Tepper, Cornelia ; Matei, Alexander ; Zarges, Jonas ; Ulbrich, Stefan ; Weigold, Matthias (2023)
Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses.
In: Production Engineering
doi: 10.1007/s11740-023-01198-3
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
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.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Tepper, Cornelia ; Matei, Alexander ; Zarges, Jonas ; Ulbrich, Stefan ; Weigold, Matthias |
| Art des Eintrags: | Bibliographie |
| Titel: | Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses |
| Sprache: | Englisch |
| Publikationsjahr: | 2023 |
| Verlag: | Springer |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Production Engineering |
| DOI: | 10.1007/s11740-023-01198-3 |
| URL / URN: | https://link.springer.com/article/10.1007/s11740-023-01198-3 |
| Kurzbeschreibung (Abstract): | 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. |
| Freie Schlagworte: | robots, milling, optimal design of experiments, Bayesian inference, stiffness estimatio |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) 16 Fachbereich Maschinenbau > Institut für Produktionsmanagement und Werkzeugmaschinen (PTW) > TEC Fertigungstechnologie |
| Hinterlegungsdatum: | 24 Apr 2023 05:28 |
| Letzte Änderung: | 24 Apr 2023 11:05 |
| PPN: | 507242688 |
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| Suche nach Titel in: | TUfind oder in Google |
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