为风力驱动的无人帆船设计了动态海洋环境下的高效覆盖路径规划方法。
Coverage Path Planning for Autonomous Sailboats in Inhomogeneous and Time-Varying Oceans: A Spatiotemporal Optimization Approach
- 结合空间拓扑约束与时间预测规划，提升路径连续性与适应性。
- 在随机非均匀海况下，路径效率优于传统方法，成功率显著提高。
- 适合长期海洋观测任务，尤其适用于多船协同场景。
无人帆船因风能驱动具备持久续航能力，适合长时间海洋观测。然而其性能高度各向异性，受非均匀、时变风场与洋流强烈影响，现有覆盖方法（如回溯式扫掠）难以奏效。本文提出一种时空联合覆盖路径规划框架：(1) 在空间域引入基于拓扑的形态学约束，保障覆盖区域紧凑连续；(2) 在时间域采用预报感知的前瞻规划，预判环境变化，实现前瞻性决策。在包含部分方向不可达性的随机非均匀、时变海洋环境中进行仿真，结果表明该方法生成的路径高效可行，而传统策略常失效。据我们所知，这是首个针对非均匀时变海洋中无人帆船覆盖路径规划的专用解决方案，为未来多帆船协同覆盖奠定基础。
原文摘要 · Abstract (English)
Autonomous sailboats are well suited for long-duration ocean observation due to their wind-driven endurance. However, their performance is highly anisotropic and strongly influenced by inhomogeneous and time-varying wind and current fields, limiting the effectiveness of existing coverage methods such as boustrophedon sweeping. Planning under these environmental and maneuvering constraints remains underexplored. This paper presents a spatiotemporal coverage path planning framework tailored to autonomous sailboats, combining (1) topology-based morphological constraints in the spatial domain to promote compact and continuous coverage, and (2) forecast-aware look-ahead planning in the temporal domain to anticipate environmental evolution and enable foresighted decision-making. Simulations conducted under stochastic inhomogeneous and time-varying ocean environments, including scenarios with partial directional accessibility, demonstrate that the proposed method generates efficient and feasible coverage paths where traditional strategies often fail. To the best of our knowledge, this study provides the first dedicated solution to the coverage path planning problem for autonomous sailboats operating in inhomogeneous and time-varying ocean environments, establishing a foundation for future cooperative multi-sailboat coverage.
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