Work

SO(2)-Equivariant Downwash Models for Close Proximity Flight

Year: 2023

Type: article

Abstract: 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,learninga 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$56\%$).

Source: IEEE Robotics and Automation Letters

DOI: 10.1109/lra.2023.3337701

Authors: Henry Smith, Ajay Shankar, Jennifer Gielis, Jan Blumenkamp, Amanda Prorok

Institution: University of Cambridge

Language: English

Topic: Aerospace and Aviation Technology

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: European Research Council

Award: G8727507575