LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection

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Resumé

The wind energy sector faces a constant need for annual inspections of wind turbine blades for damage, erosion
and cracks. These inspections are an important part of the wind turbine life cycle and can be very costly and
hazardous to specialists. This has led to the use of automated drone inspections and the need for accurate,
robust and inexpensive systems for localization of drones relative to the wing. Due to the lack of visual
and geometrical features on the wind turbine blade, conventional SLAM algorithms have a limited use. We
propose a cost-effective, easy to implement and extend system for on-site outdoor localization and mapping in
low feature environment using the inexpensive RPLIDAR and an 9-DOF IMU. Our algorithm geometrically
simplifies the wind turbine blade 2D cross-section to an elliptical model and uses it for distance and shape
correction. We show that the proposed algorithm gives localization error between 1 and 20 cm depending on
the position of the LiDAR compared to the blade and a maximum mapping error of 4 cm at distances between
1.5 and 3 meters from the blade. These results are satisfactory for positioning and capturing the overall shape
of the blade.
OriginalsprogEngelsk
TitelProceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
ForlagSCITEPRESS Digital Library
Publikationsdato2017
ISBN (Trykt)978-989-758-227-1
DOI
StatusUdgivet - 2017
Begivenhed12th International Conference on Computer Vision Theory and Applications - Porto, Portugal
Varighed: 27 feb. 20171 mar. 2017
http://www.visapp.visigrapp.org/

Konference

Konference12th International Conference on Computer Vision Theory and Applications
LandPortugal
ByPorto
Periode27/02/201701/03/2017
Internetadresse

Fingerprint

Unmanned aerial vehicles (UAV)
Wind turbines
Turbomachine blades
Inspection
Wind power
Life cycle
Cracks
Costs
Drones

Citer dette

Nikolov, I. A., & Madsen, C. B. (2017). LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection. I Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications SCITEPRESS Digital Library. https://doi.org/10.5220/0006124304180425
Nikolov, Ivan Adriyanov ; Madsen, Claus B. / LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection. Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SCITEPRESS Digital Library, 2017.
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title = "LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection",
abstract = "The wind energy sector faces a constant need for annual inspections of wind turbine blades for damage, erosionand cracks. These inspections are an important part of the wind turbine life cycle and can be very costly andhazardous to specialists. This has led to the use of automated drone inspections and the need for accurate,robust and inexpensive systems for localization of drones relative to the wing. Due to the lack of visualand geometrical features on the wind turbine blade, conventional SLAM algorithms have a limited use. Wepropose a cost-effective, easy to implement and extend system for on-site outdoor localization and mapping inlow feature environment using the inexpensive RPLIDAR and an 9-DOF IMU. Our algorithm geometricallysimplifies the wind turbine blade 2D cross-section to an elliptical model and uses it for distance and shapecorrection. We show that the proposed algorithm gives localization error between 1 and 20 cm depending onthe position of the LiDAR compared to the blade and a maximum mapping error of 4 cm at distances between1.5 and 3 meters from the blade. These results are satisfactory for positioning and capturing the overall shapeof the blade.",
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Nikolov, IA & Madsen, CB 2017, LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection. i Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SCITEPRESS Digital Library, 12th International Conference on Computer Vision Theory and Applications, Porto, Portugal, 27/02/2017. https://doi.org/10.5220/0006124304180425

LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection. / Nikolov, Ivan Adriyanov; Madsen, Claus B.

Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SCITEPRESS Digital Library, 2017.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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N2 - The wind energy sector faces a constant need for annual inspections of wind turbine blades for damage, erosionand cracks. These inspections are an important part of the wind turbine life cycle and can be very costly andhazardous to specialists. This has led to the use of automated drone inspections and the need for accurate,robust and inexpensive systems for localization of drones relative to the wing. Due to the lack of visualand geometrical features on the wind turbine blade, conventional SLAM algorithms have a limited use. Wepropose a cost-effective, easy to implement and extend system for on-site outdoor localization and mapping inlow feature environment using the inexpensive RPLIDAR and an 9-DOF IMU. Our algorithm geometricallysimplifies the wind turbine blade 2D cross-section to an elliptical model and uses it for distance and shapecorrection. We show that the proposed algorithm gives localization error between 1 and 20 cm depending onthe position of the LiDAR compared to the blade and a maximum mapping error of 4 cm at distances between1.5 and 3 meters from the blade. These results are satisfactory for positioning and capturing the overall shapeof the blade.

AB - The wind energy sector faces a constant need for annual inspections of wind turbine blades for damage, erosionand cracks. These inspections are an important part of the wind turbine life cycle and can be very costly andhazardous to specialists. This has led to the use of automated drone inspections and the need for accurate,robust and inexpensive systems for localization of drones relative to the wing. Due to the lack of visualand geometrical features on the wind turbine blade, conventional SLAM algorithms have a limited use. Wepropose a cost-effective, easy to implement and extend system for on-site outdoor localization and mapping inlow feature environment using the inexpensive RPLIDAR and an 9-DOF IMU. Our algorithm geometricallysimplifies the wind turbine blade 2D cross-section to an elliptical model and uses it for distance and shapecorrection. We show that the proposed algorithm gives localization error between 1 and 20 cm depending onthe position of the LiDAR compared to the blade and a maximum mapping error of 4 cm at distances between1.5 and 3 meters from the blade. These results are satisfactory for positioning and capturing the overall shapeof the blade.

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KW - Mapping

KW - Scanning

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Nikolov IA, Madsen CB. LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection. I Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SCITEPRESS Digital Library. 2017 https://doi.org/10.5220/0006124304180425