Dense formation flight with multirotor swarms is a powerful, nature-inspired flight regime with numerous applications in the realworld. However, when multirotors fly in close vertical proximity to each other, the propeller downwash from the vehicles can have a destabilising effect on each other. Unfortunately, even in a homogeneous team, an accurate model of downwash forces from one vehicle is unlikely to be sufficient for predicting aggregate forces from multiple vehicles in formation. In this work, we model the interaction patterns produced by one or more vehicles flying in close proximity to an ego-vehicle. We first present an experimental test rig designed to capture 6-DOF exogenic forces acting on a multirotor frame. We then study and characterize these measured forces as a function of the relative states of two multirotors flying various patterns in its vicinity. Our analysis captures strong non-linearities present in the aggregation of these interactions. Then, by modeling the formation as a graph, we present a novel approach for learning the force aggregation function, and contrast it against simpler linear models. Finally, we explore how our proposed models generalize when a fourth vehicle is added to the formation.

翻译：密集编队飞行是多旋翼无人机群的一种受自然启发的强大飞行模式，在现实世界中具有多种应用。然而，当多旋翼飞行器在垂直方向上彼此近距离飞行时，飞行器产生的螺旋桨下洗流会相互产生失稳效应。不幸的是，即使在同质编队中，单架飞行器的下洗力精确模型也不足以预测编队中多架飞行器产生的总作用力。本研究针对一架或多架飞行器在邻近自主飞行器近距离飞行时产生的相互作用模式进行建模。我们首先设计了一个实验测试台架，用于捕捉作用于多旋翼机架上的六自由度外部作用力。随后，我们研究并刻画了这些测量作用力与周围不同飞行模式的两架多旋翼相对状态之间的函数关系。我们的分析捕捉到了这些相互作用叠加中存在的强非线性。通过将编队建模为图结构，我们提出了一种新颖的学习力聚合函数方法，并将其与更简单的线性模型进行了对比。最后，我们探讨了当编队中增加第四架飞行器时，所提出模型的泛化能力。