This paper reports a new hierarchical architecture for modeling autonomous multi-robot systems (MRSs): a non-linear 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：本文提出一种用于建模自主多机器人系统（MRS）的新型分层架构：采用非线性动力学观点过程建模高层群体选择，并利用多目标行为优化建模个体决策。基于先前报道的理论成果，我们证明可通过选择较少的参数集来设计MRS的行为模式。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，通信成本随群体选项数量而非智能体数量扩展。我们通过一个假设的“探索-利用-迁移”场景，在八艘无人水面艇（USV）的现场两小时演示中验证了该方法的有效性。初步现场实验结果表明，即使在时变网络拓扑与智能体掉线的情况下，集体行为仍具有鲁棒性。