About

Udo Frese is a prominent robotics researcher whose work spans simultaneous localization and mapping (SLAM), robot control, and real-time perception systems. He is perhaps best known for his groundbreaking contributions to SLAM algorithms, particularly his development of multigrid-inspired approaches that dramatically improved computational efficiency. His landmark 2005 paper introducing a multilevel relaxation algorithm for SLAM (288 citations) and his celebrated Treemap algorithm — achieving an remarkable O(log n) complexity for indoor mapping (125 citations) — fundamentally advanced the field's ability to scale to large, complex environments. His 2006 demonstration of closing a loop over one million landmarks showcased the practical power of these methods. Beyond mapping, Frese made significant contributions to robot manipulation and human-robot interaction, including work on Cartesian impedance control for DLR's light-weight arms (277 citations), a highly influential result in flexible joint robotics. His research also extends to dynamic real-world challenges, including pioneering systems for catching flying balls using stereo vision and multiple hypothesis tracking, and developing real-time self-collision detection for humanoid robots. Through this diverse yet cohesive body of work — accumulating hundreds of citations across multiple domains — Frese has established himself as a versatile and impactful figure in modern robotics research.

Research Focus

Key Achievements

21
H-Index
51
Papers
1,705
Total Citations
33
Avg Citations/Paper
🏆 Most Cited Paper
A multilevel relaxation algorithm for simultaneous localization and mapping
288 citations · 2005
📈 Most Prolific Year: 2011 (6 Papers)
🤝 Key Collaborators: 65
🏛 Institutions: University of Bremen, Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), Deutsches Forschungsnetz, German Research Centre for Artificial Intelligence, ABB (Norway), TU Dortmund University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago