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

Autor: Matteo Bottin, Silvio Cocuzza, Nicola Comand, Alberto Doria
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Applied Sciences, Vol 10, Iss 13, p 4619 (2020)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app10134619
Popis: 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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