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Field and Service Robotics pp 479–493Cite as

Efficient Large-Scale 3D Mobile Mapping and Surface Reconstruction of an Underground Mine

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Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 92))

Abstract

Mapping large-scale underground environments, such as mines, tunnels, and caves is typically a time consuming and challenging endeavor. In April 2011, researchers at CSIRO were contracted to map the Northparkes Mine in New South Wales, Australia. The mine operators required a locally accurate 3D surface model in order to determine whether and how some pieces of large equipment could be moved through the decline. Existing techniques utilizing 3D terrestrial scanners mounted on tripods rely on accurate surveyed sensor positions and are relatively expensive, time consuming, and inefficient. Mobile mapping solutions have the potential to map a space more efficiently and completely; however, existing commercial systems are reliant on a GPS signal and navigation- or tactical-grade inertial systems. A 3D SLAM solution developed at CSIRO, consisting of a spinning 2D lidar and industrial-grade MEMS IMU was customized for this particular application. The system was designed to be mounted on a site vehicle which continuously acquires data at typical mine driving speeds without disrupting any mine operations. The deployed system mapped over 17 km of mine tunnel in under two hours, resulting in a dense and accurate georeferenced 3D surface model that was promptly delivered to the mine operators.

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Notes

  1. 1.

    “Robot Scans Silver Mine”, Photonics.com, 6 May 2008, accessed 1 June 2012. http://www.photonics.com/Article.aspx?AID=33755

  2. 2.

    While we were not running our SLAM solution while acquiring data in the mine, we can process the data at a rate that is considerably faster than real-time.

  3. 3.

    We have developed more complex volume-based methods for surface reconstruction from spinning lidar data [8]; however, for this application we decided a simpler point-based solution would be more accurate.

  4. 4.

    At the time we were in the process of switching our middleware from DDX [3] to ROS [13], and had not yet extensively field tested all of the drivers. We have since moved to using a version of the LMS driver from DDX (modified with ROS wrappers), which is considerably less CPU intensive and contains the necessary scan metadata required for robust timing.

References

  1. M. Bosse, R. Zlot. Continuous 3D scan-matching with a spinning 2D laser, in IEEE International Conference on Robotics and Automation, (2009)

    Google Scholar 

  2. M. Bosse, R. Zlot. Place recognition using regional point descriptors for 3D mapping, in International Conference on Field and Service Robotics, (2009)

    Google Scholar 

  3. P. Corke, P. Sikka, J. Roberts, E. Duff. DDX: a distributed software architecture for robotic systems, in Australasian Conference on Robotics and Automation, (2004)

    Google Scholar 

  4. J.C. Derenick, T.H. Miller, J.R. Spletzer, A. Kushleyev, T. Foote, A. Stewart, J. Bohren. The Sick LIDAR Matlab/C++ Toolbox: Software for rapidly interfacing/configuring Sick LIDARs. Technical Report LU-CSE-08-008, Lehigh University Department of Computer Science and Engineering, 2008

    Google Scholar 

  5. E. Duff, J. Roberts, P. Corke. Automation of an underground mining vehicle using reactive navigation and opportunistic localization, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, (2003)

    Google Scholar 

  6. N. Fairfield, D. Wettergreen. Evidence grid-based methods for 3D map matching, in IEEE International Conference on Robotics and Automation, (2009)

    Google Scholar 

  7. S. Fekete, M. Diederichs, M. Lato, Geotechnical and operational applications for 3-dimensional laser scanning in drill and blast tunnels. Tunn. Undergr. Space Technol. 25, 614–628 (2010)

    Article  Google Scholar 

  8. C. Holenstein, R. Zlot, M. Bosse. Watertight surface reconstruction of caves from 3D lidar data, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, (2011)

    Google Scholar 

  9. F. Lemy, S. Yong, T. Schulz. A case study of monitoring tunnel wall displacement using laser scanning technology, in International Association for Engineering Geology, (2006)

    Google Scholar 

  10. M. Magnusson, H. Andreasson, A. Nüchter, A.J. Lilienthal. Appearance-based loop detection from 3D laser data using the normal distributions transform, in IEEE International Conference on Robotics and Automation, (2009)

    Google Scholar 

  11. A. Nüchter, H. Surmann, K. Lingemann, J. Hertzberg, S. Thrun. 6D SLAM with an application in autonomous mine mapping, in textitIEEE International Conference on Robotics and Automation, (2004)

    Google Scholar 

  12. G. Petrie, Mobile mapping systems. An introduction to the technology. GeoInformatics 13(1), 32–43 (2010)

    MathSciNet  Google Scholar 

  13. M. Quigley, B. Gerkey, K. Conley, J. Faust, T. Foote, J. Leibs, E. Berger, R. Wheeler, A. Ng. ROS: an open-source robot operating system, in Proceedings of the Open-Source Software Workshop at the IEEE International Conference on Robotics and Automation, (2009)

    Google Scholar 

  14. H. Rüther, M. Chazan, R. Schroeder, R. Neeser, C. Held, S. Walker, A. Matmon, L. Howritz, Laser scanning for conservataion and research of African cultural heritage sites: the case study of Wonderwerk Cave. South Afrika. J. Archaeol. Sci. 36, 1847–1856 (2009)

    Article  Google Scholar 

  15. D. Silver, D. Ferguson, A. Morris, S. Thayer. Topological exploration of subterranean environments. J. Field Robot. 23(6/7), 395–415 (2006)

    Google Scholar 

  16. R. van Gosliga, R. Lindenbergh, N. Pfeifer, Deformation analysis of a bored tunnel by means of terrestrial laser scanning. Image Eng. Vision Metrol. 36, 167–172 (2006)

    Google Scholar 

  17. U. Wong, A. Morris, C. Lea, J. Lee, C. Whittaker, B. Garney, W. Whittaker. Comparative evaluation of range sensing technologies for underground void modeling, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, (2011)

    Google Scholar 

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Acknowledgments

The authors would like to acknowledge Northparkes Mine and the CSIRO Minerals Down Under Flagship for their support and assistance. We also thank Paul Flick for hardware support and So Jung Yun for generating the surface model imagery and animations.

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Authors and Affiliations

  1. CSIRO ICT Centre, Autonomous Systems Laboratory, Brisbane, Australia

    Robert Zlot & Michael Bosse

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  1. Robert Zlot
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  2. Michael Bosse
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Correspondence to Robert Zlot .

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Editors and Affiliations

  1. Department of Aerospace Engineering, Tohoku University, Sendai, Japan

    Kazuya Yoshida

  2. Tohoku University Graduate School of Information Sciences, Sendai, Japan

    Satoshi Tadokoro

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Zlot, R., Bosse, M. (2014). Efficient Large-Scale 3D Mobile Mapping and Surface Reconstruction of an Underground Mine. In: Yoshida, K., Tadokoro, S. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 92. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40686-7_32

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  • DOI: https://doi.org/10.1007/978-3-642-40686-7_32

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40685-0

  • Online ISBN: 978-3-642-40686-7

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