TY - CHAP

T1 - Designing Emotionally Expressive Robots

AU - Tsiourti, Christiana

AU - Weiss, Astrid

AU - Wac, Katarzyna

AU - Vincze, Markus

PY - 2017

Y1 - 2017

N2 - Socially assistive agents, be it virtual avatars or robots, need to engage in social interactions with humans and express their internal emotional states, goals, and desires. In this work, we conducted a comparative study to investigate how humans perceive emotional cues expressed by humanoid robots through five communication modalities (face, head, body, voice, locomotion) and examined whether the degree of a robot's human-like embodiment affects this perception. In an online survey, we asked people to identify emotions communicated by Pepper -a highly human-like robot and Hobbit – a robot with abstract humanlike features. A qualitative and quantitative data analysis confirmed the expressive power of the face, but also demonstrated that body expressions or even simple head and locomotion movements could convey emotional information. These findings suggest that emotion recognition accuracy varies as a function of the modality, and a higher degree of anthropomorphism does not necessarily lead to a higher level of recognition accuracy. Our results further the understanding of how people respond to single communication modalities and have implications for designing recognizable multimodal expressions for robots.

AB - Socially assistive agents, be it virtual avatars or robots, need to engage in social interactions with humans and express their internal emotional states, goals, and desires. In this work, we conducted a comparative study to investigate how humans perceive emotional cues expressed by humanoid robots through five communication modalities (face, head, body, voice, locomotion) and examined whether the degree of a robot's human-like embodiment affects this perception. In an online survey, we asked people to identify emotions communicated by Pepper -a highly human-like robot and Hobbit – a robot with abstract humanlike features. A qualitative and quantitative data analysis confirmed the expressive power of the face, but also demonstrated that body expressions or even simple head and locomotion movements could convey emotional information. These findings suggest that emotion recognition accuracy varies as a function of the modality, and a higher degree of anthropomorphism does not necessarily lead to a higher level of recognition accuracy. Our results further the understanding of how people respond to single communication modalities and have implications for designing recognizable multimodal expressions for robots.

U2 - 10.1145/3125739.3125744

DO - 10.1145/3125739.3125744

M3 - Book chapter

SN - 9781450351133

T3 - Proceedings of the 5th International Conference on Human Agent Interaction - HAI '17

SP - 213

EP - 222

BT - Proceedings of the 5th International Conference on Human Agent Interaction - HAI '17

PB - ACM Press/Addison-Wesley

CY - New York

ER -