Estimation of External Force-Torque Vector Based on Double Encoders of Industrial Robots Using a Hybrid Gaussian Process Regression and Joint Stiffness Model

Industrial robots are increasingly used in industry for contact-based manufacturing processes such as milling and forming. In order to meet part tolerances, it is mandatory to compensate tool deflections caused by the external force-torque vector. However, using a third-party measuring device for se...

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Main Authors: Eckart Uhlmann, Mitchel Polte, Julian Blumberg
Format: Article
Language:English
Published: Publishing House of Wrocław Board of Scientific Technical Societies Federation NOT 2023-06-01
Series:Journal of Machine Engineering
Subjects:
Online Access:http://jmacheng.not.pl/Estimation-of-External-Force-Torque-Vector-Based-on-Double-Encoders-of-Industrial,167359,0,2.html
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author Eckart Uhlmann
Mitchel Polte
Julian Blumberg
author_facet Eckart Uhlmann
Mitchel Polte
Julian Blumberg
author_sort Eckart Uhlmann
collection DOAJ
description Industrial robots are increasingly used in industry for contact-based manufacturing processes such as milling and forming. In order to meet part tolerances, it is mandatory to compensate tool deflections caused by the external force-torque vector. However, using a third-party measuring device for sensing the external force-torque vector lowers the cost efficiency. Novel industrial robots are increasingly equipped with double encoders, in order to compensate deviations caused by the gearboxes. This paper proposes a method for the usage of such double encoders to estimate the external force-torque vector acting at the tool centre point of an industrial robot. Therefore, the joint elasticities of a six revolute joint industrial robot are identified in terms of piecewise linear functions based on the angular deviations at the double encoders when an external force-torque vector is applied. Further, initial deviations between the encoder values caused by gravitational forces and friction are modelled with a Gaussian process regression. Combining both methods to a hybrid model enables the estimation of external force-torque vectors solely based on measurements of the joint angles of secondary encoders. Based on the proposed method, additional measurement equipment can be saved, which reduces investment costs and improves robot dynamics.
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language English
publishDate 2023-06-01
publisher Publishing House of Wrocław Board of Scientific Technical Societies Federation NOT
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spelling doaj-art-844678ffcfc447c2b4b9f8e450e751b42025-08-20T02:56:27ZengPublishing House of Wrocław Board of Scientific Technical Societies Federation NOTJournal of Machine Engineering1895-75952391-80712023-06-01233566810.36897/jme/167359167359Estimation of External Force-Torque Vector Based on Double Encoders of Industrial Robots Using a Hybrid Gaussian Process Regression and Joint Stiffness ModelEckart Uhlmann0Mitchel Polte1Julian Blumberg2Machine Tool Technology, Institute for Machine Tools and Factory Management, GermanyMachine Tool Technology, Institute for Machine Tools and Factory Management, GermanyMachine Tool Technology, Institute for Machine Tools and Factory Management, GermanyIndustrial robots are increasingly used in industry for contact-based manufacturing processes such as milling and forming. In order to meet part tolerances, it is mandatory to compensate tool deflections caused by the external force-torque vector. However, using a third-party measuring device for sensing the external force-torque vector lowers the cost efficiency. Novel industrial robots are increasingly equipped with double encoders, in order to compensate deviations caused by the gearboxes. This paper proposes a method for the usage of such double encoders to estimate the external force-torque vector acting at the tool centre point of an industrial robot. Therefore, the joint elasticities of a six revolute joint industrial robot are identified in terms of piecewise linear functions based on the angular deviations at the double encoders when an external force-torque vector is applied. Further, initial deviations between the encoder values caused by gravitational forces and friction are modelled with a Gaussian process regression. Combining both methods to a hybrid model enables the estimation of external force-torque vectors solely based on measurements of the joint angles of secondary encoders. Based on the proposed method, additional measurement equipment can be saved, which reduces investment costs and improves robot dynamics.http://jmacheng.not.pl/Estimation-of-External-Force-Torque-Vector-Based-on-Double-Encoders-of-Industrial,167359,0,2.htmlindustrial robotsdouble encodersforce-torque estimation
spellingShingle Eckart Uhlmann
Mitchel Polte
Julian Blumberg
Estimation of External Force-Torque Vector Based on Double Encoders of Industrial Robots Using a Hybrid Gaussian Process Regression and Joint Stiffness Model
Journal of Machine Engineering
industrial robots
double encoders
force-torque estimation
title Estimation of External Force-Torque Vector Based on Double Encoders of Industrial Robots Using a Hybrid Gaussian Process Regression and Joint Stiffness Model
title_full Estimation of External Force-Torque Vector Based on Double Encoders of Industrial Robots Using a Hybrid Gaussian Process Regression and Joint Stiffness Model
title_fullStr Estimation of External Force-Torque Vector Based on Double Encoders of Industrial Robots Using a Hybrid Gaussian Process Regression and Joint Stiffness Model
title_full_unstemmed Estimation of External Force-Torque Vector Based on Double Encoders of Industrial Robots Using a Hybrid Gaussian Process Regression and Joint Stiffness Model
title_short Estimation of External Force-Torque Vector Based on Double Encoders of Industrial Robots Using a Hybrid Gaussian Process Regression and Joint Stiffness Model
title_sort estimation of external force torque vector based on double encoders of industrial robots using a hybrid gaussian process regression and joint stiffness model
topic industrial robots
double encoders
force-torque estimation
url http://jmacheng.not.pl/Estimation-of-External-Force-Torque-Vector-Based-on-Double-Encoders-of-Industrial,167359,0,2.html
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AT julianblumberg estimationofexternalforcetorquevectorbasedondoubleencodersofindustrialrobotsusingahybridgaussianprocessregressionandjointstiffnessmodel