发表机构
Advanced Mining Technology Center (AMTC) and Department of Electrical Engineering, Universidad de Chile（智利大学先进采矿技术中心（AMTC）和电气工程系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对采矿中冲击锤操作自动化问题，提出实时RGB-D感知管道，结合图像实例分割与点云处理，能生成破岩姿态和3D表示，在嵌入式硬件上约10Hz运行，实验证明适用于实时自主冲击锤操作。
AI 中文摘要
冲击锤是采矿作业中的重要机器，用于二次破碎。在地下采矿中，这些机器通常是遥控操作的，限制了作业效率。本文提出了一种实时RGB-D感知管道，朝着采矿中液压冲击锤操作自动化迈进。该系统同时生成可行的破岩姿态和工作空间的无机器人3D表示。该方法将基于图像的实例分割与几何点云处理相结合，在嵌入式硬件上以约10Hz运行，总延迟约675ms。在代表性缩放场景中的实验结果表明该系统适用于实时自主冲击锤操作。
英文摘要
Impact hammers, also known as rock-breakers, are essential machines in mining operations, where they perform secondary reduction. In underground mining, these machines are typically teleoperated, limiting operational efficiency. This paper presents a real-time RGB-D perception pipeline as a step towards automating the operation of hydraulic impact hammers used in mining. The proposed system simultaneously generates operationally feasible rock-breaking poses and a robot-free 3D representation of the workspace. The proposed approach combines image-based instance segmentation with geometric point cloud processing, and operates on embedded hardware at approximately 10 Hz with a total latency of around 675 ms, enabling responsive closed-loop behavior when integrated with a control system. Experimental results in a representative scaled scenario demonstrate that the proposed system is suitable for real-time autonomous impact hammer operation.
Comments25 pages, 20 figures
