Designing a Personality-Driven Robot for a Human-Robot Interaction Scenario

In this paper, we present an autonomous AI system designed for a Human-Robot Interaction (HRI) study, set around a dice game scenario. We conduct a case study to answer our research question: Does a robot with a socially engaged personality lead to a higher acceptance than a competitive personality? The flexibility of our proposed system allows us to construct and attribute two different personalities to a humanoid robot: a socially engaged personality that maximizes its user interaction and a competitive personality that is focused on playing and winning the game. We evaluate both personalities in a user study, in which the participants play a turn-taking dice game with the robot. Each personality is assessed with four different evaluation tools: 1) the Godspeed Questionnaire, 2) the Mind Perception Questionnaire, 3) a custom questionnaire concerning the overall HRI experience, and 4) a Convolutional Neural Network analyzing the emotions on the participants' facial feedback throughout the game. Our results show that the socially engaged personality evokes stronger emotions among the participants and is rated higher in likability and animacy than the competitive one. We conclude that designing the robot with a socially engaged personality contributes to a higher acceptance within an HRI scenario.