The very first moments of co-presence, during which a robot appears to a participant for the first time, are often “off-the-record” in the data collected from human-robot experiments (video recordings, motion tracking, methodology sections, etc.). Yet, this “pre-beginning” phase, well documented in the case of human-human interactions, is not an interactional vacuum: It is where interactional work from participants can take place so the production of a first speaking turn (like greeting the robot) becomes relevant and expected. We base our analysis on an experiment that replicated the interaction opening delays sometimes observed in laboratory or “in-the-wild” human-robot interaction studies—where robots can require time before springing to life after they are in co-presence with a human. Using an ethnomethodological and multimodal conversation analytic methodology (EMCA), we identify which properties of the robot's behavior were oriented to by participants as creating the adequate conditions to produce a first greeting. Our findings highlight the importance of the state in which the robot originally appears to participants: as an immobile object or, instead, as an entity already involved in preexisting activity. Participants’ orientations to the very first behaviors manifested by the robot during this “pre-beginning” phase produced a priori unpredictable sequential trajectories, which configured the timing and the manner in which the robot emerged as a social agent. We suggest that these first instants of co-presence are not peripheral issues with respect to human-robot experiments but should be thought about and designed as an integral part of those.

Constructs intended to capture social attitudes and behaviour towards social robots are incredibly varied, with little overlap or consistency in how they may be related. In this study we conduct exploratory analyses between participants’ self-reported attitudes and behaviour towards a social robot. We designed an autonomous interaction where 102 participants interacted with a social robot (Pepper) in a hypothetical travel planning scenario, during which the robot displayed various multi-modal social behaviours. Several behavioural measures were embedded throughout the interaction, followed by a self-report questionnaire targeting participant’s social attitudes towards the robot (social trust, liking, rapport, competency trust, technology acceptance, mind perception, social presence, and social information processing). Several relationships were identified between participant’s behaviour and self-reported attitudes towards the robot. Implications for how to conceptualise and measure interactions with social robots are discussed.

With more social robots entering different industries such as educational systems, health-care facilities, and even airports, it is important to tackle problems that may hinder high quality interactions in a wild setting including group conversations. This paper presents an autonomous group conversational role coordinator system based on the proxemics of participants in the group with the robot including their distances and orientations. The system accordingly assigns to the group participants around the robot three different statuses: active, bystander, and overhearer. Once the statuses are estimated, the robot autonomously adjusts its gaze pattern in order to adapt to the group dynamics and attributes its attention in relation to the role the member in the group is playing. This system was evaluated through a pilot study (N=16), in which two participants at a time played a trivia game with the robot and had different roles to play within the interaction. The primary results imply that the participants interacting with a robot having this adaptive gaze behavior based on conversational role coordination are more likely to stand closer to the robot. In addition, the robot was perceived as more adaptable, sociable, and socially present as well as more likely to make the participants feel more attended to.