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Although multiview platforms have enhanced work efficiency in mining teleoperation systems, they also induce “cognitive tunneling” and depth-detection issues for operators. These issues inadvertently focus their attention on a restricted central view. Fully immersive virtual reality (VR) has recently attracted the attention of specialists in the mining industry to address these issues. Nevertheless, developing VR teleoperation systems remains a formidable challenge, particularly in achieving a realistic 3D model of the environment. This study investigates the existing gap in fully immersive teleoperation systems within the mining industry, aiming to identify the most optimal methods for their development and ensure operator’s safety. To achieve this purpose, a literature search is employed to identify and extract information from the most relevant sources. The most advanced teleoperation systems are examined by focusing on their visualization types. Then, various 3D reconstruction techniques applicable to mining VR teleoperation are investigated, and their data acquisition methods, sensor technologies, and algorithms are analyzed. Ultimately, the study discusses challenges associated with 3D reconstruction techniques for mining teleoperation. The findings demonstrated that the real-time 3D reconstruction of underground mining environments primarily involves depth-based techniques. In contrast, point cloud generation techniques can mostly be employed for 3D reconstruction in open-pit mining operations.
Kamran-Pishhesari et al. (Fri,) studied this question.