This project presents a comprehensive implementation of an automated drone navigation system developed using the LabVIEW programming environment. The system integrates multiple sensing technologies, including GPS, IMU, vision systems, and proximity sensors, within a unified software architecture to enable autonomous flight capabilities. By leveraging LabVIEW's graphical programming paradigm and real-time processing capabilities, the system provides robust solutions for path planning, obstacle avoidance, position estimation, and flight control. A modular design approach facilitates system expansion and adaptation to various drone platforms and mission requirements. The implementation includes a ground control station with intuitive visualization tools for mission planning and monitoring. Extensive testing demonstrates the system's reliability across diverse environmental conditions and operational scenarios. This work contributes to the advancement of accessible drone automation technologies by providing a flexible, scalable platform that bridges the gap between commercial off-the-shelf hardware and sophisticated autonomous navigation capabilities, with applications spanning industrial inspection, agricultural monitoring, search and rescue operations, and academic research.

KEYWORDS:

Unmanned Aerial Vehicle (UAV), Autonomous Navigation, LabVIEW, Flight Control Systems, Sensor Fusion, Computer Vision, Path Planning, Obstacle Avoidance, Real-time Processing, Ground Control Station, Drone Automation, GPS Integration, Inertial Measurement Unit (IMU), Kalman Filter, PID Controller