基于数字孪生的煤矿掘进机器人纠偏控制研究

薛旭升, 任众孚, 毛清华, 张旭辉, 马宏伟, 王悦

薛旭升,任众孚,毛清华,等. 基于数字孪生的煤矿掘进机器人纠偏控制研究[J]. 工矿自动化,2022,48(1):26-32. DOI: 10.13272/j.issn.1671-251x.2021100006
引用本文: 薛旭升,任众孚,毛清华,等. 基于数字孪生的煤矿掘进机器人纠偏控制研究[J]. 工矿自动化,2022,48(1):26-32. DOI: 10.13272/j.issn.1671-251x.2021100006
XUE Xusheng, REN Zhongfu, MAO Qinghua, et al. Research on deviation correction control of coal mine roadheader based on digital twin[J]. Industry and Mine Automation,2022,48(1):26-32. DOI: 10.13272/j.issn.1671-251x.2021100006
Citation: XUE Xusheng, REN Zhongfu, MAO Qinghua, et al. Research on deviation correction control of coal mine roadheader based on digital twin[J]. Industry and Mine Automation,2022,48(1):26-32. DOI: 10.13272/j.issn.1671-251x.2021100006

基于数字孪生的煤矿掘进机器人纠偏控制研究

基金项目: 陕西省自然科学基础研究计划项目(2019JQ-802);国家自然科学基金重点项目(51834006);国家自然科学基金面上项目(52174150);陕西省重点实验室开放基金项目(SKL-MEEIM201913)。
详细信息
    作者简介:

    薛旭升(1987—),男,陕西兴平人,讲师,博士,研究方向为智能检测与控制、煤矿机器人关键技术等,E-mail:xuexsh@xust.edu.cn

  • 中图分类号: TD632

Research on deviation correction control of coal mine roadheader based on digital twin

  • 摘要: 针对复杂巷道环境下掘进机器人自主纠偏控制难题,通过分析掘进机器人偏移原因,明确了掘进机器人纠偏控制功能需求,提出了一种基于数字孪生的煤矿掘进机器人纠偏控制系统,介绍了系统组成;以掘进机器人对中纠偏为例,分析了系统纠偏控制机理,提出了基于双目视觉图像信息的掘进机器人纠偏控制方法,以双目视觉检测的巷道图像为基础数据,通过提取巷道图像特征及分析巷道坐标系与掘进机器人坐标系关系,解算出掘进机器人相对于巷道空间的位姿参数,根据解算结果对掘进机器人进行纠偏控制;构建了掘进机器人和巷道数字模型及定位定向参数数据库,通过虚实映射关系,实现了掘进机器人虚拟远程纠偏控制。实验结果表明,基于数字孪生的煤矿掘进机器人纠偏控制系统在不同工况下均可有效补偿掘进机器人偏航角和偏移距离,纠偏过程可实时显示在监测监控界面,且纠偏路径规划仿真结果与实际工况一致。
    Abstract: In order to solve the problem of autonomous deviation control of roadheader in complex roadway environment, the paper analyzes the deviation reasons of roadheader, defines the functional requirements of deviation correction control of roadheader, proposes a deviation correction control system of coal mine roadheader based on digital twin, and introduces the system composition. Taking the roadheader central position control as an example, the system deviation correction control mechanism is analyzed, and a deviation correction control method of the roadheader based on binocular vision image information is proposed. Taking the roadway image detected by binocular vision as the basic data, by extracting the characteristics of the roadway image and analyzing the relationship between the roadway coordinate system and the roadheader coordinate system, the position and attitude parameters of the roadheader relative to the roadway space are calculated, and the deviation correction control of the roadheader is carried out according to the solution results. The digital model and the positioning and orientation parameter database of the roadheader and the roadway are constructed, and the virtual remote deviation correction control of the roadheader is realized through the virtual-real mapping relationship. The experimental results show that the deviation correction control system based on digital twin can compensate the yaw angle and offset distance of the roadheader under different working conditions effectively. The deviation correction process can be displayed on the monitoring interface in real time, and the simulation results of deviation correction path planning are consistent with the actual working conditions.
  • 图  1   基于数字孪生的掘进机器人纠偏控制系统组成

    Figure  1.   Composition of deviation correction control system of roadheader robot based on digital twin

    图  2   数字模型

    Figure  2.   Digital models

    图  3   掘进机器人对中纠偏控制机理

    Figure  3.   Centeral position control mechanism of roadheader

    图  4   纠偏控制模型参数关系

    Figure  4.   Parameter relationship of deviation correction control model

    图  5   对中与偏移位置关系

    Figure  5.   Relationship between central and deviation positions

    图  6   掘进机器人定位定向参数采集

    Figure  6.   Positioning and orientation parameter acquisition for roadheader

    图  7   空间坐标系

    Figure  7.   Spatial coordinate systems

    图  8   巷道图像特征提取与虚拟环境重构

    Figure  8.   Roadway image characteristic extraction and virtual environment reconstruction

    图  9   掘进机器人纠偏控制流程

    Figure  9.   Deviation correction control flow of roadheader

    图  10   掘进机器人纠偏控制实验平台

    Figure  10.   Experimental platform of deviation correction control of roadheader

    图  11   模拟实验环境

    Figure  11.   Simulated experimental environment

    图  12   掘进机器人纠偏过程显示界面

    Figure  12.   Displaying interface of deviation correction process of roadheader

    图  13   掘进机器人纠偏控制路径规划

    Figure  13.   Path planning of deviation correction control of roadheaer

    表  1   掘进机器人位姿参数

    Table  1   Position and attitude parameters of roadheader

    序号偏移距离/cm偏航角/(°)预期工况
    1 5 6 右侧偏移
    2 −2 −3 左侧偏移
    3 4 −5 左侧偏移
    4 −6 7 右侧偏移
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-10-07
  • 修回日期:  2022-01-07
  • 网络出版日期:  2022-01-18
  • 发布日期:  2022-01-19
  • 刊出日期:  2022-01-19

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