Mohammed Zakariah

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About

Mohammed Zakariah is a robotics and signal processing researcher whose work bridges autonomous navigation and speech production systems. His key research areas include mobile robot localization, visual tracking, and articulatory speech synthesis. Zakariah’s most impactful contribution is his work on enhancing mobile robot localization using the extended Kalman filter (2016, 14 citations), where he developed a system to reduce cumulative errors in dead-reckoning methods caused by wheel slippage and surface roughness—critical for reliable autonomous navigation. He further advanced this field by integrating fuzzy logic with dead-reckoning for visual tracking in unknown environments (2016, 11 citations), enabling non-holonomic wheeled mobile robots to reach targets while avoiding obstacles without prior environmental maps. In a notable interdisciplinary shift, Zakariah also contributed to speech technology with a novel speech production system based on formant estimation from tongue articulatory motion (2020, 6 citations), offering a potentially non-obtrusive alternative for speech synthesis. His work demonstrates versatility across robotics and biomedical engineering, with cumulative citations reflecting growing interest in practical, sensor-driven solutions for real-world challenges.