Yuri Bubeev
Papers
3
Total Citations
14
H-Index
2
About
Yuri Bubeev is a researcher focused on the intersection of human cognition, manual control, and human-robot interaction. His primary research areas include perceptual-motor learning, complex task training, and the development of virtual environments for operator safety. Bubeev’s major contribution is the creation of a novel tool designed to investigate and facilitate learning in demanding manual control tasks requiring manipulation of six degrees of freedom, such as docking maneuvers. This work, detailed in his most-cited paper (2017, 8 citations), provides a framework for understanding individual learning curves in complex control scenarios. He further validated this tool’s efficiency in a 2019 study (4 citations), demonstrating its utility for self-sufficient learning. More recently, Bubeev has applied his expertise to human-UAV interaction, developing virtual environments to model operator behavior in enclosed, potentially dangerous spaces (2022, 2 citations). This work is critical for improving safety and response times in hazardous inspections. Through his focused research, Bubeev is advancing both fundamental knowledge of skill acquisition and practical applications for robotic systems.
Research Focus
Key Achievements
Top Papers
- 1A Tool to Facilitate Learning in a Complex ManualControl Task8 citations · 2017
- 2Individual Learning Curves in Manual Control of Six Degrees of Freedom4 citations · 2019
- 3