• Z X Wu, J C Liu, J Z Yu, et al. Development of a novel robotic dolphin and its application to water quality monitoring. IEEE/ASME Transactions on Mechatronics, 2017, 22(5): 2130-2140.

    Article 

    Google Scholar
     

  • O Ennasr, C Holbrook, D W Hondorp, et al. Characterization of acoustic detection efficiency using a gliding robotic fish as a mobile receiver platform. Animal Biotelemetry, 2020, 8(1): 1-13.

    Article 

    Google Scholar
     

  • R K Katzschmann, J DelPreto, R MacCurdy, et al. Exploration of underwater life with an acoustically controlled soft robotic fish. Science Robotics, 2018, 3(16): eaar3449.

    Article 

    Google Scholar
     

  • Z B Xue, L L Li, Y X Song. The research of maneuverability modeling and environmental monitoring based on a robotic dolphin. Applied Bionics and Biomechanics, 2021, 2021: 4203914.

    Article 

    Google Scholar
     

  • D K Wainwright, G V Lauder. Tunas as a high-performance fish platform for inspiring the next generation of autonomous underwater vehicles. Bioinspiration & Biomimetics, 2020, 15(3): 035007.

    Article 

    Google Scholar
     

  • M I Lamas, C G Rodriguez. Hydrodynamics of biomimetic marine propulsion and trends in computational simulations. Journal of Marine Science and Engineering, 2020, 8(7): 479.

    Article 

    Google Scholar
     

  • D Scaradozzi, G Palmieri, D Costa, et al. BCF swimming locomotion for autonomous underwater robots: a review and a novel solution to improve control and efficiency. Ocean Engineering, 2017, 130: 437-453.

    Article 

    Google Scholar
     

  • Y L Yu, K J Huang. Scaling law of fish undulatory propulsion. Physics of Fluids, 2021, 33(6): 061905.

    Article 

    Google Scholar
     

  • M S Triantafyllou, G S Triantafyllou. An efficient swimming machine. Scientific American, 1995, 272(3): 64-70.

    Article 

    Google Scholar
     

  • A D Marchese, C D Onal, D Rus. Autonomous soft robotic fish capable of escape maneuvers using fluidic elastomer actuators. Soft Robotics, 2014, 1(1): 75-87.

    Article 

    Google Scholar
     

  • R Wang, S Wang, Y Wang, et al. Development and motion control of biomimetic underwater robots: A survey. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 52(2): 833-844.

    Article 

    Google Scholar
     

  • F R Xie, Q Y Zuo, Q L Chen, et al. Designs of the biomimetic robotic fishes performing body and/or caudal fin (BCF) swimming locomotion: A review. Journal of Intelligent & Robotic Systems, 2021, 102(1): 1-19.

    Article 

    Google Scholar
     

  • G V Lauder. Fish locomotion: recent advances and new directions. Annual Review of Marine Science, 2015, 7: 521-545.

    Article 

    Google Scholar
     

  • T McMillen, T Williams, P Holmes. Nonlinear muscles, passive viscoelasticity and body taper conspire to create neuromechanical phase lags in anguilliform swimmers. PLoS Computational Biology, 2008, 4(8): e1000157.

    MathSciNet 
    Article 

    Google Scholar
     

  • S Alben, C Witt, T V Baker, et al. Dynamics of freely swimming flexible foils. Physics of Fluids, 2012, 24(5): 051901.

    MATH 
    Article 

    Google Scholar
     

  • M Tanha. Complex modal analysis of carangiform swimming kinematics. East Lansing MI: Michigan State University, 2018. https://www.proquest.com/dissertations-theses/complex-modal-analysis-carangiform-swimming/docview/2100023891/se-2?accountid=28855.

  • C L Hamlet, K A Hoffman, E D Tytell, et al. The role of curvature feedback in the energetics and dynamics of lamprey swimming: A closed-loop model. PLoS Computational Biology, 2018, 14(8): e1006324.

    Article 

    Google Scholar
     

  • M A B Schwalbe, A L Boden, T N Wise, et al. Red muscle activity in bluegill sunfish Lepomis macrochirus during forward accelerations. Scientific Reports, 2019, 9(1): 1-13.

    Article 

    Google Scholar
     

  • B Jayne, G Lauder. Red muscle motor patterns during steady swimming in largemouth bass: effects of speed and correlations with axial kinematics. The Journal of Experimental Biology, 1995, 198(7): 1575-1587.

