Rahaf Nasrallah
Papers
1
Total Citations
3
H-Index
1
About
Rahaf Nasrallah is a researcher at the forefront of low-cost, accessible robotics and autonomous navigation systems. Her work centers on developing practical solutions for indoor localization, where traditional GPS is unavailable. Her most-cited paper, "Triangulation-Enhanced WiFi-Based Autonomous Localization and Navigation System: A Low-Cost Approach" (2024), introduces a novel method that leverages ubiquitous WiFi signal strength for robot positioning. By integrating mathematical models of signal propagation with triangulation techniques, Nasrallah enables dynamic, real-time navigation without expensive sensors. This contribution is particularly significant for educational robotics, small-scale automation, and assistive technologies, where cost constraints are critical. With 3 citations in its first year, the work is gaining traction as a foundational reference for WiFi-based SLAM and low-cost autonomy. Nasrallah’s research bridges the gap between theoretical signal processing and practical deployment, offering a scalable path for robots to navigate indoor environments independently. Her approach promises to democratize autonomous navigation, making it accessible to hobbyists, students, and resource-limited labs.
Research Focus
Key Achievements
Top Papers
- 1