LHD自动装载

Proceedings Fourth Annual Conference on Mechatronics and Machine Vision in Practice Pub Date : 1997-09-23 DOI:10.1109/MMVIP.1997.625330

M.K. Petty, J. Billingsley, T. Tran-Cong

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引用次数: 20

摘要

利用机器视觉技术指导地下采矿过程中矿石的自动装载。从相机图像中实时导出矿堆的三维空间数据，并用于规划挖矿过程。一种感觉集成技术将来自同一视觉系统的前馈与车轮里程计相结合，以引导车辆往返于矿桩。推导了计算效率高的车辆运动学模型，并对其应用进行了讨论。载重自卸车在地下采矿中应用广泛。不断增加的生产成本和对提高安全性的不断追求，为他们的工作周期自动化提供了巨大的动力。本研究集中在该任务的一个主要组成部分-加载自动化。所提出的装载控制器将快速安全地装载铲运机，同时将矿桩置于合适的状态，供后续铲运机使用。

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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Autonomous LHD loading

Machine vision is used for guidance of the autonomous loading of ore during underground mining. Three dimensional spatial data of the ore pile is derived in real-time from camera images and is used for planning the scooping process. A sensory integration technique combines feedforward from the same vision system with wheel odometry to guide the vehicle to and from the ore pile. A computationally efficient kinematic model of the vehicle is derived and its application discussed. LHD (load-haul-dump) vehicles are used extensively in underground mining. Increasing production costs and the ongoing quest for improved safety provide a great incentive to automate their working cycle. This research concentrates on a major component of this task-automation of loading. The proposed loading controller will load an LHD swiftly and safely while leaving the ore pile in a suitable condition for subsequent bucket scoops.

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Proceedings Fourth Annual Conference on Mechatronics and Machine Vision in Practice

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