Hafsa Imran

Academic

Career

Verbatim text

FALCON-Fusion of Al, LiDAR, and Camera based Odometry for UAV Navigation 
This project aims to design and implement a robust navigation system for Unmanned Aerial Ve hides 
(UAVs) that can operate reliably in GPS-denied and indoor environments. Traditional UAV 
navigation methods relying on GPS or vision-based odometry fai l in low-light, low-texture, or 
challenging environments, causing mission failures and safety risks. Through this project, we aim to 
create a hybrid Al-based systemthatfusesdatafrom LiDAR, cameras, and IMUsto provide accurate, 
drift-reduced navigation, enabling UAVs to perform critical tasks such as disaster management, 
indoor surveillance, and industrial inspection with high rel iability. This solution addresses the 
growing need for autonomous UAVs capable of navigating complex environments where GPS 
signals are weak or unavailable. 
Key Words: UAV Navigation, LiDAR, Visual-Inertial Odometry, Sensor Fusion, Al-Based Localization 
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Technology Used: 
Linux, Raspbian, Python, Arduino IDE, 
MATLAB, CorelDRAW, QGroundControl, 
Visual Studio, Slamtec, Gazebo, OpenCV. 
Supervisor Name: 
Dr. Shahzad Saleem 
Group Members: 
Areeba Shahid (i22-9889) 
Hafsa lmran 022-9887) 
lzza Zainab (i22 - 1830) 
FAST NUCES ISLAMABAD CAMPUS