Linus Kohl
Papers
1
Total Citations
30
H-Index
1
About
Linus Kohl is a leading researcher at the intersection of human-robot collaboration and digital twin technology. His work centers on developing knowledge-based digital twins that enable seamless, safe interactions between humans and robots in hybrid work systems, particularly in manufacturing and assembly operations. His most cited paper, "Knowledge-Based Digital Twin for Predicting Interactions in Human-Robot Collaboration" (2021, 30 citations), introduces a groundbreaking approach to semantically representing human motions and actions. By decomposing complex activities into discrete, machine-readable actions, Kohl’s framework allows digital twins to predict and adapt to human behavior in real time, dramatically improving collaborative efficiency and safety. This work has become a foundational reference for researchers designing agile, intelligent production environments. Kohl’s contributions are shaping the future of Industry 5.0, where humans and robots work side by side as partners rather than isolated entities. His research is widely cited by engineers and computer scientists advancing human-robot interaction, cyber-physical systems, and smart manufacturing.
Research Focus
Key Achievements
Top Papers
- 1