Yoav Kerner

Papers

Total Citations

H-Index

About

Yoav Kerner is a researcher whose work lies at the intersection of human-robot collaboration and optimization. His primary research area focuses on modeling and improving coordination dynamics between humans and autonomous systems, with a particular emphasis on minimizing idle time and enhancing task synchronization. Kerner’s most notable contribution is his analytical framework for Human-Robot (H-R) coordination, introduced in his highly cited 2013 paper, which has garnered 13 citations. This work systematically identifies the key parameters and decision variables that govern waiting times in collaborative settings, providing a foundational model for designing more efficient human-robot teams. By quantifying how factors like task allocation and communication latency affect overall system performance, Kerner’s research offers practical insights for fields ranging from manufacturing to service robotics. His rigorous approach to optimization has made his work a reference point for subsequent studies in human-robot interaction, demonstrating a clear impact on the growing body of literature aimed at achieving seamless, high-synchronization collaboration between human and robotic agents.