Papers
2
Total Citations
17
H-Index
2
About
Haleema Asif’s research lies at the intersection of robotic control, human-robot skill transfer, and intelligent automation. Her most-cited work, “Design and comparison of linear feedback control laws for inverse Kinematics based robotic arm” (13 citations), tackles the fundamental challenge of achieving precise, accurate robotic arm motion by solving inverse kinematics and designing efficient linear feedback controllers. This contribution is critical for enabling robots to perform tasks requiring high positional accuracy. In her subsequent work, “Preparation for Capturing Human Skills during Tooling Tasks Using Redundant Markers and Instrumented Tool” (4 citations), Asif addresses the complex domain of continuous contact tasks—such as deburring and grinding—which demand simultaneous force and position control. By developing a system to capture human expertise using redundant markers and instrumented tools, she pioneers methods to transfer nuanced human skills to robots, moving beyond simple repetitive automation. Her research has significant implications for advanced manufacturing, where robots must adapt to variable, contact-rich environments. Asif’s work demonstrates a clear trajectory from foundational control theory to applied human-robot collaboration, establishing her as a promising voice in the future of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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