LAUSR

With the advancement of science and technology, humanoid robots have been gradually adopted in human society. Given the human‐like appearance, the perceived personality of a humanoid robot can affect humans' general perceptions of the robotic agent, and even task performance. However, limited research pays attention to examining how a humanoid robot's non‐verbal cues characterize its personality traits. To solve this gap, this research aims to investigate how to use humanoid robots’ non‐verbal features (textual and gestural information) to develop different kinds of personality attributes, and how these personality characteristics affect human‐robot interaction. A total of 255 participants were recruited for this research, including pilot tests and two rounds of lab studies examining different levels of task complexity. The empirical results reveal the developed gestural cues allow a humanoid robot to distinguishably convey extrovert, ambivert, and introvert personality traits, where the perceived traits significantly affect user intentions to interact with the humanoid robot.