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ZHANG Xuhui,CHEN Xin,YANG WenJuan,et al. Research on visual positioning method of digging and anchoring equipment based on single laser beam information[J]. Coal Science and Technology,2024,52(1):311−322. DOI: 10.12438/cst.2023-1674
Citation: ZHANG Xuhui,CHEN Xin,YANG WenJuan,et al. Research on visual positioning method of digging and anchoring equipment based on single laser beam information[J]. Coal Science and Technology,2024,52(1):311−322. DOI: 10.12438/cst.2023-1674

Research on visual positioning method of digging and anchoring equipment based on single laser beam information

Funds: 

Shaanxi Coal Joint Fund Funding Project (2021JLM-03); National Natural Science Foundation of China (52104166); Key Research and Development Plan Project of Shaanxi Province (2023-YBGY-063)

More Information
  • Received Date: October 24, 2023
  • Accepted Date: December 28, 2023
  • Available Online: January 25, 2024
  • Intelligent digging and anchoring equipment in underground coal mines is the key to improve the mining imbalance problem in the industry, and the precise positioning of digging and anchoring equipment is the prerequisite to realize its intelligence. Compared with other traditional positioning methods, the vision-based pose measurement method has been initially applied in underground coal mines for its advantages of no contact and no cumulative error. Aiming at the problems of complex structure of cooperative target and cumbersome calibration of the current visual positioning method of the digging anchor equipment in the face of the underground coal mine, combining with the characteristics of the original laser pointers in the face of the digging, a visual positioning method of the digging and anchoring equipment based on the information of a single laser beam is proposed. By analyzing the laser pointer spot and beam image features, the method proposes a laser spot center extraction method based on two-dimensional inverse tangent function fitting and a laser beam centerline extraction method based on Hough straight line detection, and constructs a binocular visual position solving model based on the point and line features, which results in the real-time position of the anchor digging equipment in the roadway. Finally, in order to verify the feasibility and accuracy of the proposed feature extraction method and visual positioning method, experiments were conducted in the laboratory by building a platform to simulate the working condition environment of the digging face. The results show that the visual localization method of digging and anchoring equipment based on the information of mining laser pointers has high accuracy of position measurement. Within the test range of 50 m, the average measurement errors of the body position along the X-axis, Y-axis and Z-axis under the roadway coordinate system are 25.44, 58.64 and 31.08 mm, respectively, and the maximum errors are 55.16, 127.39 and 63.57 mm, respectively; and the average measurement errors of the pitch angle, yaw angle and roll angle of the body attitude under the roadway coordinate system are 0.22°, 0.22°, 0.41°, and their maximum errors are 0.29°, 0.37°, 0.58°, respectively. The maximum errors are 0.29°, 0.37° and 0.58°, respectively. It meets the requirement of positioning accuracy for the construction of underground roadway in coal mine.

  • [1]
    王国法,刘 峰,孟祥军,等. 煤矿智能化(初级阶段)研究与实践[J]. 煤炭科学技术,2019,47(8):1−36.

    WANG Guofa,LIU Feng,MENG Xiangjun,et al. Research and practice on intelligent coal mine construction(primary stage)[J]. Coal Science and Technology,2019,47(8):1−36.
    [2]
    石 泉,孙常军,郑洪涛,等. 掘进机机器人化的关键技术研究[J]. 煤炭科学技术,2020,48(S2):199−204.

    SHI Quan,SUN Changjun,ZHENG Hongtao,et al. Research on the key technology of robotization of roadheader[J]. Coal Science and Technology,2020,48(S2):199−204.
    [3]
    马宏伟,毛金根,毛清华,等. 基于惯导/全站仪组合的掘进机自主定位定向方法[J]. 煤炭科学技术,2022,50(8):189−195.

    MA Hongwei,MAO Jingen,MAO Qinghua,et al. Automatic positioning and orientation method of roadheader based on combination of ins and digital total station[J]. Coal Science and Technology,2022,50(8):189−195.
    [4]
    张旭辉,刘博兴,张 超,等. 掘进机全站仪与捷联惯导组合定位方法[J]. 工矿自动化,2020,46(9):1−7.

    ZHANG Xuhui,LIU Boxing,ZHANG Chao,et al. Roadheader positioning method combining total station and strapdown inertial navigation system[J]. Industry and Mine Automation,2020,46(9):1−7.
    [5]
    陶云飞,杨健健,李嘉赓,等. 基于惯性导航技术的掘进机位姿测量系统研究[J]. 煤炭技术,2017,36(1):235−237.

