实时感知矿山锤击机作业环境，自动生成破岩姿态。
A real-time RGB-D perception pipeline for autonomous impact hammers in mining: self-filtering, rock segmentation and rock-breaking poses generation
- 融合图像与点云数据，实现动态环境下的岩石分割。
- 系统运行在嵌入式设备上，帧率约10Hz，延迟仅675ms。
- 适合需要实时响应的矿山自动化设备开发人员使用。
冲击锤（又称碎岩机）是采矿作业中进行二次破碎的关键设备。在地下采矿中，这些设备通常采用远程操控，限制了作业效率。本文提出一种面向采矿液压冲击锤自动化的实时RGB-D感知流水线，可同步生成可行的破岩动作姿态及无机器人参与的三维工作空间表示。该方法结合基于图像的实例分割与几何点云处理，在嵌入式硬件上以约10 Hz的帧率运行，总延迟约为675毫秒，集成到控制系统后可实现响应迅速的闭环操作。在代表性缩比场景中的实验结果表明，该系统适用于实时自主冲击锤作业。
原文摘要 · Abstract (English)
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.
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