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：本文报告了一种用于建模自主多机器人系统（MRS）的新型层次化架构：采用非线性动力学舆论过程来模拟高层群体选择，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成果，我们证明通过选择相对较少的参数即可设计多机器人系统的行为。由此产生的行为——无论是集体行动还是个体行动——均可直观理解。该方法是完全去中心化的，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-开采-迁移”场景，在八艘无人水面艇（USV）持续两小时的野外演示中验证了该方法的有效性。初步野外实验结果表明，即使面对时变网络拓扑和智能体掉线情况，集体行为仍具有鲁棒性。