Fundamentals of Drone Navigation and the Role of Computer Vision

Abstract

Drone navigation is based on precise navigation for efficient and secure performance for delivery, surveillance, or rescue. Traditional navigation based on GPS, inertial measurement units, and magnetometers provides good guidance but is inefficient in conditions with weakened signals or unpredictable obstacles. Computer vision is changing this. By equipping drones to perceive and understand visual information about their surrounding space, it makes decision-making independent, allows for better navigation past obstacles, and builds real-time maps. Object detection, optical flow, and SLAM are some techniques being applied in aerial robotics today. Vision is complemented and enhanced when combined with other sensors like LiDAR and GPS, making navigation feasible in complex terrains. However, processing high volumes of visual data in real-time remains a challenge. Advances in edge computing and AI-driven perception are helping to overcome these limitations, bringing faster and more efficient onboard processing.