Under unforeseen circumstances, a hierarchical path planning (HPP) scheme combining global and local tasks of an unmanned surface vehicle (USV) is proposed by devising fuzzy artificial potential field (FAPF). Within the HPP scheme, the elite reservation, diversity increment, adaptive mutation probability and adaptive genetic algorithm are incorporated to generate optimally sparse waypoints together with smooth path. To exclusively accommodate unpredictable environments, the innovative FAPF method with fuzzy decision-making is developed to remove singular dilemmas, pertaining to which the obstacles on the path make the USV hesitate. By inserting virtual returning points onto the global path, a hybrid compound combining the global and local paths is established. Finally, the simulations and comparisons in various geographical areas demonstrate the effectiveness and superiority of the proposed HPP scheme.

在不可预见的情况下，通过设计模糊人工势场（FAPF），提出了结合无人水面车辆（USV）的全局和局部任务的分层路径规划（HPP）方案。在HPP方案中，结合了精英保留，多样性增加，自适应突变概率和自适应遗传算法，以生成最佳的稀疏航路点以及平滑的路径。为了专门适应不可预测的环境，开发了具有模糊决策能力的创新型FAPF方法，以消除奇异的难题，在这种难题上，道路上的障碍使USV犹豫不决。通过将虚拟返回点插入到全局路径中，可以建立结合了全局路径和局部路径的混合化合物。最后，