Robert Krug
Papers
2
Total Citations
20
H-Index
2
About
Robert Krug is a robotics researcher whose work spans robot control, manipulation, and flexible manufacturing automation. His research focuses on developing intelligent systems that bridge the gap between classical robotics and modern machine learning approaches, with particular emphasis on making robots more precise, adaptable, and industrially deployable. Among his most notable contributions is his 2022 work on hybrid inverse dynamics models for impedance control, which has garnered 11 citations. This research addresses a longstanding challenge in robot control: accurately capturing complex, hard-to-model physical phenomena such as stick-slip friction alongside well-understood rigid body dynamics. By combining end-to-end learning with traditional physics-based modeling, Krug and colleagues demonstrated how robots can achieve both precise and compliant motion — a critical requirement for delicate manipulation tasks. His 2023 work on robotic e-Bike motor assembly, cited 9 times, reflects his interest in translating advanced manipulation capabilities into real-world flexible manufacturing contexts, tackling the practical challenges of deploying intelligent robots in industrial settings. Krug's research sits at a productive intersection of control theory, machine learning, and applied robotics, making meaningful contributions toward robots that can operate reliably and intelligently in complex, real-world environments.
Research Focus
Key Achievements
Top Papers
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