Daniel Regulin
Papers
9
Total Citations
85
H-Index
5
About
Daniel Regulin is a researcher specializing in human-robot collaboration, Industry 4.0 automation, and intelligent manufacturing systems. His work sits at the intersection of robotics, industrial engineering, and human factors, addressing one of modern manufacturing's most pressing challenges: making robotic systems genuinely accessible, safe, and collaborative in real-world factory environments. Regulin's most influential contribution, "A Human-Cyber-Physical System Approach to Lean Automation Using an Industrie 4.0 Reference Architecture" (2020, 28 citations), established a foundational framework for integrating collaborative manipulators into flexible production environments. His subsequent research on deformable linear object perception (2023, 23 citations) demonstrates a notable breadth, advancing computer vision techniques critical for robotic handling of cables and wires. Across multiple papers, he has consistently championed operator empowerment — exploring how task decision autonomy and user-centered design affect both ergonomics and robot performance, ensuring human workers remain central rather than peripheral to automation. Particularly noteworthy is his focus on small and medium enterprises, developing simplified teaching approaches and risk-aware collaborative robotics frameworks that lower barriers to adoption. With nearly 85 total citations and a growing body of work spanning perception, safety, and human-centered design, Regulin represents an important voice in shaping the humane and practical future of industrial automation.
Research Focus
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