Efficient UAV Autonomous Navigation with CNNs

Kamil Mikolaj, Martin Lauersen, Tomer Tchelet, Daniel Ortiz Arroyo, Petar Durdevic

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Abstract

This paper presents a novel approach to the navi-
gation of Unmanned Aerial Vehicles (UAV) for the autonomous
inspection of wind turbines. Firstly, a Single Shot Detector
(SSD) network is trained to detect wind turbines and their
subcomponents. Then, an optimized template matching algorithm
is used to estimate the distance between the UAV and the wind
turbine, using as the template, the SSD bounding box prediction
on the left image of a stereo camera. Lastly, an Extended Kalman
Filter (EKF) estimates the position of the wind turbine’s hub. The
EKF is designed to compensate for CNN’s latency while sending
setpoints to the controller of the UAV
OriginalsprogEngelsk
Titel9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023
Antal sider6
ForlagIEEE
Publikationsdatookt. 2023
Sider1343 - 1348
Artikelnummer10284278
ISBN (Trykt)979-8-3503-1141-9
ISBN (Elektronisk)979-8-3503-1140-2
DOI
StatusUdgivet - okt. 2023
Begivenhed9th International Conference on Control, Decision and Information Technologies (CoDIT) - Rome, Italien
Varighed: 3 jul. 20236 jul. 2023
https://codit2023.com/

Konference

Konference9th International Conference on Control, Decision and Information Technologies (CoDIT)
Land/OmrådeItalien
ByRome
Periode03/07/202306/07/2023
Internetadresse
NavnInternational Conference on Control, Decision and Information Technologies (CoDIT)
ISSN2576-3555

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