Muhammad Usman Asad
University of Lahore, Dalhousie University, University of the Punjab
Papers
16
Total Citations
101
H-Index
5
About
Muhammad Usman Asad is a robotics and control systems researcher whose work spans mobile robot navigation, fuzzy logic control, and bilateral teleoperation. Over more than a decade of research, he has made consistent contributions to the field of intelligent autonomous systems, with a particular focus on applying fuzzy logic and neural network methodologies to real-world robotic challenges. Asad's early work established his reputation in mobile robotics, where his comparative analysis of Mamdani and Takagi-Sugeno fuzzy controllers for obstacle avoidance (2011, 16 citations) remains his most influential contribution. He further extended this expertise through fuzzy logic controllers for wall tracking and path tracking in indoor environments, demonstrating practical, low-cost implementations suitable for differentially steered robots. His research evolved toward more complex control problems, including bilateral teleoperation systems. His 2019 composite state convergence scheme (13 citations) advanced the theoretical foundations of master-slave robotic teleoperation, while later work explored bipedal robot gait control and Takagi-Sugeno fuzzy modeling with H∞ performance guarantees. Across his portfolio, Asad demonstrates a commendable commitment to bridging theoretical control design with experimental validation, making his work particularly valuable for students and practitioners seeking implementable solutions in intelligent robotics.
Research Focus
Key Achievements
Top Papers
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- 2A composite state convergence scheme for bilateral teleoperation systems13 citations · 2019
- 3Fuzzy logic based wall tracking controller for mobile robot navigation12 citations · 2012
- 4Fuzzy Logic Based Path Tracking Controller for Wheeled Mobile Robots11 citations · 2014
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