With ever-increasing productivity targets in mining operations, there is a growing interest in mining automation. In future mines, remote-controlled and autonomous haulers will operate underground guided by LiDAR sensors. We envision reusing LiDAR measurements to maintain accurate mine maps that would contribute to both safety and productivity. Extrapolating from a pilot project on reliable wireless communication in Boliden's Kankberg mine, we propose establishing a system-of-systems (SoS) with LIDAR-equipped haulers and existing mapping solutions as constituent systems. SoS requirements engineering inevitably adds a political layer, as independent actors are stakeholders both on the system and SoS levels. We present four SoS scenarios representing different business models, discussing how development and operations could be distributed among Boliden and external stakeholders, e.g., the vehicle suppliers, the hauling company, and the developers of the mapping software. Based on eight key variation points, we compare the four scenarios from both technical and business perspectives. Finally, we validate our findings in a seminar with participants from the relevant stakeholders. We conclude that to determine which scenario is the most promising for Boliden, trade-offs regarding control, costs, risks, and innovation must be carefully evaluated.
Huber and Vandapel and their research group also did work on underground mine mapping using robots @cite_18 . In contrast to the work by Thrun , Huber and Vandapel tried their approach in active mines. They mounted a high-resolution 3D scanner on a mobile robot, providing 8000 x 1400 pixel scans with millimeter-level accuracy. As for Groundhog, they collected scans only at certain vantage points; Each three to five meters the robot stopped for 90 seconds to obtain a complete scan. A considerable contribution of their research is related to multi-view surface matching, i.e., merging multiple 3D views into a single map. Their approach is called iterative merging, which was successfully used to create high-quality maps of an underground mine. However, their approach does not scale to large numbers of scans; Back in 2006, their approach could only generate sub-maps containing about 50 scans.
@cite_18
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For several years, our research group has been developing methods for automated modeling of 3D environments. In September, 2002, we were given the opportunity to demonstrate our mapping capability in an underground coal mine. The opportunity arose as a result of the Quecreek mine accident, in which an inaccurate map caused miners to breach an abandoned, water-lled mine, trapping them for several days. Our eld test illustrates the feasibility and potential of high resolution three-dimensional (3D) mapping of an underground coal mine using a cartmounted 3D laser scanner. This paper presents our experimental setup, the automatic 3D modeling method used, and the results of the eld test. In addition, we address issues related to laser sensing in a coal mine environment.