Physiological Data-Based Evaluation of a Social Robot Navigation System

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dc.contributor.authorKivrak, H.
dc.contributor.authorUluer, P.
dc.contributor.authorKose, H.
dc.contributor.authorGumuslu, E.
dc.contributor.authorErol, Barkana, D.
dc.contributor.authorCakmak, F.
dc.contributor.authorYavuz, S.
dc.date.accessioned2024-09-29T16:20:44Z
dc.date.available2024-09-29T16:20:44Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.descriptionet al.; Furhat Robotics; IEEE; IEEE Robotics and Automation Society (RA); Korea Robotics Society (KROS); Robotics Society of Japan (RSJ)en_US
dc.description29th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2020 -- 31 August 2020 through 4 September 2020 -- Virtual, Naples -- 164066en_US
dc.description.abstractThe aim of this work is to create a social navigation system for an affective robot that acts as an assistant in the audiology department of hospitals for children with hearing impairments. Compared to traditional navigation systems, this system differentiates between objects and human beings and optimizes several parameters to keep at a social distance during motion when faced with humans not to interfere with their personal zones. For this purpose, social robot motion planning algorithms are employed to generate human-friendly paths that maintain humans' safety and comfort during the robot's navigation. This paper evaluates this system compared to traditional navigation, based on the surveys and physiological data of the adult participants in a preliminary study before using the system with children. Although the self-report questionnaires do not show any significant difference between navigation profiles of the robot, analysis of the physiological data may be interpreted that, the participants felt comfortable and less threatened in social navigation case. © 2020 IEEE.en_US
dc.description.sponsorshipTUBITAK, (118E214); Galatasaray Üniversitesi; Türkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK; Istanbul Teknik Üniversitesi; Karabük Üniversitesien_US
dc.identifier.doi10.1109/RO-MAN47096.2020.9223539
dc.identifier.endpage999en_US
dc.identifier.isbn978-172816075-7
dc.identifier.scopus2-s2.0-85090158784en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage994en_US
dc.identifier.urihttps://doi.org/10.1109/RO-MAN47096.2020.9223539
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9288
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof29th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2020en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectdeeplearningen_US
dc.subjectemotion recognitionen_US
dc.subjectHRIen_US
dc.subjectpersonal zoneen_US
dc.subjectphysiological dataen_US
dc.subjectsocial navigationen_US
dc.titlePhysiological Data-Based Evaluation of a Social Robot Navigation Systemen_US
dc.typeConference Objecten_US

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