Path planning and collision avoidance for autonomous surface vehicles I: a review

Vagale, Anete; Oucheikh, Rachid; Bye, Robin T.; Osen, Ottar L.; Fossen, Thor I. · 2021 · OpenAlex-citations

DOI: 10.1007/s00773-020-00787-6

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Summary

This review article addresses the critical need for robust path planning and collision avoidance (COLAV) algorithms for autonomous surface vehicles (ASVs). The research is motivated by the high incidence of maritime accidents caused by human error, with statistics indicating that over 65% of casualties are attributed to human erroneous actions. The authors aim to clarify ambiguous terminology, analyze the regulatory framework, and propose a classification for path planning algorithms to support the development of safer, more efficient autonomous maritime systems. The paper employs a comprehensive literature review methodology, synthesizing existing research on guidance, navigation, and control (GNC) systems. It distinguishes between autonomous surface vehicles (ASVs), which operate without direct human intervention, and unmanned surface vehicles (USVs), which are remotely controlled. The authors clarify key technical terms, differentiating path planning (generating a geometric route), trajectory generation (adding temporal constraints), path following (tracking a geometric path without time constraints), and trajectory tracking (following a path with specific timing). The review also examines industry advancements, citing projects like Rolls-Royce’s SVAN and Yara Birkeland, and analyzes previous survey papers from 2008 to 2020 to identify gaps in current research. Key findings highlight significant ambiguities in the literature regarding vessel autonomy levels and algorithmic definitions. The authors note that while ASVs offer advantages such as reduced human error, improved safety in hazardous environments, and lower operational costs, they face challenges related to regulatory uncertainty, liability, cybersecurity, and connectivity. The review identifies limitations in existing COLAV algorithms, including a lack of consideration for dynamic environmental factors, idealized ship dynamics, and insufficient compliance with the International Regulations for Preventing Collisions at Sea (COLREGs). The paper proposes a structured classification for path planning algorithms and emphasizes the need for standardized terminology to facilitate further development. The significance of this work lies in its contribution to standardizing the field of autonomous maritime navigation. By clarifying terminology and outlining the regulatory landscape, including autonomy levels defined by Lloyd’s Register and the Norwegian Forum for Autonomous Ships, the paper provides a foundational framework for researchers and developers. It underscores the necessity for new regulations and improved algorithmic designs that account for real-world complexities, such as dynamic obstacles and strict regulatory compliance, to enable the safe commercialization of ASVs.

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