On Role Allocation in RoboCup^*

Brian P. Gerkey¹ and Maja J. Matari²

¹Robotics Laboratory, Stanford University, Stanford CA 94305, USA
gerkey@robotics.stanford.edu
http://robotics.stanford.edu/~gerkey

²Computer Science Department, University of Southern California, Los Angeles CA 90089, USA
mataric@cs.usc.edu
http://robotics.usc.edu/~maja

Abstract. A common problem in RoboCup is role allocation: given a team of players and a set of roles, how should be roles be allocated to players? Drawing on our previous work in multi-robot task allocation, we formalize the problem of role allocation as an iterated form of optimal assignment, which is a well-studied problem from operations research. From this perspective, we analyze the allocation mechanisms of a number of RoboCup teams, showing that most of them are greedy, and that many are in fact equivalent, as instances of the canonical Greedy algorithm. We explain how optimal, yet tractable, assignment algorithms could be used instead, but leave as an open question the actual benefit in terms of team performance of using such algorithms.

^*This paper is based in part on “A Framework for Studying Multi-Robot Task Allocation” by B.P. Gerkey and M.J Matari, appearing in Schultz, A., et al., eds.: Multi-Robot Systems: From Swarms to Intelligent Automata, Volume II, Kluwer Academic Publishers, the Netherlands (2003) 15–26.

LNAI 3020, p. 43 ff.

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