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Stiffness modeling and analysis of a novel 5-DOF hybrid robot

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Dong, Chenglin, Liu, Haitao, Yue, Wei and Huang, Tian (2018) Stiffness modeling and analysis of a novel 5-DOF hybrid robot. Mechanism and Machine Theory, 125 . pp. 80-93. doi:10.1016/j.mechmachtheory.2017.12.009 ISSN 0094-114X.

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Official URL: http://dx.doi.org/10.1016/j.mechmachtheory.2017.12...

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Abstract

This paper deals with the stiffness modeling and analysis of a novel 5-DOF hybrid robot named TriMule which is composed of a 3-DOF positioning parallel mechanism plus a 2-DOF wrist. The robot is especially designed as a compact yet rigid module suitable for large part on-site machining. Mainly drawing on screw theory, a semi-analytic stiffness model of the robot is formulated by taking into account the component compliances associated with the elements of both the parallel mechanism and the wrist, resulting in the Cartesian stiffness matrix that can explicitly be expressed in terms of the compliance matrices down to the joint and link level. The stiffness distributions of the tool head over a prescribed task workspace are predicted and the contributions of joint/link compliances are evaluated using a set of global indices.

Item Type: Journal Article
Subjects: T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH): Robotics -- Mathematical modelling, Machining, Screws, Theory of
Journal or Publication Title: Mechanism and Machine Theory
Publisher: Pergamon-Elsevier Science Ltd.
ISSN: 0094-114X
Official Date: July 2018
Dates:
DateEvent
July 2018Published
23 December 2017Available
7 December 2017Accepted
Volume: 125
Page Range: pp. 80-93
DOI: 10.1016/j.mechmachtheory.2017.12.009
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 23 January 2018
Date of first compliant Open Access: 23 December 2018
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
51622508 National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100001809
51420105007National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100001809
734272H2020 European Research Councilhttp://dx.doi.org/10.13039/100010663

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