Building a behaviour architecture: An approach for promoting human-robot interaction

Abstract

Human distraction behaviour is a paramount subject to take into account. Several woks in the literature try to tackle this topic mostly in the automotive industry. Following this trend, the present work proposes a system to detect the patterns of distraction/attention during an interaction activity between a human and a robot. The goal is to analyse selected patterns of distraction, such as eye gaze, head pose, blinking rate, among others, and adapting the robot behaviour, consequently promoting a more fluid interaction. A behavioural state machine that takes into account the engagement and the performance of the user in the activity is proposed.