Towards Engagement Models that Consider Individual Factors in HRI: On the Relation of Extroversion and Negative Attitude Towards Robots to Gaze and Speech During a Human–Robot Assembly Task

Abstract

Estimating the engagement is critical for human -robot interaction. Engagement measures typically rely on the dynamics of the social signals exchanged by the partners, especially speech and gaze. However, the dynamics of these signals is likely to be influenced by individual and social factors, such as personality traits, as it is well documented that they critically influence how two humans interact with each other. Here, we assess the influence of two factors, namely extroversion and negative attitude toward robots, on speech and gaze during a cooperative task, where a human must physically manipulate a robot to assemble an object. We evaluate if the score of extroversion and negative attitude towards robots co-variate with the duration and frequency of gaze and speech cues. The experiments were carried out with the humanoid robot iCub and N=56 adult participants. We found that the more people are extrovert, the more and longer they tend to talk with the robot; and the more people have a negative attitude towards robots, the less they will look at the robot face and the more they will look at the robot hands where the assembly and the contacts occur. Our results confirm and provide evidence that the engagement models classically used in human-robot interaction should take into account attitudes and personality traits.

Predicting Extraversion from Non-verbal Features During a Face-to-Face Human-Robot Interaction

“…Preliminary analysis on the EDHHI dataset reveal that extroversion and NARS influence the production of gaze and speech [9]. Here, we contend that it is possible to predict the human's extraversion from the analysis of non-verbal features.…”

“…Meerbeek et al [13] provided guidelines to design and evaluate personality and expressions in autonomous domestic robots. An important line of research is to probe into the influence of personality and individual traits on the production of verbal and non-verbal signals during HRI, as done in [9] and in our study.…”

“…Currently, a crucial challenge for Human-Robot Interaction (HRI) is the automated online estimation of the latter, such as personality traits, and the study of how they influence the exchange of verbal and non-verbal signals, as well the mechanisms underlying the production of behaviors, emotions and thoughts. These issues have been investigated in the project EDHHI [9] 1 , focused on studying social interactions between humans and the humanoid robot iCub. Within EDHHI, the researchers investigated how the production of social signals during HRI is influenced by individual factors, such as personality traits and attitude towards robots.…”

One-Shot Evaluation of the Control Interface of a Robotic Arm by Non-experts

“…Our French adaptation was used [1]. The participants also filled two post-experimental questionnaires consisting of questions/affirmations adapted from usability and technology acceptance models to a robotic context as it was done in previous works [12,9].…”

“…There is indeed prior evidence that some personality traits have significant effects on the perceived ease of use of new technologies, such as smartphones [7]. There is also evidence that personality traits and attitudes have some influence in HRI in the context of social robotics [1]. It seems therefore rational to explore the relation between individual factors and the user perception and performance in controlling a robot.…”