Admittance Control for Robotic Loading: Underground Field Trials with an LHD

  • Andrew A. Dobson
  • Joshua A. Marshall
  • Johan Larsson
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 113)


In this paper we describe field trials of an admittance-based Autonomous Loading Controller (ALC) applied to a robotic Load-Haul-Dump (LHD) machine at an underground mine near Örebro, Sweden. The ALC was tuned and field tested by using a 14-tonne capacity Atlas Copco ST14 LHD mining machine in piles of fragmented rock, similar to those found in operational mines. Several relationships between the ALC parameters and our performance metrics were discovered through the described field tests. During these tests, the tuned ALC took 61 % less time to load 39 % more payload when compared to a manual operator. The results presented in this paper suggest that the ALC is more consistent than manual operators, and is also robust to uncertainties in the unstructured mine environment.


Admittance Control Fragmented Rock Admittance Controller Digging Force Actuator Velocity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to thank Atlas Copco Rock Drills AB for facilitating this research collaboration. This research was supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC) under grant 371452-2009.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Andrew A. Dobson
    • 1
  • Joshua A. Marshall
    • 2
  • Johan Larsson
    • 3
  1. 1.Clearpath RoboticsKitchenerCanada
  2. 2.Mining Systems LaboratoryQueen’s UniversityKingstonCanada
  3. 3.Division Rocktec AutomationAtlas Copco Rock Drills ABÖrebroSweden

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