UNMANNED AERIAL AND SURFACE VEHICLES PATH COORDINATION FOR MARITIME SURVEILLANCE APPLICATIONS

This study explores the potential of utilizing cooperative unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) for cost-effective distributed maritime monitoring. By considering spatial-temporal constraints and physical characteristics, a coordinated path planning strategy is developed to minimize operating costs while ensuring the completion of essential monitoring tasks (e.g., illegal fishing, monitoring water quality, and tracking vessel traffic and air pollution). This study investigates the feasibility of transporting UAVs on USVs for certain trips, reducing operational costs and accommodating UAVs’ limited flight range. To address the path planning problem, a mixed-integer linear programming model is developed, and an efficient Adaptive Large Neighborhood Search (ALNS) algorithm is proposed for solving large-scale problems. Numerical studies have been conducted in simulated near-shore maritime environments in the context of Guangdong-Hong Kong-Macao Greater Bay Area. Overall, this study provides insights into the effectiveness and feasibility of employing cooperative UAVs and USVs for cost-effective distributed maritime monitoring.