Research on key generic technology of multi-arm intelligent coal gangue sorting robot
-
摘要:
依据我国煤矿智能绿色发展战略，深入分析了国内外智能拣矸系统的研究现状，指出研发适用于井下的多机械臂煤矸石智能分拣机器人是破解煤矸分拣难题的重要发展方向，凝练了直接影响和制约我国煤矸石智能分拣高质量发展的“煤矸石准确识别、精准跟踪和可靠抓取、多目标任务多机械臂协同分拣”三大关键共性技术难题，并给出了解决思路和方法。针对煤矿井下煤矸石被煤泥严重包裹识别难，提出了“X射线+视觉”煤矸石识别与匹配方法、基于点云数据的煤矸石抓取特征提取方法，实现目标矸石的快速识别和最优抓取特征提取；针对煤矸石形态各异、动态环境抓取难，提出了基于ORB+BEBLID特征的FLANN动态目标高效匹配方法、基于FDSST的动态目标精准跟踪方法、基于三环PID的机械臂同步跟踪轨迹规划方法，实现机械手对高速传输的动态矸石稳定抓取；针对煤矸石随机分布、障碍多、多机械臂任务分配难，提出了改进匈牙利算法的多机械臂动态空间协同分拣方法，确保系统收益的前提下实现多机械臂在动态空间中高效协同工作。现场工业性试验研究结果表明，针对三大关键共性技术所提出的方法能够有效破解煤矸石高效识别和抓取特征提取、机械臂动态目标同步跟踪稳定抓取、多机械臂高效协同分拣等难题，通过构建完整的多机械臂煤矸石智能分拣机器人系统，提高了煤矸石智能分拣系统的可靠性和分拣效率。
Abstract:According to the intelligent green development strategy of coal mine in our country, the research status of intelligent coal gangue sorting system at home and abroad is deeply analyzed. It is pointed out that the development of multi-arm coal gangue intelligent sorting robot suitable for underground is an important development direction to solve the problem of coal gangue sorting. The three key common technical problems of “accurate recognition, accurate tracking and reliable grasp of coal gangue, multi-target task and multi-arm collaborative sorting” which directly affect and restrict the high quality development of intelligent sorting of coal gangue in China have been condensed, and the solutions are given. For the problem that coal gangue is badly encapsulated by coal slime in underground coal mine, the method of “X-ray and visual” recognition and matching of coal gangue, the method of extracting feature of coal gangue based on point cloud data are put forward to realize fast recognition and optimal feature extraction of target gangue. An efficient FLANN dynamic target matching method based on the fusion of ORB and BEBLID features, an accurate dynamic target tracking method based on FDSST, and a synchronous tracking trajectory planning method for manipulator based on three-loop PID are proposed to realize the stable grasping of dynamic gangstone with high-speed transmission by manipulator. For the random distribution of coal gangue and difficult task allocation of multi-manipulators with obstacles, a dynamic space cooperative sorting method of multi-manipulators based on improved Hungarian algorithm was proposed, which realized efficient cooperative work of multi-manipulators in dynamic space on the premise of ensuring system revenue. The results of field industrial experiment show that the proposed method for the three key common technologies can effectively solve the problems of efficient recognition and grasping feature extraction of coal gangue, synchronous tracking and stable grasping of dynamic targets of manipulators, efficient cooperative sorting of multi-manipulators, and construct a complete multi-manipulator intelligent sorting robot system for coal gangue. It improves the reliability and efficiency of the gangue intelligent sorting system.