    Article 

    Google Scholar
     

  • F E Fish, G V Lauder. Passive and active flow control by swimming fishes and mammals. Annual Review of Fluid Mechanics, 2006, 38: 193-224.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • R Thandiackal, G V Lauder. How zebrafish turn: Analysis of pressure force dynamics and mechanical work. Journal of Experimental Biology, 2020, 223(16): jeb223230.

    Article 

    Google Scholar
     

  • K N Lucas, J O Dabiri, G V Lauder. A pressure-based force and torque prediction technique for the study of fish-like swimming. PloS One, 2017, 12(12): e0189225.

    Article 

    Google Scholar
     

  • T Van Buren, D Floryan, A T Bode-Oke, et al. Foil shapes for efficient fish-like propulsion. AIAA Scitech 2019 Forum, San Diego, California, January 7–11, 2019: 1379.

  • J M Anderson, K Streitlien, D S Barrett, et al. Oscillating foils of high propulsive efficiency. Journal of Fluid Mechanics, 1998, 360: 41-72.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • G V Lauder, J Lim, R Shelton, et al. Robotic models for studying undulatory locomotion in fishes. Marine Technology Society Journal, 2011, 45(4): 41-55.

    Article 

    Google Scholar
     

  • F Paraz, L Schouveiler, C Eloy. Thrust generation by a heaving flexible foil: Resonance, nonlinearities, and optimality. Physics of Fluids, 2016, 28(1): 011903.

    Article 

    Google Scholar
     

  • T Van Buren, D Floryan, N Wei, et al. Flow speed has little impact on propulsive characteristics of oscillating foils. Physical Review Fluids, 2018, 3(1): 013103.

    Article 

    Google Scholar
     

  • S Cinquemani, G Bianchi, F Resta. A coupled CFD and multibody analysis of the hydrodynamics of batoid fish. Bioinspiration, Biomimetics, and Bioreplication X. Proc. of SPIE, April 22, 2020: 11374: 113740B-1.

  • R X Li, Q Xiao, Y C Liu, et al. A multi-body dynamics based numerical modelling tool for solving aquatic biomimetic problems. Bioinspiration & Biomimetics, 2018, 13(5): 056001.

    Article 

    Google Scholar
     

  • M Porez, F Boyer, A J Ijspeert. Improved Lighthill fish swimming model for bio-inspired robots: Modeling, computational aspects and experimental comparisons. The International Journal of Robotics Research, 2014, 33(10): 1322-1341.

    Article 

    Google Scholar
     

  • F Boyer, M Porez, A Leroyer. Poincaré–Cosserat equations for the Lighthill three-dimensional large amplitude elongated body theory: Application to robotics. Journal of Nonlinear Science, 2010, 20(1): 47-79.

    MATH 
    Article 

    Google Scholar
     

  • A P S Bhalla, R Bale, B E Griffith, et al. Fully resolved immersed electrohydrodynamics for particle motion, electrolocation, and self-propulsion. Journal of Computational Physics, 2014, 256: 88-108.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • U Ehrenstein, C Eloy. Skin friction on a moving wall and its implications for swimming animals. Journal of Fluid Mechanics, 2013, 718: 321-346.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • K N Lucas, G V Lauder, E D Tytell. Airfoil-like mechanics generate thrust on the anterior body of swimming fishes. Proceedings of the National Academy of Sciences, 2020, 117(19): 10585-10592.

    MATH 
    Article 

    Google Scholar
     

  • D Zhang, J M van der Hoop, V Petrov, et al. Simulated and experimental estimates of hydrodynamic drag from bio-logging tags. Marine Mammal Science, 2020, 36(1): 136-157.

    Article 

    Google Scholar
     

  • S Verma, G Abbati, G Novati, et al. Computing the force distribution on the surface of complex, deforming geometries using vortex methods and brinkman penalization. International Journal for Numerical Methods in Fluids, 2017, 85(8): 484-501.

    MathSciNet 
    Article 

    Google Scholar
     

  • J Y Cheng, T J Pedley, J D Altringham. A continuous dynamic beam model for swimming fish. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 1998, 353(1371): 981-997.

    Article 

    Google Scholar
     

  • P P A Valdivia y Alvarado. Design of biomimetic compliant devices for locomotion in liquid environments. Massachusetts Institute of Technology, 2007, http://hdl.handle.net/1721.1/38927.

  • G Govindarajan. An investigation to identify the thrust in flapping and undulatory motion of smart Timoshenko beam. Journal of Marine Science and Technology, 2020, 25(3): 743-756.

