For motion assistance humans prefer to rely on a robot rather than on an unpredictable human
OA Location
Author(s)
Ivanova, Ekaterina
Carboni, Gerolamo
Eden, Jonathan
Krueger, Joerg
Burdet, Etienne
Type
Journal Article
Abstract
Objective: The last decades have seen a surge of robots for physical training and work assistance. How to best control these interfaces is unknown, although arguably the interaction should be similar to human movement assistance. Methods: We compare the behaviour and assessment of subjects tracking a moving target with assistance from (i) trajectory guidance (as typically used in robots for physical training), (ii) a human partner, and (iii) the reactive robot partner of Takagi et al. Results: Trajectory guidance was recognised as robotic, while the robot partner was felt as human-like. However, trajectory guidance was preferred to assistance from a human partner, which was recognised as less predictable. The robot partner also was felt to be more predictable and helpful than a human partner, and was preferred. Conclusions: While subjects like to rely on predictable interaction, such as in trajectory guidance, the control reactivity of the robot partner is essential for perceiving an interaction as human-like.
Date Issued
2020-04-16
Date Acceptance
2020-04-09
Citation
IEEE Open Journal of Engineering in Medicine and Biology, 2020, 1, pp.133-139
ISSN
2644-1276
Publisher
Institute of Electrical and Electronics Engineers
Start Page
133
End Page
139
Journal / Book Title
IEEE Open Journal of Engineering in Medicine and Biology
Volume
1
Copyright Statement
© 2020 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/
License URL
Sponsor
Commission of the European Communities
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Commission of the European Communities
Commission of the European Communities
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000653537500018&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
644727
EP/N032772/1
EP/R026092/1
829186
861166
Subjects
Science & Technology
Technology
Engineering, Biomedical
Engineering
Physical interaction
human-human
human-robot
haptic Turing test
performance and perception
PERCEPTIONS
DESIGN
Publication Status
Published
Date Publish Online
2020-04-16