近接飛行のためのSO(2)同変ダウンウォッシュモデル
SO(2)-Equivariant Downwash Models for Close Proximity Flight
複数ドローンの近接飛行時に生じるプロペラ後流（ダウンウォッシュ）の力を、問題に内在する対称性を活用した学習モデルで予測し、少ない実飛行データで高精度な3D軌道追従を実現した。
著者: H. Smith, A. Shankar, J. Gielis, J. Blumenkamp, A. Prorok
分類: cs.RO, cs.AI, cs.LG
原文アブストラクト
Multirotors flying in close proximity induce aerodynamic wake effects on each other through propeller downwash. Conventional methods have fallen short of providing adequate 3D force-based models that can be incorporated into robust control paradigms for deploying dense formations. Thus, learning a model for these downwash patterns presents an attractive solution. In this paper, we present a novel learning-based approach for modelling the downwash forces that exploits the latent geometries (i.e. symmetries) present in the problem. We demonstrate that when trained with only 5 minutes of real-world flight data, our geometry-aware model outperforms state-of-the-art baseline models trained with more than 15 minutes of data. In dense real-world flights with two vehicles, deploying our model online improves 3D trajectory tracking by nearly 36% on average (and vertical tracking by 56%).