    Article 

    Google Scholar
     

  • M Piñeirua, B Thiria, R Godoy-Diana. Modelling of an actuated elastic swimmer. Journal of Fluid Mechanics, 2017, 829: 731-750.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • F Boyer, M Porez. Multibody system dynamics for bio-inspired locomotion: from geometric structures to computational aspects. Bioinspiration & Biomimetics, 2015, 10(2): 025007.

    Article 

    Google Scholar
     

  • F Renda, F Giorgio-Serchi, F Boyer, et al. A unified multi-soft-body dynamic model for underwater soft robots. The International Journal of Robotics Research, 2018, 37(6): 648-666.

    Article 

    Google Scholar
     

  • Y W Liu, H Z Jiang, Q Huang, et al. Investigation of the resonant effect in carangiform locomotion. 2020 6th International Conference on Mechatronics and Robotics Engineering (ICMRE), Barcelona, Spain, February 12–15, 2020: 58–62.

  • H Z Jiang, Y W Liu. Nonlinear analysis of compliant robotic fish locomotion. Journal of Vibration and Control, 2021: 1077546321997608.

  • H Zhao, S C Zhen, Y H Chen. Dynamic modeling and simulation of multi-body systems using the Udwadia-Kalaba theory. Chinese Journal of Mechanical Engineering, 2013, 26(5): 839-850.

    Article 

    Google Scholar
     

  • A P S Bhalla, B E Griffith, N A Patankar. A forced damped oscillation framework for undulatory swimming provides new insights into how propulsion arises in active and passive swimming. PLoS Computational Biology, 2013, 9(6): e1003097.

    MathSciNet 
    Article 

    Google Scholar
     

  • C S Peskin. The immersed boundary method. Acta Numerica, 2002, 11: 479-517.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • S Kern, P Koumoutsakos. Simulations of optimized anguilliform swimming. Journal of Experimental Biology, 2006, 209(24): 4841-4857.

    Article 

    Google Scholar
     

  • D Xia, Q F Yin, Z H Li, et al. Numerical study on the hydrodynamics of porpoising behavior in dolphins. Ocean Engineering, 2021, 229: 108985.

    Article 

    Google Scholar
     

  • D Xia, W S Chen, J K Liu, et al. Using spanwise flexibility of caudal fin to improve swimming performance for small fishlike robots. Journal of Hydrodynamics, 2018, 30(5): 859-871.

    Article 

    Google Scholar
     

  • Z H Li, D Xia, J B Cao, et al. Hydrodynamics study of dolphin’s self-yaw motion realized by spanwise flexibility of caudal fin. Journal of Ocean Engineering and Science, 2021.

    Article 

    Google Scholar
     

  • N Y Li, H X Liu, Y M Su. Numerical study on the hydrodynamics of thunniform bio-inspired swimming under self-propulsion. PLoS One, 2017, 12(3): e0174740.

    MathSciNet 
    Article 

    Google Scholar
     

  • G S Su, H L Shen, N Y Li, et al. Numerical investigation of the hydrodynamics of stingray swimming under self-propulsion. Journal of Fluids and Structures, 2021, 106: 103383.

    Article 

    Google Scholar
     

  • S Verma, P Hadjidoukas, P Wirth, et al. Multi-objective optimization of artificial swimmers. 2017 IEEE Congress on Evolutionary Computation (CEC), Donostia, Spain, June 5–8, 2017: 1037–1046.

  • S Verma, P Hadjidoukas, P Wirth, et al. Pareto optimal swimmers. Proceedings of the Platform for Advanced Scientific Computing Conference, Lugano, Switzerland, June 26–28, 2017: 1–11.

  • D A P Reid, H Hildenbrandt, J T Padding, et al. Fluid dynamics of moving fish in a two-dimensional multiparticle collision dynamics model. Physical Review E, 2012, 85(2): 021901.

    Article 

    Google Scholar
     

  • N Thekkethil, A Sharma, A Agrawal. Three-dimensional biological hydrodynamics study on various types of batoid fishlike locomotion. Physical Review Fluids, 2020, 5(2): 023101.

    Article 

    Google Scholar
     

  • A A Shirgaonkar, M A MacIver, N A Patankar. A new mathematical formulation and fast algorithm for fully resolved simulation of self-propulsion. Journal of Computational Physics, 2009, 228(7): 2366-2390.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • P N Sun, A Colagrossi, A M Zhang. Numerical simulation of the self-propulsive motion of a fishlike swimming foil using the δ+-SPH model. Theoretical and Applied Mechanics Letters, 2018, 8(2): 115-125.

    Article 

    Google Scholar
     

  • J G Miles, N A Battista. Naut your everyday jellyfish model: exploring how tentacles and oral arms impact locomotion. Fluids, 2019, 4(3): 169.

    Article 

    Google Scholar
     

  • J G Miles, N A Battista. Exploring the sensitivity in jellyfish locomotion under variations in scale, frequency, and duty cycle. Journal of Mathematical Biology, 2021, 83(5): 1-34.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • N A Battista. Swimming through parameter subspaces of a simple anguilliform swimmer. Integrative and Comparative Biology, 2020, 60(5): 1221-1235.

    MathSciNet 
    Article 

    Google Scholar
     

  • N A Battista. Fluid-structure interaction for the classroom: interpolation, hearts, and swimming! SIAM Review, 2021, 63(1): 181-207.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • A Hemmati, U Senturk, T Van Buren, et al. The performance of a new immersed boundary method on simulating underwater locomotion and swimming. Tenth International Symposium on Turbulence and Shear Flow Phenomena, Chicago, Illinois, July 7–9, 2017: 235–240.

  • N Nangia, H Johansen, N A Patankar, et al. A moving control volume approach to computing hydrodynamic forces and torques on immersed bodies. Journal of Computational Physics, 2017, 347: 437-462.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • D Zhang, G Pan, L M Chao, et al. Mechanisms influencing the efficiency of aquatic locomotion. Modern Physics Letters B, 2018, 32(25): 1850299.

    Article 

    Google Scholar
     

  • D Zhang, L M Chao, G Pan. Ground effect on a self-propelled undulatory foil. Modern Physics Letters B, 2018, 32(11): 1850135.

    Article 

    Google Scholar
     

  • N Thekkethil, A Sharma, A Agrawal. Unified hydrodynamics study for various types of fishes-like undulating rigid hydrofoil in a free stream flow. Physics of Fluids, 2018, 30(7): 077107.

    Article 

    Google Scholar
     

  • N Thekkethil, A Sharma, A Agrawal. Self-propulsion of fishes-like undulating hydrofoil: A unified kinematics based unsteady hydrodynamics study. Journal of Fluids and Structures, 2020, 93: 102875.

    Article 

    Google Scholar
     

  • Z Cui, H Z Jiang. Numerical study of complex modal characteristics in anguilliform mode of fish swimming. Journal of Mechanical Science and Technology, 2021, 35(10): 4511-4521.

    Article 

    Google Scholar
     

  • Z Cui, Z Yang, L Shen, et al. Complex modal analysis of the movements of swimming fish propelled by body and/or caudal fin. Wave Motion, 2018, 78: 83-97.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • Z Cui, X S Gu, K K Li, et al. CFD studies of the effects of waveform on swimming performance of carangiform fish. Applied Sciences, 2017, 7(2): 149.

    Article 

    Google Scholar
     

  • P Han, J S Wang, F E Fish, et al. Kinematics and hydrodynamics of a dolphin in forward swimming. AIAA Aviation 2020 Forum, Virtual Event, June 15–19, 2020: 3015. https://doi.org/10.2514/6.2020-3015.

  • J S Wang, H Tran, M Christino, et al. Hydrodynamics and flow characterization of tuna-inspired propulsion in forward swimming. Fluids Engineering Division Summer Meeting, San Francisco, California, July 28–August 1, 2019: V001T01A025. https://doi.org/10.1115/AJKFluids2019-5472.

  • J S Wang, V Pavlov, Z P Lou, et al. Computational investigation of thrust production of a dolphin at various swimming speeds. Fluids Engineering Division Summer Meeting, August 10–12, 2021: V001T02A044. https://doi.org/10.1115/FEDSM2021-65792.

  • A N Zurman-Nasution, B Ganapathisubramani, G D Weymouth. Influence of three-dimensionality on propulsive flapping. Journal of Fluid Mechanics, 2020, 886: A25.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • N S Lagopoulos, G D Weymouth, B Ganapathisubramani. Universal scaling law for drag-to-thrust wake transition in flapping foils. Journal of Fluid Mechanics, 2019, 872: R1.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • I Borazjani, F Sotiropoulos. Numerical investigation of the hydrodynamics of anguilliform swimming in the transitional and inertial flow regimes. Journal of Experimental Biology, 2009, 212(4): 576-592.

    Article 

    Google Scholar
     

  • S A Ghaffari, S Viazzo, K Schneider, et al. Simulation of forced deformable bodies interacting with two-dimensional incompressible flows: Application to fish-like swimming. International Journal of Heat and Fluid Flow, 2015, 51: 88-109.

    Article 

    Google Scholar
     

  • M Bergmann, A Iollo. Modeling and simulation of fish-like swimming. Journal of Computational Physics, 2011, 230(2): 329-348.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • C Hamlet, L J Fauci, E D Tytell. The effect of intrinsic muscular nonlinearities on the energetics of locomotion in a computational model of an anguilliform swimmer. Journal of Theoretical Biology, 2015, 385: 119-129.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • M Gazzola, M Argentina, L Mahadevan. Scaling macroscopic aquatic locomotion. Nature Physics, 2014, 10(10): 758-761.

    Article 

    Google Scholar
     

  • G Novati, S Verma, D Alexeev, et al. Synchronisation through learning for two self-propelled swimmers. Bioinspiration & Biomimetics, 2017, 12(3): 036001.

    Article 

    Google Scholar
     

  • G Tokić, D K P Yue. Optimal shape and motion of undulatory swimming organisms. Proceedings of the Royal Society B: Biological Sciences, 2012, 279(1740): 3065-3074.

    Article 

    Google Scholar
     

  • M Gazzola, W M Van Rees, P Koumoutsakos. C-start: optimal start of larval fish. Journal of Fluid Mechanics, 2012, 698: 5-18.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • A J Wiens, A E Hosoi. Self-similar kinematics among efficient slender swimmers. Journal of Fluid Mechanics, 2018, 840: 106-130.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • T L Williams, T McMillen. Strategies for swimming: explorations of the behaviour of a neuro-musculo-mechanical model of the lamprey. Biology Open, 2015, 4(3): 253-258.

    Article 

    Google Scholar
     

  • C Wagenbach. Biological beam bending: How lamprey muscles can change the viscoelastic properties of their bodies. Medford, MA: Tufts University, 2018. https://www.proquest.com/dissertations-theses/biological-beam-bending-how-lamprey-muscles-can/docview/2027407928/se-2?accountid=28855.

  • N K Patel, A P S Bhalla, N A Patankar. A new constraint-based formulation for hydrodynamically resolved computational neuromechanics of swimming animals. Journal of Computational Physics, 2018, 375: 684-716.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • T Y Ming, B W Jin, J L Song, et al. 3D computational models explain muscle activation patterns and energetic functions of internal structures in fish swimming. PLoS Computational Biology, 2019, 15(9): e1006883.

    Article 

    Google Scholar
     

  • Z J Zhao, L Dou. Modeling and simulation of the intermittent swimming gait with the muscle-contraction model of pre-strains. Ocean Engineering, 2020, 207: 107391.

    Article 

    Google Scholar
     

  • G Tokić, D K P Yue. Energetics of optimal undulatory swimming organisms. PLOS Computational Biology, 2019, 15(10): e1007387.

    Article 

    Google Scholar
     

  • Y Q Xu, Y T Peet. Optimum gaits of 2D thunniform locomotion for efficient swimming and performance of fish pair. 2018 Fluid Dynamics Conference, Atlanta, Georgia, June 25–29, 2018: 2915.

  • R Tong, Z X Wu, D Chen, et al. Design and optimization of an untethered high-performance robotic tuna. IEEE/ASME Transactions on Mechatronics, 2022. https://doi.org/10.1109/TMECH.2022.3150982.

  • L C Xu, F B Tian, J C S Lai, et al. Optimal efficiency and heaving velocity in flapping foil propulsion. AIAA Journal, 2021, 59(6): 2143-2154.

    Article 

    Google Scholar
     

  • G Eguchi, Y Aoki, S Torisawa, et al. Mechanical efficiency of fish thrust induced by tail beating: comparison between kinetic energy and metabolic energy. Journal of Aero Aqua Bio-mechanisms, 2019, 8(1): 54-62.

    Article 

    Google Scholar
     

  • S Kern. Bioinspired optimization algorithms for the design of anguilliform swimmers. Zurich: ETH Zurich, 2007. https://doi.org/10.3929/ethz-a-005566433.

  • W M Van Rees, M Gazzola, P Koumoutsakos. Optimal morphokinematics for undulatory swimmers at intermediate Reynolds numbers. Journal of Fluid Mechanics, 2015, 775: 178-188.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • C Eloy, L Schouveiler. Optimisation of two-dimensional undulatory swimming at high Reynolds number. International Journal of Non-Linear Mechanics, 2011, 46(4): 568-576.

    Article 

    Google Scholar
     

  • C Eloy. On the best design for undulatory swimming. Journal of Fluid Mechanics, 2013, 717: 48-89.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • N Nangia, R Bale, N Chen, et al. Optimal specific wavelength for maximum thrust production in undulatory propulsion. PloS One, 2017, 12(6): e0179727.

