![](/images/graphics-bg.png)
An ANN-Based Precision Compensation Method for Industrial Manipulators via Optimization of Point Selection
Joint Authors
Chen, Zhangwei
Mao, Chentao
Wang, Zhirong
Zhang, Xiang
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-20
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Industrial manipulators are widely used in the manufacture of products due to their high flexibility and low costs.
High absolute positioning accuracy is the key to guarantee the product quality, which is commonly improved through the error compensation technology.
Due to the variety, complexity, and unpredictability of the error sources, the influence of the nongeometric errors on the absolute positioning accuracy of manipulators is uncertain.
In result, the existing error compensation methods are difficult to obtain satisfying results, especially for manipulators with large joint flexibility that need to work in different task scenarios.
In this paper, an artificial neural network- (ANN-) based precision compensation method via optimization of point selection is proposed, which deals with the kinematic errors and joint stiffness errors in different task scenarios.
Firstly, the quasi-random sequence (QRS) method and the product of exponentials (POE) model are combined to identify and compensate the geometric parameters.
The QRS method can select points evenly in the workspace.
And the POE model can avoid the singularity problem of Denavit–Hartenberg (DH) model.
Secondly, a continuous joint stiffness compensation model in the whole workspace is established through ANN.
In order to get better compensation results for the current task scenario, the point selection method based on trajectory similarity is adopted to determine the training data of ANN.
Finally, the experiments are conducted on a 6-DOF industrial manipulator to demonstrate the validity of the proposed method.
The results show that the ANN-based method via optimization of point selection could be an effective solution for the precision compensation.
American Psychological Association (APA)
Wang, Zhirong& Chen, Zhangwei& Mao, Chentao& Zhang, Xiang. 2020. An ANN-Based Precision Compensation Method for Industrial Manipulators via Optimization of Point Selection. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1201956
Modern Language Association (MLA)
Wang, Zhirong…[et al.]. An ANN-Based Precision Compensation Method for Industrial Manipulators via Optimization of Point Selection. Mathematical Problems in Engineering No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1201956
American Medical Association (AMA)
Wang, Zhirong& Chen, Zhangwei& Mao, Chentao& Zhang, Xiang. An ANN-Based Precision Compensation Method for Industrial Manipulators via Optimization of Point Selection. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1201956
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201956