Manuel Zaremski
Papers
2
Total Citations
11
H-Index
2
About
Manuel Zaremski is a researcher at the forefront of agile and human-robot collaboration in manufacturing, with a specific focus on the challenging domain of remanufacturing. His work addresses a critical industrial tension: the need for extreme flexibility in uncertain environments versus the high cost of both human labor and traditional robot programming. Zaremski’s key contributions lie in developing systems that enable robots to learn and adapt. His most cited work, "Agiles Produktionssystem mittels lernender Roboter bei ungewissen Produktzuständen" (2022, 7 citations), proposes a learning robotic system for agile disassembly of starters, showcasing how robots can handle unpredictable product conditions. Complementing this, his research on "Erfassung und Interpretation menschlicher Handlungen" (2022, 4 citations) explores intuitive programming by demonstration, allowing workers to teach robots through natural actions rather than complex code. By bridging machine learning with practical production needs, Zaremski is paving the way for cost-effective, flexible automation in remanufacturing, making his work essential for anyone interested in the future of sustainable, intelligent manufacturing systems.
Research Focus
Key Achievements
Top Papers
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