M. Gharib

Papers

Total Citations

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About

M. Gharib is a robotics researcher whose work focuses on mobile robot localization, sensor fusion, and stochastic estimation methods. Their most-cited paper, "Mobile robot position estimation using Euler-Maruyama algorithm" (2019), introduces a novel approach to improving position accuracy in unmanned vehicles by applying stochastic differential equations to sensor data processing. This contribution addresses a critical challenge in autonomous navigation—reliable state estimation under uncertainty—and has garnered 7 citations, establishing a foundation for further work in probabilistic robotics. Gharib’s research bridges theoretical algorithm development and practical implementation for commercial, industrial, and military mobile robot applications, particularly in obstacle avoidance and environmental perception. By integrating the Euler-Maruyama method into position estimation frameworks, they offer a computationally efficient alternative to traditional filtering techniques, enhancing robustness in dynamic settings. This work is notable for its interdisciplinary approach, combining control theory, probability, and robotics, and positions Gharib as a contributor to advancing autonomous systems’ reliability in real-world deployments. Their ongoing efforts continue to explore sensor integration and adaptive estimation for complex environments.