TY - GEN
T1 - Physiological Data-Based Evaluation of a Social Robot Navigation System
AU - Kivrak, Hasan
AU - Uluer, Pinar
AU - Kose, Hatice
AU - Gumuslu, Elif
AU - Erol Barkana, Duygun
AU - Cakmak, Furkan
AU - Yavuz, Sirma
N1 - Funding Information:
This work is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) under the Grant number 118E214 1Department of Computer Engineering, Karabuk University, TURKEY [email protected] 2Department of Computer Engineering, Galatasaray University, TURKEY [email protected] 3Department of Computer Engineering, Istanbul Technical University, TURKEY {kivrakh, pinar.uluer, hatice.kose}@itu.edu.tr 4Department of Electrical and Electronics Engineering, Yeditepe University, TURKEY [email protected], [email protected] 5Department of Computer Engineering, Yildiz Technical University, TURKEY {fcakmak, smyavuz}@yildiz.edu.tr
Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - The 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.
AB - The 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.
KW - deeplearning
KW - emotion recognition
KW - HRI
KW - personal zone
KW - physiological data
KW - social navigation
UR - http://www.scopus.com/inward/record.url?scp=85090158784&partnerID=8YFLogxK
U2 - 10.1109/RO-MAN47096.2020.9223539
DO - 10.1109/RO-MAN47096.2020.9223539
M3 - Conference contribution
AN - SCOPUS:85090158784
T3 - 29th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2020
SP - 994
EP - 999
BT - 29th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 29th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2020
Y2 - 31 August 2020 through 4 September 2020
ER -