Renat Kermenov
Papers
6
Total Citations
47
H-Index
4
About
Renat Kermenov is a researcher at the forefront of intelligent manufacturing and human-robot collaboration, whose work bridges the gap between industrial robotics and adaptive automation. His primary research areas include anomaly detection, predictive maintenance, and the development of collaborative robotic systems for complex manufacturing tasks. Kermenov's most impactful contribution is his work on "Anomaly Detection and Concept Drift Adaptation for Dynamic Systems," which has garnered 23 citations and provides a general method for fault diagnosis in industrial collaborative robots operating in flexible manufacturing environments. He has also made significant strides in automating the hand layup process for composite parts, specifically addressing the challenging task of protective film removal using collaborative robots. His research extends to motor diagnosis techniques for Permanent Magnet Synchronous Motors (PMSMs), where he has compared Motor Current Signature Analysis and Motor Torque Analysis under transient conditions. Kermenov's recent work on human-robot co-transportation of flexible materials, including fabrics and composite materials, demonstrates his commitment to developing safe, ISO-compliant strategies for human-robot collaboration. His innovative approaches to near time-optimal trajectories and deformation constraints for co-transportation tasks highlight his ability to solve practical industrial challenges while maintaining safety standards.
Research Focus
Key Achievements
Top Papers
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