Unmanned surface vehicles are finding more and more prominent applications in military field with the development of autonomous control technology.The intelligent control technology of Mine Countermeasures Unmanned Surface Vehicle (MCM USV) is one of the current research hotspots.Aimed at the local path planning problem of MCM USV,a hierarchical reinforcement learning method is proposed,which is used for training the evolutionary artificial neural network used as path planner of the UAV.The Unity physics engine is adopted to build a simulation environment,and a USV model with environment awareness and autonomous decision-making capabilities is established.Experimental result verifies the effectiveness of the algorithm on local path planning.