A Lightweight Artificial Cognition Model for Socio-Affective Human-Robot Interaction

Abstract

The software submission presents a fully working artificial cognition model, which controls a NAO social robot. The model was specifically designed to control a socio-affective companion robot for use in a medical setting. It was deployed using embedded hardware: a Raspberry Pi 4B and a Jetson Nano Board, and an external RGB-D camera. Based on the ROS operating system, this software package includes components for social signal processing, behaviour selection, affective behaviour rendering, and a web-based user interface. The robot's behaviours are selected by a planning system, which generates the robot's behaviours based on the state of the interaction, the progress of the medical procedure, and the user's affective state. The system has been tested in simulated environments and is currently being used in two clinics to perform a usability test and will subsequently be used to carry out a series of clinical trials