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About

Dr. Said Grami is a robotics researcher whose work centers on intelligent control systems, mobile robot navigation, and friction compensation in robotic manipulators. His most impactful contribution, the 2019 paper “A Vision-Based Kinematic Tracking Control System Using Enhanced-PRM for Differential Wheeled Mobile Robot” (11 citations), introduces a novel integration of vision sensors with an enhanced probabilistic roadmap (PRM) algorithm, enabling differential wheeled robots to achieve precise kinematic tracking in dynamic environments. This work bridges computer vision and motion planning, offering a practical solution for autonomous navigation. Dr. Grami has also made significant strides in addressing the persistent challenge of friction in robot manipulators. His 2013 study on GMS (Generalized Maxwell Slip) friction compensation (8 citations) employs an online least-squares algorithm to model and counteract realistic friction in a two-degree-of-freedom planar robot, improving control accuracy. Subsequent works, including a 2021 paper using artificial neural networks (2 citations), extend this research into adaptive, learning-based approaches. With a cumulative citation count of 24, Dr. Grami’s contributions are foundational for researchers developing robust, real-world robotic systems, particularly in precision manufacturing and autonomous vehicles.