-
-
![]()
图 1 煤矸石分拣机器人关键技术逻辑关系
Figure 1. Logical relation of key technology of coal gangue sorting robot
![]()
图 4 “X射线+视觉”煤矸石快速匹配方法原理
Figure 4. Schematic of the “X-ray + vision” coal gangue rapid matching method
![]()
图 7 基于点云数据的煤矸石抓取特征提取方法流程
Figure 7. Process of gangue capture feature extraction method based on point cloud data
![]()
图 9 基于ORB+BEBLID特征的FLANN匹配算法
Figure 9. FLANN matching algorithm based on ORB+BEBLID features
![]()
图 11 FDSST位置滤波器和尺度滤波器目标位置估计示意
Figure 11. FDSST position filter and scale filter target position estimation schematic
![]()
图 13 基于三环PID机械臂轨迹规划原理
Figure 13. Based on the trajectory planning schematic of the three-ring PID manipulator
![]()
图 14 三环PID控制算法动态目标轨迹规划曲线
Figure 14. Dynamic target trajectory planning curve of three-ring PID control algorithm
![]()
图 15 动态空间下多机械臂协同分拣过程
Figure 15. Multi-robot collaborative sorting process in dynamic space
![]()
图 18 多机械臂煤矸石分拣机器人工业样机
Figure 18. Industrial prototype of multi-arm coal gangue sorting robot
![]()
图 17 轨迹协同后机械臂分拣轨迹示意
Figure 17. Schematic of the sorting trajectory of the robotic arm after trajectory coordination
![]()
图 19 同一含矸率不同带速下不同方法的分拣效果
Figure 19. Sorting effect of different methods under different belt speeds of the same content rate
![]()
图 20 不同含矸率不同方法的分拣率
Figure 20. Sorting rates of different methods with different content rates
-
[1] 王 鹏, 曹现刚, 夏 晶, 等. 基于机器视觉的多机械臂煤矸石分拣机器人系统研究[J]. 工矿自动化, 2019, 45(9): 47-53. WANG Peng, CAO Xiangang, XIA jing, et al. Research on multi-manipulator coal and gangue sorting robot system based on machine vision[J]. Industry and Mine Automation, 2019, 45(9): 47-53.
[2] 孙稚媛. 基于视觉信息的煤矸石自动分拣机器人系统研究[D]. 北京: 中国矿业大学(北京), 2021. SUN Zhiyuan. Research on automatic coal gangue sorting robot system based on visual information[D]. Beijing: China University of Mining & Technology-Beijing, 2021.
[3] 赵明辉,宣鹏程,张少宾. 并联煤矸石分拣机器人的结构设计及分析[J]. 机床与液压,2021,49(5):55−59. doi: 10.3969/j.issn.1001-3881.2021.05.011 ZHAO Minghui,XUAN Pengcheng,ZHANG Shaobin. Structure design and analysis for parallel gangue sorting robot[J]. Machine Tool & Hydraulics,2021,49(5):55−59. doi: 10.3969/j.issn.1001-3881.2021.05.011
[4] 董华飞. 基于Delta并联机器人的煤矸石分拣方法研究[D]. 太原: 中北大学, 2022. DONG Huafei. Research on coal gangue sorting method based on Delta parallel robot[D]. Taiyuan: North University of China, 2022.
[5] 张 烨,马宏伟,王 鹏,等. 煤矸石智能分拣机器人研究进展与关键技术[J]. 工矿自动化,2022,48(12):42−48,56. doi: 10.13272/j.issn.1671-251x.2022100048 ZHANG Ye,MA Hongwei,WANG Peng,et al. Research progress and key technologies of intelligent coal-gangue sorting robot[J]. Journal of Mine Automation,2022,48(12):42−48,56. doi: 10.13272/j.issn.1671-251x.2022100048
[6] 王文鑫,黄 杰,王秀宇,等. X射线透射煤矸智能识别方法[J]. 工矿自动化,2022,48(11):27−32,62. WANG Wenxin,HUANG Jie,WANG Xiuyu,et al. X-ray transmission intell igent coal-gangue recognition method[J]. Industry and Mine Automation,2022,48(11):27−32,62.
[7] 司 垒,谭 超,朱嘉皓,等. 基于X射线图像和激光点云的煤矸识别方法[J]. 仪器仪表学报,2022,43(9):193−205. doi: 10.19650/j.cnki.cjsi.J2209683 SI Lei,TAN Chao,ZHU Jiahao,et al. A coal-gangue recognition method based on X-ray image and laser point cloud[J]. Chinese Journal of Scientific Instrument,2022,43(9):193−205. doi: 10.19650/j.cnki.cjsi.J2209683
[8] PICCARDO, H R, HONDERED, G. A new approsch to on-line path planning and generation for robots in non-static environment, [J]. Robotics Autonom Systems, 1991(8): 187-201.
[9] 苏剑波, 冯纯伯. 机器人抓取运动目标的轨迹规划方法[J]. 机器人, 1994(2): 71-76. SU Jianbo, FENG Chunbo. Trajectory planning method of robot grasping moving object[J]. Robot, 1994, (2): 71-76.
