矿井环境高精定位技术研究现状与发展

doi:10.11872/j.issn.1005-2518.2021.01.177

黄金科学技术 ›› 2021, Vol. 29 ›› Issue (1): 3-13.doi: 10.11872/j.issn.1005-2518.2021.01.177

矿井环境高精定位技术研究现状与发展

毕林^1,²(),王黎明^1,²(),段长铭³

^1.中南大学资源与安全工程学院，湖南长沙 410083
^2.中南大学数字矿山研究中心，湖南长沙 410083
^3.中移（上海）信息通信科技有限公司，湖北武汉 200120

收稿日期:2020-09-28 修回日期:2021-01-06 出版日期:2021-02-28 发布日期:2021-03-22
通讯作者: 王黎明 E-mail:Mr.BiLin@163.com;1170794515@qq.com
作者简介:毕林（1975-），男，四川通江人，副教授，从事GIS、数字矿山和铲运机无人化等方面的研究工作。Mr.BiLin@163.com
基金资助:
国家自然科学基金项目 “基于深度学习和距离场的复杂金属矿体三维建模技术研究”(41572317);国家重点研发计划项目“基于大数据的金属矿开采装备智能管控技术研发与示范”(2019YFC0605300)

Research Situation and Development of High-precision Positioning Technology for Underground Mine Environment

Lin BI^1,²(),Liming WANG^1,²(),Changming DUAN³

^1.School of Resources and Safety Engineering，Central South University，Changsha 410083，Hunan，China
^2.Digital Mine Research Center，Central South University，Changsha 410083，Hunan，China
^3.China Mobile （Shanghai） Information and Communication Technology Co. ，Ltd. ，Wuhan 200120，Hubei，China

Received:2020-09-28 Revised:2021-01-06 Online:2021-02-28 Published:2021-03-22
Contact: Liming WANG E-mail:Mr.BiLin@163.com;1170794515@qq.com

摘要/Abstract

摘要：

地下矿山开采环境恶劣，井下设备的自动化、智能化发展势在必行。井下设备高精度自主定位技术是推动地下智能开采的关键技术之一。为了系统地了解和研究国内外矿井设备定位技术的发展情况和问题所在，基于国内外井下设备高精定位的研究现状分析，综合评述了当前井下定位的核心技术和发展前景。首先归纳了井下常用的环境感知传感器；然后根据井下设备定位的技术手段、硬件基础及算法特点，对当前的研究成果进行了归类分析；最后进行了总结展望，认为不需要外部设备辅助的多传感器融合技术（如基于SLAM的定位方法）是当前地下矿山井下设备定位发展的必然趋势。

关键词: 地下矿山, 自主定位, 无线通讯, 环境感知, SLAM, 多传感器融合

Abstract:

The environmental conditions in underground mines are harsh.In recent years，with the continuous increase in the mining depth of underground mines and the improvement of mining technology requirements，the underground mines are faced with the bad environment of high temperature and high ground pressure，and the working conditions of underground mines workers have become more complex.Ensuring the safety and health of underground personnel is of great significance to promote the stable development of mining enterprises，and it is also one of the core contents of contemporary mine intelligent construction.Therefore，with the rapid development of technologies in the fields of big data，Internet of Things（IOT），unmanned driving and three-dimensional visualization，it is imperative to develop the automation and intelligence of underground equipment.For underground mines，the high-precision autonomous positioning technology of downhole equip-ment is one of the key technologies to promote underground intelligent mining，and it is also the basic guarantee for the realization of automated mining of underground mining equipment.High-precision positioning can ensure that underground personnel and equipment are within an accurate measurable range.At the same time，it is also particularly critical to advance the construction of underground unmanned equipment mining platforms （such as the development of underground LHD）.Based on the existing research results of high-precision positioning of underground equipment at home and aboard，after analyzing its development status，the categories of downhole equipment positioning sensors and the latest positioning technologies developed on this basis were summarized，which can be divided into two categories：One is the positioning technology that requires the addition of external equipment in the mine environment for auxiliary positioning，and the other is the positioning technology that only relies on the sensors carried by the equipment itself.The core technology and development prospects of underground mine high-precision positioning were put forward.This paper mainly introduces the current technical status，technical characteristics and development trend of underground mines equipment positioning.Firstly，the environmental sensing sensors commonly used in underground mines was summarized.Then，according to the technical means，hardware basis and algorithm characteristics of un-derground equipment positioning，the current research results were classified and analyzed.After analyzing and comparing the advantages and disadvantages of various positioning technologies，a summary and prospect were made，and it is considered that multi-sensor fusion technology without the assistance of external equipment（such as SLAM-based positioning method） is the inevitable trend of underground equipment positioning development in underground mines，so as to ensure the stability and accuracy of underground mine positioning to promote mine development smoothly entered the stage of true intelligence.

Key words: underground mine, autonomous positioning, wireless communication, environmental perception, SLAM, multi-sensor fusion

中图分类号:

TD52

毕林,王黎明,段长铭. 矿井环境高精定位技术研究现状与发展[J]. 黄金科学技术, 2021, 29(1): 3-13.

