The project focuses on the development of an Unmanned Aerial Vehicle (UAV) application designed for manual keyboard-controlled navigation, real-time Simultaneous Localization and Mapping (SLAM) utilizing RTAB-Map (Real-Time Appearance-Based Mapping), and advanced computer vision-based human detection using YOLO.

  By leveraging custom CAD digital modeling, modern robotics frameworks, and artificial intelligence, this system establishes a scalable platform suitable for complex, large-scale missions such as surveillance, mapping, and search-and-rescue operations. Full technical documentation and architectural details are available in the Master’s Thesis (currently available in Greek).

System	Ubuntu 24.04 LTS (Noble Numbat)
IDE & Tools	Visual Studio 2013, Qt Creator
Programming Languages	C++ (Low-level performance/development), Python (High-level script orchestration)
Robotics Framework	ROS 2 (Jazzy Jalisco)
UAV Modeling	SolidWorks with URDF Exporter plugin (URDF & STL generation)
Simulation	Gazebo (Harmonic), RViz
Flight Control Stack	PX4 Autopilot Stack
SLAM Package	RTAB-Map (Real-Time Appearance-Based Mapping)
Computer Vision Packages	OpenCV, YOLO (You Only Look Once)
Ground Control & Telemetry	QGroundControl (Real-time flight operation management)
Repository