    Article 

    Google Scholar
     

  • B Sprinkle, R Bale, A P S Bhalla, et al. Hydrodynamic optimality of balistiform and gymnotiform locomotion. European Journal of Computational Mechanics, 2017, 26(1-2): 31-43.

    MathSciNet 
    Article 

    Google Scholar
     

  • T Bujard, F Giorgio-Serchi, G D Weymouth. A resonant squid-inspired robot unlocks biological propulsive efficiency. Science Robotics, 2021, 6(50): eabd2971.

    Article 

    Google Scholar
     

  • E Demirer, Y C Wang, A Erturk, et al. Effect of actuation method on hydrodynamics of elastic plates oscillating at resonance. Journal of Fluid Mechanics, 2021, 910: A4.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • D Floryan, C W Rowley. Clarifying the relationship between efficiency and resonance for flexible inertial swimmers. Journal of Fluid Mechanics, 2018, 853: 271-300.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • M Gazzola, M Argentina, L Mahadevan. Gait and speed selection in slender inertial swimmers. Proceedings of the National Academy of Sciences, 2015, 112(13): 3874-3879.

    Article 

    Google Scholar
     

  • E D Tytell, C Y Hsu, L J Fauci. The role of mechanical resonance in the neural control of swimming in fishes. Zoology, 2014, 117(1): 48-56.

    Article 

    Google Scholar
     

  • R Thandiackal, C H White, H Bart-Smith, et al. Tuna robotics: hydrodynamics of rapid linear accelerations. Proceedings of the Royal Society B, 2021, 288(1945): 20202726.


    Google Scholar
     

  • G Li, I Ashraf, B François, et al. Burst-and-coast swimmers optimize gait by adapting unique intrinsic cycle. Communications Biology, 2021, 4(1): 1-7.

    Article 

    Google Scholar
     

  • X H Li, J Y Gu, Z Q Yao. Numerical study on the hydrodynamics of tuna morphing median fins during C-turn behaviors. Ocean Engineering, 2021, 236: 109547.

    Article 

    Google Scholar
     

  • Z H Yang, W J Gong, H Chen, et al. Research on the turning maneuverability of a bionic robotic dolphin. IEEE Access, 2022, 10: 7368-7383.

    Article 

    Google Scholar
     

  • S Gupta, N Thekkethil, A Agrawal, et al. Body-caudal fin fish-inspired self-propulsion study on burst-and-coast and continuous swimming of a hydrofoil model. Physics of Fluids, 2021, 33(9): 091905.

    Article 

    Google Scholar
     

  • T M Currier, S Lheron, Y Modarres-Sadeghi. A bio-inspired robotic fish utilizes the snap-through buckling of its spine to generate accelerations of more than 20g. Bioinspiration & Biomimetics, 2020, 15(5): 055006.

    Article 

    Google Scholar
     

  • Z Q Xin, C J Wu. Vorticity dynamics and control of the turning locomotion of 3D bionic fish. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2018, 232(14): 2524-2535.


    Google Scholar
     

  • J O Dabiri, S P Colin, B J Gemmell, et al. Jellyfish and fish solve the challenges of turning dynamics similarly to achieve high maneuverability. Fluids, 2020, 5(3): 106.

    Article 

    Google Scholar
     

  • Y K Feng, H X Liu, Y Y Su, et al. Numerical study on the hydrodynamics of C-turn maneuvering of a tuna-like fish body under self-propulsion. Journal of Fluids and Structures, 2020, 94: 102954.

    Article 

    Google Scholar
     

  • J S Wang, P Han, X L Deng, et al. Effects of flapping waveforms on the performance of burst-and-coast swimming in viscous flows. 2018 AIAA Aerospace Sciences Meeting, Kissimmee, Florida, January 8–12, 2018: 0812.

  • D Xia, W S Chen, J K Liu, et al. The energy-saving advantages of burst-and-glide mode for thunniform swimming. Journal of Hydrodynamics, 2018, 30(6): 1072-1082.

    Article 

    Google Scholar
     

  • E Akoz, A Mivehchi, K W Moored. Intermittent unsteady propulsion with a combined heaving and pitching foil. Physical Review Fluids, 2021, 6(4): 043101.

    Article 

    Google Scholar
     

  • C Wei, Q Hu, T J Zhang, et al. Passive hydrodynamic interactions in minimal fish schools. Ocean Engineering, 2022, 247: 110574.