[10] 张朝阳. 基于视觉的机器人废金属分拣系统研究[D]. 北京: 中国农业大学. 2015. ZHANG Chaoyang. Research on robot scrap metal sorting robot with machine vision[D]. Beijing: China Agricultural University, 2015.
[11] 曹现刚,李 宁,王 鹏,等. 基于比例导引法的机械臂拣矸过程轨迹规划方法研究[J]. 煤炭工程,2019,51(5):154−158. CAO Xiangang,LI Ning,WANG Peng,et al. Research and simulation on priority and path planning of manipulator gangue picking[J]. Coal Engineering,2019,51(5):154−158.
[12] 李世杰, 左治江, 李 涵. 基于深度学习的机器人抓取系统[J/OL]. 中国测试: 1-10[2022-12-17].http://kns.cnki.net/kcms/detail/51.1714.TB.20221115.1900.005.html LI Shijie, ZUO Zhijiang, LI Han. Design of robot grasping system based on deep learning [J/OL]. China Measurement & Test: 1-10[2022-12-17].http://kns.cnki.net/kcms/detail/51.1714.TB.20221115.1900.005.html
[13] 王 鹏,曹现刚,夏 晶,等. 基于机器视觉的多机械臂煤矸石分拣机器人系统研究[J]. 工矿自动化,2019,45(9):47−53. doi: 10.13272/j.issn.1671-251x.17442 WANG Peng,CAO Xiangang,XIA jing,et al. Research on multi-manipulator coal and gangue sorting robot system based on machine vision[J]. Industry and Mine Automation,2019,45(9):47−53. doi: 10.13272/j.issn.1671-251x.17442
[14] 曹现刚,吴旭东,王 鹏,等. 面向煤矸分拣机器人的多机械臂协同策略[J]. 煤炭学报,2019,44(S2):763−774. doi: 10.13225/j.cnki.jccs.2019.0734 CAO Xiangang,WU Xudong,WANG Peng,et al. Collaborative strategy of multi-manipulator for coal-gangue sorting robot[J]. Journal of China Coal Society,2019,44(S2):763−774. doi: 10.13225/j.cnki.jccs.2019.0734
[15] 黄 贺. 基于点云的散乱堆放棒料位姿识别技术研究[D]. 哈尔滨: 哈尔滨工业大学, 2021. HUANG He. Research on postition and recognition techonlogy of randomly syacked bars based on point clouds[D]. Harbin: Harbin Institute of Technology, 2021.
[16] 王培俊,王文静,陈 鹏,等. 基于OBB算法和前向预防的快速碰撞检测[J]. 西南交通大学学报,2011,46(6):1003−1007. doi: 10.3969/j.issn.0258-2724.2011.06.019 WANG Peijun,WANG Wenjing,CHEN Peng,et al. Rapid collision detection based on OBB algorithm and penetration avoidance mechanism[J]. Journal of Southwest Jiaotong University,2011,46(6):1003−1007. doi: 10.3969/j.issn.0258-2724.2011.06.019
[17] 孙孟寒, 任维政. 基于动态阈值的视频场景切换检测[J]. 计算机系统应用,2023,32(2):234-241. SUN Menghan, REN Weizheng. Video scene switching detection based on dynamic threshold[J]. Computer Systems & Applications,2023,32(2):234-241.
[18] 张 迁, 王 剑, 楚瑞博, 等. 基于BRISK-BEBLID特征的无人机图像快速配准方法[J/OL]. 激光杂志: 1-10[2022-12-18]. http://kns.cnki.net/kcms/detail/50.1085.TN.20221208.1422.009.html. ZHANG Qian, WANG Jian, CHU Ruibo, et al. A fast registration method for UAV images based on BRISK-BEBLID features[J/OL]. Laser Journal: 1-10[2022-12-18]. http://kns.cnki.net/kcms/detail/50.1085.TN.20221208.1422.009.html.
