Personalizing Care Through Robotic Assistance and Clinical Supervision - Sorrentino, Alessandra; Fiorini, Laura; Mancioppi, Gianmaria; Cavallo, Filippo; Umbrico, Alessandro; Cesta, Amedeo; Orlandini, Andrea (Frontiers in Robotics and AI, 2022)
By 2030, the World Health Organization (WHO) foresees a worldwide workforce shortfall of health-care professionals, with dramatic consequences for patients, economies and communities. Research in Assistive Robotics has experienced an increasing attention during the last decade demonstrating its utility in the realization of intelligent robotic solutions for health-care and social assistance, also to compensate such workforce shortage. Nevertheless, a challenge for effective assistive robots is dealing with a high variety of situations and contextualizing their interactions according to living contexts and habits (or preferences) of assisted people. This paper presents a novel cognitive system for assistive robots that rely on Artificial Intelligence (AI) representation and reasoning features/services to support decision-making processes of healthcare assistants. We propose an original integration of AI-based features, i.e., knowledge representation and reasoning and automated planning to: (i) define a human-in-the-loop continuous assistance procedure that help clinicians in evaluating and managing patients and; (ii) to dynamically adapt robot behaviors to the specific needs and interaction abilities of patients. The system is deployed in a realistic assistive scenario to demonstrate its feasibility to support a clinician taking care of several patients with different conditions and needs.