Lu He
Papers
1
Total Citations
11
H-Index
1
About
Lu He is a leading researcher in intelligent manufacturing and human-robot collaboration, with a focus on dynamic task allocation and digital twin technologies. His most-cited work, "A dynamic task allocation framework for human-robot collaborative assembly based on digital twin and IGA-TS" (2025), has garnered 11 citations, establishing a novel framework that integrates digital twins with an improved genetic algorithm and tabu search to optimize real-time task distribution in collaborative assembly environments. This contribution addresses critical challenges in adaptive manufacturing, enhancing efficiency and safety in human-robot interactions. He’s research bridges theoretical optimization and practical implementation, offering scalable solutions for Industry 4.0. His work is notable for its interdisciplinary approach, combining artificial intelligence, robotics, and simulation, and has been recognized for its potential to transform flexible production systems. As an emerging scholar, He continues to advance the field, with his framework serving as a foundational reference for future studies in adaptive collaborative robotics and digital twin-driven automation.
Research Focus
Key Achievements
Top Papers
- 1