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摘要: 水陆两栖机器人凭借其跨介质运动能力, 在巡检、侦察、生态监测等多个领域展现出广阔的应用前景. 仿生学通过借鉴水陆两栖动物的形态结构与运动策略, 为提升机器人的环境适应性与运动机动性提供重要的设计思路. 首先, 系统梳理具有不同形态特征的典型水陆两栖生物, 并阐明其推进机制对机器人设计所产生的双向促进作用. 其次, 以推进策略为主线, 将现有两栖机器人划分为采用统一驱动的单一推进机制(包括鳍推进、刚性肢体推进、柔性肢体推进及连续体波推进)以及采用不同驱动方式的混合推进机制, 分别介绍各类代表性仿生两栖机器人原型样机, 并分析各种推进方式在不同介质的适应性变化及效能. 随后, 总结感知、驱动与控制等关键技术的当前发展状况, 比较不同推进模式下控制策略的共性与差异. 最后, 结合跨介质多场景运动、具身智能及物理智能等前沿理念, 探讨水陆仿生两栖机器人未来的研究方向与应用前景.Abstract: Amphibious robots, capable of cross-medium locomotion, exhibit considerable potential and prospects in applications such as inspection, reconnaissance, and ecological monitoring. Drawing inspiration from the morphological structure and locomotion strategies of amphibious animals, bionics provides essential design principles for enhancing environmental adaptability and maneuverability of robots. This paper first presents a systematic review of representative amphibious organisms with diverse morphological characteristics and elucidates the bidirectional interaction between propulsion mechanisms and robotic design. Subsequently, using propulsion strategy as the primary classification criterion, existing amphibious robots are categorized into two main types. The first type utilizes unified actuation with single propulsion mechanisms, including fin propulsion, rigid limb propulsion, flexible limb propulsion, and continuous body wave propulsion. The second type adopts hybrid propulsion mechanisms that employ distinct actuation modes. Representative prototypes of bionic amphibious robots for each category are introduced, followed by an analysis of their adaptability and efficacy across different media. Furthermore, the current development state of key enabling technologies, including perception, actuation, and control, is comprehensively reviewed, and the commonalities and differences of control strategies under different propulsion modes are compared. Finally, by incorporating emerging concepts such as cross-medium multi-scenario locomotion, embodied intelligence, and physical intelligence, this paper discusses future research directions and potential application prospects for bionic amphibious robots.
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Key words:
- amphibious robots /
- cross-medium locomotion /
- bionic robot /
- propulsion strategy
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图 12 鳍推进类仿生两栖机器人[44−48], 经许可转载自文献[44−48], ©IEEE, 2009; ©Elsevier BV, 2024; ©Springer, 2017; ©Taylor & Francis Ltd., 2015; ©Springer Nature, 2017
Fig. 12 Fin-propelled bionic amphibious robots[44−48], reproduced with permission from reference [44−48], ©IEEE, 2009; ©Elsevier BV, 2024; ©Springer, 2017; ©Taylor & Francis Ltd., 2015; ©Springer Nature, 2017
图 13 刚体推进类两栖机器人[4, 49−53, 55−56], 经许可转载自文献[4, 49−53, 55−56], ©IEEE, 1996; ©Marine Tech- nology Society, 2016; ©Elsevier, 2017; ©IEEE, 2015; ©IEEE, 2017; ©Springer, 2017; ©IEEE, 2005; ©IEEE, 2012
