An Ad-Hoc Communication Assisted Distributed Particle Swarm Optimization Scheme for AUVs Underwater Search Task

Coordinating Autonomous Underwater Vehicles (AUVs) for cooperative search operations presents significant challenges. While Distributed Particle Swarm Optimization (DPSO) offers a powerful swarm algorithm for this task, its effectiveness is limited by local communication constraints. This paper introduces a novel two-phase Ad-Hoc Communication Assisted Distributed Particle Swarm Optimization (AA-DPSO) search strategy augmented by ad-hoc communication to overcome these limitations and extend the algorithm's efficacy. Our approach optimizes AUV formation and message exchange protocols, enabling the dissemination of high-quality search information across the swarm, even to distant vehicles. Simulation results demonstrate that this method achieves improved search times and robustness against false targets compared to traditional DPSO implementations. The proposed AA-DPSO strategy enhances the capability of AUV swarms in underwater search operations, offering potential applications in marine exploration, rescue missions, and environmental monitoring.