Autonomous Wind-Turbine Blade Inspection Using LiDAR-Equipped Unmanned Aerial Vehicle

This paper presents a LiDAR-equipped unmanned aerial vehicle (UAV) performing semi-autonomous wind-turbine blade inspection which includes traversing to the blade tip and back, while keeping constant relative distance and heading to the blade plane. Plane detection is performed applying the RANSAC method on a subset of the gathered pointcloud. Utilizing the relative distance to the inferred plane as well as its normal vector, the UAV is able to maintain a constant distance and heading towards the plane while moving in parallel with it. The proposed procedure performs successful wind-turbine blade inspections with minimal operator involvement. Inspection results include high-resolution blade images as well as a 3D model of the wind-turbine structure. Finally, to show the feasibility of this approach, simulations are performed on a wind-turbine model and experimental results are presented for an outdoor single-blade inspection scenario both on a mock-up setup and a full-scale wind-turbine blade. It is worth noting that the system’s adequacy has been fully validated in real conditions on an operational wind farm.

[1]  Stjepan Bogdan,et al.  State estimation, robust control and obstacle avoidance for multicopter in cluttered environments: EuRoC experience and results , 2015, 2015 International Conference on Unmanned Aircraft Systems (ICUAS).

[2]  Guido Morgenthal,et al.  Quality Assessment of Unmanned Aerial Vehicle (UAV) Based Visual Inspection of Structures , 2014 .

[3]  Lucian Busoniu,et al.  Vision and Control for UAVs: A Survey of General Methods and of Inexpensive Platforms for Infrastructure Inspection , 2015, Sensors.

[4]  K. Narendra,et al.  A common Lyapunov function for stable LTI systems with commuting A-matrices , 1994, IEEE Trans. Autom. Control..

[5]  Cyrille Berger,et al.  Toward rich geometric map for SLAM: online detection of planets in 2D LIDAR , 2012 .

[6]  Karol Miadlicki,et al.  Ground plane estimation from sparse LIDAR data for loader crane sensor fusion system , 2017, 2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR).

[7]  Emil Fresk,et al.  Autonomous visual inspection of large-scale infrastructures using aerial robots , 2019, ArXiv.

[8]  Tor A. Johansen,et al.  Autonomous visual navigation of Unmanned Aerial Vehicle for wind turbine inspection , 2015, 2015 International Conference on Unmanned Aircraft Systems (ICUAS).

[9]  Jingxuan Sun,et al.  A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes , 2016, Sensors.

[10]  Hao Jiang,et al.  Feasible Computationally Efficient Path Planning for UAV Collision Avoidance , 2018, 2018 IEEE 14th International Conference on Control and Automation (ICCA).

[11]  Stjepan Bogdan,et al.  Geometric Tracking Control of Aerial Robots Based on Centroid Vectoring , 2019, 2019 18th European Control Conference (ECC).

[12]  Rami A. Mattar,et al.  Development of a Wall-Sticking Drone for Non-Destructive Ultrasonic and Corrosion Testing , 2018 .

[13]  Hyun Myung,et al.  Graph-based SLAM approach for environments with laser scan ambiguity , 2015, 2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI).

[14]  Lucía Díaz-Vilariño,et al.  Lidar-equipped uav for building information modelling , 2014 .

[15]  Andrew Calway,et al.  Simultaneous Drone Localisation and Wind Turbine Model Fitting During Autonomous Surface Inspection , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[16]  Vijay Kumar,et al.  Minimum snap trajectory generation and control for quadrotors , 2011, 2011 IEEE International Conference on Robotics and Automation.

[17]  C. Glennie,et al.  CALIBRATION AND STABILITY ANALYSIS OF THE VLP-16 LASER SCANNER , 2016 .

[18]  Guanrong Chen,et al.  Kalman Filtering with Real-time Applications , 1987 .

[19]  Manish Kumar,et al.  Autonomous Wall-Following Based Navigation of Unmanned Aerial Vehicles in Indoor Environments , 2015 .

[20]  Konstantin Kondak,et al.  The AEROARMS Project: Aerial Robots with Advanced Manipulation Capabilities for Inspection and Maintenance , 2018, IEEE Robotics & Automation Magazine.

[21]  Ajai Kumar Singh,et al.  ROAD SURFACE DETECTION FROM MOBILE LIDAR DATA , 2018 .