AutoRef: Towards real-robot soccer complete automated refereeing

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Abstract

Preparing for robot soccer competitions by empirically evaluating different possible game strategies has been rather limited in leagues using real robots. Such limitation comes from factors related to the difficulty of extensively experimenting with games with real robots, such as their inevitable wear and tear and their usual limited number. RoboCup real robot teams have therefore developed simulation environments to enable experimentation. However, in order to run complete games in such simulation environments, an automated referee is needed. In this paper, we present AutoRef, as a contribution towards a complete automated referee for the RoboCup Small-Size League (SSL). We have developed and used AutoRef in an SSL simulation to run full games to evaluate different strategies, as we illustrate and show results. AutoRef is designed as a finite-state machine that transitions between the states of the game being either on or required to stop. AutoRef purposefully only uses the same visual and game information provided in SSL games with physical robots, which it uses to compute the features needed by the rules and to make decisions to transition between its states. Due to this real input to AutoRef, we have partially applied it to games of the physical robots. As AutoRef does not include all the rules of the real SSL games, we currently view it as an aid to human referees of SSL games, and discuss the challenges in automating several specific SSL game rules. AutoRef could be extended to other RoboCup real soccer leagues if a combined view of the game field, ball, and players is available.

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APA

Zhu, D., Biswas, J., & Veloso, M. (2015). AutoRef: Towards real-robot soccer complete automated refereeing. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 8992, pp. 419–430). Springer Verlag. https://doi.org/10.1007/978-3-319-18615-3_34

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