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
Quantifying Uncertainties of Contact Classifications in a Human-Robot Collaboration with Parallel Robots
Aran Mohammad, Hendrik Muscheid, Moritz Schappler, Thomas Seel
Safe Collision and Clamping Reaction for Parallel Robots During Human-Robot Collaboration
Aran Mohammad, Moritz Schappler, Tim-Lukas Habich, Tobias Ortmaier
Collision Isolation and Identification Using Proprioceptive Sensing for Parallel Robots to Enable Human-Robot Collaboration
Aran Mohammad, Moritz Schappler, Tobias Ortmaier
Towards Human-Robot Collaboration with Parallel Robots by Kinetostatic Analysis, Impedance Control and Contact Detection
Aran Mohammad, Moritz Schappler, Tobias Ortmaier