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The unmanned surface vehicles (USVs) have become a major trend in the construction of naval equipment and its flexibility and intelligence making it widely used in real-scenes. For cooperative defense with multiple USVs to intercept intruders, it is proposed that planning the path with obstacle avoidance and protecting the target by task allocation actions. The particle swarm optimization based on probe mechanism (PM-PSO) is proposed for pathing planning with obstacle avoidance. With the consideration of the constraints of different defense schemes such as the path cost, the interception loss, the defense income and so on, it is proposed that the dispersed particle swarm optimization based on genetic algorithm (GA-PSO) for the interception task allocation. Furthermore, the fitness function is proposed to evaluate the feasibility of the interception path and the quality of the allocation scheme. Extensive simulation experiments are conducted and demonstrated the effectiveness, rationality and superiority of the proposed methods.
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