Nico Huebel
ETH Zurich, KU Leuven, Flanders Make (Belgium), University of Antwerp
Papers
10
Total Citations
133
H-Index
5
About
Nico Huebel is a robotics researcher whose work spans robot learning, autonomous navigation, knowledge representation, and human-robot interaction. He is perhaps best known for his pioneering research in robotic calligraphy, where he developed a robot testbed capable of learning to write Chinese and Japanese characters through visual feedback and spline-based stroke representation — work that attracted over 40 citations and opened new avenues for studying motor learning in robotic systems. His contributions to indoor robot navigation are equally significant, with his semantic mapping extension for OpenStreetMap — garnering 33 citations — providing robots with rich topological and geometric environmental understanding. Huebel has also advanced the field through time-optimal trajectory generation for robotic manipulators and database benchmarking tools for multi-robot systems. His later work explores transformer-based sonar perception, heterogeneous knowledge integration for search and rescue missions, and clutter-resilient navigation, reflecting a career-long commitment to making robots more adaptable and intelligent in complex real-world environments. With nearly 130 total citations across diverse research threads, Huebel represents a versatile contributor to modern robotics whose influence reaches from low-level motor control to high-level semantic reasoning.
Research Focus
Key Achievements
Top Papers
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- 3Towards robotic calligraphy21 citations · 2012
- 4Time-Optimal Online Trajectory Generator for Robotic Manipulators15 citations · 2013
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