Authors: Jones, EW

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DOI https://doi.org/10.36487/ACG_repo/2035_0.01

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Jones, EW 2020, 'Mobile LiDAR for underground geomechanics: learnings from the teens and directions for the twenties', in J Wesseloo (ed.), Proceedings of the Second International Conference on Underground Mining Technology, Australian Centre for Geomechanics, Perth, pp. 3-26, https://doi.org/10.36487/ACG_repo/2035_0.01

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Abstract:
Mobile LiDAR mapping techniques took a vast step forward during the twenty-teens, from research and development to consumer products. The promise of spatially mapping GPS-denied environments opened a world of possibilities; applications in underground geomechanics has been just one. The sensor technology and associated hardware has improved immensely and the future promises exciting developments. However, the data acquisition is only the first step in what is a whole new workflow applied to underground mining geomechanics. The workflow from data acquisition to final interpretation is not currently an automated, algorithmic process. Rather, it currently requires a conceptual understanding of the hardware, and various data processing methods to arrive at implementable results. The technology provides a valuable tool for aiding mining and geomechanical engineers. Its advantages include greater spatial coverage, detailed rock mass assessments, and safe access to previously inaccessible areas. The twenty-twenties hold great promise for the technology. This paper details the background to how mobile mapping technology has been introduced into underground mining geomechanics. The hardware and processing limitations are discussed with reference to case examples from the author’s experience using the technology. Finally, some speculation is offered into the hardware developments and industry adoption over the coming years.

