Self-organization Method of USV Swarm Target Strike Task Based on Ant Colony Algorithm

Abstract

Unmanned surface vehicle (USV) swarm warfare is the main mode of warfare for future unmanned combat platforms at sea. In order to improve the autonomous cooperative warfare capability of the USV swarm, this study designed a multi-USV cooperative self-organizing framework based on ant colony hunting behavior, proposed a distributed raid-pattern ant colony algorithm in view of the USV swarm target strike task, and established a mathematical model of the self-organizing problem of the USV swarm target strike task Moreover, the related state movement rule and pheromone updating mechanism of the algorithm were designed, and the improved USV movement rule with overall view was also introduced in this study. This study confirmed the effectiveness of the self-organizing method of the designed USV swarm target strike task through simulation experiments, compared the advantage of algorithm after introducing the overall view of movement rules, and verified the general applicability of the algorithm for different USV swarms at the same time.