Simplified Pain Matrix Method for Artificial Pain Activation Embedded into Robot Framework

Anshar, M; Williams, MA

Simplified Pain Matrix Method for Artificial Pain Activation Embedded into Robot Framework

Anshar, M

Williams, MA

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Publisher:: Springer
Publication Type:: Journal Article
Citation:: International Journal of Social Robotics, 2021, 13, (2), pp. 187-195
Issue Date:: 2021-01-01

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Field	Value	Language
dc.contributor.author	Anshar, M https://orcid.org/0000-0002-6477-5257
dc.contributor.author	Williams, MA
dc.date.accessioned	2022-05-20T05:21:10Z
dc.date.available	2022-05-20T05:21:10Z
dc.date.issued	2021-01-01
dc.identifier.citation	International Journal of Social Robotics, 2021, 13, (2), pp. 187-195
dc.identifier.issn	1875-4791
dc.identifier.issn	1875-4805
dc.identifier.uri	http://hdl.handle.net/10453/157552
dc.description.abstract	Physical interaction in Human Robot Interaction is a predominant factor to determine the existence of collaboration between humans and robots. However, a prolonged physical interaction may lead humans to experience what is called as pain which possibly arises due to uncoordinated movements between humans and robots, internal humans’ physical constraints or other feasible causes. This paper introduces a novel method,simplified Pain Matrix (PM), which a PM to generate and activate the kinds of synthetic pain embedded into a robot framework with simplifications on some features of the Pain Matrix. Two scenarios of experiments are constructed and dedicated to demonstrate the activation procedure of the proposed pain mechanism, and the results show a reliable outcome by accurately invoking a particular synthetic pain based on stimulus obtained from the robot joint sensor, which is then followed by reactive prevention actions generated by the Robot Mind.
dc.language	English
dc.publisher	Springer
dc.relation	http://purl.org/au-research/grants/arc/DP160102693
dc.relation.ispartof	International Journal of Social Robotics
dc.relation.isbasedon	10.1007/s12369-020-00632-1
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 0915 Interdisciplinary Engineering, 2002 Cultural Studies
dc.title	Simplified Pain Matrix Method for Artificial Pain Activation Embedded into Robot Framework
dc.type	Journal Article
utslib.citation.volume	13
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0915 Interdisciplinary Engineering
utslib.for	2002 Cultural Studies
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 - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-05-20T05:21:09Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	13
utslib.citation.issue	2

Abstract:

Physical interaction in Human Robot Interaction is a predominant factor to determine the existence of collaboration between humans and robots. However, a prolonged physical interaction may lead humans to experience what is called as pain which possibly arises due to uncoordinated movements between humans and robots, internal humans’ physical constraints or other feasible causes. This paper introduces a novel method,simplified Pain Matrix (PM), which a PM to generate and activate the kinds of synthetic pain embedded into a robot framework with simplifications on some features of the Pain Matrix. Two scenarios of experiments are constructed and dedicated to demonstrate the activation procedure of the proposed pain mechanism, and the results show a reliable outcome by accurately invoking a particular synthetic pain based on stimulus obtained from the robot joint sensor, which is then followed by reactive prevention actions generated by the Robot Mind.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/157552