[19] 程 健,闫鹏鹏,郁华森,等. 基于有向线段误匹配剔除的煤矿巷道复杂场景图像拼接方法[J]. 煤炭科学技术,2022,50(9):179−191. doi: 10.13199/j.cnki.cst.2021-0219 CHEN Jian,YAN Pengpeng,YU Huasen,et al. Image stitching method for the complicated scene of coalmine tunnel based on mismatched elimination with directed line segments[J]. Coal Science and Technology,2022,50(9):179−191. doi: 10.13199/j.cnki.cst.2021-0219
[20] 曹现刚, 乔欢乐, 吴旭东, 等. 考虑含矸率时变性的多臂协同策略优化方法[J/OL]. 机械科学与技术: 1-9[2022-12-11].DOI: 10.13433/j.cnki.1003-8728.20220159. CAO Xiangang, QIAO Huanle, WU Xudong, et al. Multi-arm cooperative strategy optimization method considering time variability of gangue rate[J/OL]. Mechanical Science and Technology for Aerospace Engineering : 1-9[2022-12-11].DOI: 10.13433/j.cnki.1003-8728.20220159.
-
期刊类型引用(18)
1. 何琪, 周雨, 钟涛平, 李振雷. 冲击地压煤层大巷保护煤柱合理尺寸研究. 煤炭科技. 2025(03) 
百度学术
2. 刘永立, 王振锁. 基于极限平衡理论的大断面软岩巷道煤柱宽度研究. 黑龙江科技大学学报. 2025(03) 百度学术
3. 罗波远，张涛，安彦成，姚新宇，刘志刚，李树文. 厚煤层大巷保护煤柱合理尺寸优化. 煤炭技术. 2025(01): 48-51 . 百度学术
4. 蔡音飞，刘健松，冀哲，李晓静. 以煤层倾向为参考方向的锐角优化垂线法煤柱设计方法. 矿业安全与环保. 2024(04): 127-132+138 . 百度学术
5. 魏志国，张科星，杨彬. 特厚煤层下山煤柱冲击地压因素分析及防治技术. 山西焦煤科技. 2024(08): 22-26 . 百度学术
6. 吴登超. 钱营孜煤矿W3_211工作面断层防水煤柱合理宽度留设分析. 兰州工业学院学报. 2023(01): 1-5 . 百度学术
7. 牛明星. 厚煤层综放工作面区段煤柱合理留设宽度研究. 山西能源学院学报. 2023(03): 28-30 . 百度学术
8. 韩敬. 东曲煤矿28214工作面区段煤柱留设宽度分析研究. 煤炭与化工. 2023(07): 23-26 . 百度学术
9. 杨永亮，杨森. 基于塑性区演化的煤柱宽度留设及柔性锚索支护技术研究. 中国矿业. 2023(10): 136-143 . 百度学术
10. 杜宗庆，陈东. 皖北孙疃煤矿防砂煤岩柱开采可行性研究. 长春工程学院学报(自然科学版). 2023(04): 1-7 . 百度学术
11. 朱翔斌，杨张杰，程雁斌，丁晶，王庆牛，陈康. 基于煤柱应力实测的沿空掘巷煤柱宽度留设与围岩控制技术. 煤炭工程. 2022(01): 40-44 . 百度学术
12. 周礼杰，陈亮，程志恒，艾国，孔德中，王蕾，王宏冰，郭凯. 突出厚煤层沿空掘巷煤柱留设宽度优化研究. 煤炭科学技术. 2022(03): 92-101 . 本站查看
13. 苏鹏. 厚煤层综放沿空掘巷围岩变形机理研究. 山东煤炭科技. 2022(04): 1-3 . 百度学术
14. 司广宏，王刚，李钢，王洋. 煤巷群受动压扰动范围分析及护巷技术应用. 山西煤炭. 2022(02): 61-67 . 百度学术
15. 王高昂，朱斯陶，姜福兴，李士栋，刘金海，周涛，宁廷洲，李欢，孔震. 高应力厚煤层大巷孤立煤体蠕变失稳冲击机理及防治研究. 岩土工程学报. 2022(09): 1689-1698+9 . 百度学术
16. 张金贵，程志恒，陈昊熠，殷帅峰，陈亮，薛傲. 区段煤柱留设宽度分析及优化——以崖窑峁煤矿为例. 煤炭科学技术. 2022(10): 60-67 . 本站查看
17. 王照明. 小保当一号煤矿巷道稳定性的煤柱留设宽度效应研究. 内蒙古煤炭经济. 2022(24): 52-54 . 百度学术
18. 韩刚，王黔，吕玉磊. 区段煤柱对沿空巷道动力显现影响机制研究. 煤炭科学技术. 2022(S2): 153-159 . 本站查看
其他类型引用(4)
下载:
