M. Bayoumi

Papers

Total Citations

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About

M. Bayoumi is a researcher focused on autonomous robotics and computer vision, with particular expertise in indoor positioning and mobile robot navigation. Their most impactful work, "A Low Cost Indoor Positioning System Using Computer Vision" (2019, 8 citations), addresses a critical challenge in robotics: the limitations of GPS in indoor environments. By developing a vision-based alternative, Bayoumi offers a practical solution for precise localization where satellite signals fail, enabling more reliable autonomous operation in warehouses, factories, and other indoor settings. This contribution is especially valuable for the growing field of service and industrial robotics. Earlier work, "Vision-Based Road Tracking of Wheeled Mobile Robot" (2013, 2 citations), laid groundwork in autonomous navigation, exploring how wheeled mobile robots can follow paths without human guidance—a capability essential for applications from logistics to military reconnaissance. Bayoumi’s research bridges the gap between theoretical computer vision and real-world robotic autonomy, providing cost-effective methods that make advanced robotics more accessible. Their work continues to support the development of fully autonomous systems capable of operating in unstructured environments, contributing to the broader goal of robots that can navigate and interact with the world independently.