Artificial intelligence algorithms in unmanned surface vessel task assignment and path planning: A survey

Kaizhou Gao, Minglong Gao, Mengchu Zhou, Zhenfang Ma

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number101505
JournalSwarm and Evolutionary Computation
Volume86
DOIs
StatePublished - Apr 2024
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Mathematics

Keywords

  • AI-based algorithms
  • Obstacle avoidance
  • Path planning
  • Task assignment
  • Unmanned surface vessel

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