近海复杂环境下UUV动态路径规划方法研究

Dynamic path-planning method of UUV in an offshore complex environment

为解决近海环境下水下无人航行器(unmanned underwater vehicle,UUV)的动态路径规划问题,本文提出一种结合全局和局部动态路径规划的算法。首先,本文提出一种基于自适应目标引导的快速拓展随机树算法,以增加随机树生长的方向性,并通过转向和重选策略减少无效拓展加快算法的收敛速度。接着,获得全局路径之后使用自适应子节点选取策略获取动态窗口法的子目标点,将复杂的全局动态任务规划分解为多个简单的动态路劲规划,从而防止动态窗口法陷入局部极小值。最后,通过UUV出港任务仿真实验验证了算法的有效性和实用性。

This paper proposes an algorithm that combines global and local dynamic path-planning methods to solve the dynamic path-planning problem for unmanned underwater vehicles(UUVs)in near-shore environments.First,a fast-expanding random tree algorithm based on adaptive target guidance is proposed to increase the directionality of random tree growth.The algorithm then achieves rapid convergence using turning and reselection strategies to reduce ineffective expansion.Further,an adaptive sub-node selection strategy is used after obtaining the global path to acquire sub-target points for the dynamic window approach.This approach decomposes the complex global dynamic task planning into multiple simple dynamic path-planning tasks,preventing the dynamic window approach from falling into local minima.Finally,the effectiveness and practicality of the algorithm are verified using simulation experiments of UUV departure tasks.