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 - Page 3
IRIS: An Immersive Robot Interaction System
Xinkai Jiang, Qihao Yuan, Enes Ulas Dincer, Hongyi Zhou, Ge Li, Xueyin Li, Julius Haag, Nicolas Schreiber, Kailai Li, Gerhard Neumann, Rudolf LioutikovDemonstrating a Control Framework for Physical Human-Robot Interaction Toward Industrial Applications
Bastien Muraccioli (CNRS-AIST JRL), Celerier Mathieu (CNRS-AIST JRL), Benallegue Mehdi (CNRS-AIST JRL), Venture Gentiane (CNRS-AIST JRL, UTokyo)
Cross-Modality Embedding of Force and Language for Natural Human-Robot Communication
Ravi Tejwani, Karl Velazquez, John Payne, Paolo Bonato, Harry AsadaA Null Space Compliance Approach for Maintaining Safety and Tracking Performance in Human-Robot Interactions
Zi-Qi Yang, Miaomiao Wang, Mehrdad R. KermaniSound Judgment: Properties of Consequential Sounds Affecting Human-Perception of Robots
Aimee Allen (1), Tom Drummond (2), Dana Kulić (1) ((1) Monash University - Australia, (2) University of Melbourne - Australia)
RDMM: Fine-Tuned LLM Models for On-Device Robotic Decision Making with Enhanced Contextual Awareness in Specific Domains
Shady Nasrat, Myungsu Kim, Seonil Lee, Jiho Lee, Yeoncheol Jang, Seung-joon YiIntegrating Reinforcement Learning and AI Agents for Adaptive Robotic Interaction and Assistance in Dementia Care
Fengpei Yuan, Nehal Hasnaeen, Ran Zhang, Bryce Bible, Joseph Riley Taylor, Hairong Qi, Fenghui Yao, Xiaopeng Zhao
Evaluating Efficiency and Engagement in Scripted and LLM-Enhanced Human-Robot Interactions
Tim Schreiter, Jens V. Rüppel, Rishi Hazra, Andrey Rudenko, Martin Magnusson, Achim J. LilienthalConnection-Coordination Rapport (CCR) Scale: A Dual-Factor Scale to Measure Human-Robot Rapport
Ting-Han Lin, Hannah Dinner, Tsz Long Leung, Bilge Mutlu, J. Gregory Trafton, Sarah Sebo
Testing Human-Hand Segmentation on In-Distribution and Out-of-Distribution Data in Human-Robot Interactions Using a Deep Ensemble Model
Reza Jalayer, Yuxin Chen, Masoud Jalayer, Carlotta Orsenigo, Masayoshi TomizukaInductive Learning of Robot Task Knowledge from Raw Data and Online Expert Feedback
Daniele Meli, Paolo FioriniGestLLM: Advanced Hand Gesture Interpretation via Large Language Models for Human-Robot Interaction
Oleg Kobzarev, Artem Lykov, Dzmitry TsetserukouMulti-face emotion detection for effective Human-Robot Interaction
Mohamed Ala Yahyaoui, Mouaad Oujabour, Leila Ben Letaifa, Amine Bohi