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
Touch in Human Social Robot Interaction: Systematic Literature Review with PRISMA Method
Christiana Tsirka, Anna-Maria Velentza, Nikolaos Fachantidis
Demonstration of real-time event camera to collaborative robot communication
Laura Duarte, Michele Polito, Laura Gastaldi, Pedro Neto, Stefano Pastorelli
Human-centered In-building Embodied Delivery Benchmark
Zhuoqun Xu, Yang Liu, Xiaoqi Li, Jiyao Zhang, Hao Dong
Enhancing LLM-Based Human-Robot Interaction with Nuances for Diversity Awareness
Lucrezia Grassi, Carmine Tommaso Recchiuto, Antonio Sgorbissa
Real-Time Remote Control via VR over Limited Wireless Connectivity
H. P. Madushanka, Rafaela Scaciota, Sumudu Samarakoon, Mehdi Bennis