journal article·2020-07-03Open access

Modeling and Identification of an Industrial Robot with a Selective Modal Approach

Matteo Bottin, Silvio Cocuzza, Nicola Comand, Alberto Doria

Applied Sciences· Volume 10· Issue 13

Abstract

The stiffness properties of industrial robots are very important for many industrial applications, such as automatic robotic assembly and material removal processes (e.g., machining and deburring). On the one hand, in robotic assembly, joint compliance can be useful for compensating dimensional errors in the parts to be assembled; on the other hand, in material removal processes, a high Cartesian stiffness of the end-effector is required. Moreover, low frequency chatter vibrations can be induced when low-stiffness robots are used, with an impairment in the quality of the machined surface. In this paper, a compliant joint dynamic model of an industrial robot has been developed, in which joint stiffness has been experimentally identified using a modal approach. First, a novel method to select the test configurations has been developed, so that in each configuration the mode of vibration that chiefly involves only one joint is excited. Then, experimental tests are carried out in the selected configurations in order to identify joint stiffness. Finally, the developed dynamic model of the robot is used to predict the variation of the natural frequencies in the workspace.
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Research context

OpenAlex topics: Robotic Mechanisms and Dynamics · Advanced machining processes and optimization · Iterative Learning Control Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Industrial Engineering, University of Padova, 35131 Padova, Italy

Department of Management and Engineering, University of Padova, 36100 Vicenza, Italy

Funding

Università degli Studi di Padova · Fondazione Aldo Gini · Ermenegildo Zegna Founder

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