Human Robot Interaction
Human-robot interaction (HRI) research focuses on designing robots that can effectively and naturally interact with humans, aiming to improve collaboration, communication, and overall user experience. Current research emphasizes developing robots capable of understanding and responding to diverse human behaviors, including speech, gestures, and even physiological signals, often employing machine learning models like vision transformers, convolutional neural networks, and reinforcement learning algorithms to achieve this. These advancements are significant because they pave the way for safer, more intuitive, and productive human-robot collaborations across various domains, from industrial settings to assistive technologies and service robotics.
Papers
Improving Human Legibility in Collaborative Robot Tasks through Augmented Reality and Workspace Preparation
Yi-Shiuan Tung, Matthew B. Luebbers, Alessandro Roncone, Bradley Hayes
SCRITA 2023: Trust, Acceptance and Social Cues in Human-Robot Interaction
Alessandra Rossi, Patrick Holthaus, Gabriella Lakatos, Sílvia Moros, Lewis Riches
Real-time Addressee Estimation: Deployment of a Deep-Learning Model on the iCub Robot
Carlo Mazzola, Francesco Rea, Alessandra Sciutti