This review explores the recent advancements in AI-driven autonomous sailboat navigation, underscoring its pivotal role in ocean monitoring and real-time maritime data collection. Drawing on an extensive range of primary and secondary sources, the study critically evaluates current challenges, innovative control algorithms, and path planning strategies, with a particular emphasis on AI techniques. A major contribution of this study is the comparative analysis of these AI methods to assess their efficacy in achieving robust autonomy amid dynamic and uncertain maritime environments. The review also addresses notable gaps in the literature, highlighting the limited adoption of AI-specific methodologies in sailboat control systems. It explores hybrid and adaptive approaches that integrates advanced sensing and obstacle avoidance technologies to improve real-time decision-making and navigation accuracy. Furthermore, the paper traces the evolution of path planning from traditional graph-based methods to state-of-the-art learning algorithms, identifying future research directions focused on enhancing robustness, adaptability, and the practical deployment of autonomous sailboats beyond simulations. Ultimately, this review serves a foundational resource for researchers and practitioners aiming to advance sustainable, efficient, and reliable autonomous sailboat technologies for marine exploration and environmental Management.
AI-Based Autonomous Sailboat Navigation: A Review
Mankina V.
Primo
;Guerra R.;Distante C.
2025-01-01
Abstract
This review explores the recent advancements in AI-driven autonomous sailboat navigation, underscoring its pivotal role in ocean monitoring and real-time maritime data collection. Drawing on an extensive range of primary and secondary sources, the study critically evaluates current challenges, innovative control algorithms, and path planning strategies, with a particular emphasis on AI techniques. A major contribution of this study is the comparative analysis of these AI methods to assess their efficacy in achieving robust autonomy amid dynamic and uncertain maritime environments. The review also addresses notable gaps in the literature, highlighting the limited adoption of AI-specific methodologies in sailboat control systems. It explores hybrid and adaptive approaches that integrates advanced sensing and obstacle avoidance technologies to improve real-time decision-making and navigation accuracy. Furthermore, the paper traces the evolution of path planning from traditional graph-based methods to state-of-the-art learning algorithms, identifying future research directions focused on enhancing robustness, adaptability, and the practical deployment of autonomous sailboats beyond simulations. Ultimately, this review serves a foundational resource for researchers and practitioners aiming to advance sustainable, efficient, and reliable autonomous sailboat technologies for marine exploration and environmental Management.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
