Discrimination of emotion from movement and addition of emotion in movement to improve human-coexistence robot´s personal affinity

This paper presents the result of trials of the discrimination of emotion from movement and the addition of emotion in movement on a teddy bear robot, aiming at both expressing a robot´s emotion by movement and improving a robot´s personal affinity. We addressed four kinds of emotion - joy, anger, sadness, and fear. In this research, two standpoints were considered - a performer and an observer - to establish the data of emotional movement used for analysis. The data of movement were collected as a performer´s standpoint and they were sorted out in an observer´s standpoint. In discriminating the emotion included in movement from the data of movement, both the method using Laban´s feature quantity and the method using principal component analysis were tried. By the discrimination using principal component analysis, about 70% of rate of correct discrimination was obtained on all the four emotions. The feature of movement that each emotion could be interpreted was presumed from the coefficient of the discrimination function obtained in the discrimination using principal component analysis. Using the obtained feature the design principle of movement to add emotion into a basic movement was defined. From the verification experiment, it was suggested that the movement which people can interpret the intended emotion with relatively high probability would be produced about joy and anger. About fear and sadness, since the movement to express those emotions has small and little motions, it would be difficult to distinguish the feature and to produce clear emotional movement.