系统综述多艘无人船协同控制挑战与前沿进展
Coordinated control of multiple autonomous surface vehicles: challenges and advances -- a systematic review
- 采用系统化方法筛选文献,减少偏见
- 聚焦欠驱动无人船的定制化控制策略
- 融合机器学习提升自主性,适合智能航运研究者
随着无人水面艇(ASVs)在海洋环境中应用日益广泛,其控制技术的研究也迅速发展。尤其多艘ASV的协同控制带来了新挑战与机遇,涉及机器人学、控制理论、通信系统和海洋科学等多学科交叉。这些船只可协同执行多样化任务,适用于多种控制技术的组合与创新,包括利用机器学习解决以往难以实现的问题。本文通过系统性综述,全面探讨了协同控制中的关键技术,弥补了以往综述的空白。与以往工作不同,本研究采用系统化方法确保文献选取的完整性与客观性。重点分析了欠驱动ASV的定制化控制策略,并探讨了机器学习在提升自主性方面的集成应用。通过整合最新进展并识别新兴趋势,为该领域未来发展提供了深刻见解,既呈现了当前最先进的技术体系,也为后续研究指明方向。
原文摘要 · Abstract (English)
The increasing use and implementation of Autonomous Surface Vessels (ASVs) for various activities in maritime environments is expected to drive a rise in developments and research on their control. Particularly, the coordination of multiple ASVs presents novel challenges and opportunities, requiring interdisciplinary research efforts at the intersection of robotics, control theory, communication systems, and marine sciences. The wide variety of missions or objectives for which these vessels can be collectively used allows for the application and combination of different control techniques. This includes the exploration of machine learning to consider aspects previously deemed infeasible. This review provides a comprehensive exploration of coordinated ASV control while addressing critical gaps left by previous reviews. Unlike previous works, we adopt a systematic approach to ensure integrity and minimize bias in article selection. We delve into the complex world of sub-actuated ASVs with a focus on customized control strategies and the integration of machine learning techniques for increased autonomy. By synthesizing recent advances and identifying emerging trends, we offer insights that drive this field forward, providing both a comprehensive overview of state-of-the-art techniques and guidance for future research efforts.
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