针对自主水下航行器（Autonomous Underwater Vehicles，AUV）在全局路径规划环境模型的复杂性问题，本文采用栅格法进行环境建模。在数学优化模型中，综合了路径长度、能耗和路径平滑度为评价准则。本文提出一种考虑海洋地形及涡流影响的AUV路径规划改进蚁群算法，通过改进初始信息素分布，提出一种基于轴向-基础双高斯混合分布的初始化策略，并采用自适应的启发函数因子以及信息素因子和挥发素得到最优解。同时，考虑AUV在海底运行时的三维空间，需要目标点进行引导来加快收敛速度进而改进启发函数。最后根据海底地形信息和由涡流形成的洋流模型，设置2种地形进行仿真实验。通过实验可以得出，本文所提算法求解精度更高、收敛速度更快、稳定性更强。
For the AUV its complexity problem in global path planning environment modelling when, this paper uses the raster method for environment modelling. In the mathematical optimisation model, path length, energy consumption and path smoothness are integrated as evaluation criteria. In addition, this paper proposes an improved ant colony algorithm for AUV path planning considering the influence of ocean topography and eddy currents by improving the initial pheromone distribution, proposing an initialisation strategy based on the axial-basic double Gaussian mixture distribution, and adopting an adaptive heuristic function factor as well as pheromone factor and volatiles to obtain the optimal solution. At the same time, considering that AUVs operate in three-dimensional space when running on the seabed, target points are needed to guide them in order to accelerate convergence speed and improve the heuristic function. Finally, based on the information of seabed topography and the current model formed by eddy currents, two kinds of topography are set up for simulation experiments. And by comparing with other algorithms, repeated experiments can be concluded that the algorithm proposed in this paper has higher solution accuracy, faster convergence speed and stronger stability.
2026,48(2): 157-165 收稿日期：2025-5-28
DOI：10.3404/j.issn.1672-7649.2026.02.024
分类号：U675
基金项目：国家自然科学基金资助项目（62303157）
作者简介：王海龙(2002-),男,硕士研究生,研究方向为水下潜航器路径规划与运动控制
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