Detection of road surface damage using mobile robot equipped with 2D laser scanner

This paper introduces a road surface damage detection using mobile robot. Our research is aimed autonomous sidewalk investigation with mobile robot, for reduce the burden of human workers engaged in road maintenance. A mobile robot moves along the route for investigation and obtain shape information of road surface using 2D laser scanner. From this road surface information, road damage section will be automatically detected. By showing the detection result instead of site investigation by human workers, it expects to reduce the burden of human workers. Road surface have gradual curves and some road damage is small and less than 2 cm. Hence, our method uses random sampling to detect irregularity as road damage. This paper explains the measurement of road surface using mobile robot equipped with 2D laser scanner and the road damage detection method. In this paper, some experimental results also is shown.

[1]  Takashi Tsubouchi,et al.  Path-following algorithms and experiments for an unmanned surface vehicle , 2009 .

[2]  Piotr Jasiobedzki,et al.  Stereo-Vision Based 3D Modeling and Localization for Unmanned Vehicles , 2008 .

[3]  Wolfram Burgard,et al.  An Efficient Extension to Elevation Maps for Outdoor Terrain Mapping and Loop Closing , 2007, Int. J. Robotics Res..

[4]  Christoph Mertz.  Continuous Road Damage Detection Using Regular Service Vehicles , 2011 .

[5]  Pankaj Kumar,et al.  Initial Results From European Road Safety Inspection (eursi) Mobile Mapping Project , 2010 .

[6]  Sebastian Thrun,et al.  Stanley: The robot that won the DARPA Grand Challenge , 2006, J. Field Robotics.

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

[8]  D. Fox,et al.  Classification and Semantic Mapping of Urban Environments , 2011, Int. J. Robotics Res..

[9]  Takashi Tsubouchi,et al.  Autonomous robot navigation in outdoor cluttered pedestrian walkways , 2009, J. Field Robotics.

[10]  Hiromi Yoshida,et al.  A Binarization Method for Crack Detection in a Road Surface Image with the Fractal Dimension , 2009, MVA.

[11]  Philip H. S. Torr,et al.  Automatic dense visual semantic mapping from street-level imagery , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  Naoki Tanaka,et al.  A Crack Detection Method in Road Surface Images Using Morphology , 1998, MVA.