Azura Che Soh

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About

Azura Che Soh’s research lies at the intersection of intelligent control systems, robotics, and mechatronic design, with a focus on enhancing robotic manipulation and autonomy. Her most cited work, “Effect of Fuzzy Logic Controller Implementation on a Digitally Controlled Robot Movement” (12 citations), explores how fuzzy logic can augment conventional controllers to improve robotic performance, demonstrating that intelligent control complements—rather than replaces—traditional approaches. In “Development of an Adjustable Gripper for Robotic Picking and Placing Operation” (11 citations), she addresses a critical challenge in industrial automation: designing grippers that can adapt to objects of varying shapes and sizes, moving beyond single-purpose designs. Her contributions extend to wireless robotics with “A wireless flipper robot using interface free controller” (5 citations), which introduces novel, simplified interfacing methods, and “Position control of arm mechanism using PID controller” (3 citations), where she applies rotary encoder feedback for precise gripper motion. Though her citation counts are modest, Soh’s work is foundational in practical robotics—bridging theory and application to make robotic systems more flexible, responsive, and accessible. Her research is particularly valuable for students and engineers seeking to integrate intelligent control with real-world robotic tasks.