[论文解读] A real-time analysis of rock fragmentation using UAV technology

Thomas Bamford, Kamran Esmaeili+1 more|arXiv (Cornell University)|Jul 14, 2016

Robotics and Sensor-Based Localization参考文献 8被引用 4

一句话总结

本文提出了一种基于四旋翼无人机（UAV）搭载摄像头的实时岩石破碎分析系统，用于捕获岩堆的高分辨率图像。通过利用动作捕捉系统实现对无人机的精确控制，该方法实现了自动化、高时间与空间分辨率的颗粒尺寸分布测量，在实验室内实验中，其速度和准确性优于人工方法。

ABSTRACT

Accurate measurement of blast-induced rock fragmentation is of great importance for many mining operations. The post-blast rock size distribution can significantly influence the efficiency of all the downstream mining and comminution processes. Image analysis methods are one of the most common methods used to measure rock fragment size distribution in mines regardless of criticism for lack of accuracy to measure fine particles and other perceived deficiencies. The current practice of collecting rock fragmentation data for image analysis is highly manual and provides data with low temporal and spatial resolution. Using UAVs for collecting images of rock fragments can not only improve the quality of the image data but also automate the data collection process. Ultimately, real-time acquisition of high temporal- and spatial-resolution data based on UAV technology will provide a broad range of opportunities for both improving blast design without interrupting the production process and reducing the cost of the human operator. This paper presents the results of a series of laboratory-scale rock fragment measurements using a quadrotor UAV equipped with a camera. The goal of this work is to highlight the benefits of aerial fragmentation analysis in terms of both prediction accuracy and time effort. A pile of rock fragments with different fragment sizes was placed in a lab that is equipped with a motion capture camera system for precise UAV localization and control. Such an environment presents optimal conditions for UAV flight and thus, is well-suited for conducting proof-of-concept experiments before testing them in large-scale field experiments. The pile was photographed by a camera attached to the UAV, and the particle size distribution curves were generated in almost real-time. The pile was also manually photographed and the results of the manual method were compared to the UAV method.

研究动机与目标

• 开发一种用于采矿作业中岩石破碎的实时自动化测量方法。
• 通过基于无人机的航拍成像替代人工图像采集，提高数据质量和分辨率。
• 减少传统爆破后岩石尺寸分析所涉及的人工劳动和时间成本。
• 在受控的实验室规模条件下，验证基于无人机的破碎分析的可行性。
• 对比基于无人机的颗粒尺寸分布与人工方法在准确性和效率方面的表现。

提出的方法

• 使用搭载摄像头的四旋翼无人机拍摄受控岩石碎片堆的航拍图像。
• 动作捕捉系统为无人机提供精确的定位与控制，确保飞行路径的一致性。
• 应用图像处理算法，从无人机捕获的图像中近乎实时地提取颗粒尺寸分布。
• 将无人机方法与同一岩石堆的人工摄影及图像分析进行基准对比。
• 利用计算机视觉技术，自动从无人机数据生成颗粒尺寸分布曲线。
• 在实验室内环境进行测试，以模拟理想条件，为野外部署做准备。

实验结果

研究问题

• RQ1 基于无人机的成像在岩石破碎分析中能否实现比人工方法更高的时间与空间分辨率？
• RQ2 从无人机图像中提取的颗粒尺寸分布与人工方法相比，其准确性如何？
• RQ3 无人机技术在多大程度上可以减少爆破后岩石破碎评估的时间与人力投入？
• RQ4 是否能够在无人机平台上实现岩石碎片数据的实时处理？
• RQ5 动作捕捉系统是否能够实现无人机的精确飞行，从而在受控环境中确保一致的数据采集？

主要发现

• 基于无人机的方法实现了颗粒尺寸分布曲线的近乎实时生成，与人工方法相比显著缩短了处理时间。
• 从无人机图像中提取的颗粒尺寸分布与人工测量结果高度一致，表明其具有高准确性。
• 动作捕捉系统的应用实现了无人机的精确定位，确保了图像采集的一致性与可靠的数据采集。
• 该系统展示了自动化潜力，减少了对人工操作员在数据采集中的依赖。
• 实验室内规模的设置验证了基于无人机的破碎分析在今后野外应用中的可行性。
• 该方法提供的空间分辨率更高，对岩石堆的覆盖范围也优于人工摄影。