Frequent observations are key to detect any change occurring in underground mines. The conventional observation strategies (such as tell tales, extensometers, shear-meters) include localised mapping that is often time-consuming and unscaleable to map changes happening at a large scale. Further, conditions in the underground mines such as unavailability of global navigation satellite system (GNSS) signal, suboptimal lighting conditions, limited access and intrinsic safety requirements restrict the use of large-scale mapping technologies such as photogrammetry, terrestrial laser scanning (TLS) and RADAR. With recent advancements in the field of simultaneous localisation and mapping (SLAM) using laser scanning technology, it has now become possible to use portable mobile mapping systems to generate large-scale 3D models. Most of the current SLAM based mobile mapping systems perform better in non-mining (ordinary indoor) environments but poses technical challenges when used in underground mines. Nevertheless, the system shows huge potential in capturing the geometry of the mine site including structural support systems such as rock bolts and cable bolts. The system generates a digitised pattern of three-dimensional points called point could which provides unprecedented details that could be extracted automatically with the help of tailored machine learning-based algorithms.
CITATION: Singh, S K, Raval, S and Banerjee, B P, 2019. Mobile 3D imaging in underground coal mines: a case study, in Proceedings Future Mining 2019, pp 145148 (The Australasian Institute of Mining and Metallurgy: Melbourne).