Engaged by a Bartender Robot: Recommendation and Personalisation in Human-Robot Interaction

Abstract

BRILLO (Bartending Robot for Interactive Long-Lasting Operations) project aims to deploy an autonomous robotic bartender that can naturally interact with customers in a real-world service point. In such a scenario, this work presents a multi-modal personalised recommendation method for increasing users’ engagement with a bartending robot. The personalised recommendation is adopted at two levels: one for the recommendation of the service (i.e. drinks), and another for selecting the human-robot interaction (HRI) modalities. The envisioned multi-modal personalised recommendation method enables the BRILLO robot to intelligently adapt its dialogues, pose and gestures, according to the user’s moods, attention behaviours, personal traits, and situational context (drink orders, group dynamics, etc.).