Hierarchical Attack-Defense Strategy of Unmanned Surface Vehicles for Domain Protection and Invasion Task

This paper introduces an innovative hierarchical framework tailored to meet the offensive and defensive needs of swarm-based unmanned surface vehicles (USVs) for domain protection and invasion tasks. The framework is structured into three layers: The top layer handles target allocation, the middle layer focuses on action strategy, and the bottom layer ensures safety. For domain protection tasks, the top layer leverages auction theory to effectively match attackers and defenders, enabling the distributed allocation of multiple defenders to respective invaders. The middle layer employs an adaptive guidance method, allowing each defender to follow a guidance law aligned with the optimal interception point. The bottom layer uses an enhanced potential field function to guarantee collision-free interception of invaders. For invasion tasks, the top layer similarly applies auction theory for the allocation of virtual waypoints. The middle layer introduces an Artificial Potential Field (APF)-based angle-adaptive attack strategy, enabling invaders to evade defender interception. The bottom layer remains consistent with the domain protection framework. This paper marks the first hybrid virtual-real experiment in multi-USV confrontation, demonstrating its reliability and effectiveness in real maritime conditions. Experiments conducted within a 5000-m radius, with vessels traveling at speeds up to 12[Formula: see text]m/s, confirmed the framework’s robustness and practical applicability in near-realistic combat scenarios.