Imed Hadda

Tunis University, École Nationale d'Ingénieurs de Gabès

Papers

Total Citations

H-Index

About

Imed Hadda’s research lies at the intersection of mobile robotics, computer vision, and autonomous navigation, with a particular focus on low-cost, real-world mapping and localization systems. His work addresses the critical challenge of enabling robots to build accurate maps of unknown environments while simultaneously determining their own position within them—a problem central to the field of simultaneous localization and mapping (SLAM). Hadda’s most cited paper, “Low cost 3D mapping for indoor navigation” (2015, 14 citations), demonstrates a practical, affordable approach using a Kinect 3D scanner and SIFT feature points for robust place recognition, making indoor robot navigation more accessible. In his earlier work, “Global mapping and localization for mobile robots using stereo vision” (2013, 5 citations), he developed a method using stereo cameras and a hybrid map structure of nodes and arcs to achieve autonomous navigation. Though his citation counts are modest, Hadda’s contributions are notable for their emphasis on cost-effective solutions that bridge the gap between laboratory research and deployable robotic systems. His work is particularly relevant for students and researchers interested in practical SLAM implementations using off-the-shelf sensors.