Real- Time LiDAR-based Power Lines Detection for Unmanned Aerial Vehicles

The growing dependence of modern-day societies on electricity increases the importance of effective monitoring and maintenance of power lines. Endowing UAVs with the appropriate sensors for inspecting power lines, the costs and risks associated with the traditional foot patrol and helicopter-based inspections can be reduced. However, this implies the development of algorithms to make the inspection process reliable and autonomous. Visual methods are usually applied to locate the power lines and their components, but poor light conditions or a background rich in edges may compromise their results. To overcome those limitations, we propose to address the problem of power line detection and modeling based on LiDAR. A novel approach to the power line detection was developed, the PL2DM - Power Line LiDAR-based Detection and Modeling. It is based in a scan-by-scan adaptive neighbor minimalist comparison for all the points in a point cloud. The power line final model is obtained by matching and grouping several line segments, using their collinearity properties. Horizontally, the power lines are modeled as a straight line, and vertically as a catenary curve. The algorithm was validated with a real dataset, showing promising results both in terms of outputs and processing time, adding real-time object-based perception capabilities for other layers of processing.

[1]  Christoph Stiller,et al.  Segmentation of 3D lidar data in non-flat urban environments using a local convexity criterion , 2009, 2009 IEEE Intelligent Vehicles Symposium.

[2]  Myung Jin Chung,et al.  Online urban object recognition in point clouds using consecutive point information for urban robotic missions , 2014, Robotics Auton. Syst..

[3]  Qi Zhang,et al.  Extraction of power-transmission lines from vehicle-borne lidar data , 2016 .

[4]  Paolo Gamba,et al.  MODEL INDEPENDENT OBJECT EXTRACTION FROM DIGITAL SURFACE MODELS , 2000 .

[5]  Bart Custers,et al.  Drone Technology: Types, Payloads, Applications, Frequency Spectrum Issues and Future Developments , 2016 .

[6]  Dirk Wollherr,et al.  A clustering method for efficient segmentation of 3D laser data , 2008, 2008 IEEE International Conference on Robotics and Automation.

[7]  Roberto Teti,et al.  A roadmap for automated power line inspection. Maintenance and repair. , 2013 .

[8]  F. Rottensteiner,et al.  Classification of trees and powerlines from medium resolution airborne laserscanner data in urban environments , 2005 .

[9]  Gregory R. Stockton,et al.  Advances in applications for aerial infrared thermography , 2006, SPIE Defense + Commercial Sensing.

[10]  Martin Buss,et al.  Realtime segmentation of range data using continuous nearest neighbors , 2009, 2009 IEEE International Conference on Robotics and Automation.

[11]  Myung Jin Chung,et al.  Fast point cloud segmentation for an intelligent vehicle using sweeping 2D laser scanners , 2012, 2012 9th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI).

[12]  André Dias,et al.  PLineD: Vision-based power lines detection for Unmanned Aerial Vehicles , 2017, 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC).

[13]  Robert A. McLaughlin,et al.  Extracting transmission lines from airborne LIDAR data , 2006, IEEE Geoscience and Remote Sensing Letters.

[14]  Aamir Saeed Malik,et al.  A novel method for vegetation encroachment monitoring of transmission lines using a single 2D camera , 2014, Pattern Analysis and Applications.

[15]  Gunho Sohn,et al.  Wind adaptive modeling of transmission lines using minimum description length , 2017 .

[16]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[17]  M. Himmelsbach,et al.  Real-time object classification in 3D point clouds using point feature histograms , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  David E. Smith,et al.  Space Lidar and Applications , 2001 .

[19]  Peter Axelsson,et al.  Processing of laser scanner data-algorithms and applications , 1999 .

[20]  Matthew J. McGill,et al.  Lidar Remote Sensing , 2013 .

[21]  Changming Sun,et al.  Measuring the distance of vegetation from powerlines using stereo vision , 2006 .

[22]  Sebastian Thrun,et al.  Probabilistic Terrain Analysis For High-Speed Desert Driving , 2006, Robotics: Science and Systems.

[23]  Shuang Song,et al.  Automatic Clearance Anomaly Detection for Transmission Line Corridors Utilizing UAV-Borne LIDAR Data , 2018, Remote. Sens..

[24]  Qingquan Li,et al.  An Improved Method for Power-Line Reconstruction from Point Cloud Data , 2016, Remote. Sens..

