Bassant M. El Bagoury
Papers
1
Total Citations
2
H-Index
1
About
Bassant M. El Bagoury is a researcher at the intersection of artificial intelligence and robotics, with a primary focus on case-based reasoning (CBR) and humanoid robot motion control. Her most cited work, "Enhancing Case-Based Retrieval Engine with Case Retrieval Nets for Humanoid Robot Motion Controller" (2015), addresses a critical challenge in robotics: efficiently retrieving relevant motion cases from vast databases to enable complex, real-time humanoid robot control. By applying case-retrieval nets—a specialized CBR technique—El Bagoury demonstrated how to streamline the retrieval process, reducing computational overhead while maintaining accuracy. This contribution is foundational for developing more responsive and adaptive humanoid robots, particularly in dynamic environments where rapid decision-making is essential. Though her citation count is modest, her work represents a targeted advancement in CBR applications for robotics, bridging theoretical AI methods with practical engineering challenges. El Bagoury’s research is particularly valuable for students and engineers exploring how intelligent retrieval systems can enhance robot autonomy, offering a clear example of how algorithmic efficiency directly impacts physical system performance.
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Top Papers
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