Mahmoud Gabalah

Arab Academy for Science, Technology, and Maritime Transport

Papers

Total Citations

H-Index

About

Mahmoud Gabalah is a robotics researcher whose work centers on autonomous systems and intelligent material handling, with a particular focus on mechatronics and computer vision. His most-cited paper, "Design of an Autonomous Forklift Using Kinect" (2018), has garnered 11 citations and exemplifies his hands-on approach to solving real-world industrial challenges. In this work, Gabalah details the full mechatronics design and implementation of a self-driving forklift that leverages a Kinect sensor for perception, aiming to reduce labor costs and human fatigue in factory environments. His contributions lie at the intersection of robotics, automation, and sensor integration, demonstrating how off-the-shelf depth cameras can be repurposed for autonomous navigation and object manipulation in logistics. While his citation count is modest, Gabalah’s work represents a practical, applied contribution to the field of autonomous mobile robots, offering a blueprint for cost-effective automation in manufacturing. His research is particularly relevant for students and engineers interested in the end-to-end design of robotic systems, from hardware integration to control algorithms, and highlights the growing role of autonomous ground vehicles in modern industry.