[25]  Michael Himmelsbach,et al.  Fast segmentation of 3D point clouds for ground vehicles , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[26]  Jing Liang,et al.  A New Power-Line Extraction Method Based on Airborne LiDAR Point Cloud Data , 2011, 2011 International Symposium on Image and Data Fusion.

[27]  Angelika Wronkowicz Automatic fusion of visible and infrared images taken from different perspectives for diagnostics of power lines , 2016 .

[28]  Akira Kojima,et al.  Segmentation of 3D Lidar Points Using Extruded Surface of Cross Section , 2015, 2015 International Conference on 3D Vision.

[29]  Hiroshi MASAHARU,et al.  THREE-DIMENSIONAL CITY MODELING FROM LASER SCANNER DATA BY EXTRACTING BUILDING POLYGONS USING REGION SEGMENTATION METHOD , 2010 .

[30]  S. Ashidate,et al.  Development of a Helicopter-Mounted Eye-Safe Laser Radar System for Distance Measurement between Power Transmission Lines and Nearby Trees , 2001, IEEE Power Engineering Review.

[31]  Roland Siegwart,et al.  A comparison of line extraction algorithms using 2D range data for indoor mobile robotics , 2007, Auton. Robots.

[32]  Prabir K. Pal,et al.  Segmentation of point cloud from a 3D LIDAR using range difference between neighbouring beams , 2015, AIR '15.

[33]  Aamir Saeed Malik,et al.  Vegetation encroachment monitoring for transmission lines right-of-ways: A survey , 2013 .

[34]  D. Jones Power line inspection - a UAV concept , 2005 .

[35]  Qing Xiang 3D Reconstruction of 138 KV Power-lines from Airborne LiDAR Data , 2014 .

[36]  C. Briese,et al.  Extraction and Modeling of Power Lines from ALS Point Clouds , 2004 .

[37]  Yu Wang,et al.  Extraction of Urban Power Lines from Vehicle-Borne LiDAR Data , 2014, Remote. Sens..

[38]  Y. Tseng,et al.  LIDAR DATA SEGMENTATION AND CLASSIFICATION BASED ON OCTREE STRUCTURE , 2004 .

[39]  André Dias,et al.  Collision avoidance for safe structure inspection with multirotor UAV , 2017, 2017 European Conference on Mobile Robots (ECMR).

[40]  D. Burschka,et al.  Motion segmentation and scene classification from 3D LIDAR data , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[41]  Naoya Takeishi,et al.  Recent Developments in Aerial Robotics: A Survey and Prototypes Overview , 2017, ArXiv.

[42]  Miao Wang,et al.  Automatic 3D feature extraction from structuralized LIDAR data , 2005 .

[43]  Yoonseok Jwa,et al.  AUTOMATIC 3D POWERLINE RECONSTRUCTION USING AIRBORNE LiDAR DATA , 2009 .

[44]  Roland Siegwart,et al.  Multimodal detection and tracking of pedestrians in urban environments with explicit ground plane extraction , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[45]  Edwin Olson,et al.  Graph-based segmentation for colored 3D laser point clouds , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[46]  Jun Zhou,et al.  An Automatic Technique for Power Line Pylon Detection from Point Cloud Data , 2017, 2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

[47]  Yuri Owechko,et al.  On Real-Time LIDAR Data Segmentation and Classification , 2013 .

[48]  Uwe Stilla,et al.  SEGMENTATION OF LASER ALTIMETER DATA FOR BUILDING RECONSTRUCTION: DIFFERENT PROCEDURES AND COMPARISON , 2000 .

[49]  S. Jasanoff Knowing Earth , 2020, Earth 2020.

[50]  Markus Ax,et al.  UAV Based Laser Measurement for Vegetation Control at High-Voltage Transmission Lines , 2012 .

[51]  J. Shan,et al.  Urban DEM generation from raw lidar data: A labeling algorithm and its performance , 2005 .

[52]  Juha Hyyppä,et al.  Remote sensing methods for power line corridor surveys , 2016 .

[53]  Nikolaos Papanikolopoulos,et al.  Fast segmentation of 3D point clouds: A paradigm on LiDAR data for autonomous vehicle applications , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[54]  Bertrand Douillard,et al.  On the segmentation of 3D LIDAR point clouds , 2011, 2011 IEEE International Conference on Robotics and Automation.