About

Niels Dehio is a leading researcher in multi-robot systems and whole-body control, whose work fundamentally advances how robots physically interact with their environment and with humans. His research centers on three interconnected areas: multi-objective task optimization, impact-aware control, and physical human-multi-robot collaboration. Dehio's major contributions include pioneering methods for continuously shaping projection operators in hierarchical control, enabling smooth transitions between task priorities—a critical advancement over traditional rigid prioritization schemes. His work on impact-aware control, with over 25 citations for his impact dynamics models, has transformed how robots can safely generate high-speed contacts, moving beyond the conventional near-zero velocity approach to enable dynamic tasks like rapid box grabbing. Notably, his 2021 study on impedance-based physical human-multi-robot collaboration, demonstrating four torque-controlled manipulators working with humans, represents a landmark achievement in the field. With over 200 total citations across his most-cited papers, Dehio's research at the intersection of control theory, impact mechanics, and multi-agent systems continues to shape the future of collaborative robotics.

Research Focus

Key Achievements

10
H-Index
17
Papers
258
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Multiple task optimization with a mixture of controllers for motion generation
32 citations · 2015
📈 Most Prolific Year: 2022 (4 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: Bielefeld University, Karlsruhe Institute of Technology, Technische Universität Braunschweig, Centre National de la Recherche Scientifique, Maastricht University, KUKA (Germany)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago