Estimating wind using a quadrotor | Zendy

Gautier Hattenberger | Zendy; Murat Bronz | Zendy; Jean-Philippe Condomines | Zendy

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Estimating wind using a quadrotor

Author(s) -

Gautier Hattenberger,

Murat Bronz,

Jean-Philippe Condomines

Publication year - 2022

Publication title -

international journal of micro air vehicles

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.324

H-Index - 21

eISSN - 1756-8307

pISSN - 1756-8293

DOI - 10.1177/17568293211070824

Subject(s) - drone , trajectory , kalman filter , extended kalman filter , computer science , calibration , drag , wind speed , simulation , aerospace engineering , engineering , meteorology , artificial intelligence , geography , statistics , physics , genetics , mathematics , astronomy , biology

The aim of this work is to estimate the average wind influencing a quadrotor drone only based on standard navigation sensors and equations of motion. It can be used in several situation, including atmospheric studies, trajectory planning under environmental constraints, or as a reference for studying flights in shear layer. For this purpose, a small quadrotor drone with spherical shape has been developed. Flight data are recorded from telemetry during indoor and outdoor flight tests and are post-processed. The proposed solution is based on a calibration procedure with global optimization to extract the drag model and a Kalman Filter for online estimation of the wind speed and direction. Finally, an on-board implementation of the real-time estimation is demonstrated with real flights in controlled indoor environment.

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