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Modeling Aggregate Downwash Forces for Dense Multirotor Flight

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Experimental Robotics (ISER 2023)

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 30))

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Abstract

Dense formation flight with multirotor swarms is a powerful, nature-inspired flight regime with numerous applications in the real-world. 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.

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Notes

  1. 1.

    We liken this to the “observer effect”.

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Acknowledgment

This work was supported in part by ARL DCIST CRA W911NF-17-2-0181, the European Research Council (ERC) Project 949940 (gAIa), and by a gift from Arm. J. Gielis was supported by an EPSRC Doctoral Training studentship. Their support is gratefully acknowledged.

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Correspondence to Jennifer Gielis .

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Gielis, J., Shankar, A., Kortvelesy, R., Prorok, A. (2024). Modeling Aggregate Downwash Forces for Dense Multirotor Flight. In: Ang Jr, M.H., Khatib, O. (eds) Experimental Robotics. ISER 2023. Springer Proceedings in Advanced Robotics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-031-63596-0_35

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