水下仿生波动推进机器人研究现状综述OA
Review of Current Research Status of Underwater Biomimetic Undulating Propulsion Robots
仿生波动推进技术因具备高机动性和低噪声等优势,已成为水下无人航行器的重要研究方向,但其水动力性能与真实生物仍存在显著差距,推进机理、流固耦合与精确控制等关键问题尚待突破.对近二十年来该领域的研究进展进行了系统综述,重点分析了波动推进机器人的结构与驱动方式、理论建模方法、数值模拟技术、控制策略及应用现状.研究表明:传统电机驱动与智能材料驱动样机均已实现多模态运动,最高推进效率可超过 0.75,但多数游动速度仍低于 0.5 m/s;理论研究中流体阻力模型等半经验方法应用广泛,而高精度性能预测模型尚不成熟;数值模拟主要采用 URANS 模型,LES 及浸没边界法等高精度方法应用有限;控制方面,CPG 与强化学习已用于多模态与闭环控制.综合分析认为,融合多尺度流体动力学、高保真数值方法、柔性结构设计与智能控制,是提升波动推进机器人性能的关键发展方向.
Biomimetic undulating propulsion has attracted increasing attention as an alternative propulsion mode for unmanned underwater vehicles due to its high maneuverability and low noise characteristics.However,a significant performance gap still exists between artificial systems and biological counterparts,and key issues such as propulsion mechanisms,fluid-structure interaction,and precise control remain unresolved.This paper presents a systematic review of the research progress over the past two decades,focusing on the design and actuation,theoretical modeling approaches,numerical simulation methods,control strategies,and potential applications of undulating propulsion robots.The review indicates that both motor-driven and smart material-driven prototypes have achieved multimodal locomotion,with reported peak propulsive efficiencies exceeding 0.75,while most swimming speeds remain below 0.5 m/s.In theoretical studies,semi-empirical approaches such as fluid resistance models are widely adopted,whereas high-fidelity performance prediction models are still not mature.Numerical investigations are predominantly based on URANS models,with limited application of high-accuracy methods such as LES and immersed boundary methods.In terms of control,central pattern generators and reinforcement learning techniques have been applied to multimodal and closed-loop control.Overall,the integration of multiscale hydrodynamics,high-fidelity numerical modeling,flexible structural design,and intelligent control is identified as a key direction for improving the performance of undulating propulsion robots.
胡桥;岳丹枫;张堂佳;石鑫东;李士杰;曾杨彬
西安交通大学 机械工程学院,陕西 西安 710049||西安交通大学 陕西省智能机器人重点实验室,陕西 西安 710049西安交通大学 机械工程学院,陕西 西安 710049西安交通大学 机械工程学院,陕西 西安 710049西安交通大学 机械工程学院,陕西 西安 710049西安交通大学 机械工程学院,陕西 西安 710049西安交通大学 机械工程学院,陕西 西安 710049
信息技术与安全科学
仿生推进波动鳍水下机器人水动力性能数值模拟控制策略
biomimetic propulsionundulating finunderwater robothydrodynamic performancenumerical simulationcontrol strategy
《数字海洋与水下攻防》 2026 (1)
2-31,30
国家自然科学基金"基于刚柔感知融合的水下机器人波动推进步态与时变流场自匹配研究"(52371337),"叶企孙"科学基金"水下流电复合侧线阵列高精度感知机制与方法研究(U2441288).
评论