Human Robot Collaboration
Human-robot collaboration (HRC) focuses on designing systems where humans and robots work together efficiently and safely to achieve shared goals. Current research emphasizes improving communication and understanding between humans and robots, often employing large language models (LLMs), deep learning models for perception (e.g., computer vision, human pose estimation), and advanced planning algorithms (e.g., hierarchical task networks, Bayesian optimization) to enable more natural and adaptable interactions. This field is crucial for advancing automation in various sectors, from manufacturing and construction to healthcare and domestic settings, by creating more efficient, safer, and user-friendly collaborative workspaces.
Papers
Vocal Sandbox: Continual Learning and Adaptation for Situated Human-Robot Collaboration
Jennifer Grannen, Siddharth Karamcheti, Suvir Mirchandani, Percy Liang, Dorsa Sadigh
Improving Trust Estimation in Human-Robot Collaboration Using Beta Reputation at Fine-grained Timescales
Resul Dagdanov, Milan Andrejevic, Dikai Liu, Chin-Teng Lin