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

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

1 Citationer (Scopus)
137 Downloads (Pure)

Abstrakt

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.
OriginalsprogEngelsk
BogserieIFAC-PapersOnLine
Vol/bind52
Udgave nummer8
Sider (fra-til)61-66
Antal sider6
ISSN1474-6670
DOI
StatusUdgivet - jul. 2019
BegivenhedIFAC Symposium Intelligent Autonomous Vehicles - 10th IAV 2019 - Gdansk, Polen
Varighed: 3 jul. 20195 jul. 2019
http://www.konsulting.gda.pl/iav2019/web/

Konference

KonferenceIFAC Symposium Intelligent Autonomous Vehicles - 10th IAV 2019
LandPolen
ByGdansk
Periode03/07/201905/07/2019
Internetadresse

Fingeraftryk Dyk ned i forskningsemnerne om 'Vision Aided Navigation of a Quad-Rotor for Autonomous Wind-Farm Inspection'. Sammen danner de et unikt fingeraftryk.

Citationsformater