    TAO Yunfei,YANG Jianjian,LI Jiageng,et al. Research on position and orientation measurement system of heading machine based on inertial navigation technology[J]. Coal Technology,2017,36(1):235−237.
    [6]
    田 原. 悬臂式掘进机惯性定位技术研究与试验[J]. 煤矿机电,2020,41(1):9−12.

    TIAN Yuan. Research and test on inertial positioning technology of boom-type roadheader[J]. Colliery Mechanical and Electrical Technology,2020,41(1):9−12.
    [7]
    陶云飞,宗 凯,张敏骏,等. 基于iGPS的掘进机单站多点分时机身位姿测量方法[J]. 煤炭学报,2015,40(11):2611−2616.

    TAO Yunfei,ZONG Kai,ZHANG Minjun,et al. Aposition and orientationmeasurement method of singlestation,multipoint and time-sharing forroadheaderbody based on iGPS[J]. Journal of China Coal Society,2015,40(11):2611−2616.
    [8]
    陶云飞,李 瑞,李嘉赓,等. iGPS的单站多点分时测量系统对掘进机偏向位移精度研究[J]. 煤炭技术,2017,36(2):246−247.

    TAO Yunfei,LI Rui,LI Jiageng,et al. Research on positioning accuracy of roadheader based on singlestation,multipoint and time-shared of iGPS measurement system[J]. Coal Technology,2017,36(2):246−247.
    [9]
    符世琛,李一鸣,宗 凯,等. 面向掘进机的超宽带位姿检测系统精度分析[J]. 仪器仪表学报,2017,38(8):1978−1987. doi: 10.3969/j.issn.0254-3087.2017.08.016

    FU Shichen,LI Yiming,ZONG Kai,et al. Accuracy analysis of UWB pose detection system for roadheader[J]. Chinese Journal of Scientific Instrument,2017,38(8):1978−1987. doi: 10.3969/j.issn.0254-3087.2017.08.016
    [10]
    符世琛,成 龙,陈慎金,等. 面向掘进机的超宽带位姿协同检测方法[J]. 煤炭学报,2018,43(10):2918−2925.

    FU Shichen,CHENG Long,CHEN Shenjin,et al. Ultra-wideband pose collaborative detection method of roadheader[J]. Journal of China Coal Society,2018,43(10):2918−2925.
    [11]
    张旭辉,刘永伟,杨文娟,等. 矿用悬臂式掘进机截割头姿态视觉测量系统[J]. 工矿自动化,2018,44(8):63−67.

    ZHANG Xuhui,LIU Yongwei,YANG Wenjuan,et al. Vision measurement system for cutting head attitude of mine-used boom-type roadheader[J]. Journal of Mine Automation,2018,44(8):63−67.
    [12]
    张旭辉,赵建勋,杨文娟,等. 悬臂式掘进机视觉导航与定向掘进控制技术[J]. 煤炭学报,2021,46(7):2186−2196.

    ZHANG Xuhui,ZHAO Jianxun,YANG Wenjuan,et al. Vision-based navigation and directional heading control technologies of boom-type roadheader[J]. Journal of China Coal Society,2021,46(7):2186−2196.
    [13]
    杜雨馨,刘 停,童敏明,等. 基于机器视觉的悬臂式掘进机机身位姿检测系统[J]. 煤炭学报,2016,41(11):2897−2906.

    DU Yuxin,LIU Ting,TONG Minming,et al. Pose measurement system of boom-type roadheader based on machine vision[J]. Journal of China Coal Society,2016,41(11):2897−2906.
    [14]
    田 原. 悬臂式掘进机视觉定位方法研究[J]. 矿山机械,2019,47(3):8−12. doi: 10.3969/j.issn.1001-3954.2019.03.003

    TIAN Yuan. Research on vision positioning method for boom-type roadheader[J]. Mining and Processing Equipment,2019,47(3):8−12. doi: 10.3969/j.issn.1001-3954.2019.03.003
    [15]
    张旭辉,沈奇峰,杨文娟,等. 基于三激光点标靶的掘进机机身视觉定位技术研究[J]. 电子测量与仪器学报,2022,36(6):178−186.

