Panagiotis Giannis

Papers

Total Citations

H-Index

About

Panagiotis Giannis is a researcher in the field of robotics and computer vision, with a primary focus on simultaneous localization and mapping (SLAM) and autonomous navigation. His most cited work, "Appearance-Based Loop Closure Detection with Scale-Restrictive Visual Features" (2019, 22 citations), addresses a critical challenge in SLAM: enabling robots to recognize previously visited locations under varying scales and viewpoints. By introducing scale-restrictive visual features, Giannis improved the robustness and efficiency of loop closure detection, a key component for long-term autonomous operation in dynamic environments. This contribution has practical implications for applications like autonomous driving, drone navigation, and mobile robotics, where accurate mapping is essential. Giannis’s work demonstrates a strong ability to bridge theoretical computer vision with real-world robotic systems, making him a notable emerging voice in the SLAM community. His research continues to influence how robots perceive and navigate complex spaces, with his citation record reflecting growing recognition among peers. For students and researchers, Giannis’s approach offers a clear example of how focused innovations in feature selection can solve persistent problems in autonomous navigation.