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arXiv · 2509.16079

Real-Time Maneuver Planning for Fixed-Wing UAVs in Unsteady Flows Using a GPU-Accelerated Vortex Particle Model

Ashwin Gupta·Kevin Wolfe·Gino Perrotta·Joseph Moore
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Abstract

Unsteady aerodynamic effects can have a profound impact on aerial vehicle flight performance, especially during agile maneuvers and in complex aerodynamic environments. In this paper, we present a real-time planning and control approach capable of reasoning about unsteady aerodynamics. Our approach relies on a lightweight GPU-accelerated vortex particle model (VPM) and a sampling-based policy optimization strategy capable of leveraging the VPM for predictive reasoning. Through hardware experiments, we show that by replanning with our unsteady aerodynamics model, we can improve the performance of a post-stall fixed-wing perching maneuver in the presence of unsteady environmental flow disturbances.

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Ashwin Gupta, Kevin Wolfe, Gino Perrotta, Joseph Moore. 2026-09-16. Real-Time Maneuver Planning for Fixed-Wing UAVs in Unsteady Flows Using a GPU-Accelerated Vortex Particle Model. https://arxiv.org/abs/2509.16079

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