综掘工作面设备智能化程度是制约煤矿智能化发展的主要原因，而巷道锚固支护效率低是其中的关键因素，巷道锚固支护自动化控制是实现煤矿巷道掘进智能化、无人化的主要环节。钻锚机器人一定程度上可以自主完成钻孔与锚固作业，降低工人劳动强度，可有效提高巷道支护效率，为综掘工作面的智能化、少人化甚至无人化掘进奠定基础。针对煤矿井下高粉尘、低照度的复杂工况，论文提出一种粉尘浓度相关的位姿视觉测量方法与两机械臂协同控制策略，利用单目视觉测量技术得到巷道坐标系下设备位姿，基于双目视觉测量模型获得钻孔相对于机身坐标的位姿，在此基础上研究钻锚机器人协同控制策略，实现钻锚机器人机身精确定位、钻孔精确定位及钻锚机器人自动化控制。

针对钻锚机器人运动学求解问题，根据多自由度钻锚机器人系统结构，论文利用D-H法建立钻锚机器人机械臂连杆坐标系，得到相邻关节之间的坐标转换关系，通过钻锚机器人运动学分析得到其运动学正解和运动学逆解。在此基础上，利用蒙特卡洛法对钻锚机器人机械臂的工作空间进行分析，并采用三次样条插值算法对机械臂的运动轨迹进行规划。

针对煤矿井下复杂工况环境中设备定位难的问题，提出一种自适应粉尘浓度的钻锚机器人机身位姿测量方法。通过研究掘进工作面粉尘扩散机理，建立粉尘浓度与激光光斑灰度值的关系模型，采用单目视觉测量技术，建立其机身测量坐标系，以红外激光指向仪的点-线为特征，构建基于“门型三线”的机身位姿解算模型，通过防爆相机采集图像并经过一系列图像处理算法，获得巷道坐标系下设备的位姿信息。

针对煤矿井下钻孔定位难的问题，提出一种基于双目立体视觉的钻孔定位方法。采用双目立体视觉测量技术，以钢带孔作为目标特征，利用安装在钻臂上的双目相机采集钢带孔图像并对图像进行边缘检测与椭圆拟合处理，得到钻孔相对于双目相机坐标系的位姿信息。最后，根据系统测量坐标系之间的关系，获取钻孔相对于机身的位姿信息。

针对综掘工作面支护与锚固效率不高导致智能化程度低、采掘失衡问题，提出一种钻锚机器人多机械臂协同控制方法。通过研究钻孔与锚固工艺流程、作业质量要求以及各系统之间的关系，提出钻锚机器人多臂协同控制策略，并针对该策略建立钻锚机器人协同控制系统模型。构建了钻锚机器人末端执行器与钢带孔之间的位姿误差模型，并设计了基于滑模变结构的控制器，完成钻锚机器人自动钻孔、找孔，最终实现钻锚机器人协同控制。

最后，设计钻锚机器人上位机软件，实现数据采集、图像处理、位姿解算以及协同控制等功能，在实验室针对各模块搭建实验平台进行功能验证以及性能测试。实验结果表明论文提出的钻锚机器人视觉定位方法及多臂协同控制策略均达到了设计要求，粉尘浓度相关的钻锚机器人机身位姿测量方法和基于双目视觉的钻孔位姿测量方法可以保障协同控制系统的控制精度，并有效提升钻孔与锚固效率，实现了钻锚机器人自动化控制。

The intelligent degree of equipment in fully mechanized mining face is the main reason for restricting the development of intelligent coal mine, and the low efficiency of roadway anchorage support is one of the key factors. The automatic control of roadway anchorage support is the main link to realize the intelligent and unmanned coal mine roadway excavation. To a certain extent, the drilling and anchoring robot can independently complete the drilling and anchoring operation, reduce the labor intensity of workers, effectively improve the efficiency of roadway support, and lay the foundation for the intelligent, unmanned and even unmanned tunneling of fully mechanized mining face. In view of the complex working conditions of high dust and low illumination in underground coal mines, this paper proposes a visual measurement method of dust concentration-related pose and a cooperative control strategy of two manipulators. The monocular vision measurement technology is used to obtain the pose of the equipment in the roadway coordinate system. Based on the binocular vision measurement model, the pose of the borehole relative to the fuselage coordinate is obtained. On this basis, the cooperative control strategy of the drilling and anchor robot is studied to achieve the precise positioning of the fuselage, the precise positioning of the borehole and the automatic control of the drilling and anchor robot.

Aiming at the kinematics problem of the drilling and anchoring robot, according to the structure of the multi-degree-of-freedom drilling and anchoring robot system, this paper uses the D-H method to establish the connecting rod coordinate system of the manipulator of the drilling and anchoring robot, and obtains the coordinate transformation relationship between adjacent joints. Through the kinematics analysis of the drilling and anchoring robot, the positive and inverse kinematics solutions are obtained. On this basis, the workspace of the drilling and anchoring robot manipulator is analyzed by Monte Carlo method, and the cubic spline interpolation algorithm is used to plan the trajectory of the manipulator.

Aiming at the problem of difficult equipment positioning in complex working conditions of coal mine, an adaptive dust concentration measurement method of drilling and anchoring robot body posture is proposed. By studying the dust diffusion mechanism of heading face, the relationship model between dust concentration and the gray value of laser spot was established. The monocular vision measurement technology was used to establish the fuselage measurement coordinate system. Taking the point-line of infrared laser pointer as the feature, the fuselage pose calculation model based on the “ gate type three lines ” was constructed. The image was collected by the explosion-proof camera and the pose information of the equipment in the roadway coordinate system was obtained through a series of image processing algorithms.

Aiming at the problem of difficult drilling positioning in coal mine, a drilling positioning method based on binocular stereo vision is proposed. Using binocular stereo vision measurement technology, the steel strip hole is taken as the target feature, and the binocular camera installed on the drilling arm is used to collect the steel strip hole image. The edge detection and ellipse fitting of the image are carried out to obtain the pose information of the borehole relative to the binocular camera coordinate system. Finally, according to the relationship between the measurement coordinate system of the system, the pose information of the borehole relative to the fuselage is obtained.

Aiming at the problems of low intelligence and unbalanced mining caused by low support and anchoring efficiency of fully mechanized working face, a cooperative control method of multi-arms of drilling and anchoring robot is proposed. By studying the process flow of drilling and anchoring, operation quality requirements and the relationship between each system, the multi-arm cooperative control strategy of drilling and anchoring robot is proposed, and the cooperative control system model of drilling and anchoring robot is established for this strategy. The pose error model between the end actuator of the drilling and anchoring robot and the steel strip hole is constructed, and the controller based on the sliding film variable structure is designed to complete the automatic drilling and hole finding of the drilling and anchoring robot, and finally realize the cooperative control of the drilling and anchoring robot.

Finally, the host computer software of the drilling and anchor robot is designed to realize the functions of data acquisition, image processing, pose calculation and collaborative control. The experimental platform for each module is built in the laboratory for functional verification and performance test. The experimental results show that the visual positioning method and multi-arm cooperative control strategy of the drilling and anchoring robot proposed in this paper meet the design requirements. The pose measurement method of the drilling and anchoring robot body related to dust concentration and the borehole pose measurement method based on binocular vision can ensure the control accuracy of the cooperative control system, effectively improve the efficiency of drilling and anchoring, and realize the automatic control of the drilling and anchoring robot.

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