基于分步视觉伺服的钻锚机器人控制方法  

Research on step-by-step visual servo control system of anchor drilling robot

作　　者：雷孟宇 张旭辉[1,2] 杨文娟 万继成[1] 杜昱阳 余恒翰 田琛辉 LEI Mengyu;ZHANG Xuhui;YANG Wenjuan;WAN Jicheng;DU Yuyang;YU Henghan;TIAN Chenhui(College of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an 710054,China;Shaanxi Key Laboratory of Intelligent Detection and Control for Mining Electromechanical Equipment,Xi’an 710054,China)

机构地区：[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检测与控制重点实验室,陕西西安710054

出　　处：《煤炭学报》2025年第3期1827-1837,共11页Journal of China Coal Society

基　　金：国家自然科学基金资助项目(52174149,52104166);陕煤联合基金资助项目(2021JLM-03)。

摘　　要：煤矿巷道支护装备的自动化和智能化程度不足,严重阻碍了煤矿巷道成形效率的提升,成为造成“采掘失衡”现象的关键因素之一。为解决煤矿巷道支护装备自动化程度低、支护效率差的难题,设计了一种集成悬臂式掘进机和多自由度机械臂的钻锚机器人,提出了基于分步视觉伺服的钻锚机器人控制方法。首先提出了基于双目视觉的锚钻孔空间定位方法,利用三角原理实现锚钻孔精确定位;其次,通过机械臂关节布置的位移传感器和角度传感器检测对应关节的移动距离和旋转角度,利用改进的Denavit-Hartenberg(MDH)方法构建钻锚机器人机械臂运动学模型,实现机械臂末端执行器空间位置解算,确定末端执行器初始位置和目标位置;然后,提出一种基于分步视觉伺服的钻锚机器人机械臂运动控制方法,利用末端执行器位置构建基于位置的视觉控制模型,控制机械臂接近目标锚钻孔,实现机械臂的粗略控制;以锚钻孔外切矩形4个顶点的图像坐标为特征点,建立特征点运动速度与机械臂关节运动速度的映射关系,构建基于图像的视觉伺服控制模型,控制末端执行器快速精确对准目标锚钻孔中心,实现机械臂的精确控制;最后,搭建钻锚机器人实验平台,在实验室环境下完成锚钻孔视觉定位与机械臂视觉伺服控制仿真及实验。结果表明:提出的锚钻孔定位方法在X、Y和Z3个方向定位平均误差分别为7.5、7.8、8.1mm;提出的分步视觉伺服控制方法能够实现机械臂的粗略和精确控制,末端执行器可以快速精确到达目标锚钻孔目标位置。基于分步视觉伺服的钻锚机器人控制方法能够有效提升支护系统的自动化程度,为巷道支护的减人提效奠定了良好基础。The insufficient automation and intelligentization of coal mine roadway support equipment has severely hindered the improvement of roadway formation efficiency,emerging as one of the critical factors contributing to the im-balance of excavation and support.To address the challenges of low automation levels and poor support efficiency in ex-isting roadway support systems,this study has developed an anchor drilling robot integrating a boom-type roadheader with a multi-degree-of-freedom manipulator,proposing a step-by-step visual servo-based control methodology.Firstly,a bin-ocular vision-based spatial positioning method for drilling holes was established utilizing triangulation principles to achieve precise hole localization.Secondly,through displacement and angular sensors deployed on manipulator joints,this study constructed an enhanced kinematic model using the modified Denavit-Hartenberg(MDH)method,enabling accur-ate spatial position resolution of the end-effector and determination of its initial and target positions.Thirdly,a novel step-by-step visual servo control strategy was developed:a position-based visual control model governs the manipulator's coarse positioning near target holes,followed by an image-based visual servo model that establishes mapping relation-ships between feature point velocities(derived from circumscribed rectangle vertices of drilling holes)and joint velocities,enabling precise centering alignment.Finally,an experimental platform was established to validate the proposed methods under laboratory conditions.Test results demonstrate average positioning errors of 7.5,7.8,and 8.1 mm in X,Y,and Z axes respectively,with the step-by-step control approach successfully achieving both coarse positioning and fine alignment.This research significantly enhances the automation level of support systems,laying a technical foundation for workforce reduction and efficiency improvement in roadway support operations.

关 键 词：钻锚机器人 视觉定位 位置视觉控制 图像视觉伺服控制 锚钻孔 

分 类 号：TD421.5[矿业工程—矿山机电]