TY - GEN
T1 - A Survey of Robotics and Emotion
T2 - 29th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2020
AU - Savery, Richard
AU - Weinberg, Gil
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - As emotion plays a growing role in robotic research it is crucial to develop methods to analyze and compare among the wide range of approaches. To this end we present a survey of 1427 IEEE and ACM publications that include robotics and emotion. This includes broad categorizations of trends in emotion input analysis, robot emotional expression, studies of emotional interaction and models for internal processing. We then focus on 232 papers that present internal processing of emotion, such as using a human's emotion for better interaction or turning environmental stimuli into an emotional drive for robotic path planning. We conducted constant comparison analysis of the 232 papers and arrived at three broad categorization metrics - emotional intelligence, emotional model and implementation - each including two or three subcategories. The subcategories address the algorithm used, emotional mapping, history, the emotional model, emotional categories, the role of emotion, the purpose of emotion and the platform. Our results show a diverse field of study, largely divided by the role of emotion in the system, either for improved interaction, or improved robotic performance. We also present multiple future opportunities for research and describe intrinsic challenges common in all publications.
AB - As emotion plays a growing role in robotic research it is crucial to develop methods to analyze and compare among the wide range of approaches. To this end we present a survey of 1427 IEEE and ACM publications that include robotics and emotion. This includes broad categorizations of trends in emotion input analysis, robot emotional expression, studies of emotional interaction and models for internal processing. We then focus on 232 papers that present internal processing of emotion, such as using a human's emotion for better interaction or turning environmental stimuli into an emotional drive for robotic path planning. We conducted constant comparison analysis of the 232 papers and arrived at three broad categorization metrics - emotional intelligence, emotional model and implementation - each including two or three subcategories. The subcategories address the algorithm used, emotional mapping, history, the emotional model, emotional categories, the role of emotion, the purpose of emotion and the platform. Our results show a diverse field of study, largely divided by the role of emotion in the system, either for improved interaction, or improved robotic performance. We also present multiple future opportunities for research and describe intrinsic challenges common in all publications.
UR - https://www.scopus.com/pages/publications/85095734256
UR - https://ieeexplore.ieee.org/xpl/conhome/9219088/proceeding
UR - https://ewh.ieee.org/soc/ras/conf/financiallycosponsored/roman/RO-MAN2020/ro-man2020.unina.it/organizing-committee.html
U2 - 10.1109/RO-MAN47096.2020.9223536
DO - 10.1109/RO-MAN47096.2020.9223536
M3 - Conference contribution
AN - SCOPUS:85095734256
T3 - 29th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2020
SP - 986
EP - 993
BT - 29th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2020
A2 - Rossi, Silvia
A2 - Tapus, Adriana
A2 - Siciliana, Bruno
A2 - Kuic, Dana
A2 - Lee, Dongheui
A2 - Shiomi, Masahiro
A2 - Ferland, Francois
A2 - Morocco, Davide
PB - IEEE, Institute of Electrical and Electronics Engineers
Y2 - 31 August 2020 through 4 September 2020
ER -