基于视觉测量的快速掘进机器人纠偏控制研究

张旭辉, 周创, 张超, 谢楠, 张楷鑫, 刘博兴

张旭辉，周创，张超，等.基于视觉测量的快速掘进机器人纠偏控制研究［J］.工矿自动化，2020,46（9）：21-26.. DOI: 10.13272/j.issn.1671-251x.17639
引用本文: 张旭辉，周创，张超，等.基于视觉测量的快速掘进机器人纠偏控制研究［J］.工矿自动化，2020,46（9）：21-26.. DOI: 10.13272/j.issn.1671-251x.17639
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ZHANG Xuhui, ZHOU Chuang, ZHANG Chao, XIE Nan, ZHANG Kaixin, LIU Boxing. Research on deviation correction control of rapid tunneling robot based on vision measurement[J]. Journal of Mine Automation, 2020, 46(9): 21-26. DOI: 10.13272/j.issn.1671-251x.17639
Citation: ZHANG Xuhui, ZHOU Chuang, ZHANG Chao, XIE Nan, ZHANG Kaixin, LIU Boxing. Research on deviation correction control of rapid tunneling robot based on vision measurement[J]. Journal of Mine Automation, 2020, 46(9): 21-26. DOI: 10.13272/j.issn.1671-251x.17639
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基于视觉测量的快速掘进机器人纠偏控制研究

  • 1.

    西安科技大学 机械工程学院， 陕西 西安710054

  • 2.

    陕西省矿山机电装备智能监测重点实验室， 陕西 西安710054

基金项目: 

国家自然科学基金项目（51974228）

陕西省创新能力支撑计划项目(2018TD-032)

陕西省重点研发计划项目(2018ZDCXL-GY-06-04)

详细信息

  • 中图分类号: TD632

Research on deviation correction control of rapid tunneling robot based on vision measurement

  • 1.

    College of Mechanical Engineering， Xi''an University of Science and Technology， Xi''an 710054, China；2.Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligence Monitoring，Xi''an 710054, China

摘要

    摘要
  • 摘要: 针对在煤矿井下高粉尘、低照度环境中，掘进机器人定位与控制精度不高的问题，设计了一种基于视觉测量的快速掘进机器人纠偏控制系统。利用安装在快速掘进机器人上的防爆相机，对后方的激光指向仪进行图像采集，通过以太网将采集的图像信息传输给防爆计算机；利用防爆计算机对图像进行预处理，根据位姿解算模型解算出快速掘进机器人位姿；将解算出的位姿信息与巷道设计轴线信息进行比较，计算出快速掘进机器人位姿与巷道设计轴线间的位姿偏差；根据位姿偏差的类型与大小，采用不同的控制策略计算出修正后的控制量，并输出控制指令；控制指令控制电磁比例阀的阀芯移动，实现对伸缩油缸的控制，根据各区域伸缩油缸的伸缩量不同，对快速掘进机器人进行位姿调整，实现纠偏控制。实验结果表明：位姿视觉测量精度为X方向平均偏差21.334 mm，Y方向平均偏差34.154 mm，偏航角平均偏差为0.493°；纠偏控制精度在X方向小于30 mm，满足实际工况要求。
    Abstract: Aiming at problems of insufficient positioning and control accuracy of tunneling robot in environment with high dust and low illumination of coal mine, a deviation correction control system of rapid tunneling robot based on vision measurement is designed. The explosion-proof camera installed on rapid tunneling robot is used to collect image of laser pointing instrument at the rear, and the collected image information is transmitted to explosion-proof computer through Ethernet. The explosion-proof computer is used to preprocess the image and then the pose of the rapid tunneling robot is calculated according to pose calculation model. The calculated pose information is compared with designed roadway axis information, and the pose deviation between the pose of the rapid tunneling robot and the roadway design axis is calculated. According to type and size of the pose deviation, different control strategies are adopted to calculate corrected control quantity and control instructions are output. The control command controls spool movement of solenoid proportional valve to control telescopic oil cylinder. According to the different expansion amount of the telescopic cylinder in each area, the pose of the rapid tunneling robot is adjusted to realize deviation correction control. The experimental results show that the average deviation of vision meosurement accuracy in X direction is 21.334 mm, that in Y direction is 34.154 mm, that of yaw angle is 0.493 ° and the error of deviation correction control in X direction is less than 30 mm, which meets requirements of actual working conditions.
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  • 刊出日期:  2020-08-19

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