Eleni Charalampoglou

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About

Eleni Charalampoglou is a researcher whose work lies at the intersection of robotics, computer vision, and knowledge representation. Her primary research focuses on developing intelligent systems for autonomous object manipulation, with a particular emphasis on bridging the gap between high-level semantic understanding and low-level robotic control. Her most notable contribution, the paper "Ontology-based 3D pose estimation for autonomous object manipulation" (2012), introduces a novel framework that leverages ontological reasoning to guide robotic grippers in manipulation tasks. The approach is structured around two key modules—training and testing—that enable robots to learn and recognize object poses using structured semantic knowledge. While her citation count is modest, her work represents an early and innovative integration of formal ontologies into robotic perception and control, a concept that has since gained traction in the field of cognitive robotics. Charalampoglou’s research is particularly valuable for students and researchers interested in how symbolic AI can enhance the autonomy and adaptability of robotic systems in unstructured environments.