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高机动仿生机器鱼综述:机构创新与流体动力增益效应*(2026年01期 v.47 1-15页)

‖  文章供稿:王晓广 钟勇
‖  字体: [大] [中] [小]

王晓广 钟勇

(华南理工大学吴贤铭智能工程学院,广东 广州 511442)

摘要:随着水下作业环境从广阔海洋向非结构化复杂水域转变,传统自主水下航行器面临机动性不足的严峻挑战。该文综述了高机动仿生机器鱼在机构创新、流体动力增益以及性能评价等方面的最新研究进展。首先,基于生物学观测分析鱼类通过躯干变刚度、多鳍协同、内源性姿态调节机制实现高机动性的生物运动机理;然后,阐述高机动仿生机器鱼机械系统的设计范式,对比线驱动拮抗机构、阻塞变刚度机构、智能材料驱动等变刚度技术,以及多鳍矢量推进的实现路径;接着,从非定常流体动力学角度,揭示瞬态爆发、矢量推进与涡流操控的流体动力增益机理,并探讨基于中枢模式发生器与强化学习的高机动控制策略;最后,总结仿生机器鱼当前在动力学建模与解算、流场感知与控制、硬件集成与驱动及实海况环境验证等方面存在的挑战,并对其未来发展方向进行展望。

关键词:仿生机器鱼;高机动性;变刚度;多鳍协同;非定常流体动力学;流体动力增益

中图分类号:TP242                文献标志码:A             文章编号:1674-2605(2026)01-0001-15

DOI:10.12475/aie.20260101                                   开放获取


Review of High-maneuverability Biomimetic Robotic Fish:Mechanism Innovation and Hydrodynamic Dynamic Gain Effects

WANG Xiaoguang   ZHONG Yong

(Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, Guangdong 511442, China)

Abstract: As underwater operational environments shift from vast oceans to unstructured and complex waters, traditional autonomous underwater vehicles face significant challenges due to insufficient maneuverability. This paper reviews the latest research progress in high-maneuverability biomimetic robotic fish, focusing on mechanical innovation, fluid dynamic gain, and performance evaluation. Firstly, based on biological observations, it analyzes the locomotion mechanisms by which fish achieve high maneuverability through body variable stiffness, multi-fin coordination, and endogenous attitude regulation. Secondly, it elaborates on the design paradigms of the mechanical systems of high-maneuverability biomimetic robotic fish, comparing variable stiffness technologies such as cable-driven antagonistic mechanisms, jamming-based variable stiffness structures, and smart material-based actuators, as well as the implementation approaches for multi-fin vector propulsion. Thirdly, from the perspective of unsteady fluid dynamics, it reveals the fluid dynamic gain mechanisms of transient bursts, vector propulsion, and vortex manipulation, and discusses high-maneuverability control strategies based on central pattern generators and reinforcement learning. Finally, it summarizes the current challenges in biomimetic robotic fish, including dynamic modeling and computation, flow field perception and control, hardware integration and actuation, and validation in real marine environments, while offering insights into future development directions.

Keywords: biomimetic robotic fish; high maneuverability; variable stiffness; multi-fin synergy; unsteady hydrodynamics; hydrodynamic dynamic gain


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