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

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