Based on the analysis of non-verbal inter-human interaction, this paper proposes a model for estimating human friendships in the presence of a humanoid robot. Our previous study in an elementary school provided rich video data of two months of interhuman interaction in the presence of a humanoid robot. Such data are particularly useful for developing a robot's social ability: a friendship estimation capability. We analyzed the video based on an observation method to analyze the interaction among children and the robot. From their non-verbal interactions, several important factors for friendship estimation were retrieved, including touch, gaze, co-presence, and distance. Gender was also considered a factor in the model, since gender differences were observed in non-verbal interactions. The model discriminated between friendly and non-friendly relationships among the children with 74.5% accuracy for boys and 83.8% for girls.

1This paper investigates human behavior around an interactive robot at a science museum. To develop a communication robot that works in daily environments, it is important to investigate the available information from a robot about people's behavior. Such information will enable the robot to predict people's behavior so that the robot can optimize its interactive behavior. We analyzed visitor behavior toward a simple interactive robot exhibited at a science museum in relation to information from sound level and range sensors. We discovered factors that influence the way people approach, maintain distance, and interact both physically and verbally with the robot. This enabled us to extract meaningful information from the sensory information and apply it to communication robots.

Abstract-Coding can contribute to robot design by suggesting behavioural benchmarks. These, however, depend on the level of analysis. In illustration, semi-formalised rules are used to investigate child-robot encounters. By using behaviour-level codes, we extract information about how children use the robot. This leads to findings about longditudinal changes in how children evaluate its behaviours. Children, we find, use the robot as a social mediator-to prompt synchronized social events. By focusing on a behavioural level, coding can benefit designers of robots, software and sensors.

No abstract