Purpose

This paper aims to propose a measurement principle and a calibration method of measurement system integrated with serial robot and 3D camera to identify its parameters conveniently and achieve high measurement accuracy.

Design/methodology/approach

A stiffness and kinematic measurement principle of the integrated system is proposed, which considers the influence of robot weight and load weight on measurement accuracy. Then an error model is derived based on the principle that the coordinate of sphere center is invariant, which can simultaneously identify the parameters of joint stiffness, kinematic and hand-eye relationship. Further, considering the errors of the parameters to be calibrated and the measurement error of 3D camera, a method to generate calibration observation data is proposed to validate both calibration accuracy and parameter identification accuracy of calibration method.

Findings

Comparative simulations and experiments of conventional kinematic calibration method and the stiffness and kinematic calibration method proposed in this paper are conducted. The results of the simulations show that the proposed method is more accurate, and the identified values of angle parameters in modified Denavit and Hartenberg model are closer to their real values. Compared with the conventional calibration method in experiments, the proposed method decreases the maximum and mean errors by 19.9% and 13.4%, respectively.

Originality/value

A new measurement principle and a novel calibration method are proposed. The proposed method can simultaneously identify joint stiffness, kinematic and hand-eye parameters and obtain not only higher measurement accuracy but also higher parameter identification accuracy, which is suitable for on-site calibration.

中文翻译：

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串行机器人和3D相机集成测量系统的关节刚度、运动学和手眼参数的同时识别

目的

本文旨在提出一种串行机器人和3D相机集成的测量系统的测量原理和标定方法，以方便地识别其参数并实现较高的测量精度。

设计/方法/方法

提出了集成系统的刚度和运动学测量原理，考虑了机器人重量和负载重量对测量精度的影响。然后根据球心坐标不变的原理推导出一个误差模型，该模型可以同时识别关节刚度、运动学和手眼关系等参数。进一步考虑待标定参数的误差和3D相机的测量误差，提出一种标定观测数据的生成方法，以验证标定方法的标定精度和参数识别精度。

发现

对传统的运动学标定方法与本文提出的刚度和运动学标定方法进行了对比仿真和实验。仿真结果表明，该方法更加准确，修正后的Denavit和Hartenberg模型中角度参数的识别值更接近真实值。与传统的实验校准方法相比，该方法的最大误差和平均误差分别降低了19.9%和13.4%。

原创性/价值

提出了一种新的测量原理和一种新的校准方法。该方法可以同时识别关节刚度、运动学和手眼参数，不仅获得更高的测量精度，而且获得更高的参数识别精度，适用于现场标定。