Two Supervised Machine Learning Approaches for Wind Velocity Estimation Using Multi-Rotor Copter Attitude Measurements

Two Supervised Machine Learning Approaches for Wind Velocity Estimation Using Multi-Rotor Copter Attitude Measurements

In this work we address the adequacy of two machine learning methods to tackle the problem of wind velocity estimation in the lowermost region of the atmosphere using on-board inertial drone data within an outdoor setting. We fed these data, and accompanying wind tower measurements, into a K-nearest...

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Bibliographic Details
Main Authors: David Crowe, Raghava Pamula, Hing Yuet Cheung, Stephan F. J. De Wekker
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Sensors
Subjects:
wind estimation
machine learning
drone attitude
quadcopter
long short-term memory (LSTM)
k-nearest neighbors (KNN)
Online Access:https://www.mdpi.com/1424-8220/20/19/5638

Internet

https://www.mdpi.com/1424-8220/20/19/5638

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