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A self-centering active probing technique for kinematic parameter identification and verification of articulated arm coordinate measuring machines

机译:一种自定心主动探测技术,用于关节臂坐标测量机的运动学参数识别和验证

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摘要

A crucial task in the procedure of identifying the parameters of a kinematic model of an articulated arm coordinate measuring machine (AACMM) or robot arm is the process of capturing data. In this paper a capturing data method is analyzed using a self-centering active probe, which drastically reduces the capture time and the required number of positions of the gauge as compared to the usual standard and manufacturer methods. The mathematical models of the self-centering active probe and AACMM are explained, as well as the mathematical model that links the AACMM global reference system to the probe reference system. We present a self-calibration method that will allow us to determine a homogeneous transformation matrix that relates the probe's reference system to the AACMM last reference system from the probing of a single sphere. In addition, a comparison between a self-centering passive probe and self-centering active probe is carried out to show the advantages of the latter in the procedures of kinematic parameter identification and verification of the AACMM.
机译:识别关节臂坐标测量机(AACMM)或机器人手臂的运动模型参数的过程中的关键任务是捕获数据的过程。在本文中,使用自对中有源探头对捕获数据方法进行了分析,与常规的标准方法和制造商方法相比,该方法大大减少了捕获时间并减少了所需的量规位置。解释了自动定心有源探头和AACMM的数学模型,以及将AACMM全局参考系统链接到探头参考系统的数学模型。我们提出了一种自校准方法,该方法将使我们能够确定均匀转换矩阵,该矩阵将探针的参考系统与AACMM最后的参考系统从单个球体的探测关联起来。此外,对自对中无源探头和自对中有源探头进行了比较,以显示后者在运动参数识别和AACMM验证过程中的优势。

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