Prediction of the eigenfrequency of industrial robots based on the ANN model

Wu, Kai; Li, Jiaquan

doi:10.1109/cac53003.2021.9728068

2021 China Automation Congress (CAC) 2021

DOI: 10.1109/cac53003.2021.9728068

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Prediction of the eigenfrequency of industrial robots based on the ANN model

Kai Wu

Jiaquan Li

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Review of Industrial Robot Stiffness Identification and Modelling

Zhao

et al. 2022

Applied Sciences

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Due to their high flexibility, large workspace, and high repeatability, industrial robots are widely used in roughing and semifinishing fields. However, their low machining accuracy and low stability limit further development of industrial robots in the machining field, with low stiffness being the most significant factor. The stiffness of industrial robots is affected by the joint deformation, transmission mechanism, friction, environment, and coupling of these factors. Moreover, the stiffness of a robot has a nonlinear distribution throughout the workspace, and external forces during processing cause irregular deviations of the robot, thereby affecting the machining accuracy and surface quality of the workpiece. Many scholars have researched identifying the stiffness of industrial robots and have proposed methods for improving the performance of industrial robots, mainly by optimizing the body structure of the robot and compensating for deformation errors with stiffness models. This paper reviews recent research on the stiffness modelling of industrial robots, which can be broadly classified as finite element analysis (FEA), matrix structure analysis (MSA), and virtual joint modelling (VJM) methods. Each method is studied from three aspects: algorithms, implementation, and limitations. In addition, common measurement techniques have been introduced for measuring deformation. Further research directions are also discussed.

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Review of Industrial Robot Stiffness Identification and Modelling

Zhao

et al. 2022

Applied Sciences

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Prediction of the eigenfrequency of industrial robots based on the ANN model

Cited by 1 publication

References 16 publications

Review of Industrial Robot Stiffness Identification and Modelling

Review of Industrial Robot Stiffness Identification and Modelling

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