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TopLiterature Review
In recent years, research on SLAM technology in the mining sector has deepened. It has been widely applied to terrain mapping, positioning, navigation, and environmental perception tasks in both underground and open-pit mines. Current related research can be broadly categorized into three categories, based on application scenarios and technical approaches.
One category focuses on the evaluation of data quality and mapping performance. Fahle et al. (2022) compared its potential for geotechnical monitoring in underground mining using optical detection and ranging data. By testing two underground mines, they assessed the data quality of SLAM-based mobile laser scanning (MLS) systems—laser mapping platforms that collect 3D data while in motion—and proposed a comprehensive set of quality indicators. The results showed that specific SLAM processing methods significantly improved relative accuracy, reducing drift errors by up to 90%. The SLAM-based MLS system not only provided high-quality data but also effectively detected geological changes and demonstrated efficiency advantages in large-scale mine layouts.
A second category addresses map construction and updating strategies for open-pit mines. Wang et al. (2023) developed a high-definition map construction and updating system based on SLAM technology. By analyzing map elements and environmental features in open-pit mining processes, they proposed a multimodal, multilayered map structure, along with a method integrating positioning and perception and a multi-scene updating strategy. Field tests in unstructured road scenes demonstrated that this system reduced map data storage space by 98% compared to point cloud maps, which achieving high update accuracy and real-time performance, with errors limited to 0.15 m.