The Impact of Social Inter-Robot Encounters on User Perception

摘要

In recent years, there has been a growing trend of integrating robots into various dimensions of daily life, to improve user experiences and offer a range of services. This study explores the interactions of robots showing social behavior towards other robots and their impact on human perceptions. We focus on three types of social behavior: social sensitivity, attention-sharing, and helping, aiming to understand how these interactions affect human perceptions of robots. Utilizing Duckiebot mobile robots in carefully crafted experimental setups, participants observed video recordings of these robots’ interactions, which either included or excluded each targeted social behavior. The study measured user responses using established scales such as the Mind Attribution Scale (MAS), the Goodspeed Scale, and the Robotic Social Attributes Scale (RoSAS). The results demonstrated that robots displaying social behavior towards other robots were perceived more positively compared to those that did not exhibit such behavior. Specifically, social sensitivity positively impacted animacy, experience, likability, perceived intelligence, safety, and warmth. Attention-sharing improved perceptions of competence, experience, likability, perceived intelligence, and warmth. Additionally, helping behavior positively affected agency, animacy, anthropomorphism, competence, experience, likability, perceived intelligence, safety, and warmth. This research contributes valuable insights into Human-Robot Interaction (HRI), highlighting the significant impact of robots’ interactions with each other on user experiences and perceptions. The exploration of social behavior lays a foundation for designing robots that evoke positive responses, fostering smoother integration of robotic technology into various aspects of society.