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About

Omar Y. Ismael is a robotics researcher whose work spans autonomous navigation, omnidirectional locomotion, brain-computer interfaces, and robust control systems. His most impactful contribution, a 2024 paper on Nonlinear Model Predictive Control (NMPC) for collision avoidance, has already garnered 11 citations by proposing a single-layer LiDAR-based system that safely navigates cluttered environments with unknown static and dynamic obstacles. Ismael has also made foundational advances in omnidirectional mobile robots, with two 2016 papers (totaling 13 citations) detailing the analysis, design, and implementation of three-Omni-wheel platforms—including one integrating a low-cost CMUcam5 Pixy vision system for ball tracking and following. His 2022 work on shared control of a robot arm using BCI and computer vision (6 citations) addresses the challenge of noisy, low-dimensional neural commands by fusing them with visual feedback for high-DOF teleoperation. Most recently, his 2025 paper on robust magnetic levitation control via linear extended state observer (LESO) feedback linearization, optimized by a modified flood algorithm, demonstrates his versatility in applying advanced control theory to mechatronic systems. Ismael’s research consistently bridges theoretical control methods with practical robotic implementations, making him a notable figure in autonomous systems and human-robot interaction.