Haidi Ibrahim
Papers
5
Total Citations
153
H-Index
4
About
Haidi Ibrahim is a leading researcher in robotics and computer vision, with a primary focus on advancing Simultaneous Localization and Mapping (SLAM) systems for dynamic and unstructured environments. His major contributions include the development of MVS-SLAM, an enhanced multiview geometry approach that significantly improves semantic RGBD SLAM performance in environments with moving objects, and FADM-SLAM, a fast and accurate dynamic intelligent motion SLAM system designed for autonomous robot exploration involving movable objects. These works address critical limitations of traditional SLAM systems, which typically assume static environments. Ibrahim's research has garnered substantial attention, with his most cited paper, "MVS-SLAM," accumulating 55 citations since 2023, and his comprehensive survey on homomorphic filtering techniques in frequency domain earning 42 citations. Beyond SLAM, he has contributed to digital image enhancement, particularly for poor illumination conditions, and has explored navigation principles for AGVs and AMRs. Ibrahim also co-edited the proceedings of the 9th International Conference on Robotic, Vision, Signal Processing and Power Applications, underscoring his active role in the research community. His work continues to shape the development of robust, real-time robotic perception systems.
Research Focus
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