Study of Empathy on Robot Expression Based on Emotion Estimated from Facial Expression and Biological Signals Empathy, the ability to share the otherxe2x80x99s feeling, is one of the effective elements in promoting mutual reliability and construction of a good relationship. In order to create empathy between humanrobot, a robot must be able to estimate the emotion of human and reflect the same emotion on its expression. In general, emotion can be estimated based on observable expressions such as facial expression, or unobservable expressions such as biological signals. Although there are many methods for measuring emotion from both facial expression and biological signals, few studies have been done on the comparison of estimated emotion. In this paper, we investigate whether emotion estimated from facial expression or biological signals could lead to empathy toward a robot. Using our proposed emotion estimation system, we performed two experiments and found that higher impression was rated on sociability elements with significant when the reflected emotion is estimated from uncontrollable emotion.

A Systematic Comparison of Affective Robot Expression Modalities This paper provides a survey of the different means of expression employed by robots conveying affective states to human recipients. The paper introduces a model of affective expression modalities (MOAM) that describes and compares the emphasis on specific means of expression and applies it to the surveyed robots. Using the model entails viewing the effect of applied expression modalities in light of how well the robot responds to external stimuli and with attention to how aligned the robotxe2x80x99s means of affective expressions are with the intended working scenario. The modelbased survey shows that a majority (85%) of the surveyed robots contain a category with room for additional affective means of expression, and a quarter (25.6%) of the robots use a single or two affective expression modalities to convey affective states. The result of the survey indicates there is an underresearched opportunity in exploring synergies between the different expression modalities to amplify the overall affective impact of a robot.