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
Providers-Clients-Robots: Framework for spatial-semantic planning for shared understanding in human-robot interaction
Tribhi Kathuria, Yifan Xu, Theodor Chakhachiro, X. Jessie Yang, Maani Ghaffari
Toward Ethical Robotic Behavior in Human-Robot Interaction Scenarios
Shengkang Chen, Vidullan Surendran, Alan R. Wagner, Jason Borenstein, Ronald C. Arkin
Preference Change in Persuasive Robotics
Matija Franklin, Hal Ashton