This paper reports a new hierarchical architecture for modeling autonomous multi-robot systems (MRSs): a nonlinear dynamical opinion process is used to model high-level group choice, and multi-objective behavior optimization is used to model individual decisions. Using previously reported theoretical results, we show it is possible to design the behavior of the MRS by the selection of a relatively small set of parameters. The resulting behavior - both collective actions and individual actions - can be understood intuitively. The approach is entirely decentralized and the communication cost scales by the number of group options, not agents. We demonstrated the effectiveness of this approach using a hypothetical `explore-exploit-migrate' scenario in a two hour field demonstration with eight unmanned surface vessels (USVs). The results from our preliminary field experiment show the collective behavior is robust even with time-varying network topology and agent dropouts.

翻译：本文提出了一种用于建模自主多机器人系统的新型分层架构：采用非线性动力学意见过程来建模高层群体选择，并利用多目标行为优化来建模个体决策。基于先前报道的理论结果，我们证明可以通过选择相对较小的参数集来设计多机器人系统的行为。由此产生的行为——包括集体行动与个体行动——均可被直观理解。该方法完全去中心化，且通信成本随群体选项数量而非智能体数量增长。我们通过八艘无人水面艇在两小时实地演示中，利用假设性“探索-利用-迁移”场景验证了该方法的有效性。初步实地实验结果表明，即使在时变网络拓扑和智能体退出的情况下，集体行为仍具有鲁棒性。