Forming friendship with peers from diverse backgrounds is key to children’s social emotional development. In this study, we explored the use of social robot, Haru, as mediator for remote communication in children group, to support connection and friendship building. We invited children from different countries aged from 10 to 15 to participate in two interaction sessions with peers from other countries, after which we conducted interviews with children from three countries, focusing on their experiences, and perceptions of the robot’s roles in the process. The findings indicated that social robot Haru effectively served as an icebreaker and entertainer; However, improvements are needed in conversation flow, transitions between different roles, and supporting children’s autonomy in guiding the conversation and the depth of their communication.

Social robots for children have focused mainly on conventional education domains such as teaching language, science, and math, while applications focusing on the enhancement of cultural competency are quite scarce. In this paper, we present a prototype of a robot-mediation framework for cross-cultural communication. This framework paves the way for a social robot to act as a mediator between groups of schoolchildren from different countries. First, we conducted a participatory design activity by an interdisciplinary team, resulting in the extraction of the design, robot’s roles, and technical requirements. Based on these requirements, we built the robot-mediation system prototype. We conducted a pilot study using the system with groups of high school children in Japan and Australia and our results show the potential of the system to drive children’s interest in communicating, sharing, and discussing cultural themes with their remote peers through the social robot.

The development and integration of robots capable of expressing gaze directionality through eye-head movements are crucial for effective human-robot interaction, especially for those with eye designs on 2D screens. Our proposed mutual eye-head gaze model aligns eye movements with head/body rotation, incorporating an attention engine for estimating the most saliency location, and a retina-fovea engine for precise gaze alignment. Additionally, the eye-head engine controls head movements, enhancing the robot’s ability to perform responsive coordinated eye-head gaze behaviors. This improvement leads to enhanced human subjective perception of direct gaze from the robot, ultimately holding potential for advancing human-robot interaction in social dynamics and human-centered robot development research.