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
PGA: Personalizing Grasping Agents with Single Human-Robot Interaction
Junghyun Kim, Gi-Cheon Kang, Jaein Kim, Seoyun Yang, Minjoon Jung, Byoung-Tak Zhang
Object-Aware Impedance Control for Human-Robot Collaborative Task with Online Object Parameter Estimation
Jinseong Park, Yong-Sik Shin, Sanghyun Kim