Collaborative Robot
Collaborative robots (cobots) aim to improve human-robot interaction by enabling safer and more efficient collaboration in various settings, primarily manufacturing and healthcare. Current research focuses on enhancing cobot adaptability through techniques like adaptive intelligence and self-labeling for improved intention recognition (often employing deep learning models such as MViT2), developing intuitive interfaces for programming and control (including natural language processing and mixed reality approaches), and optimizing robot motion for safety and ergonomics using methods such as model predictive control and reinforcement learning. These advancements are significantly impacting industrial productivity and the potential for assistive robotics in areas like rehabilitation and elder care.
Papers
Enabling Waypoint Generation for Collaborative Robots using LLMs and Mixed Reality
Cathy Mengying Fang, Krzysztof Zieliński, Pattie Maes, Joe Paradiso, Bruce Blumberg, Mikkel Baun Kjærgaard
Cellular-enabled Collaborative Robots Planning and Operations for Search-and-Rescue Scenarios
Arnau Romero, Carmen Delgado, Lanfranco Zanzi, Raúl Suárez, Xavier Costa-Pérez