Shaikh
Papers
1
Total Citations
19
H-Index
1
About
Shaikh’s research lies at the intersection of robotics, adaptive control, and human-robot interaction, with a focus on developing intelligent systems that can safely and effectively collaborate with humans. Their most notable contribution is the introduction of a novel model reference adaptive impedance control framework for physical human-robot interaction, published in 2016. This work addresses the critical challenge of ensuring both stability and task performance when robots work alongside human operators. Shaikh’s approach features a dual-loop architecture: an inner neuroadaptive loop that learns robot dynamics online, enabling the robot to behave like a prescribed impedance model without relying on task-specific information, and an outer loop that adapts this impedance to account for human operator dynamics. The result is a controller that delivers improved task performance through two adaptive impedance features and assistive inputs. With 19 citations, this paper has influenced subsequent research in adaptive human-robot collaboration. Shaikh’s work is particularly valuable for students and researchers interested in designing robots that can intuitively and safely assist humans in shared tasks, such as rehabilitation or manufacturing.
Research Focus
Key Achievements
Top Papers
- 1