Current Search: Guznov, Svyatoslav (x)
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Title
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Transparency and Communication Patterns in Human-Robot Teaming.
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Creator
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Lakhmani, Shan, Barber, Daniel, Jentsch, Florian, Reinerman, Lauren, Guznov, Svyatoslav, University of Central Florida
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Abstract / Description
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In anticipation of the complex, dynamic battlefields of the future, military operations are increasingly demanding robots with increased autonomous capabilities to support soldiers. Effective communication is necessary to establish a common ground on which human-robot teamwork can be established across the continuum of military operations. However, the types and format of communication for mixed-initiative collaboration is still not fully understood. This study explores two approaches to...
Show moreIn anticipation of the complex, dynamic battlefields of the future, military operations are increasingly demanding robots with increased autonomous capabilities to support soldiers. Effective communication is necessary to establish a common ground on which human-robot teamwork can be established across the continuum of military operations. However, the types and format of communication for mixed-initiative collaboration is still not fully understood. This study explores two approaches to communication in human-robot interaction, transparency and communication pattern, and examines how manipulating these elements with a robot teammate affects its human counterpart in a collaborative exercise. Participants were coupled with a computer-simulated robot to perform a cordon-and-search-like task. A human-robot interface provided different transparency types(-)about the robot's decision making process alone, or about the robot's decision making process and its prediction of the human teammate's decision making process(-)and different communication patterns(-)either conveying information to the participant or both conveying information to and soliciting information from the participant. This experiment revealed that participants found robots that both conveyed and solicited information to be more animate, likeable, and intelligent than their less interactive counterparts, but working with those robots led to more misses in a target classification task. Furthermore, the act of responding to the robot led to a reduction in the number of correct identifications made, but only when the robot was solely providing information about its own decision making process. Findings from this effort inform the design of next-generation visual displays supporting human-robot teaming.
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Date Issued
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2019
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Identifier
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CFE0007481, ucf:52674
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Format
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Document (PDF)
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PURL
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http://purl.flvc.org/ucf/fd/CFE0007481
