Vision Aided Navigation of a Quad-Rotor for Autonomous Wind-Farm Inspection

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Abstract

This work presents a vision based navigation system for an autonomous drone that is capable of recognizing and locating wind mills. WindMillNet, a Deep Neural Network created for this purpose was specially trained to recognize wind mills on camera images using transfer learning techniques. The drone powered by WindMillNet scans the horizon to find wind mills, and after perceiving a wind mill, navigates towards it, with the goal of performing its inspection. A hierarchical control system, implemented in the drone provides stability and control of its movements. Our framework was designed using a cyber-physical systems approach using high-level abstractions in modeling, communication, control and computation.
Original languageEnglish
Book seriesIFAC-PapersOnLine
Volume52
Issue number8
Pages (from-to)61-66
Number of pages6
ISSN1474-6670
DOIs
Publication statusPublished - Jul 2019
EventIFAC Symposium Intelligent Autonomous Vehicles - 10th IAV 2019 - Gdansk, Poland
Duration: 3 Jul 20195 Jul 2019
http://www.konsulting.gda.pl/iav2019/web/

Conference

ConferenceIFAC Symposium Intelligent Autonomous Vehicles - 10th IAV 2019
Country/TerritoryPoland
CityGdansk
Period03/07/201905/07/2019
Internet address

Keywords

  • UAV
  • Control
  • Artificial Intelligence
  • Vision
  • Neural Networks
  • Deep Learning
  • Machine Learning

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