School of Mechanical and Electrical Engineering, China University of Mining and Technology
Xuzhou XCMG Heavy Vehicle Co., Ltd.
CCTEG Taiyuan Research Institute

无人驾驶是矿山智能化关键技术之一，其中即时定位与地图构建（SLAM）技术是实现无人驾驶的关键环节。为推动SLAM技术在矿山无人驾驶领域的发展，对SLAM技术原理、成熟地面SLAM方案、现阶段矿山SLAM研究现状、未来矿山SLAM发展趋势进行了探讨。根据SLAM技术所使用的传感器，从视觉、激光及多传感器融合3个方面分析了各自的技术原理及相应框架，指出视觉和激光SLAM技术通过单一相机或激光雷达实现，存在易受环境干扰、无法适应复杂环境等缺点，多传感器融合SLAM是目前最佳的解决方法。探究了目前矿山SLAM技术的研究现状，分析了视觉、激光、多传感器融合3种SLAM技术在井工煤矿、露天矿山的适用性与研究价值，指出多传感器融合SLAM是井工煤矿领域的最佳方案，SLAM技术在露天矿山领域研究价值不高。基于现阶段井下SLAM技术存在的难点（随时间及活动范围积累误差、各类场景引起的不良影响、各类传感器无法满足高精度SLAM算法的硬件要求），提出矿山无人驾驶领域SLAM技术未来应向多传感器融合、固态化、智能化方向发展。

Autonomous driving is identified as one of the key technologies for mining intelligence, with simultaneous localization and mapping (SLAM) technology serving as a key link to realize autonomous driving. To advance the development of SLAM technology in autonomous mining, this paper discusses the principles of SLAM technology, mature ground SLAM solutions, the current research status of mining SLAM, and future development trends. Based on the sensors employed in SLAM technology, the study analyzes the technical principles and corresponding frameworks from three aspects: vision, laser, and multi-sensor fusion. It is noted that visual and laser SLAM technologies, which utilize single cameras or LiDAR, are susceptible to environmental interference and cannot adapt to complex environments. Multi-sensor fusion SLAM emerges as the most effective solution. The research examines the status of mining SLAM technology, analyzing the applicability and research value of visual, laser, and multi-sensor fusion SLAM technologies in underground coal mines and open-pit mines. It concludes that multi-sensor fusion SLAM represents the optimal research approach for underground coal mines, while the research value of SLAM technology in open-pit mines is limited. Based on the challenges identified in underground SLAM technology, such as accumulated errors over time and activity range, adverse effects from various scenes, and the inadequacy of various sensors to meet the hardware requirements for high-precision SLAM algorithms, it is proposed that future developments in SLAM technology for autonomous mining should focus on multi-sensor fusion, solid-state solutions, and intelligent development.

江苏省科技成果转化专项资金项目（BA2023035）；煤矿采掘机械装备国家工程实验室开放课题项目（GCZX-2023-01）；江苏高校优势学科建设工程资助项目（PAPD）。

崔邵云，鲍久圣，胡德平，等. SLAM技术及其在矿山无人驾驶领域的研究现状与发展趋势[J]. 工矿自动化，2024，50（10）：38-52.

CUI Shaoyun, BAO Jiusheng, HU Deping, et al. Research status and development trends of SLAM technology in autonomous mining field[J]. Journal of Mine Automation，2024，50（10）：38-52.