Evolutionary Robot Calibration and Nonlinear Compensation Methodology Based on GA-DNN and an Extra Compliance Error Model
Joint Authors
Zhang, Qiuju
Chen, Xiaoyan
Sun, Yilin
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-14
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
This study addresses the problem of nonlinear error predictive compensation to achieve high positioning accuracy for advanced industrial applications.
An improved calibration method based on the generalisation performance evaluation is proposed to enhance the stability and accuracy of robot calibration.
With the development of technology, a deep neural network (DNN) optimised by a genetic algorithm (GA) is applied to predict the nonlinear error of the calibrated robot.
To address the change of external payload, an extra compliance error model is established with a linear piecewise method.
A global compensation method combining the GA-DNN nonlinear regression prediction model and the compliance error model is then proposed to achieve the robot’s high-precision positioning performance under any external payload.
Experimental results obtained on a Staubli RX160L robot with a FARO laser tracker are introduced to demonstrate the effectiveness and benefits of our proposed methodology.
The enhanced positioning accuracy can reach 0.22 mm with 98% probability (i.e., the maximum positioning error in all test data).
American Psychological Association (APA)
Chen, Xiaoyan& Zhang, Qiuju& Sun, Yilin. 2020. Evolutionary Robot Calibration and Nonlinear Compensation Methodology Based on GA-DNN and an Extra Compliance Error Model. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1194845
Modern Language Association (MLA)
Chen, Xiaoyan…[et al.]. Evolutionary Robot Calibration and Nonlinear Compensation Methodology Based on GA-DNN and an Extra Compliance Error Model. Mathematical Problems in Engineering No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1194845
American Medical Association (AMA)
Chen, Xiaoyan& Zhang, Qiuju& Sun, Yilin. Evolutionary Robot Calibration and Nonlinear Compensation Methodology Based on GA-DNN and an Extra Compliance Error Model. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1194845
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194845