Creation and Evaluation of emotion expression with body movement, sound and eye color for humanoid robots

Abstract

The ability to display emotions is a key feature in human communication and also for robots that are expected to interact with humans in social environments. For expressions based on Body Movement and other signals than facial expressions, like Sound, no common grounds have been established so far. Based on psychological research on human expression of emotions and perception of emotional stimuli we created eight different expressional designs for the emotions Anger, Sadness, Fear and Joy, consisting of Body Movements, Sounds and Eye Colors. In a large pre-test we evaluated the recognition ratios for the different expressional designs. In our main experiment we separated the expressional designs into their single cues (Body Movement, Sound, Eye Color) and evaluated their expressivity. The detailed view at the perception of our expressional cues, allowed us to evaluate the appropriateness of the stimuli, check our implementations for flaws and build a basis for systematical revision. Our analysis revealed that almost all Body Movements were appropriate for their target emotion and that some of our Sounds need a revision. Eye Colors could be identified as an unreliable component for emotional expression.

Living with robots : investigating the user acceptance of social robots in domestic environments

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Mimebot—Investigating the Expressibility of Non-Verbal Communication Across Agent Embodiments

“…Emotional body laguage for the Nao robot was studied by [5] and [12]. For a non-humanoid sphere-shaped robot (Maru), sound, colors, and vibrations were used to express emotional behaviors [26].…”

Vocal Interactivity in-and-between Humans, Animals, and Robots

“…However, many challenges need to be addressed in order to meet such a requirement (Baker et al, 2009a;Moore, 2013Moore, , 2015, not least how to evolve the complexity of voice-based interfaces from simple structured dialogs to more flexible conversational designs without confusing the user (Bernsen et al, 1998;McTear, 2004;Lopez Cozar Delgado and Araki, 2005;Phillips and Philips, 2006;Moore, 2016b). In particular, seminal work by Nass and Brave (2005) showed how attention needs to be paid to users' expectations [e.g., selecting the "gender" of a system's voice (Crowell et al, 2009)], and this has inspired work on "empathic" vocal robots (Breazeal, 2003;Fellous and Arbib, 2005;Haring et al, 2011;Eyssel et al, 2012;Lim and Okuno, 2014;Crumpton and Bethel, 2016). On the other hand, user interface experts, such as Balentine (2007), have argued that such agents should be clearly machines rather than emulations of human beings, particularly to avoid the "uncanny valley effect" (Mori, 1970), whereby mismatched perceptual cues can lead to feelings of repulsion (Moore, 2012).…”