人工智能仿生机器鱼研究进展与趋势探讨
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S951.2;TP242.6

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国家重点研发计划(2023YFD2401302);国家自然科学基金(41876141)


Research progress and trend analysis of AI-enabled soft bionic robotic fish
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    摘要:

    仿生鱼凭借生物启发的推进机制,在水下航行中兼具高推进效率、良好机动性以及低航行噪声,可在复杂水域环境中稳定作业,为海洋环境监测、渔业资源探测与水下工程作业等提供新的技术路径。本研究系统梳理了2005—2024年人工智能软体仿生鱼的研究进展,围绕生物原型机理、仿生设计理论、结构与驱动方式、智能控制算法及能源供给系统等维度进行总结,并按推进模式、驱动类型和典型应用场景开展对比分析。结果表明: BCF(Body and/or caudal fin)推进模式在长距离、高速巡航中效率更优,MPF(Median and/or paired fin)推进模式在低速机动与近底精细作业中稳定性更强;人工肌肉与柔性驱动在低噪声、高仿生运动上取得显著突破,但在循环寿命、输出一致性和工程化成本等方面仍存在瓶颈;多模态感知、自主决策与分布式协同控制已取得阶段性成果,但跨平台、复杂海况下自适应能力与实海可复现性仍显不足。未来需以人工智能与智能控制深度融合、新型智能材料研发、跨介质作业能力拓展为核心突破方向,重点建立统一测试基准、长期海试验证体系与标准化工程设计规范,全面提升仿生机器鱼在海洋探测、渔业资源调查与水下作业场景的工程化应用水平。

    Abstract:

    Driven by bio-inspired propulsion mechanisms, bionic robotic fish exhibit high propulsion efficiency, superior maneuverability, and low navigation noise during underwater locomotion, enabling stable operation in complex aquatic environments. This provides new technical pathways for marine environmental monitoring, fishery resource surveys, and underwater engineering operations. This paper systematically reviews the research progress of AI-enabled soft bionic robotic fish from 2005 to 2024, summarizing key developments across core dimensions including biological prototype mechanisms, bionic design theories, structural and actuation approaches, intelligent control algorithms, and power supply systems. Comparative analyses are conducted based on propulsion modes, actuation types, and typical application scenarios.The results show that the BCF (Body and/or caudal fin) propulsion mode delivers superior efficiency for long-distance, high-speed cruising, while the MPF (Median and/or paired fin) propulsion mode offers enhanced stability for low-speed maneuvering and near-bottom precision operations. Significant breakthroughs have been achieved in artificial muscles and flexible actuation for low-noise, highly biomimetic locomotion, yet bottlenecks remain in cycle life, output consistency, and engineering costs. Phased progress has been made in multimodal perception, autonomous decision-making, and distributed cooperative control, yet cross-platform adaptability, performance in complex sea conditions, and reproducibility in real-sea trials remain insufficient.Future research should prioritize three core breakthrough directions: deep integration of artificial intelligence and intelligent control, development of novel smart materials, and expansion of cross-medium operational capabilities. Key priorities include establishing unified testing benchmarks, long-term sea trial verification systems, and standardized engineering design specifications to comprehensively enhance the engineering application level of soft bionic robotic fish in marine exploration, fishery resource surveys, and underwater operation scenarios.

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陈新军,黄小双,张英,孔祥洪,刘必林,张学军.人工智能仿生机器鱼研究进展与趋势探讨[J].上海海洋大学学报,2026,35(5):1133-1145.
CHEN Xinjun, HUANG Xiaoshuang, ZHANG Ying, KONG Xianghong, LIU Bilin, ZHANG Xuejun. Research progress and trend analysis of AI-enabled soft bionic robotic fish[J]. Journal of Shanghai Ocean University,2026,35(5):1133-1145.

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  • 收稿日期:2026-05-07
  • 最后修改日期:2026-08-07
  • 录用日期:2026-08-17
  • 在线发布日期: 2026-09-08
  • 出版日期: 2026-09-30
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