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Authors: Ivan Nikolov and Claus Madsen

Affiliation: Aalborg University, Denmark

Keyword(s): Localization, Mapping, Scanning, LiDAR, IMU, UAV, SLAM, Wind Turbine Blades Inspection.

Related Ontology Subjects/Areas/Topics: Active and Robot Vision ; Applications ; Computer Vision, Visualization and Computer Graphics ; Motion, Tracking and Stereo Vision ; Optical Flow and Motion Analyses ; Pattern Recognition ; Robotics ; Software Engineering ; Tracking and Visual Navigation

Abstract: 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. (More)

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Paper citation in several formats:
Nikolov, I. and Madsen, C. (2017). LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 6: VISAPP; ISBN 978-989-758-227-1; ISSN 2184-4321, SciTePress, pages 418-425. DOI: 10.5220/0006124304180425

@conference{visapp17,
author={Ivan Nikolov. and Claus Madsen.},
title={LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 6: VISAPP},
year={2017},
pages={418-425},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006124304180425},
isbn={978-989-758-227-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 6: VISAPP
TI - LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection
SN - 978-989-758-227-1
IS - 2184-4321
AU - Nikolov, I.
AU - Madsen, C.
PY - 2017
SP - 418
EP - 425
DO - 10.5220/0006124304180425
PB - SciTePress