Sohail Razzaq
Papers
1
Total Citations
7
H-Index
1
About
Sohail Razzaq is a robotics researcher whose work lies at the intersection of control systems, friction modeling, and industrial automation. His most-cited paper, "Control of an Anthropomorphic Manipulator using LuGre Friction Model - Design and Experimental Validation" (2021, 7 citations), tackles a critical challenge in flexible automation: achieving precise, autonomous control of robotic arms. By integrating the LuGre friction model into manipulator control, Razzaq addresses the nonlinear friction effects that degrade performance in real-world industrial settings, offering a validated design that bridges theory and practice. This contribution is pivotal for advancing the autonomy of anthropomorphic manipulators, which are central to modern manufacturing and service robotics. Beyond this work, Razzaq's research explores the broader landscape of automation technology, emphasizing practical solutions for emerging industrial applications. His findings have implications for improving precision and reliability in robotic systems, from assembly lines to collaborative environments. With a growing citation footprint, Razzaq is establishing himself as a thoughtful contributor to the field, demonstrating how nuanced modeling can unlock greater autonomy in robotics—a key step toward smarter, more adaptable factories.
Research Focus
Key Achievements
Top Papers
- 1