煤矿用钻孔机器人钻臂定位误差补偿研究

Positioning error compensation of drilling robot arm for coal mine

  • 摘要: 目前钻孔机器人位姿调节多采用手动遥控调节与人工复测结合,未实现全自动调节,开环控制精度低、自动化能力低、无法实现煤矿用探放水、防突和防冲钻孔机器人精确开孔定位与孔群全自动施工。通过分析钻孔机器人钻臂结构和动作,建立了钻臂运动学模型;通过对加工误差、机身变形、装配间隙等影响因素分析,发现采用回转减速器蜗轮蜗杆结构间隙会引起倾角和方位角误差放大,并在机身平时会引起倾角和方位角误差最大达0.85°;为消除误差,首先采用传统钻臂运动学误差补偿方法建立了钻臂静、动态误差补偿模型,利用全站仪测试关节间隙和变形量,基于补偿模型和RBF神经网络法求逆解得到误差补偿量,钻臂期望位姿与实际位姿误差的x方向平均误差为9.6 mm,y方向平均误差为18.2 mm,z方向平均误差为16 mm,满足工程应用要求;其次为解决传统全站仪试验测量的方法的复杂性和非实时性问题,提出了一种通过激光测距仪和高精度开孔定向仪组合获得位姿误差检测的方法,通过测距实时计算实际和理论倾角、方位角差值,作为误差补偿后的新倾角和方位角的控制输入量,对钻臂进行实时误差检测与补偿;最后利用传统全站仪精度检测方法对激光测距组合位姿误差补偿模型进行验证。试验表明:激光测距组合定位误差检测法最大误差差值在±0.5°以内,方位角最大误差在±0.5°以内,比未采用误差补偿前分别提高了41.1%和37.5%,满足了钻孔机器人开孔定位误差要求。在煤炭行业开展了钻孔机器人钻臂在线精确定位与误差补偿研究,对钻孔机器人精确自动开孔定位及孔群全自动施工具有重要的借鉴和指导意义。

     

    Abstract: At present, the pose of drilling robots is mostly adjusted by manual remote control and manual retest in combination. Full automatic adjustment has not been achieved. Besides, due to the low precision of open-loop control and inadequate automation capability, the accurate hole positioning and automatic construction of hole groups cannot be realized by drilling robots with water exploration and discharge, outburst prevention and punching prevention in coal mines. Herein, the kinematic model of drilling arm was established by analyzing the structure and action of the drilling robot’s drilling arm. Meanwhile, the dip angle factors such as machining error, body deformation and assembly clearance were analyzed. It is found that the dip angle and azimuth error will be enlarged because of the structure clearance of worm gear of the rotary reducer, which may be up to 0.85° in the body. Firstly, in order to eliminate the errors, the static and dynamic error compensation model of the drilling arm was established using the traditional kinematics error compensation method of the drilling arm. Besides, the joint clearance and deformation were measured by a total station. Then, the error compensation was obtained by inverse solution based on the compensation model and RBF neural network method. The average error between the expected and the actual pose of drilling arm is 9.6 mm in x direction, 18.2 mm in y direction, and 16 mm in z direction, which meets the requirements of engineering application. Secondly, in order to solve the complexity and non-real-time problems of the traditional test measurement method by a total station, a method to detect the pose error with the laser rangefinder and the high-precision open-hole orienteer in combination was proposed. Thereby, the difference between the actual and theoretical dip angle and azimuth were calculated in real time through ranging, which was used as the control input of the new dip angle and azimuth after error compensation for the real-time error detection and compensation of drilling arm. Finally, the pose error compensation model of laser ranging combination was verified using the traditional total station accuracy detection method. The test shows that: The maximum error difference and the maximum azimuth error obtained by the positioning error detection method of laser ranging combination are within ±0.5° and within ±0.5°, respectively, which are 41.1% and 37.5% higher than that before error compensation, meeting the requirements of drilling robot opening hole positioning error. In this paper, research was firstly carried out on the online accurate positioning and error compensation of the drilling robot’s drilling arm in coal industry, which has important reference and guiding significance for the accurate automatic hole positioning of drilling robots and the automatic construction of hole group.

     

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