Mushtaq Al-Mohammed
Papers
3
Total Citations
20
H-Index
3
About
Mushtaq Al-Mohammed is a robotics researcher specializing in adaptive control systems, robotic grasping, and assistive robotics. His work addresses one of the fundamental challenges in robotic manipulation: enabling robots to reliably grip novel, unknown objects with minimal and precisely calibrated force — a problem with profound implications for both industrial automation and assistive technology. Al-Mohammed's most influential contributions center on developing adaptive control frameworks for robotic grippers. His 2018 paper introduced a reduced-order adaptive controller enabling intuitive "1-click" grasping of previously unseen objects, garnering 9 citations. Building on this foundation, his 2022 work advanced the field further with a switched adaptive controller, demonstrating asymptotic stability through rigorous Lyapunov-based analysis across both translational and rotational grasping dynamics, earning 8 citations. Most recently, his 2025 research extends these principles into the UCF-MANUS intelligent assistive robotic manipulator — a second-generation system designed to enhance independence for users with physical disabilities, incorporating user-study-driven interface improvements. Collectively, Al-Mohammed's research bridges theoretical control design and real-world assistive applications, making meaningful strides toward robots that can interact safely and intelligently with unstructured environments.
Research Focus
Key Achievements
Top Papers
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