Nowadays advances in robotics and computer science have made possible the development of sociable and attractive robots. A challenging objective of the field of humanoid robotics is to make robots able to interact with people in a believable way. Recent studies have demonstrated that human-like robots with high similarity to human beings do not generate the sense of unease that is typically associated to human-like robots. For this reason designing of aesthetically appealing and socially attractive robots becomes necessary for realistic human-robot interactions. In this paper HEFES (Hybrid Engine for Facial Expressions Synthesis), an engine for generating and controlling facial expressions both on physical androids and 3D avatars is described. HEFES is part of a software library that controls a human robot called FACE (Facial Automaton for Conveying Emotions). HEFES was designed to allow users to create facial expressions without requiring artistic or animatronics skills and it is able to animate both FACE and its 3D replica. The system was tested in human-robot interaction studies aimed to help children with autism to interpret their interlocutors' mood through facial expressions understanding. © 2012 IEEE

Abstract:Humans have an innate tendency to anthropomorphize surrounding entities and have always been fascinated by the creation of machines endowed with human-inspired capabilities and traits. In the last few decades, this has become a reality with enormous advances in hardware performance, computer graphics, robotics technology, and artificial intelligence. New interdisciplinary research fields have brought forth cognitive robotics aimed at building a new generation of control systems and providing robots with social, empathetic and affective capabilities. This paper presents the design, implementation, and test of a human-inspired cognitive architecture for social robots. State-of-the-art design approaches and methods are thoroughly analyzed and discussed, cases where the developed system has been successfully used are reported. The tests demonstrated the system's ability to endow a social humanoid robot with human social behaviors and with in-silico robotic emotions.

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Non-verbal signals expressed through body language play a crucial role in multi-modal human communication during social relations. Indeed, in all cultures, facial expressions are the most universal and direct signs to express innate emotional cues. A human face conveys important information in social interactions and helps us to better understand our social partners and establish empathic links. Latest researches show that humanoid and social robots are becoming increasingly similar to humans, both esthetically and expressively. However, their visual expressiveness is a crucial issue that must be improved to make these robots more realistic and intuitively perceivable by humans as not different from them. This study concerns the capability of a humanoid robot to exhibit emotions through facial expressions. More specifically, emotional signs performed by a humanoid robot have been compared with corresponding human facial expressions in terms of recognition rate and response time. The set of stimuli included standardized human expressions taken from an Ekman-based database and the same facial expressions performed by the robot. Furthermore, participants’ psychophysiological responses have been explored to investigate whether there could be differences induced by interpreting robot or human emotional stimuli. Preliminary results show a trend to better recognize expressions performed by the robot than 2D photos or 3D models. Moreover, no significant differences in the subjects’ psychophysiological state have been found during the discrimination of facial expressions performed by the robot in comparison with the same task performed with 2D photos and 3D models.