The application of multi-agent systems in robotics is a very challenging field. Several competitions involving such systems are proposed to foster research and development of strategies and mechanisms using games as the underlying domain. Among them are the ones from the \textit{IEEE Very Small Soccer (VSSS)} category, which is the case study described in this paper. In VSSS, two teams of three robots each compete in a very dynamic environment of a soccer game. Thus, coordination of robots' behavior during the game is crucial to win it. In this paper, we present a Behavior-Tree-based approach to support multi-robot coordination within the VSSS team of the ThundeRatz robotics team from the Universidade de S$\tilde{a}$o Paulo. Moreover, a comparison between the proposed approach and the previous one, which was based on a Finite State Machine (FSM), was conducted using the FIRASim simulator. Besides that, the performance of this new strategy was further evaluated in an academic robotics competition.

翻译：多智能体系统在机器人领域的应用极具挑战性。为促进相关策略与机制的研究与开发，学界提出了多个涉及此类系统的竞赛，并以游戏作为底层领域。其中包含来自《IEEE超小型足球（VSSS）》类别的竞赛，这也是本文所述的研究案例。在VSSS中，两支各由三台机器人组成的队伍在高度动态的足球比赛环境中展开竞技。因此，比赛中机器人行为的协调对取胜至关重要。本文提出了一种基于行为树的方法，用于支持圣保罗大学ThundeRatz机器人团队的VSSS队伍实现多机器人协调。此外，我们使用FIRASim模拟器将所提方法与先前基于有限状态机（FSM）的方法进行了对比。除此以外，该新策略的性能还在一次学术机器人竞赛中得到了进一步评估。