Underwater gliders (UGs) have emerged as highly effective unmanned vehicles for ocean exploration. However, their operation in dynamic and complex underwater environments necessitates robust path-planning strategies. Previous studies have primarily focused on global energy or time-efficient path planning in explored environments, overlooking challenges posed by unpredictable flow conditions and unknown obstacles in varying and dynamic areas like fjords and near-harbor waters. This paper introduces and improves a real-time path planning method, Multi-Point Potential Field (MPPF), tailored for UGs operating in 3D space as they are constrained by buoyancy propulsion and internal actuation. The proposed MPPF method addresses obstacles, flow fields, and local minima, enhancing the efficiency and robustness of UG path planning. A low-cost prototype, the Research Oriented Underwater Glider for Hands-on Investigative Engineering (ROUGHIE), is utilized for validation. Through case studies and simulations, the efficacy of the enhanced MPPF method is demonstrated, highlighting its potential for real-world applications in underwater exploration.

翻译：水下滑翔机（UGs）已成为高效的海洋探测无人航行器。然而，其在动态复杂水下环境中的运行需要鲁棒的路径规划策略。已有研究主要关注已知环境中基于全局能量或时间效率的路径规划，忽略了峡湾和近港水域等动态变化区域中不可预测流场与未知障碍物带来的挑战。本文针对受浮力推进与内部驱动限制的三维空间水下滑翔机，提出并改进了一种实时路径规划方法——多点势场法（MPPF）。所提MPPF方法能够同时处理障碍物、流场与局部极小值问题，提升了UG路径规划的效能与鲁棒性。为验证该方法，采用低成本原型机——面向研究实践工程的水下滑翔机（ROUGHIE）。通过案例研究与仿真实验，展示了增强型MPPF方法的有效性，并凸显其在水下探测实际应用中的潜力。