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

作　　者：张宏瀚[1] 王亚博 李娟[1] 王元慧 严浙平 ZHANG Honghan;WANG Yabo;LI Juan;WANG Yuanhui;YAN Zheping(College of Intelligent Systems Science And Engineering,Harbin Engineering University,Harbin 150001,China)

机构地区：[1]哈尔滨工程大学智能科学与工程学院,黑龙江哈尔滨150001

出　　处：《智能系统学报》2024年第1期114-121,共8页CAAI Transactions on Intelligent Systems

基　　金：国家自然科学基金项目(51909044);黑龙江省自然科学基金项目(E2018023)。

摘　　要：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.

关 键 词：水下无人航行器 动态路径规划 快速拓展随机树 动态窗口 自适应 水下环境 局部路径规划 避障 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]