A K Nearest Neighborhood-Based Wind Estimation for Rotary-Wing VTOL UAVs

A K Nearest Neighborhood-Based Wind Estimation for Rotary-Wing VTOL UAVs

Blog Article

Wind speed estimation for rotary-wing vertical take-off and landing (VTOL) UAVs is challenging due to the low accuracy of airspeed sensors, which can be severely affected by the rotor’s down-wash effect.Unlike Anti Theft System traditional aerodynamic modeling solutions, in this paper, we present a K Nearest Neighborhood learning-based method which does not require the details of the aerodynamic information.The proposed method includes two stages: an off-line training stage and an on-line wind estimation stage.

Only flight data is used for the on-line estimation stage, without direct airspeed measurements.We use Parrot AR.Drone as the testing quadrotor, and a commercial fan is used to generate wind disturbance.

Experimental Tapes results demonstrate the accuracy and robustness of the developed wind estimation algorithms under hovering conditions.