Coverage Path Planning for Autonomous Sailboats in Inhomogeneous and Time-Varying Oceans: A Spatiotemporal Optimization Approach
Yang An, Zhikang Ge, Taiyu Zhang, Jean-Baptiste R. G. Souppez, Gaofei Xu, Zhengru Ren

TL;DR
This paper introduces a novel spatiotemporal coverage path planning framework for autonomous sailboats, effectively addressing the challenges posed by inhomogeneous and time-varying ocean conditions to improve long-duration ocean observation.
Contribution
It presents the first dedicated solution for coverage path planning of autonomous sailboats in complex, dynamic ocean environments, integrating morphological and forecast-aware planning strategies.
Findings
Efficient coverage paths generated in stochastic ocean scenarios.
Outperforms traditional strategies in partial directional accessibility cases.
Demonstrates feasibility and robustness of the proposed method.
Abstract
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…
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Taxonomy
TopicsMaritime Navigation and Safety · Robotic Path Planning Algorithms · Underwater Vehicles and Communication Systems
