Ahmed Issa
Papers
5
Total Citations
40
H-Index
4
About
Ahmed Issa is a robotics and automation researcher whose work spans intelligent robotic systems, manipulator design, and advanced manufacturing technologies. His research integrates hardware development with sophisticated software frameworks, bridging theoretical modeling and practical implementation across a range of engineering challenges. Issa's most recognized contribution is his 2017 paper on intelligent maze-solving robots, which combines image processing with graph theory algorithms to enable autonomous shortest-path navigation — a work that has garnered 25 citations and remains his most influential publication. This study exemplifies his ability to fuse computer vision with algorithmic problem-solving in embedded robotic systems. Beyond autonomous navigation, Issa has made notable contributions to industrial manipulator design, developing palletizing and SCARA robotic systems controlled through Arduino, MATLAB, and LabVIEW platforms, each incorporating kinematics modeling using Denavit-Hartenberg parameters. His 5-DOF manipulator work further demonstrates his commitment to full-cycle robot development — from mechanical design through automated control. His 2019 foray into tele-operated, multi-material 3D printing reflects a growing interest in additive manufacturing innovation. Collectively, Issa's portfolio reveals a researcher dedicated to practical, interdisciplinary solutions at the intersection of robotics, vision systems, and intelligent automation.
Research Focus
Key Achievements
Top Papers
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- 2Palletizing Manipulator Design and Control Using Arduino and MATLAB4 citations · 2017
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