    Article 

    Google Scholar
     

  • M Saadat, F Berlinger, A Sheshmani, et al. Hydrodynamic advantages of in-line schooling. Bioinspiration & Biomimetics, 2021, 16(4): 046002.

    Article 

    Google Scholar
     

  • S Heydari, E Kanso. School cohesion, speed and efficiency are modulated by the swimmers flapping motion. Journal of Fluid Mechanics, 2021, 922: A27.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • P Han, Y Pan, G Liu, et al. Propulsive performance and vortex wakes of multiple tandem foils pitching in-line. Journal of Fluids and Structures, 2022, 108: 103422.

    Article 

    Google Scholar
     

  • M M Macias, I F Souza, A C P B Junior, et al. Three-dimensional viscous wake flow in fish swimming-A CFD study. Mechanics Research Communications, 2020, 107: 103547.

    Article 

    Google Scholar
     

  • M S U Khalid, J Wang, H Dong, et al. Flow transitions and mapping for undulating swimmers. Physical Review Fluids, 2020, 5(6): 063104.

    Article 

    Google Scholar
     

  • D Zhang, G Pan, L M Chao, et al. Effects of Reynolds number and thickness on an undulatory self-propelled foil. Physics of Fluids, 2018, 30(7): 071902.

    Article 

    Google Scholar
     

  • D Floryan, T Van Buren, A J Smits. Swimmers’ wake structures are not reliable indicators of swimming performance. Bioinspiration & Biomimetics, 2020, 15(2): 024001.

    Article 

    Google Scholar
     

  • G Li, D Kolomenskiy, H Liu, et al. On the interference of vorticity and pressure fields of a minimal fish school. Journal of Aero Aqua Bio-mechanisms, 2019, 8(1): 27-33.

    Article 

    Google Scholar
     

  • A P Maertens, A Gao, M S Triantafyllou. Optimal undulatory swimming for a single fish-like body and for a pair of interacting swimmers. Journal of Fluid Mechanics, 2017, 813: 301-345.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • A Gao, M S Triantafyllou. Independent caudal fin actuation enables high energy extraction and control in two-dimensional fish-like group swimming. Journal of Fluid Mechanics, 2018, 850: 304-335.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • L Z Dai, G W He, X Zhang, et al. Stable formations of self-propelled fish-like swimmers induced by hydrodynamic interactions. Journal of The Royal Society Interface, 2018, 15(147): 20180490.

    Article 

    Google Scholar
     

  • S Verma, G Novati, P Koumoutsakos. Efficient collective swimming by harnessing vortices through deep reinforcement learning. Proceedings of the National Academy of Sciences, 2018, 115(23): 5849-5854.

    Article 

    Google Scholar
     

  • L Li, M Nagy, J M Graving, et al. Vortex phase matching as a strategy for schooling in robots and in fish. Nature Communications, 2020, 11(1): 1-9.

    Article 

    Google Scholar
     

  • L M Chao, G Pan, D Zhang, et al. On the thrust generation and wake structures of two travelling-wavy foils. Ocean Engineering, 2019, 183: 167-174.

    Article 

    Google Scholar
     

  • S M Li, C Li, L Y Xu, et al. Numerical simulation and analysis of fish-like robots swarm. Applied Sciences, 2019, 9(8): 1652.

    Article 

    Google Scholar
     

  • S M Li, C Li, L Y Xu, et al. The research on efficiency of bionic robotic fish cruising formation. 2019 IEEE International Conference on Real-time Computing and Robotics (RCAR), Irkutsk, Russia, August 4–9, 2019: 379–384.

  • I Ashraf, R Godoy-Diana, J Halloy, et al. Synchronization and collective swimming patterns in fish (Hemigrammus bleheri). Journal of the Royal Society Interface, 2016, 13(123): 20160734.

    Article 

    Google Scholar
     

  • Y P Wang, X B Yang, Y F Chen, et al. A biorobotic adhesive disc for underwater hitchhiking inspired by the remora suckerfish. Science Robotics, 2017, 2(10): eaan8072.

    Article 

    Google Scholar
     

  • S Q Wang, L Li, W Zhao, et al. A biomimetic remora disc with tunable, reversible adhesion for surface sliding and skimming. Bioinspiration & Biomimetics, 2022, 17(3): 036001.

    Article 

    Google Scholar
     

  • L Wen, J C Weaver, P J M Thornycroft, et al. Hydrodynamic function of biomimetic shark skin: effect of denticle pattern and spacing. Bioinspiration & Biomimetics, 2015, 10(6): 066010.

