Boundary adaptive and dynamic neural network dual layer path planning algorithm for polar multi-mission area under-ice feature scanning

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering Pub Date : 2025-06-30 DOI:10.1016/j.oceaneng.2025.121936

Lin Zhou , Zhongchao Deng , Nan Zhou , Guiqiang Bai , Hongde Qin , Zhongben Zhu

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引用次数: 0

Abstract

Autonomous Underwater Vehicles play a crucial role in polar under-ice feature scanning, contributing to explore ecological changes in polar regions. However, multi-mission under-ice feature scanning face significant challenges due to complex boundaries, energy constraints, and environmental uncertainties. To address these issues, this paper proposes a Boundary Adaptive and Dynamic Neural Network Dual Layer path planning algorithm, which consists of coverage path planning and connectivity path planning. First, Boundary Adaptive Coverage based on Dynamic Grid algorithm is introduced, which optimizes coverage paths by adaptively inserting boundary waypoints to improve coverage efficiency of AUV. Second, Dynamic Neural Network based on Ocean Current Energy Consumption algorithm is proposed, which integrates ocean current effects to save energy and real time replan connection paths. Simulation results demonstrate that it outperforms current methods in terms of total path length, turning times, and energy consumption, and its practicality is verified by “Xing Hai 1000” AUV field experiments.

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极地多任务区冰下特征扫描边界自适应动态神经网络双层路径规划算法

自主水下航行器在极地冰下特征扫描中发挥着至关重要的作用，有助于探索极地生态变化。然而，由于复杂的边界、能量限制和环境不确定性，多任务冰下特征扫描面临着重大挑战。针对这些问题，本文提出了一种边界自适应动态神经网络双层路径规划算法，该算法由覆盖路径规划和连通性路径规划两部分组成。首先，介绍了基于动态网格的边界自适应覆盖算法，该算法通过自适应插入边界路径点来优化覆盖路径，提高水下机器人的覆盖效率；其次，提出了基于洋流能量消耗的动态神经网络算法，该算法综合了洋流的节能效果和实时重新规划连接路径；仿真结果表明，该方法在总路径长度、转弯次数、能耗等方面均优于现有方法，并通过“星海1000”水下航行器现场实验验证了其实用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Ocean Engineering 工程技术-工程：大洋

CiteScore

7.30

自引率

34.00%

发文量

2379

审稿时长

8.1 months

期刊介绍： Ocean Engineering provides a medium for the publication of original research and development work in the field of ocean engineering. Ocean Engineering seeks papers in the following topics.