用数据驱动方法提升海洋机器人控制能力，迈向高自主时代。
Control of Marine Robots in the Era of Data-Driven Intelligence
- 结合机器学习构建数据驱动控制框架，突破传统模型局限。
- 涵盖单体与集群系统，展示先进控制方法在真实场景的进展。
- 适合关注智能海洋机器人、自主控制的研究者参考。
海洋机器人控制长期依赖基于经典与现代控制理论的模型驱动方法。然而，机器人动力学的非线性与不确定性，以及海洋环境的复杂性，暴露了传统控制方法的局限。机器学习的快速发展为控制策略引入数据驱动智能开辟了新路径，推动海洋机器人控制范式转型。本文从这一新兴范式出发，综述近期进展，涵盖单体与协同海洋机器人系统，重点展示数据驱动控制在海洋机器人中的显著成果，并总结支持先进控制方法开发与验证的开源资源。最后，提出若干未来研究方向，旨在指导实现海洋机器人在真实应用中的高水平自主。本文旨在为数据驱动智能时代的下一代海洋机器人控制框架提供路线图。
原文摘要 · Abstract (English)
The control of marine robots has long relied on model-based methods grounded in classical and modern control theory. However, the nonlinearity and uncertainties inherent in robot dynamics, coupled with the complexity of marine environments, have revealed the limitations of conventional control methods. The rapid evolution of machine learning has opened new avenues for incorporating data-driven intelligence into control strategies, prompting a paradigm shift in the control of marine robots. This paper provides a review of recent progress in marine robot control through the lens of this emerging paradigm. The review covers both individual and cooperative marine robotic systems, highlighting notable achievements in data-driven control of marine robots and summarizing open-source resources that support the development and validation of advanced control methods. Finally, several future perspectives are outlined to guide research toward achieving high-level autonomy for marine robots in real-world applications. This paper aims to serve as a roadmap toward the next-generation control framework of marine robots in the era of data-driven intelligence.
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