Robotic platform for deep change detection for rail safety and security

Felix is the first robot measuring switch dimension parameters and geometrical railway ones together with potentially dangerous situations. It increases the quality and the consistency of the measures and offers the chance to increase the safety of operators and ultimately of final users. This paper presents a novel approach mixing visual and point cloud information for effective change detection for railways safety and security application. Main contributions are on the proposed data platform and on the mix of point-based measurements (switch dimensions) and on surrounding change detection (dangerous trees or abnormal railway trawlers) based multi-view camera and linear laser, processed by a classification process. Results, coming from a real rail scenario using the Felix platform, show the feasibility of the approach and the fast surveying capabilities with strong implications on safety and security.

[1]  Emanuele Frontoni,et al.  A vision based algorithm for active robot localization , 2005, 2005 International Symposium on Computational Intelligence in Robotics and Automation.

[2]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[3]  Roderik Lindenbergh,et al.  Change detection and deformation analysis using static and mobile laser scanning , 2015 .

[4]  Halim Setan,et al.  DEFORMATION ANALYSIS OF A GEODETIC MONITORING NETWORK , 2001 .

[5]  Benjamin T. Crosby,et al.  Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska , 2013, Remote. Sens..

[6]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[7]  Giorgio C. Buttazzo,et al.  A framework based on real-time OS and multi-agents for intelligent autonomous robot competitions , 2016, 2016 11th IEEE Symposium on Industrial Embedded Systems (SIES).

[8]  Jens C. O. Nielsen,et al.  Simulation of wheel-rail contact and damage in switches & crossings , 2009 .

[9]  P. Zingaretti,et al.  Vision and sonar sensor fusion for mobile robot localization in aliased environments , 2006, 2006 2nd IEEE/ASME International Conference on Mechatronics and Embedded Systems and Applications.

[10]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[11]  Claus Scheiblauer,et al.  Potree : Rendering Large Point Clouds in Web , 2016 .

[12]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[13]  Bo Ai,et al.  The issues of cloud computing security in high-speed railway , 2011, Proceedings of 2011 International Conference on Electronic & Mechanical Engineering and Information Technology.

[14]  Joe-Air Jiang,et al.  Applications of the Integrated High-Performance CMOS Image Sensor to Range Finders — from Optical Triangulation to the Automotive Field , 2008, Sensors.

[15]  M. Singh,et al.  Autonomous Rail Track Inspection using Vision Based System , 2006, 2006 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety.

[16]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[17]  W. Al-Nuaimy,et al.  Train-mounted GPR for high-speed rail trackbed inspection , 2004, Proceedings of the Tenth International Conference on Grounds Penetrating Radar, 2004. GPR 2004..

[18]  Gergana Antova.  Terrestrial Laser Scanning for Dam Deformation Monitoring - Case Study , 2015 .

[19]  D. Girardeau-Montaut,et al.  CHANGE DETECTION ON POINTS CLOUD DATA ACQUIRED W ITH A GROUND LASER SCANNER , 2005 .

[20]  C. Hancock,et al.  A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures , 2016 .

[21]  Emanuele Frontoni,et al.  Visual and Textual Sentiment Analysis of Brand-Related Social Media Pictures Using Deep Convolutional Neural Networks , 2017, ICIAP.

[22]  Anthony Stefanidis,et al.  DIFFERENTIAL SNAKES FOR CHANGE DETECTION IN ROAD SEGMENTS , 2001 .

[23]  M. Crosetto,et al.  Deformation measurement using terrestrial laser scanning data and least squares 3D surface matching , 2008 .

[24]  Jun Zhu,et al.  Impacts of the Wenchuan Earthquake on the Chaping River upstream channel change , 2012 .

[25]  D. Lu,et al.  Change detection techniques , 2004 .

[26]  Xiaohua Tong,et al.  Detection of geometric change in railway curves caused by earthquakes, using high-resolution stereo satellite images , 2015, Natural Hazards.

[27]  Vassilios Kappatos,et al.  The application of long range ultrasonic testing (LRUT) for examination of hard to access areas on railway tracks , 2011 .

[28]  Emanuele Frontoni,et al.  Road Change Detection from Multi-Spectral Aerial Data , 2010, 2010 20th International Conference on Pattern Recognition.