Human Robot
Human-robot interaction (HRI) research focuses on designing robots that can effectively collaborate with humans, encompassing physical tasks, communication, and shared decision-making. Current research emphasizes improving robot perception and control through techniques like model predictive control, reinforcement learning, and the integration of large language models for natural communication and intent recognition. These advancements aim to create safer, more efficient, and intuitive human-robot teams for applications ranging from industrial assembly to assistive robotics, impacting both the robotics and human-computer interaction fields.
Papers
Open-Ended Instructable Embodied Agents with Memory-Augmented Large Language Models
Gabriel Sarch, Yue Wu, Michael J. Tarr, Katerina Fragkiadaki
Robot-Assisted Navigation for Visually Impaired through Adaptive Impedance and Path Planning
Pietro Balatti, Idil Ozdamar, Doganay Sirintuna, Luca Fortini, Mattia Leonori, Juan M. Gandarias, Arash Ajoudani