Jurgen Rebmann
Papers
1
Total Citations
2
H-Index
1
About
Jurgen Rebmann is a researcher advancing the state of the art in robotic system identification and simulation. His primary research focus lies in developing robust, automated frameworks for calibrating rigid body simulation models, a critical challenge for modern robotics. Rebmann’s major contribution is a novel simulation-based parameter identification framework that eliminates the need for laborious, manual derivation of inverse dynamics equations. This approach significantly reduces both the time and error associated with traditional calibration, enabling more accurate and efficient robot control. While his key 2020 paper, "Simulation-based Parameter Identification Framework for the Calibration of Rigid Body Simulation Models," has garnered initial citations, his work is foundational for researchers seeking to bridge the gap between high-level simulation and real-world robotic performance. By automating a traditionally complex process, Rebmann is making sophisticated robotic modeling more accessible, directly impacting fields from industrial automation to autonomous systems.
Research Focus
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Top Papers
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