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A Normal Sensor Calibration Method Based on an Extended Kalman Filter for Robotic Drilling

机译：基于扩展卡尔曼滤波的机器人钻井常规传感器标定方法

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摘要

To enhance the perpendicularity accuracy in the robotic drilling system, a normal sensor calibration method is proposed to identify the errors of the zero point and laser beam direction of laser displacement sensors simultaneously. The procedure of normal adjustment of the robotic drilling system is introduced firstly. Next the measurement model of the zero point and laser beam direction on a datum plane is constructed based on the principle of the distance measurement for laser displacement sensors. An extended Kalman filter algorithm is used to identify the sensor errors. Then the surface normal measurement and attitude adjustments are presented to ensure that the axis of the drill bit coincides with the normal at drilling point. Finally, simulations are conducted to study the performance of the proposed calibration method and experiments are carried out on a robotic drilling system. The simulation and experimental results show that the perpendicularity of the hole is within 0.2°. They also demonstrate that the proposed calibration method has high accuracy of parameter identification and lays a basis for high-precision perpendicularity accuracy of drilling in the robotic drilling system.
机译：为了提高机器人钻孔系统的垂直精度，提出了一种常规的传感器标定方法来同时识别激光位移传感器的零点误差和激光束方向。首先介绍了机器人钻孔系统的正常调整过程。接下来，根据激光位移传感器的距离测量原理，建立基准面上的零点和激光束方向的测量模型。扩展的卡尔曼滤波算法用于识别传感器错误。然后进行表面法线测量和姿态调整，以确保钻头的轴线与钻点的法线重合。最后，进行仿真以研究所提出的校准方法的性能，并在机器人钻孔系统上进行了实验。仿真和实验结果表明，孔的垂直度在0.2°以内。他们还证明了所提出的校准方法具有很高的参数识别精度，并为机器人钻孔系统中的高精度钻孔垂直度奠定了基础。

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