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
Workspace Optimization Techniques to Improve Prediction of Human Motion During Human-Robot Collaboration
Yi-Shiuan Tung, Matthew B. Luebbers, Alessandro Roncone, Bradley Hayes
Integrating Human Expertise in Continuous Spaces: A Novel Interactive Bayesian Optimization Framework with Preference Expected Improvement
Nikolaus Feith, Elmar Rueckert