Delivery Services Using Artificial Intelligence and Automating Drone Navigation

Abstract

Artificial Intelligence has transformed the navigation system of unmanned aerial vehicles; delivery drones can now navigate complex environments autonomously, have accurate localization, and plan optimal flight paths to deliver goods in the last mile. Modern architectures trade off efficiency, reliability, and safety in urban and rural environments by combining deep learning-based visual perception, reinforcement learning-based dynamic obstacle avoidance, and classical algorithms-based global path planning. Hybrid edge-cloud systems enable real-time inference and model updates on the fly, and multi-agent coordination strategies allow scaling fleet operations. The experience of state-of-the-art research in sensor fusion, simultaneous localization and mapping (SLAM), model predictive control, and domain-specific payload delivery indicates the high benefit of mission success probability, delivery accuracy, and energy consumption. Recent developments in safe exploration, federated learning, and digital twin validation show further robustness, privacy, and regulatory compliance improvements that will enable the extensive introduction of AI-based drone delivery services.