Bakur
Papers
1
Total Citations
19
H-Index
1
About
Bakur’s research lies at the intersection of robotics, control theory, and human-robot interaction, with a focus on adaptive impedance control for physical collaboration. Their most cited work, “Model reference adaptive impedance control for physical human-robot interaction” (2016, 19 citations), introduces a novel dual-loop control system that ensures stability and task performance. The inner neuroadaptive loop learns robot dynamics in real time, enabling the robot to behave like a prescribed impedance model without requiring task-specific trajectory information. The outer loop adapts this impedance to account for human operator dynamics, optimizing joint system behavior for task goals. This non-standard model reference adaptive control framework yields a controller that simultaneously provides adaptive impedance characteristics and assistive inputs, demonstrably improving task performance in human-robot teams. Through simulation of repetitive point-to-point motion tasks, Bakur showed that their approach enhances coordination and reduces effort for human partners. This work represents a significant step toward safer, more intuitive physical human-robot collaboration, with potential applications in manufacturing, rehabilitation, and assistive robotics.
Research Focus
Key Achievements
Top Papers
- 1