Article

Neural-Fly: Online Adaptive Control for Quadrotors in Strong Winds

Neural-Fly proposes a residual aerodynamic force adaptation law that combines wind-invariant representations with online least squares for online adaptive control of quadrotors in strong winds. The method trains a network on public flight data and conducts comparative figure-8 trajectory tracking experiments with a PyBullet quadrotor in a steady wind field, demonstrating rapid adaptation enabled by domain-shift separation.

Part of the event: Neural-Fly proposes online adaptive control method for quadrotors in strong winds

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