Effects of Robot’s Adaptive Autonomy on Users Experience in a Museum Scenario

Integration of robots in society implies the need to design systems with adaptive behavior, especially in social domains like cultural heritage, healthcare, and education. This study examines user satisfaction when interacting with a robot guided by a computational cognitive model that incorporates Adjustable Social Autonomy principles. We conducted a within-subjects experiment in the Cultural Heritage domain, where museum visitors interacted with the humanoid robot Nao. The robot’s task was to recommend a museum exhibition to visit, exercising different degrees of autonomy based on its capability to have a theory of mind. The findings showed that as the robot’s autonomy in task adoption increased, user satisfaction with the robot decreased, while satisfaction with the tour itself improved. These results underscore the potential of adjustable social autonomy for developing autonomous adaptive social robots that enhance user experiences in Cultural Heritage scenarios like museums