Investigation of Perception Towards Robot Expressions Considering Attitude and Personality

Abstract

As robots become ever more sophisticated, ubiquitous, and continue to permeate into our everyday life, an important agenda for future studies will be to design and evaluate robots that can adapt its expressions based on user characteristics in real-time and study their effect on perception of the user. To explore the effective expression in human-robot interaction, we intended to endow the humanoid robot Pepper with seven expression patterns showing different combinations of voice and motion traits. The Negative and Anxiety Scale and Big Five Domain Scale were chosen as the phycological indicators, and an online video-based questionnaire was utilized to investigate human perception of robot different expressions. Results have uncovered that robot's different expressions can elicit individual distinguishing evaluations towards robot. The prominent distinction of personal perceptions among different participants emerges from the data, boosting the idea that the personalized robot with adaptive expression is essential for different individuals and various scenarios. This study provides the first investigations into how to make social robots generate appropriate reactions according to individual inner conditions including personality and attitude towards robots. Keywords: human-robot interaction (HRI), human perception, negative and anxiety attitudes, personality Social robots have become the part of our everyday lives. Research in social robotics has shown its potential impact on numerous applications by assisting people in various scenarios [1]. However, few studies focused on the cognitive, psychological, and social determinants that impact the design of robots' communication strategies. By providing the evidence of human perception difference, the interdisciplinary study can be an effective tool to promote the development of user-centered design for human-robot interaction (HRI). A significant challenge obstructing present progress is how to achieve harmonious communication between humans and robots. To address this, more and more research in the field of HRI has focused on adapting the behavior of a robot to the user it interacts with. The adaptation can be based on the personality of the user, the affective state of the user, or different body signals [2-4]. Besides the impact of the mere physical presence of the robot on human in the HRI literature, it emerges that the design of the ways robot's interact with the users may also affect how people judge its behavior, how they react to it, and their task performance [5-7]. Unraveling human perception of social robots is vital to mapping how people understand others' mental states, explain as well as predict their behavior, determine the most appropriate behavioral response, and maintain relationships. Such perspectives could prove beneficial in human-robot coordinative mechanisms, which are crucial in supporting more effective and efficient interactions. However, studies among different disciplines have heretofore failed to fully get through mechanisms of human cognition, making robots duplicate the mechanism of the Graduate School of Systems Design, Tokyo Metropolitan University human mind seem hopeless [8]. Additionally, the social signals are perceived as blunted when displayed by a virtual agent, regardless of whether its appearance was realistic or simple [3]. And while parameters allow for sophisticated social expressions, a question emerges as to whether this is necessary, as people are already able to recognize intentional social signals from behavior patterns from a robot [9]. Some research has substantiated that there is a sophisticated relationship between people's attitudes, personality and emotions toward the robots and their behaviors in the interaction with social robots [10-12]. The research is still insufficient when it comes to deciphering robot's expressions considering the particular task and individual psychological traits. Maintaining this emphasis on social robotics places the objective of attaining more natural and automatic interaction at the forefront of our study, with a focus on verbal and non-verbal communicative cues. We also stress that, for more natural and long-term interaction to be possible in HRI, embodied individual perception differences must be taken into account. In this study, considerable attention has been paid to the relationship among one's personality , attitudes towards robots and how people perceive robots' expression styles given that the meaningful interaction requires the understanding and integration of those factors. To be more specific, an experiment was performed including videos showing different robot expression styles, and online questionnaire using the Likert-scale method were utilized to explore the influence of the robot expression on human perception. The design of robot expression style is based on different motion (head and arm) and verbal features (pitch and speed). Given the hypothesis that there would be a gap among different individuals' perception because of personal mental state discrepancy, on one hand, we involved the attitudes scale-Negative Attitudes toward Robots Scale and 777