Int J Soc Robot DOI 10.1007/s12369-010-0071-x Communication of Emotion in Social Robots through Simple Head and Arm Movements Jamy Li · Mark Chignell Accepted: 2 August 2010 © Springer Science & Business Media BV 2010 Abstract Understanding how people perceive robot ges- tures will aid the design of robots capable of social inter- action with humans. We examined the generation and per- ception of a restricted form of gesture in a robot capable of simple head and arm movement, referring to point-light an- imation and video experiments in human motion to derive our hypotheses. Four studies were conducted to look at the effects of situational context, gesture complexity, emotional valence and author expertise. In Study 1, four participants created gestures with corresponding emotions based on 12 scenarios provided. The resulting gestures were judged by 12 participants in a second study. Participants’ recognition of emotion was better than chance and improved when sit- uational context was provided. Ratings of lifelikeness were found to be related to the number of arm movements (but not head movements) in a gesture. In Study 3, five novices and five puppeteers created gestures conveying Ekman’s six ba- sic emotions which were shown to 12 Study 4 participants. Puppetry experience improved identification rates only for the emotions of fear and disgust, possibly because of limi- tations with the robot’s movement. The results demonstrate the communication of emotion by a social robot capable of only simple head and arm movement. Funding provided by the Japan Society for the Promotion of Science (JSPS), the Natural Sciences and Engineering Research Council of Canada (NSERC), Bell University Labs and the University of Toronto. J. Li ( ) · M. Chignell Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, ON M5S 3G8, Canada e-mail: jamy.li@utoronto.ca M. Chignell e-mail: chignell@mie.utoronto.ca Keywords Human-robot interaction · Gesture design · Communication of emotions · Puppetry 1 Introduction Modern robots are no longer being designed only to function as manufacturing aids, but they are also being introduced as social partners. In light of the roles robots are adopting as household pets (e.g., Sony’s AIBO), domestic helpers (iRobot’s Roomba), healthcare assistants (RIKEN Japan’s Ri-Man), emotional companions (AIST’s PARO) and ed- ucational aids (MIT’s Kismet and Leo), appropriate social behaviour is critical for people to develop personal relation- ships with such agents. Many authors have called for better design of robots capable of engaging in meaningful social interactions with people (e.g., [1, 2]). This new breed of robots is called “socially interactive robots” or “social ro- bots” [1]. The use of gestures has been identified as crucial to the design of such robots [2]. Research on robot gestures is needed because: (1) studying gesture interpretation is nec- essary to improve human-robot interaction especially for ro- bots that have limited ability for vocal and facial expressiv- ity; (2) previous research in HRI has focused on how ges- tures are created without evaluating people’s understanding of those gestures, so little is known about what factors affect gesture perception; and (3) no previous work has investi- gated the characteristics of “good” designers and the role of expertise in gesture authorship. Current practice in the de- sign of robot gestures has robot inventors and researchers devising gestures based on their own experience and some- times drawing upon fields such as dance (e.g. [3]). These methods may be convenient but little work has been done to