The Affective Loop: A Tool for Autonomous and Adaptive Emotional Human-Robot Interaction

The paper presents an affective model for social robotics, where the robot is capable of behavior adaptation, in accordance with the needs and preferences of a particular user. The proposed approach differs from other studies in human-robot interaction as these usually have been using the 'Wizard of Oz' technique, where a person remotely operates a robot. On the other side, simulated robots are not able of personalized behaviors and behave according to the preprogrammed set of rules. We provide a tool to personalize affective artificial behaviors in cooperative human-robot scenarios, where human emotion recognition, appropriate robotic behavior selection and expression of robotic emotions play a key role. The preliminary experiments show that the personalized affective robotic behavior can achieve better results in a scenario in which a robot motivates children in learning. We believe that human-robot interfaces which mimic how humans interact with one another in an empathic way could ultimately lead to robots being accepted in the wider domain.