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About

Mohamed Emharraf is a researcher specializing in mobile robotics, autonomous navigation, and simultaneous localization and mapping (SLAM). His work focuses on enabling robots to intelligently perceive, map, and navigate unknown indoor environments — a foundational challenge in modern robotics. Emharraf's most influential contribution, his 2016 study on SLAM implementation for unknown indoor environments, has garnered 8 citations and addresses one of the field's core problems: equipping robots with the ability to localize themselves while constructing environmental maps in real time. His earlier work on grid map building and self-localization (2014) laid important groundwork for these approaches, while his research on interactive teleoperation models (2012) demonstrated a broader interest in human-robot interaction and remote control systems. More recently, his 2024 comparative analysis of LiDAR 2D and visual SLAM reflects an ongoing commitment to advancing indoor navigation technologies relevant to autonomous robots, smart homes, and industrial automation. Collectively accumulating over 20 citations, Emharraf's body of work spans more than a decade of sustained contribution to mobile robotics, making his research a valuable resource for students and practitioners exploring autonomous navigation and robotic mapping systems.