In order to solve the problems of dynamic path planning for Unmanned Aerial Vehicles (UAVs) confronted with sudden threats,a dynamic UAV path-planning method is proposed based on multi-strategy SSO (Social Spider Optimization) and the improved A* algorithm.The UAV path planning is divided into two stages: static path planning and real-time evasion under sudden threat.At the stage of static path planning,multi-strategy SSO optimization algorithm is used to solve the polar-coordinate path-planning model,and the mechanisms of perfect elastic collision and adaptive skipping are introduced,which can improve the feasibility of the path-planning results while satisfying the restraints of flight performance.At the stage of real-time evasion under unexpected threat,the improved A* algorithm is used for path planning in local regions for a second time.Through expanding the number of neighborhood for A* algorithm and introducing the minimum “bent” estimation cost function,a smoother optimal path can be obtained while satisfying the real-time requirements.The simulation results show that the proposed method can provide more satisfactory dynamic path-planning for UAVs.