Stiffness identification system and identification method of industrial robot based on six-dimensional virtual joint model

Abstract

The invention discloses an industrial robot stiffness identification system and an identification method based on a six-dimensional virtual joint model. The system includes an industrial robot, a load force loading device and a laser tracker; The device consists of a mounting plate and four hollow columns; each hollow column is provided with two force loading points, and each force loading point is equipped with a force loading direction converter, a lasso and a weight. mechanism; the load force loading device has eight force loading mechanisms that can apply loads at the end of the industrial robot in multiple positions, so that the measurement data can fully reflect the stiffness change of the robot, which is more conducive to the identification of the stiffness parameters of the industrial robot. The identification method of the present invention The stiffness error model of the industrial robot is established based on the six-dimensional virtual joint model, which can completely describe the stiffness characteristics of the industrial robot and effectively improve the positioning accuracy of the end of the industrial robot.

Description

technical field [0001] The invention relates to the technical field of industrial robot parameter calibration, in particular to an industrial robot stiffness identification system and an identification method based on a six-dimensional virtual joint model. Background technique [0002] As the focus of the development of high-end manufacturing industry, industrial robots have become an important symbol to measure the level of scientific and technological innovation of a country. With the rapid development of robot technology, the application fields of industrial robots are also expanding, such as hole making and riveting in the aerospace industry. These applications have higher and higher precision requirements for industrial robots. The absolute positioning error of industrial robots is mainly divided into geometric parameter errors and non-geometric parameter errors, of which geometric parameter errors account for about 90% of the total error, such errors can be compensated...

AI Technical Summary

Problems solved by technology

At present, the joint stiffness error models for industrial robots mainly include the stiffness model based on the assumption of joint flexible rotation deformation and the supplementary stiffness model based on the assumption of joint flexible rotation deformation. Due to flexibility, there is only compliance deformation along the direction of joint rotation, while ignoring robot assembly deformation, connecting rod deformation, and stiffness parameters in other dimensions. When the load at the end of the robot is large, it may still lead to large positioning errors.

At present, the static load method of the robot is often used to identify the stiffness of industrial robots, but the identification system has problems such as the complexity of the implementation of the stiffness identification experiment, especially when the load on the end of the flange plate of the robot is less, and the measurement data cannot fully reflect the stiffness change of the industrial robot. It will lead to low identification accuracy of industrial robot stiffness parameters, which will directly affect the control accuracy and control performance of industrial robots

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