2021 年 33 巻 4 号 p. 777-786
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.