The AGILO autonomous robot soccer team: computational principles, experiences, and perspectives

  • Authors:
  • Michael Beetz;Sebastian Buck;Robert Hanek;Thorsten Schmitt;Bernd Radig

  • Affiliations:
  • Munich University of Technology, Munich, Germany;Munich University of Technology, Munich, Germany;Munich University of Technology, Munich, Germany;Munich University of Technology, Munich, Germany;Munich University of Technology, Munich, Germany

  • Venue:
  • Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
  • Year:
  • 2002

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Abstract

This paper describes the computational model underlying the AGILO autonomous robot soccer team, its implementation, and our experiences with it. 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 ample 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 distinguishes the AGILO software from many others applied to mid-size autonomous robot soccer. The paper discusses the computational techniques and necessary extensions based on experimental data from the 2001 robot soccer world championship.