Adrian Kotelba
Papers
4
Total Citations
40
H-Index
4
About
Adrian Kotelba’s research lies at the frontier of human-robot collaboration, cognitive ergonomics, and industrial entropy modeling. His work redefines how we understand psychomotor work—the physical and cognitive tasks performed by humans, cyborgs, and robots—by introducing the **Principle of Least Psychomotor Action (PLPA)**. This variational framework models situated entropy in workplaces, showing how uncertainty in assembly, orientation, and task composition can be minimized to optimize performance. Kotelba’s most-cited paper (13 citations) applies PLPA to psychomotor work across three worker types, while his follow-up work (10 citations each) extends the model to cognitive factories and aligns human psychomotor traits with robots, exoskeletons, and augmented reality. His contributions offer a mathematical foundation for designing smarter, safer human-robot systems, with direct implications for Industry 4.0 and cyborg-enhanced labor. By treating entropy as a situated, measurable quantity, Kotelba provides engineers and researchers a powerful lens for reducing inefficiency in physical work—whether performed by a human hand, a robotic gripper, or a hybrid.
Research Focus
Key Achievements
Top Papers
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