Designing robots with socio-emotional skills is a challenging research topic still in its infancy. These skills are important for robots to be able to provide not only physical, but also social support to human users, and to engage in and sustain long-term interactions with them in a variety of application domains that require human-robot interaction, including healthcare, education, entertainment, manufacturing, and many others. The availability of commercial robotic platforms and developments in collaborative academic research provide us a positive outlook, however, the capabilities of current social robots are quite limited. The main challenge is understanding the underlying mechanisms of the humans in responding to and interacting with real life situations, and how to model these mechanisms for the embodiment of naturalistic, human-inspired behaviors via robots. To address this challenge successfully requires an understanding of the essential components of social interaction including nonverbal behavioral cues such as interpersonal distance, body position, body posture, arm and hand gestures, head and facial gestures, gaze, silences, vocal outbursts and their dynamics. To create truly intelligent social robots, these nonverbal cues need to be interpreted to form an understanding of the higher level phenomena including first-impression formation, social roles, interpersonal relationships, focus of attention, synchrony, affective states, emotions, and personality, and in turn defining optimal protocols and behaviors to express these phenomena through robotic platforms in an appropriate and timely manner. Achieving this goal requires the fields of psychology, nonverbal behavior, vision, social signal processing, affective computing, and HRI to constantly interact with one another. This Research Topic aims to foster such interactions and collaborations by bringing together the latest works and developments from across a range of research groups and disciplines working in these fields. The Research Topic is a collection of 14 articles that span across five research themes. Three articles co-authored by Terada and Takeuchi, Jung et al., and Kennedy et al. explore the design of “social and affective cues” for robots and investigate their effects on human-robot interaction. Mirnig et al., Bremner et al., and Strait et al. investigate people’s “perceptions of robots” in different settings and scenarios, such as when robots make errors. Articles by Lee et al., Leite et al., and Heath et al. investigate the factors that shape “dialogic interaction with robots,” such as interaction context. The articles under the theme “social and affective therapy” by Rouaix et al., Rudovic et al., and Matsuda et al. report on how individuals from clinical populations, such as those with dementia, autism, and other pervasive developmental disorders (PDDs), interact with robots in therapeutic scenarios. Finally, Miklósi et al. and Durantin et al. offer “new perspectives in human-robot interaction” with a focus on reframing social interaction and human-robot relationships. We are excited about sharing this rich collection with the scientific community and about its contributions to the human-robot interaction literature.
