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About

Abdelkader Mami is a researcher whose work sits at the intersection of robotics, embedded systems, and intelligent control. His primary research areas include field programmable gate array (FPGA) circuit design, fuzzy logic control, and multi-robot swarm optimization. Mami’s major contributions span from hardware-level motor control to high-level autonomous navigation. Notably, he explored the use of low-consumption, rapid-response FPGA circuits for controlling DC motors in small robotic prostheses, offering an attractive solution for restoring mobility. In the domain of agricultural robotics, he developed a comprehensive dataset for smart harvesting of Deglet Nour date palms, addressing key computer vision tasks like branch detection and optimal cutting point localization. His work on fuzzy logic control has advanced safe and adaptive mobile robot navigation in complex environments, while his research on democratic multi-robot exploration introduced a novel method for computing the global best parameter in Particle Swarm Optimization. With several papers published in 2023 and 2025, Mami’s contributions are gaining traction, with his most cited works accumulating 3 and 2 citations respectively, signaling growing interest in his practical, application-driven approach to robotics and intelligent systems.