Flight Path Planning and Optimization for High-Resolution Imaging in Open Pit Mines by UAVs
Mining and Metallurgical Engineering
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The past decade has witnessed an unparallel augmentation in the field of Unmanned Aerial Vehicles (UAVs). With the increased availability of cost-effective drones and skilled personnel, there are many potential applications of drones in an open pit mining operation like tension crack detection and characterization, drill holes accuracy measurement, blast fragmentation or evaluating the condition of ramps. All these applications require high resolution and accurate 3-D models of the mine. For example, despite advances in slope monitoring, identification of tension crack remains an open problem for geotechnical engineers. With the increasing size and depth of the mines, traditional tension crack mapping is a laborious and dangerous task which eventually has necessitated automation. A crucial bottleneck to accomplish this task is the availability of millimeter resolution three-dimensional terrain models of the benches. This thesis aims to address the problem of tension crack detection on the benches of open pit mines by using Unmanned Aerial Vehicles. A UAV fitted with an image sensor has been used for imaging the open pit benches to generate high-resolution 3-Dimensional surface models of the mine. The contributions of this work include 1) Semi-automatic procedure for generating 3-D models of the mine, 2) Battery consumption model for the given UAV, 3) Path planning and optimization algorithm for taking high-resolution imaging of the open pit benches, and 4) An android application for flight planning of the UAV in the mine.