Lin BI,Liming WANG,Changming DUAN. Research Situation and Development of High-precision Positioning Technology for Underground Mine Environment[J]. Gold Science and Technology, 2021, 29(1): 3-13.

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参考文献 0

	Bi Lin，Duan Changming，Ren Zhuli，2020.Roadway edge detection algorithm based on RANSAC in underground mine［J］.Gold Science and Technology，28（1）：105-111.;
	Bosse M，Zlot R，2008.Map matching and data association for large-scale two-dimensional laser scan-based SLAM［J］.The International Journal of Robotics Research，27（6）：667-691.<br />
	Chi Hongpeng，Li Xin，Zang Huaizhuang，al et，2015.Research on positioning and navigation method with laser ranging for underground vehicles［J］.Mining & Processing Equipment，43（9）：114-118.<br />
	Cypriani M，Delisle G，Hakem N，2013.Wi-Fi-based positioning in underground mine tunnels［C］//2013 International Conference on Indoor Positioning and Indoor Navigation.New York：IEEE.<br />
	Fan Q G，Li W，Hui J，al et，2014.Integrated positioning for coal mining machinery in enclosed underground mine based on SINS/WSN［J］.Scientific World Journal，（1）：460415.<br />
	Firoozabadi A D，Azurdia-Meza C，Soto I，al et，2019.A novel frequency domain visible light communicate-on （VLC） three-dimensional trilateration system for localization in underground mining［J］.Applied Sciences，9：1488.<br />
	Gao L L，Ma F，Jin C，2019.A Model-based method for estimating the attitude of underground articulated vehicles［J］.Sensors （Basel），19（23）：5245.<br />
	Gu Desheng，2014.Intelligent mining，touching the future of mining industry［J］.Mining Equipment，（1）：24-26.<br />
	Huang B C，Zhao J，Liu J B，2020.A survey of simultaneous localization and mapping with an envision in 6G wireless networks［EB/OL］.（2020-02-14）［2020-03-20］..<br />
	Jin C，Liu T，Shen Y H，al et，2015.State estimation of the electric drive articulated dump truck based on UKF［J］.Journal of Harbin Institute of Technology，（6）：21-30.<br />
	Kanellakis C，Nikolakopoulos G，2016.Evaluation of visual localization systems in underground mining［C］//24th Mediterranean Conference on Control and Automation（MED）.New York：IEEE：539-544.<br />
	Kummerle R，Grisetti G，Strasdat H，al et，2011.G2o：A general framework for graph optimization［C］//IEEE International Conference on Robotics & Automation. New York：IEEE.<br />
	Li Jianguo，2016.Research on the Automonous Control of Driving and Dumping for Underground Load-Haul-Dump［D］.Beijing：University of Science and Technology.<br />
	Li M G，Zhu H，You S Z，al et，2019.Efficient laser-based 3D SLAM for coal mine rescue robots［J］. IEEE Access，7：14124-14138.<br />
	Li M G，Zhu H，You S Z，al et，2020.UWB-based localization system aided with inertial sensor for underground coal mine applications［J］.IEEE Sensors Journal，20（12）：6652-6669.<br />
	Makela H，2001.Overview of LHD navigation without artificial beacons［J］.Robotics and Autonomous Systems，36（1）：21-35.<br />
	Nuchter A，Surmann H，Lingemann K，al et，2004.6D SLAM with an application in autonomous mine mapping［C］//Proc IEEE International Conference on Robotics and Automation ICRA. New Orleans：IEEE：1998-2003.<br />
	Park B，Myung H，2014.Underground localization using dual magnetic field sequence measurement and pose graph SLAM for directional drilling［J］.Measurement Science and Technology，25（12）：125101.<br />
	Qin Y Q，Wang F，Zhou C J，2015.A distributed UWB-based localization system in underground mines［J］.Journal of Networks，10（3）：134-140.<br />
	Ren Z L，Wang L G，Bi L，2019.Robust GICP-Based 3D Lidar SLAM for underground mining environment［J］.Sensors，19（13）：2915.<br />
	Wang Ence，2019.Research on Localization Algorithm in Wireless Sensor Networks［D］.Hangzhou：Hangzhou Dianzi University.<br />
	Wang Xia，Zuo Yifan，2020.Research progress of visual SLAM［J］.CAAI Transactions on Intelligent Systems，15（5）：825-834.<br />
	Wang Z，Wu L X，Li H Y，2011.Key technology of mine underground mobile positioning based on Lidar and coded sequence pattern［J］.Transactions of Nonferrous Metals Society of China，21：S570-S576.<br />
	Wu D，Meng Y，Zhan K，al et，2018.A Lidar SLAM based on point-line features for underground mining vehicle［C］//2018 Chinese Automation Congress（CAC）.New York：IEEE.<br />
	Wu Di，2019.Positioning Technology of LHD Based on Stereo Vision Odometer ［D］.Beijing：Beijing University of Science and Technology.<br />
	Wu G，Fang X Q，Zhang L，al et，2020.Positioning accuracy of the shearer based on a strapdown inertial navigation system in underground coal mining［J］.Applied Sciences-Basel，10（6）：2176.<br />
	Wu Qunying，Jiang Lin，Wang Guofa，al et，2020.Top-level architecture design and key technologies of smart mine［J］.Coal Science and Technology，48（7）：80-91.<br />
	Wu Xian，2016.Research on Localization Method of Mobile Robots Based on Multi-sensor Data Fusion［D］.Beijing：Beijing Jiaotong University.<br />
	Xu Z R，Yang W，You K M，al et，2017.Vehicle autonomous localization in local area of coal mine tunnel based on vision sensors and ultrasonic sensors［J］.Plos One，12（1）：e171012.<br />
	Yan Bo，Zhan Kai，Xin Guo，al et，2018.Assistant location algorithm based on beacon identification in underground LHD［J］.Nonferrous Metals （Mine Section），70（5）：78-81.<br />
	Yang Chao，Chen Shuxin，Liu Li，al et，2011.Reactive navigation for underground autonomous scraper［J］.Journal of Coal Science，36（11）：1943-1948.<br />
	Zeng F，Jacobson A，Smith D，al et，2019.LookUP：Vision-only real-time precise underground localisation for autonomous mining vehicles［C］//2019 International Conference on Robotics and Automation （ICRA）.New York：IEEE：1444-1450.<br />
	Zhang Bo，2016.Feature Extraction and Characterization of Unstructured Terrain Based on Laser Lidar［D］.Xiamen：Xiamen University.<br />
	Zhang J，Singh S，2017.Low-drift and real-time lidar odometry and mapping［J］.Autonomous Robots，41（2）：401-416.<br />
	Zhang Junhao，He Baiyue，Yang Xusheng，al et，2019.A review on wearable inertial sensor based human motion tracking［J］.Acta Automatica Sinica，45（8）：1439-1454.<br />
	Zhang Ke，2019.Study on Three Key Technologies of Wireless Sensor Network Underground Mine Monitoring System［D］.Hengyang：University of South China.<br />
	Zhu D X，Sun X T，Liu S L，al et，2019.A SLAM method to improve the safety performance of mine robot［J］.Safety Science，120：422-427.<br />
	毕林，段长铭，任助理，2020.基于RANSAC的地下矿山巷道边线检测算法［J］.黄金科学技术，28（1）：105-111.<br />
	迟洪鹏，李鑫，臧怀壮，等，2015.井下车辆激光测距—定位导航方法研究［J］.矿山机械，43（9）：114-118.<br />
	古德生，2014.智能采矿触摸矿业的未来［J］.矿业装备，（1）：24-26.<br />
	李建国，2016.地下铲运机自主行驶及卸载的控制研究［D］.北京：北京科技大学.<br />
	王恩策，2019.无线传感器网络定位算法研究［D］.杭州：杭州电子科技大学.<br />
	王霞，左一凡，2020.视觉SLAM研究进展［J］.智能系统学报，15（5）：825-834.<br />
	吴荻，2019.基于立体视觉里程计的地下铲运机定位技术研究［D］.北京：北京科技大学.<br />
	吴群英，蒋林，王国法，等，2020.智慧矿山顶层架构设计及其关键技术［J］.煤炭科学技术，48（7）：80-91.<br />
	吴显，2016.基于多传感器信息融合的移动机器人定位方法研究［D］.北京：北京交通大学.<br />
	严勃，战凯，郭鑫，等，2018.地下铲运机信标识别辅助定位算法［J］.有色金属（矿山部分），70（ 5）：78-81.<br />

