Autonomous UAV Swarms: Powering Up with AI

Abstract

Abstract: This study offers a thorough analysis of autonomous UAV swarming, focusing on its merits, important technologies, applications, difficulties, and prospects for the future. The idea of autonomous UAV swarming entails the coordination and decentralised cooperation of several UAVs to accomplish common objectives. The foundations of UAV swarming are thoroughly covered, including its essential ideas, advantages, architectures, and swarm behaviour. We emphasise the role of artificial intelligence (AI), more especially reinforcement learning (RL) and particle swarm optimisation (PSO), in promoting thoughtful decision-making, task allocation, and coordination within UAV swarms. The study examines the many uses of autonomous UAV swarming in fields including infrastructure inspection, search and rescue, agriculture, and disaster response. It also discusses UAV swarming's difficulties and restrictions, such as scalability, communication, fault tolerance, and ethical issues. In addition to standardisation initiatives, the study suggests future research possibilities for swarm intelligence, edge computing, cognitive capacities, and human swarm interaction.