The Impacts of Social Humanoid Robot's Nonverbal Communication on Perceived Personality Traits

The use of humanoid robots has surged in recent decades. However, the nonverbal features in shaping robot personalities remain underexplored. This study investigates how nonverbal cues (including textual and gestural elements) can generate a spectrum of robot personality traits (introvert, ambivert, and extrovert) and evaluates their impact on users' cognitive perceptions. Textual manipulations involved three iterations, adjusting word count, information structure, and visual effects. Gestural designs underwent two iterations, altering movement frequency, speed, and size. Multiple empirical studies were conducted to assess the development of robot personality traits and their effects. The results confirm the effectiveness of these nonverbal approaches in characterizing diverse robot personalities and significantly influencing users' cognitive framing. This research provides valuable design guidelines for leveraging a humanoid robot's nonverbal features to create a variety of personality traits. Our findings emphasize the importance of considering a spectrum of robot personalities rather than focusing solely on extreme traits.