Enhancing Autonomous Drone Navigation with Neural Networks

Abstract

Autonomous drones have vast potential for applications in various fields, including delivery, surveillance, search and rescue, and environmental monitoring. Neural networks are playing a crucial role in enhancing drone navigation systems, enabling them to make real-time, context-aware decisions based on sensor data. This article explores how neural networks, particularly deep learning models, are used to improve autonomous drone navigation, including object detection, path planning, obstacle avoidance, and adaptive decision-making. We examine the challenges and opportunities of using neural networks in drone navigation systems, including real-time processing, safety concerns, and the integration of AI models with existing drone hardware.