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

Ivan Nikolov, Claus Madsen

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.

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Paper Citation


in Harvard Style

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 - Volume 6: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 418-425. DOI: 10.5220/0006124304180425


in Bibtex Style

@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 - Volume 6: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={418-425},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006124304180425},
isbn={978-989-758-227-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)
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
AU - Nikolov I.
AU - Madsen C.
PY - 2017
SP - 418
EP - 425
DO - 10.5220/0006124304180425