Keywords: mobile LiDAR, SLAM, monitoring, geomechanics

References:
Arp, H., Griesbach, J.C., and Burns, J.P. 1982. Mapping in tropical forests:
a new approach using the laser APR. Photogrammetric Engineering and
Remote Sensing, Vol. 48, No. 1, pp. 91100.
Arp, H., Griesbach, J.C., and Burns, J.P. 1982. Mapping in tropical forests:
a new approach using the laser APR. Photogrammetric Engineering and
Remote Sensing, Vol. 48, No. 1, pp. 91100.
Arp, H, Greisbach, JC & Burns, JP 1982, ‘Mapping in tropical forests: a new approach using the laser APR’, Photogrammetric Engineering and Remote Sensing, vol. 48, no. 1, pp. 91–100.
Artan, U, Marshall, J & Lavigne, N 2011, Robotic mapping of underground mine passageways’, Mining Technology, vol. 120,
pp. 18–24,
Baylis, C & Kewe, D 2020, New technologies and methods for rock mass characterisations and domining, presentation at East Australian Geomechanics Group, Adelaide, South Australia.
Baylis, C, Kewe, D & Jones, E 2020, ‘Mobile drone LiDAR structural data collection and analysis’, in J Wesseloo (ed.), Proceedings of the Second International Conference on Underground Mining Technology, Australian Centre for Geomechanics, Perth, pp. 325–334.
Bosse, M & Zlot, R 2009, ‘Continuous 3D scan-matching with a spinning 2D laser’, Proceedings of the IEEE International Conference on Robotics and Automation, Institute of Electrical and Electronics Engineer, Piscataway.
CloudCompare 2019, 3D point cloud and mesh processing software, computer software, version 2.9, http://www.cloudcompare.org/
Counter, DB 2019, 'Laser-based scanning to manage geotechnical risk in deep mines', in J Hadjigeorgiou & M Hudyma (eds), Proceedings of the Ninth International Symposium on Ground Support in Mining and Underground Construction, Australian Centre for Geomechanics, Perth, pp. 43–58,
DARPA 2020, Subterranean Challenge, accessed 10 October 2020,
Drover, C & Villaescusa, E 2015, ‘Estimation of dynamic load demand on a ground support scheme due to a large structurally controlled violent failure – a case study’, Mining Technology, vol. 125, pp. 1–14,
Duff, E 2016, Zebedee, accessed 17 September 2020,
Dunn, M, Reid, P & Malos, J 2020, ‘Development of a protective enclosure for remote sensing applications—case study: laser scanning in underground coal mines’, Resources, vol. 9, no. 5,
Durrant-Whyte, H & Bailey, T 2006, ‘Simultaneous Localisation and Mapping (SLAM): Part I The Essential Algorithms’, IEEE Robotics & Automation Magazine, vol. 13, issue 2, pp. 99–110.
Gallant, M & Marshall, JA 2016, ‘Automated rapid mapping of joint orientations with mobile LiDAR’, International Journal of Rock Mechanics and Mining Sciences, vol. 90, pp. 1–14.
Gelinas, LP, Falmagne, V, Bedard, B & Matte, O 2019, 'Advanced geotechnical monitoring technology to assess ground support effectiveness', in J Hadjigeorgiou & M Hudyma (eds), Proceedings of the Ninth International Symposium on Ground Support in Mining and Underground Construction, Australian Centre for Geomechanics, Perth,
pp. 59–74, 
Hancock, E & Jones, E 2019, ‘Budgeting for deformation’, in SAB da Fontoura, RJ Rocca & JO Mendoza (eds), Rock Mechanics for Natural Resources and Infrastructure Development - Full Papers; Proceedings of the 14th International Congress on Rock Mechanics and Rock Engineering, CRC Press, London, pp. 1433–1441.
Hickman, GD & Hogg, JE 1969, ‘Application of an airborne pulsed laser for near shore bathymetric measurements’, Remote Sensing of Environment, vol. 1, pp. 47–58,
Jiao, Y & Hudson, JA 1995, ‘The fully-coupled model for rock engineering systems’, International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, vol. 32, pp. 491–512.
Jones, E & Beck, D 2017, ‘The use of 3D laser scanning for deformation monitoring in underground mines’, Proceedings of the 13th AusIMM Underground Operators’ Conference, The Australasian Institute of Mining and Metallurgy, Melbourne, pp. 267–270.
Jones, E & Hancock, E 2019, ‘Managing the deformation of ground support and reinforcement’, Rock Mechanics for Natural Resources and Infrastructure Development - Full Papers; Proceedings of the 14th International Congress on Rock Mechanics and Rock Engineering, CRC Press, London, pp. 822–830.
Jones, E, Beck, D & Reusch, F 2016, ‘The use of underground laser mapping for numerical model calibration’, Proceedings of EUROCK 2016, International Society of Rock Mechanics, Lisbon, pp. 1237–1242,
Jones, E, Ghabraie, B & Beck, D 2018, ‘A method for determining field accuracy of mobile scanning devices for geomechanics applications’, Proceedings of the 10th Asian Rock Mechanics Symposium, International Society for Rock Mechanics and Rock Engineering, Lisbon.
Jones, E, Reardon, D & Hrabar, S 2019a, ‘The use of automated drones in underground hard rock mines’, Proceedings Future Mining 2019, The Australasian Institute of Mining and Metallurgy, Melbourne, pp. 34–46.
Jones, E, Sofonia, J, Canales, C, Hrabar, S & Kendoul, F 2019b, 'Advances and applications for automated drones in underground mining operations', in W Joughin (ed.), Proceedings of the Ninth International Conference on Deep and High Stress Mining, The Southern African Institute of Mining and Metallurgy, Johannesburg, pp. 323334,
Lato, M & Diederichs, M 2014, ‘Mapping shotcrete thickness using LiDAR and photogrammetry data: Correcting for over-calculation due to rockmass convergence’, Tunnelling and Underground Space Technology, vol. 41, pp. 234–240,
LKAB 2020, ‘One month after the seismic event in the Kiruna Mine’, LKAB news, viewed 12 October 2020,
Lynch, B, Marr, J, Marshall, J & Greenspan, M 2017, ‘Mobile LiDAR-based convergence detection in underground tunnel environments’,
sequence=1&isAllowed=y
Maiman, T 1960, ‘Stimulated optical radiation in ruby’, Nature, vol. 187, no. 4736, pp. 493–494,
Nelson, R 2014, ‘How did we get here? An early history of forestry lidar 1’, Canadian Journal of Remote Sensing, vol. 39, pp. S6–S17,
Nuchter, A, Surmann, H, Lingemann, K, Hertzberg, J & Thrun, S 2004, ‘6D SLAM with an application in autonomous mine mapping’, Proceedings of the IEEE International Conference on Robotics and Automation,
Peck, RB 1969, ‘Advantages and limitations of the observational method in applied soil mechanics’, Géotechnique, vol. 19, issue 2, pp. 171–187.
Raval, S, Banerjee, B, Canbulat, I & Singh, SK 2019, ‘A preliminary investigation of mobile mapping technology for underground mining’, Proceedings of the IEEE International Geoscience and Remote Sensing Symposium,
Reeves, B, Noon, D, Stickley, G & Longstaff, I 2001, ‘Slope stability radar for monitoring mine walls’, in C Nguyen (ed.), Proceedings of Subsurface and Surface Sensing Technologies and Applications III,
Rogers, EM 1962, Diffusion of innovations, Free Press of Glencoe, New York.
Ross, B 2017, Rise to the Occasion: Lessons from the Bingham Canyon Manefay Slide, Society for Mining, Metallurgy & Exploration, Englewood.
Singh, SK, Raval, S & Banerjee, BP 2019, ‘Mobile 3D imaging in underground coal mines: a case study’, Proceedings of Future Mining 2019, The Australasian Institute of Mining and Metallurgy, Melbourne, pp. 145–148.
Szwedzicki, T 2001, ‘Geotechnical precursors to large-scale ground collapse in mines’, International Journal of Rock Mechanics and Mining Sciences, vol. 38, pp. 957–965,
Szwedzicki, T 2003, ‘Rock mass behaviour prior to failure’, International Journal of Rock Mechanics and Mining Sciences, vol. 40, pp. 573–584,
Tversky, A & Kahneman, D 1974, ‘Judgment under uncertainty: heuristics and biases’, Science, vol. 185, issue 4157, pp. 1124–1131,
Vallejos, C 2019, Structural recognition and rock mass characterisation in underground mines: a UAV and LiDAR mapping based approach, MSc thesis, Universidad De Concepcion, Santiago.
Vidas, S & Moghadam, P 2013, ‘HeatWave: A handheld 3D thermography system for energy auditing’, Energy and Buildings, vol. 66, pp. 445–460,
Watson, C & Marshall, J 2018, ‘Estimating underground mine ventilation friction factors from low density 3D data acquired by a moving LiDAR’, International Journal of Mining Science and Technology, vol. 28,
Woolmer, D, Jones, E, Taylor, J, Baylis, C & Kewe, D 2021, ‘Use of drone-based LiDAR technology at Olympic Dam mine and Initial technical applications’, Proceedings of the Eighth International Conference & Exhibition on mass Mining, submitted for publication.
Zhang, D & Zhou, G 2016, ‘Estimation of soil moisture from optical and thermal remote sensing: a review’, Sensors, vol. 16, issue 8,
Zlot, R & Bosse, M 2012, ‘Efficient large-scale 3D mobile mapping and surface reconstruction of an underground mine’, Field and Service Robotics, vol. 92,




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