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
HyperPalm: DNN-based hand gesture recognition interface for intelligent communication with quadruped robot in 3D space
Elena Nazarova, Ildar Babataev, Nipun Weerakkodi, Aleksey Fedoseev, Dzmitry Tsetserukou
Exploring Human-robot Interaction by Simulating Robots
Khaled Kassem, Florian Michahelles
Task-Agnostic Adaptation for Safe Human-Robot Handover
Ruixuan Liu, Rui Chen, Changliu Liu