Enhanced Cooperative UAV Swarm Search via LoPSO Integration and Adaptive Sequential Stopping Strategy

Abstract

An in-depth analysis and extension of a hybrid approach, combining Local Particle Swarm Optimization (LoPSO) and an optimal stopping strategy inspired by the Secretary Problem, is presented for the search and validation of mobile targets by Unmanned Aerial Vehicles (UAVs). The mathematical foundations of the system model, communication primitives, the LoPSO optimization algorithm, and robust sequential decision strategies are detailed. Furthermore, recent advances in intelligent UAVs, specific LoPSO topologies, and challenges related to swarm coordination and decision-making in constrained environments are incorporated. Key additions include a detailed energy model, a formal communication model, pseudocode for all algorithms, complexity analysis, comparative tables of hardware platforms, and a plan for future experimentation. Finally, ethical and regulatory considerations are discussed, and directions for real-world implementation.