Fig. 13 Rigid-body propulsion amphibious ro-bots[4, 49−53, 55−56], reproduced with permission from reference [4, 49−53, 55−56], ©IEEE, 1996; ©Marine Technology Society, 2016; ©Elsevier, 2017; ©IEEE, 2015; ©IEEE, 2017; ©Springer, 2017; ©IEEE, 2005; ©IEEE, 2012
图 14 柔性肢体推进两栖机器人[6, 57−67], 经许可转载自文献 [6, 57−67], ©IOP Publishing, 2016; ©IEEE, 2013; ©IOP Publishing, 2015; ©IOP Publishing, 2015; ©IOP Publishing, 2021; ©IEEE, 2019; ©IEEE, 2017; ©IEEE, 2021; ©Mary Ann Liebert, Inc., 2018; ©IEEE, 2023; ©IEEE, 2020; ©IOP Publishing, 2019
Fig. 14 Flexible limb-propelled amphibious robots[6, 57−67], reproduced with permission from reference [6, 57−67], ©IOP Publishing, 2016; ©IEEE, 2013; ©IOP Publishing, 2015; ©IOP Publishing, 2015; ©IOP Publishing, 2021; ©IEEE, 2019; ©IEEE, 2017; ©IEEE, 2021; ©Mary Ann Liebert, Inc., 2018; ©IEEE, 2023; ©IEEE, 2020; ©IOP Publishing, 2019
图 15 连续体波推进与混合推进两栖机器人[28, 35, 40, 68−73], 经许可转载自文献[28, 35, 40, 68−73], ©Mary Ann Liebert, Inc., 2024; ©AAAS, 2007; ©The Royal Society, 2016; ©IEEE, 2007; ©AAAS, 2024; ©IEEE, 2013; ©John Wiley & Sons Inc., 2017; ©Elsevier, 2023; ©American Chemical Society, 2022
Fig. 15 Continuous body wave propulsion and hybrid pro-pulsion amphibious robots[28, 35, 40, 68−73], reproduced with permission from reference [28, 35, 40, 68−73], ©Mary Ann Liebert, Inc., 2024; ©AAAS, 2007; ©The Royal Society, 2016; ©IEEE, 2007; ©AAAS, 2024; ©IEEE, 2013; ©John Wiley & Sons Inc., 2017; ©Elsevier, 2023; ©American Chemical Society, 2022
图 17 驱动方式原理图[44, 97−99], 经许可转载自文献[44, 97−99], ©IEEE, 2009; ©Royal Society of Chemistry, 2021; ©Springer Nature, 2015; ©Wiley, 2015
Fig. 17 Diagrams of actuation principles[44, 97−99], reproduced with permission from reference [44, 97−99], ©IEEE, 2009; ©Royal Society of Chemistry, 2021; ©Springer Nature, 2015; ©Wiley, 2015
图 18 控制策略图 ((a)行为驱动型控制方法图; (b)模型驱动型控制方法图; (c)生物神经网络控制方法图)
Fig. 18 Control strategy diagrams ((a) Behavior-driven control method diagram; (b) Model-driven control method diagram; (c) Biological neural network control method diagram)
表 1 典型传感器及功能
Table 1 Typical sensors and functions
功能目标 典型传感器 作用 文献 环境识别/介质判断 水探测传感器 判定介质环境并感知流体扰动, 支持模式切换与环境适应 [76] 人工侧线 [77–78] 外界障碍/地形感知 超声/声呐测距 获取障碍与地形信息, 实现避障与路径规划 [79–80] 相机/双目/RGB-D [81–82] 红外传感器 [83] 定位与航向 IMU 提供姿态与定位信息, 保障多环境下的稳定导航 [84–85] GPS [85] 深度/压力与介质状态 压力/深度传感器 监测水压与深度, 维持水下安全与稳定 [86] 感知与运动调控 霍尔传感器 感知腿部柔顺性, 进而实现地形分类; 控制机器人前进速度 [76, 87] 接近传感器 实现微型机器人的自主抓取、避障, 辅助在复杂/狭窄空间内的操作与定位 [88–89] 
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表 2 驱动方式表
Table 2 Table of actuation methods
驱动类型 优势 局限性 典型案例 电机驱动 技术成熟, 控制精度较高 体积较大, 密封防水设计复杂 文献[55, 92–93] 光驱动 无接触驱动, 微型化潜力大, 空间分辨率高 能量转换效率低, 受光源照射条件限制 文献[73, 94] 流体驱动 PAM 柔顺性好, 功率重量比高, 适合复杂环境 控制精度低, 系统复杂, 气源依赖大 文献[62–63, 95] FEA 柔顺性高, 安全性好, 结构简单 推力小, 适合轻载, 控制精度受限 文献[64] 磁驱动 非接触式驱动, 密封性好, 适用于微型机器人 控制精度受磁场分布限制, 输出力矩较小 文献[61, 96] 智能材料驱动 SMA 结构紧凑, 适合微小机构 能效低, 循环疲劳寿命有限 文献[6, 66] IPMC 低电压驱动, 兼具传感与驱动功能 输出力和位移有限, 长期稳定性差 文献[88] DE 轻薄柔顺, 响应快, 适合高频驱动 需高压驱动, 封装难度大, 易介电击穿 文献[52]
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