Dino Bortot

Technical University of Munich

Papers

7

Total Citations

216

H-Index

6

About

Dino Bortot is a researcher specializing in human-robot interaction (HRI), human-machine systems, and collaborative automation in industrial environments. His work sits at the intersection of robotics, cognitive ergonomics, and safety engineering, with a focus on making shared workspaces between humans and machines both safer and more efficient. Bortot's most influential contribution is his taxonomic framework for human-machine cooperation, published in 2012 and cited 64 times, which systematically categorizes cooperative systems across five layers — intention, modes of cooperation, allocation, interfaces, and contact — providing a foundational reference for designers of assistance systems. Complementing this, his 2011 work on human arm motion modeling (53 citations) advanced the field by demonstrating how predicting operator movement patterns can enable robots to respond adaptively and safely in real time. His investigations into robot trajectory design — exploring whether industrial robots should approach humans directly or via detours — garnered significant attention (collectively over 65 citations), offering practical design guidance rooted in empirical behavioral research. His earlier 2010 studies laid important groundwork for integrating human behavioral models into robot control systems. Across his body of work, Bortot has made enduring contributions to the principles governing safe, intuitive, and efficient human-robot collaboration in industrial settings.

Research Focus

Key Achievements

6
H-Index
7
Papers
216
Total Citations
31
Avg Citations/Paper
🏆 Most Cited Paper
Interaction Principles for Cooperative Human-Machine Systems
64 citations · 2012
📈 Most Prolific Year: 2012 (2 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Technical University of Munich

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago