Wind Measurement and Simulation Techniques in Multi-Rotor Small Unmanned Aerial Vehicles

Pramod Abichandani, Deepan Lobo, Gabriel Ford, Donald Bucci, Moshe Kam

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Wind disturbance presents a formidable challenge to the flight performance of multi-rotor small unmanned aerial vehicles (sUAVs). This paper presents a comprehensive review of techniques for measuring wind speed and airspeed for multi-rotor sUAVs. Three categories of sensing techniques are reviewed: flow sensors, anemometers, and tilt-angle based approaches. We also review techniques for generating wind disturbances in simulation. Wind simulation techniques that use power spectral density (PSD) functions, computational fluid dynamics (CFD), and probabilistic models are examined. Finally, we provide an open-source Python implementation of the Dryden wind turbulence model and embedded code to interface with an ultrasonic anemometer.

Original languageEnglish (US)
Article number9020170
Pages (from-to)54910-54927
Number of pages18
JournalIEEE Access
Volume8
DOIs
StatePublished - 2020

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

Keywords

  • Unmanned aerial vehicles
  • measurement
  • simulation

Fingerprint

Dive into the research topics of 'Wind Measurement and Simulation Techniques in Multi-Rotor Small Unmanned Aerial Vehicles'. Together they form a unique fingerprint.

Cite this