Robot-assisted feeding: A systematic review and future prospects

Abstract

BackgroundRobot-assisted feeding systems aim to promote independence for individuals with motor impairments. Despite significant technological progress, widespread adoption remains limited due to challenges related to adaptability, safety, and cost.ObjectiveThis review investigates recent advancements in robot-assisted feeding, highlights key technical and usability challenges, and outlines future directions to improve system adaptability, autonomy, and cost-effectiveness.MethodsA systematic literature search was conducted for peer-reviewed articles published in the past decade. The analysis focuses on critical domains including hardware architecture, human-robot interaction (HRI) modalities, and control strategies.ResultsAdvances in artificial intelligence (AI) and HRI have enhanced system autonomy and user adaptability. Nevertheless, unresolved issues persist in handling diverse food types, achieving real-time responsiveness, and minimizing system costs. Emerging solutions-such as adaptive learning, Artificial Intelligence of Things (AIoT) integration, and modular design-offer promising pathways to overcome these barriers and support scalable deployment in real-world care settings.