Studies in machine learning and robotics for automated construction

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The aim of this PhD research is to achieve a step-change in how underground digital twins are constructed by leveraging recent advances in sensor data fusion and machine learning (ML). Digital ground surveying techniques (e.g. ground penetrating radars, seismic scanner, camera and Lidar) will be used to develop 3D mapping of the underground space during construction. A scalable ML framework will be developed to achieve accurate 3D reconstruction and perform perception, prediction and planning tasks. The fused sensory inputs will subsequently be used to build the digital twin. The developed framework will be developed and validated through real-world data provided by industry partner and infraTech start-up hyperTunnel Ltd.