Ergonomic Role Allocation Framework

Ergonomic role allocation frameworks aim to optimize human-robot collaboration (HRC) by assigning tasks to humans or robots based on ergonomic risk assessments, minimizing musculoskeletal disorders and maximizing efficiency. Current research focuses on developing dynamic allocation methods using models like AND/OR graphs and incorporating real-time human state measurements (e.g., posture, muscle activity) with machine learning algorithms (e.g., reinforcement learning) to predict and mitigate ergonomic risks. This research is significant for improving workplace safety and productivity by creating more comfortable and efficient HRC systems across various industries, from manufacturing to healthcare.