Comparing Cognitive and Affective Theory of Mind for an Assistive Robotics Application

Human-robot interaction in cooperative and assistive scenarios requires robotic systems to assess the task state and coherently choose their next move. Moreover, it is also fundamental to correctly recognize how the user's stress and emotional response are changing to offer support appropriately. The robot should be able to adapt to different user reactions, considering the situational context, and displaying empathetic behaviors aiming to support and encourage the users. In this work, we aim to assess the impact of empathetic supporting behaviors on the perception of the robot and the users' performance during a collaborative task, as opposed to assistive strategies focusing only on the task's performance. With this objective in mind, we propose a robotic architecture to assist a user in playing a memory game in real-time using a Furhat robot. We conducted a user study where 60 participants played with the robot to evaluate the effects of the two types of Theory of Mind on the assistive task and their perception of the robot. To this extent, the participants interacted with a robot endowed with either Cognitive or Affective Theory of Mind to respectively allow the robot to understand intentions and beliefs, and to show empathetic behaviors to improve the collaboration. The two conditions resulted in achieving the same results in terms of task performance, but the participants rated the emotionally engaged robot higher in perceived social intelligence.