    ZHANG Xuhui,SHEN Qifeng,YANG Wenjuan,et al. Research on visual positioning technology of roadheader body based on three laser point target[J]. Journal of Electronic Measurement and Instrumentation,2022,36(6):178−186.
    [16]
    杨文娟,张旭辉,张 超,等. 基于三激光束标靶的煤矿井下长距离视觉定位方法[J]. 煤炭学报,2022,47(2):986−1001.

    YANG Wenjuan,ZHANG Xuhui,ZHANG Chao,et al. Long distance vision localization method based on triple laser beams target in coal mine[J]. Journal of China Coal Society,2022,47(2):986−1001.
    [17]
    张 超,张旭辉,杜昱阳,等. 基于双目视觉的悬臂式掘进机位姿测量技术[J]. 煤炭科学技术,2021,49(11):225−235.

    ZHANG Chao,ZHANG Xuhui,DU Yuyang,et al. Measuring technique of cantilever roadheader position based on binocular stereo vision[J]. Coal Science and Technology,2021,49(11):225−235.
    [18]
    熊德华,顾金良,李 建,等. 基于双目视觉的弹丸外弹道轨迹测试[J]. 自动化与仪表,2022,37(4):70−74.

    XIONG Dehua,GU Jinliang,LI Jian,et al. Projectile external trajectory measurement based on binocular vision[J]. Automation and Instrumentation,2022,37(4):70−74.
    [19]
    袁靖肖,汪 洋. 基于统计学的小尺寸光点质心快速定位算法[J]. 计算机仿真,2022,39(3):407−412. doi: 10.3969/j.issn.1006-9348.2022.03.080

    YUAN Jingxiao,WANG Yang. Fast centroid location algorithm of small size light spot based on statistics[J]. Computer Simulation,2022,39(3):407−412. doi: 10.3969/j.issn.1006-9348.2022.03.080
    [20]
    张新雨,李思雨,李婧华,等. 基于改进智能霍夫变换的红热圆形工件直径检测[J]. 西安理工大学学报,2022,38(1):41−47.

    ZHANG Xinyu,LI Siyu,LI Jinghua,et al. An improved intelligent Hough transform for detecting the diameter of red-hot circular workpiece[J]. Journal of Xi’an University of Technology,2022,38(1):41−47.
    [21]
    XU Xiaobin,FEI Zhongwen,TAN Zhiying,et al. Improved calibration method based on the RANSAC approach and an improved gray centroid method for a laser-line-based structured light system[J]. Applied Optics,2019,58(35):9603−9613. doi: 10.1364/AO.58.009603
    [22]
    孔 兵,王 昭,谭玉山. 激光光斑的高斯拟合[J]. 激光技术,2002,26(4):277−278.

    KONG Bing,WANG Zhao,TAN Yushan. Gaussian fitting technique of laser spot[J]. Laser Technology,2002,26(4):277−278.
    [23]
    MUKHOPADHYAY P,CHAUDHURI B B. A survey of hough transform[J]. Pattern Recognition,2015,48(3):993−1010. doi: 10.1016/j.patcog.2014.08.027
    [24]
    YANG Xin,XU Weidong,JIA Qi,et al. Research on extraction and reproduction of deformation camouflage spot based on generative adversarial network model[J]. Defence Technology,2020,16(3):555−563. doi: 10.1016/j.dt.2019.06.021
    [25]
    李天宇,王明泉,郝利华,等. 基于高斯拟合的信号弹光斑中心定位方法[J]. 激光与红外,2022,52(3):422−426. doi: 10.3969/j.issn.1001-5078.2022.03.018

    LI Tianyu,WANG Mingquan,HAO Lihua,et al. Signal flare spot center location method based on Gaussian fitting[J]. Laser and Infrared,2022,52(3):422−426. doi: 10.3969/j.issn.1001-5078.2022.03.018
    [26]
    TIAN Bin,WEI Wei. Research overview on edge detection algorithms based on deep learning and image fusion[J]. Security and Communication Networks,2022.
    [27]
    张 惠,李国平,张 勇,等. 基于三维反正切函数拟合的光斑质心提取算法[J]. 红外与激光工程,2019,48(2):268−275.

    ZHANG Hui,LI Guoping,ZHANG Yong et al. Spot centroid extraction algorithm based on three-dimensional arctangent function fitting[J]. Infrared and Laser Engineering,2019,48(2):268−275.
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