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Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses

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Bibliographic Details
Main Authors: Cornelia, Tepper, Alexander, Matei, Jonas, Zarges
Format: Book
Language:English
Published: Springer 2023
Subjects:
TCP
Online Access:https://link.springer.com/article/10.1007/s11740-023-01198-3
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8024
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spelling oai:localhost:PNK-80242023-04-18T03:02:46Z Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses Cornelia, Tepper Alexander, Matei Jonas, Zarges TCP CC BY In this paper a cost and time efficient approach to setup a compliance model for industrial robots is presented. The compliance model is distinctly determined by the gear’s stiffness parameters which are tuned by an optimal design of experiments approach. The experimental setup consists of different poses of the robot’s axes together with the applied force at the tool center point (TCP). These robot poses represent together with defined forces the experimental setup where the deviation of the robot under defined force is measured. Based on measurements of the displacement of the TCP the stiffness parameters for the compliance model are estimated and afterwards validated in new experiments. The efficiency of this approach lies in the reduced amount of experiments that are needed to identify the stiffness parameters that are parameters inherent to the compliance and the less complex experimental setup. 2023-04-18T03:02:46Z 2023-04-18T03:02:46Z 2023 Book https://link.springer.com/article/10.1007/s11740-023-01198-3 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8024 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic TCP
spellingShingle TCP
Cornelia, Tepper
Alexander, Matei
Jonas, Zarges
Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses
description CC BY
format Book
author Cornelia, Tepper
Alexander, Matei
Jonas, Zarges
author_facet Cornelia, Tepper
Alexander, Matei
Jonas, Zarges
author_sort Cornelia, Tepper
title Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses
title_short Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses
title_full Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses
title_fullStr Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses
title_full_unstemmed Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses
title_sort optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s11740-023-01198-3
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8024
_version_ 1763543256310743040
score 8.881002

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