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Robotic Shotcrete Thickness Estimation Using Fiducial Registration

[+] Author Affiliations
Michael R. Wrock, Scott B. Nokleby

University of Ontario: Institute of Technology, Oshawa, ON, Canada

Paper No. DETC2018-85688, pp. V05AT07A074; 10 pages
doi:10.1115/DETC2018-85688
From:
  • ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5A: 42nd Mechanisms and Robotics Conference
  • Quebec City, Quebec, Canada, August 26–29, 2018
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5180-7
  • Copyright © 2018 by ASME

abstract

This paper presents the results of shotcrete thickness estimation for mining applications using a mobile robot. The method uses a fiducial marker based registration method to align initial and posterior LIDAR scans. The shotcrete thickness was calculated using point to point estimation. The registration and thickness estimation were tested in a mock mine using a LIDAR scanner on a mobile robot. It was found that the registration based thickness estimates had repeatability within a millimeter when compared to thickness estimates generated without the need for registration.

Copyright © 2018 by ASME
Topics: Gunite , Robotics

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