Project description
Acoustic wind sensors for multirotor estimation technology
In the past decade, drones have been used for challenging tasks such as inspection and maintenance. However, their susceptibility to unpredictable wind forces hinders their widespread adoption. With the support of Marie Skłodowska-Curie Actions programme, the MEW project seeks to integrate acoustic wind sensors into a sophisticated and mathematically robust estimation framework. The project’s goal is to develop novel algorithms for accurately estimating wind forces. Real-world testing will facilitate the creation of software implementations poised for adoption by industry. The project’s outcomes will pave the way for new applications of multirotor technology and innovative approaches to wind dynamics estimation.
Objective
In the last decade both remotely-piloted and autonomous multirotor aerial systems have been employed for a wide range of challenging tasks, including visual inspection and physical maintenance, that were previously either dangerous or impractical. Wide-spread adoption is, however, hindered by the sensitivity of existing systems to unpredictable disturbances caused by wind forces that they are not able to estimate and hence mitigate. With funding provided by Marie Skodowska-Curie Actions programme, the MEW project seeks to use recently developed acoustic wind sensors in a sophisticated and mathematically sound estimation framework. Researchers will design entirely new algorithms for the estimation of wind forces so that they may be compensated for by the multirotor flight control system. Real-world tests and experiments will demonstrate the soundness of the research and lead to software implementations that are ready to be adopted by industry. The results of the MEW project will lead to a new wave of application domains for multirotor technology, and will create new approaches to estimating wind dynamics that may extend to other engineering and scientific questions around fluid dynamics.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencessoftware
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
7522 NB Enschede
Netherlands