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类别	主要传感器技术	精度	主要特征
无线通信	Zigbee、WIFI、Bluetooth、RFID、UWB、IrDA、VLC	精度为米级至分米级	通过组建WAN进行定位，需要提前铺设传感器节点。不同传感器在通讯距离（1~200 m）、频段、传输速率、传输容量、供电等方面具有不同特征
惯性	陀螺仪、加速计、IMU、INS	短时间内位移精度为亚米级	实时性高，但存在累计误差、误差随测量时长增加
视觉	单目、双目、多目相机及RGB-D相机	精度能够达到分米级	提取图像特征及测量深度，定位精度取决于算法
激光	单线束（二维）和多线束（三维）激光雷达	测量精度为厘米级	抗干扰能力强，不受光照变动影响；测量精度和角度分辨率高，定位精度与算法有关
其他	里程计（光电编码传感器）、角度传感器、磁场感应传感器等	里程计精度跟标定及轮胎打滑等因素有关；角度传感器精度可达秒级	里程计测量频率高，输出通常作为定位初值；角度传感器对设备运动模型进行约束，辅助定位;磁场传感器受地磁、温度变化和湿度变化等影响

传感器类型	优点	缺点
单目相机	成本低、结构简单、速度快	没有尺度和深度信息
双目相机	可通过基线估计深度	计算量大
RGB-D相机	可估计像素级深度信息	测量范围窄、噪声大
事件相机	动态范围广、时间分辨率高、延时及功耗低	噪声大、特征点提取复杂

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矿井环境高精定位技术研究现状与发展

Research Situation and Development of High-precision Positioning Technology for Underground Mine Environment

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