计算机视觉在某钾肥矿山掘进机自动选切中的应用

Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments Pub Date : 1991-06-19 DOI:10.1109/ICAR.1991.240622

J. Orteu, M. Devy

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引用次数: 6

摘要

采矿作业的自动化涉及使用传感、远程监测和控制系统，以便应付各种情况和环境条件。矿山整体经济的基本要求有时要求进行选择性切割，以便在切割阶段将富矿与废矿分离。基本上，要解决的问题是对一个不受控制的、不断变化的矿山环境进行建模，并对机器进行编程以相应地切割图案。作者指出了彩色图像分割、自动图像分类、相机标定和三维场景感知如何协同解决选择性切割这样的复杂问题

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Application of computer vision to automatic selective cutting with a roadheader in a potash mine

Automation of mining operations involves the use of sensing, remote monitoring and control systems in order to confront a variety of situations and environmental conditions. The basic requirement of the overall economy of the mine sometimes requires that selective cutting be performed in order to separate rich ore from waste at the cutting stage. Basically, the problems to be solved are those of modelling an uncontrolled, changing mine environment and programming the machine to cut a pattern accordingly. The authors indicate how color image segmentation, automatic image classification, camera calibration and 3D scene perception can cooperate to solve such a complex problem as selective cutting.<>

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Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments

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