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The aim is to develop a control framework for autonomous surface vessels to navigate safely through ice floes.

Iterative Learning Control for Path-Following of ASV With the Ice Floes Auto-Select Avoidance Mechanism

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The aim is to develop a control framework for autonomous surface vessels to navigate safely through ice floes.
Proposed an iterative learning control framework divided into guidance and control components.
Identified and classified ice floes into threatening and non-threatening categories.
Developed a robust adaptive ILC system that improves accuracy with iterations.
Demonstrated increased control accuracy with more iterations in the path-following task.
Proved the stability of the closed-loop system using the Lyapunov theorem.
Evaluated the algorithm's effectiveness through two numerical examples with irregular ice floes.

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Randomized trial implements path-following guidance in autonomous surface vessels, highlighting improved navigation through ice floes.

Zhang et al. (2025) studied this question.

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