Florentin Alexandru Iftimie

Universitatea Națională de Știință și Tehnologie Politehnica București

Papers

Total Citations

H-Index

About

Florentin Alexandru Iftimie’s research lies at the intersection of robotics and indoor positioning systems, with a focus on automating labor-intensive data acquisition processes. His most-cited work, “Automatic Data Acquisition with Robots for Indoor Fingerprinting” (2018), tackles a critical bottleneck in Received Signal Strength (RSS) fingerprinting—the manual effort required to build accurate indoor localization maps. By deploying a robotic platform equipped with basic odometer sensors in a university building, Iftimie demonstrated a scalable, repeatable method for collecting signal-strength data autonomously, reducing human error and time costs. This contribution directly addresses the practical challenges of deploying indoor navigation systems in environments like hospitals, warehouses, or smart campuses. With 5 citations, the paper has influenced subsequent research in robotic-assisted mapping and sensor fusion. Iftimie’s work exemplifies how robotics can streamline infrastructure-dependent tasks, offering a pragmatic solution for real-world localization. His approach—combining low-cost hardware with algorithmic efficiency—makes his research particularly accessible for students and engineers seeking to bridge the gap between theoretical positioning models and deployable systems.