Swarm Intelligence in Coordinated Missions of Unmanned Underwater Vehicles

Abstract

The application of swarm intelligence principles to the coordinated missions of Unmanned Underwater Vehicles (UUVs) offers a transformative approach to underwater exploration and operations. This paper explores the utilization of decentralized decision-making processes that enable UUVs to communicate and collaborate effectively, adapting to dynamic underwater environments. We present a framework that integrates algorithms inspired by biological swarms, such as ant colonies and fish schools, allowing for collective behavior and task allocation among multiple UUVs. Experimental results demonstrate the effectiveness of swarm intelligence in optimizing mission objectives, improving coverage, and enhancing robustness against environmental challenges. This research highlights the potential of swarm-based strategies to revolutionize UUV operations in various applications, including environmental monitoring, search and rescue missions, and underwater surveillance.