  BRILLO (Bartending Robot for Interactive Long-Lasting Operations) project has
the overall goal of creating an autonomous robotic bartender that can interact
with customers while accomplishing its bartending tasks. In such a scenario,
people's novelty effect connected to the use of an attractive technology is
destined to wear off and, consequently, it negatively affects the success of
the service robotics application. For this reason, providing personalised
natural interaction while accessing its services is of paramount importance for
increasing users' engagement and, consequently, their loyalty. In this paper,
we present the developed three-layers ROS architecture integrating a perception
layer managing the processing of different social signals, a decision-making
layer for handling multi-party interactions, and an execution layer controlling
the behaviour of a complex robot composed of arms and a face. Finally, user
modelling through a beliefs layer allows for personalised interaction.
