek, A Hofhauser and T Schmitt), In RoboCup International Symposium 2002, 2002. 
Bibtex Entry:
@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.},
}
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Informatik IX

Image Understanding and Knowledge-Based Systems

Boltzmannstrasse 3
85748 Garching

info@iuks.in.tum.de