This paper introduces a dynamic path planning method for the UAV that can avoid both static and moving obstacles. The condition with sudden threats can better reflect the real situation of the UAV in the real environment. First of all, the A* algorithm is adopted to generate an optimal path in a known environment in this method. Then, in the situation of static sudden threats, a series of candidate paths are generated by the principle of cubic spline second-order continuity. In order to make the static sudden threat at the center of a cluster of candidate paths, they need to be adjusted. After that, this path cluster completely surrounds the sudden threat and has symmetry about the sudden threat. When encountering a sudden threat of movement, factors such as the speed, acceleration and certain parameters of the movement obstacle or the UAV are considered, and a correlation model of the dynamic sudden threat is established. Finally, the total cost function is established to select the optimal obstacle avoidance path, and the total cost function contains four sub-cost functions, they are static security cost function, smoothness cost function, consistency cost function and dynamic security cost function. The simulation results demonstrate the effectiveness of the proposed method.

本文介绍了一种可以避免静态和动态障碍物的无人机动态路径规划方法。突如其来的威胁状况可以更好地反映无人机在真实环境中的真实情况。首先，该方法采用A *算法在已知环境中生成最优路径。然后，在静态突然威胁的情况下，根据三次样条二阶连续性原理生成了一系列候选路径。为了使静态突然威胁处于候选路径群集的中心，需要对其进行调整。此后，此路径簇完全包围了突发威胁，并对突发威胁具有对称性。遇到突然移动的威胁时，诸如速度，考虑运动障碍物或无人机的加速度和某些参数，建立了动态​​突击威胁的相关模型。最后，建立总成本函数以选择最优的避障路径，总成本函数包含四个子成本函数，分别为静态安全成本函数，平滑度成本函数，一致性成本函数和动态安全成本函数。仿真结果证明了该方法的有效性。一致性成本函数和动态安全成本函数。仿真结果证明了该方法的有效性。一致性成本函数和动态安全成本函数。仿真结果证明了该方法的有效性。