A ROS Architecture for Personalised HRI with a Bartender Social Robot
This work addresses the problem of user disengagement in service robotics for bartending applications, presenting an incremental improvement in human-robot interaction through personalization.
The paper tackles the challenge of maintaining user engagement with a bartending robot after the novelty effect wears off by developing a three-layer ROS architecture that integrates perception, decision-making, and execution for personalized interactions, resulting in a system designed to increase user loyalty through tailored services.
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.