TY - JOUR
T1 - Artificial intelligence algorithms in unmanned surface vessel task assignment and path planning
T2 - A survey
AU - Gao, Kaizhou
AU - Gao, Minglong
AU - Zhou, Mengchu
AU - Ma, Zhenfang
N1 - Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2024/4
Y1 - 2024/4
N2 - Due to the complex environment and variable demands, unmanned surface vessel (USV) task assignment and path planning have received much attention from academia and industry in recent years. Artificial intelligence technologies are increasingly adopted for solving the USV task assignment and path planning problems. This paper aims to give a comprehensive literature review of achievements, trends and challenges about the USV tasks assignment and path planning. First, the concerned problems are divided into two categories (single-USV and multi-USV), and the related work is thoroughly reviewed. Second, the solution methods, especially artificial intelligence (AI) related technologies and approaches, are analyzed and discussed. Third, the common external constraints and disturbances in the maritime environment are described. In particular, the obstacle avoidance strategies and algorithms are discussed and summarized systematically. Next, the applications to scientific exploration, military, and fishery industry are presented. Finally, we conclude this survey and indicate future research directions.
AB - Due to the complex environment and variable demands, unmanned surface vessel (USV) task assignment and path planning have received much attention from academia and industry in recent years. Artificial intelligence technologies are increasingly adopted for solving the USV task assignment and path planning problems. This paper aims to give a comprehensive literature review of achievements, trends and challenges about the USV tasks assignment and path planning. First, the concerned problems are divided into two categories (single-USV and multi-USV), and the related work is thoroughly reviewed. Second, the solution methods, especially artificial intelligence (AI) related technologies and approaches, are analyzed and discussed. Third, the common external constraints and disturbances in the maritime environment are described. In particular, the obstacle avoidance strategies and algorithms are discussed and summarized systematically. Next, the applications to scientific exploration, military, and fishery industry are presented. Finally, we conclude this survey and indicate future research directions.
KW - AI-based algorithms
KW - Obstacle avoidance
KW - Path planning
KW - Task assignment
KW - Unmanned surface vessel
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U2 - 10.1016/j.swevo.2024.101505
DO - 10.1016/j.swevo.2024.101505
M3 - Article
AN - SCOPUS:85185829418
SN - 2210-6502
VL - 86
JO - Swarm and Evolutionary Computation
JF - Swarm and Evolutionary Computation
M1 - 101505
ER -