Cartesian Inertia Optimization via Redundancy Resolution for Physical Human-Robot Interaction

Sutjipto, S; Woolfrey, J; Carmichael, MG; Paul, G

Cartesian Inertia Optimization via Redundancy Resolution for Physical Human-Robot Interaction

Sutjipto, S Woolfrey, J Carmichael, MG Paul, G

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), 2021, 2021-August, pp. 570-575
Issue Date:: 2021-10-05

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Field	Value	Language
dc.contributor.author	Sutjipto, S
dc.contributor.author	Woolfrey, J
dc.contributor.author	Carmichael, MG
dc.contributor.author	Paul, G https://orcid.org/0000-0002-3478-0020
dc.date	2021-08-23
dc.date.accessioned	2022-06-20T08:14:24Z
dc.date.available	2022-06-20T08:14:24Z
dc.date.issued	2021-10-05
dc.identifier.citation	2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), 2021, 2021-August, pp. 570-575
dc.identifier.isbn	9781665418737
dc.identifier.issn	2161-8070
dc.identifier.issn	2161-8089
dc.identifier.uri	http://hdl.handle.net/10453/158274
dc.description.abstract	The objective of introducing robotic manipulators into human-centric domains is to improve the efficacy of tasks in a safe and practical manner. The shift toward collaborative manipulator platforms has facilitated physical human-robot interaction (pHRI) in such environments. Often, these platforms are kinematically redundant and possess more degrees of freedom (DOF) than needed to complete a desired task. When no additional task is defined, it is possible for the manipulator to converge upon joint configurations that are unfavourable for the collaborative task. Consequently, there is potential for the posture of the manipulator to affect the interaction experienced. This paper investigates an inertia-based optimization control method for redundant manipulators interacting with an active agent. The inertia-based reconfiguration is evaluated through simulations and quantified with real-life experiments conducted with a robot-robot dyad. It was found that resolving redundancy to reconfigure the Cartesian inertia reduced the energy expenditure of the active agent during the interaction.
dc.language	en
dc.publisher	IEEE
dc.relation	Innovative Manufacturing Cooperative Research Centre
dc.relation.ispartof	2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)
dc.relation.ispartof	2021 IEEE 17th International Conference on Automation Science and Engineering
dc.relation.isbasedon	10.1109/case49439.2021.9551663
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.title	Cartesian Inertia Optimization via Redundancy Resolution for Physical Human-Robot Interaction
dc.type	Conference Proceeding
utslib.citation.volume	2021-August
utslib.location.activity	Lyon, France
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2023-10-31T00:00:00+1000Z
dc.date.updated	2022-06-20T08:14:22Z
pubs.finish-date	2021-08-27
pubs.publication-status	Published
pubs.start-date	2021-08-23
pubs.volume	2021-August

Abstract:

The objective of introducing robotic manipulators into human-centric domains is to improve the efficacy of tasks in a safe and practical manner. The shift toward collaborative manipulator platforms has facilitated physical human-robot interaction (pHRI) in such environments. Often, these platforms are kinematically redundant and possess more degrees of freedom (DOF) than needed to complete a desired task. When no additional task is defined, it is possible for the manipulator to converge upon joint configurations that are unfavourable for the collaborative task. Consequently, there is potential for the posture of the manipulator to affect the interaction experienced. This paper investigates an inertia-based optimization control method for redundant manipulators interacting with an active agent. The inertia-based reconfiguration is evaluated through simulations and quantified with real-life experiments conducted with a robot-robot dyad. It was found that resolving redundancy to reconfigure the Cartesian inertia reduced the energy expenditure of the active agent during the interaction.

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http://hdl.handle.net/10453/158274