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Abstract-This paper describes a new methodological approach and robot system to trigger more prosocial human reactions towards a robot by transferring social-psychological principles from human-human interaction to human-robot interaction (HRI). The main idea is to trigger increased helpfulness by proactively creating similarity through dynamic emotional adaption of the robot to the mood of the human. This is achieved in an explicit and implicit way: Explicitly, by a similarity-statement of the robot of being in the same mood as the user, and implicitly by controlling the affective parameters of facial and verbal expressions of a robot head in an interaction scenario such that the current values of the human mood in the dimensions of pleasure, arousal, and dominance (PAD) are matched. In a first step, this is accomplished by an initial self-assessment by the human participant to be extended by automatic emotion recognition modules in a later stage. The effectiveness of the approach is confirmed by significant experimental results.

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This article describes an emotional adaption approach to proactively trigger increased helpfulness towards a robot in task-related human-robot interaction (HRI). Based on social-psychological predictions of human behavior, the approach aims at inducing empathy, paired with a feeling of similarity in human users towards the robot. This is achieved by two differently expressed emotional control variables: by an explicit statement of similarity before task-related interaction, and implicitly expressed by adapting the emotional state of the robot to the mood of the human user, such that the current values of the human mood in the dimensions of pleasure, arousal, and dominance (PAD) are matched. The thereby shifted emotional state of the robot serves as a basis for the generation of task-driven emotional facial-and verbal expressions, employed to induce and sustain high empathy towards the robot throughout the interaction. The approach is evaluated in a user study utilizing an expressive robot head. The effectiveness of the approach is confirmed by significant experimental results. An analysis of the individual components of the approach reveals significant effects of explicit emotional adaption on helpfulness, as well as on the HRI-key concepts anthropomorphism and animacy.

An emotion core for autonomous robots based on a hidden Markov model is proposed. Different emotional robot characters can be designed by tuning state transition probabilities. Perception of stimuli has an impact on emotional state transitions, and, thus, affects emotion dynamics and observable expressions/actions. This paper proposes the methodology of design and implementation, and shows integration into a decision and control architecture. The application potential in emotion-based human-robot interaction is discussed.