    Article 

    Google Scholar
     

  • F Giorgio-Serchi, A K Lidtke, G D Weymouth. A soft aquatic actuator for unsteady peak power amplification. IEEE/ASME Transactions on Mechatronics, 2018, 23(6): 2968-2973.

    Article 

    Google Scholar
     

  • J H Long Jr, M E Porter, R G Root, et al. Go reconfigure: how fish change shape as they swim and evolve. Integrative and Comparative Biology, 2010, 50(6): 1120-1139.

    Article 

    Google Scholar
     

  • L M Chao, G Pan, D Zhang. Effect of the asymmetric geometry on the wake structures of a pitching foil. Chinese Physics B, 2018, 27(11): 114701.

    Article 

    Google Scholar
     

  • I Nesteruk, G Passoni, A Redaelli. Shape of aquatic animals and their swimming efficiency. Journal of Marine Biology, 2014, 2014: 470715.

    Article 

    Google Scholar
     

  • S Reddy, S Sen, C Har. Effect of flexural stiffness distribution of a fin on propulsion performance. Mechanism and Machine Theory, 2018, 129: 218-231.

    Article 

    Google Scholar
     

  • R Ramamurti, J Geder, K Viswanath, et al. Propulsion characteristics of flapping caudal fins and its upstream interaction with pectoral fins. AIAA Scitech 2019 Forum, San Diego, California, January 7–11, 2019: 1618.

  • R Mittal, H B Dong, M Bozkurttas, et al. Locomotion with flexible propulsors: II. Computational modeling of pectoral fin swimming in sunfish. Bioinspiration & Biomimetics, 2006, 1(4): S35.

    Article 

    Google Scholar
     

  • J S Wang, D K Wainwright, R E Lindengren, et al. Tuna locomotion: a computational hydrodynamic analysis of finlet function. Journal of the Royal Society Interface, 2020, 17(165): 20190590.

    Article 

    Google Scholar
     

  • A P Mignano, S Kadapa, J L Tangorra, et al. Passing the wake: using multiple fins to shape forces for swimming. Biomimetics, 2019, 4(1): 23.

    Article 

    Google Scholar
     

  • G Liu, B Geng, X D Zheng, et al. An image-guided computational approach to inversely determine in vivo material properties and model flow-structure interactions of fish fins. Journal of Computational Physics, 2019, 392: 578-593.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • F Boyer, M Porez, F Morsli, et al. Locomotion dynamics for bio-inspired robots with soft appendages: Application to flapping flight and passive swimming. Journal of Nonlinear Science, 2017, 27(4): 1121-1154.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • Y Luo, Q Xiao, G Y Shi, et al. A fluid–structure interaction solver for the study on a passively deformed fish fin with non-uniformly distributed stiffness. Journal of Fluids and Structures, 2020, 92: 102778.

    Article 

    Google Scholar
     

  • W B Wu. Locomotion of a flexible plate: How the boundary condition of the leading edge affects the self-propulsion performance. European Journal of Mechanics-B/Fluids, 2020, 84: 40-50.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • C Y Zhang, H B Huang, X Y Lu. Effect of trailing-edge shape on the self-propulsive performance of heaving flexible plates. Journal of Fluid Mechanics, 2020, 887: A7.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • A Matta, J Bayandor, F Battaglia, et al. Effects of fish caudal fin sweep angle and kinematics on thrust production during low-speed thunniform swimming. Biology Open, 2019, 8(7): bio040626.

    Article 

    Google Scholar
     

  • D Siebelts, A Kater, T Meurer. Modeling and motion planning for an artificial fishtail. IFAC-PapersOnLine, 2018, 51(2): 319-324.

    Article 

    Google Scholar
     

  • P Liu, S Q Wang, R R Liu, et al. Effects of St and Re on propulsive performance of bionic oscillating caudal fin. Ocean Engineering, 2020, 217: 107933.

    Article 

    Google Scholar
     

  • A Hussein, S A Ragab, H E Taha, et al. Optimal tail kinematics for fish-like locomotion using the unsteady vortex lattice method. 2018 AIAA Aerospace Sciences Meeting, Kissimmee, Florida, January 8–12, 2018: 0311.

  • T T Nguyen, B R Lee, T Q Vo. Dynamic analysis of a robotic fish propelled by flexible folding pectoral fins. Robotica, 2020, 38(4): 699-718.

    Article 

    Google Scholar
     

  • X F Zhou, Z H Li, Y Y Zhu, et al. Effect of pectoral fin flapping motion on swimming performance of robotic dolphin. 2020 IEEE International Conference on Mechatronics and Automation (ICMA), Beijing, China, October 13–16, 2020: 880–885.

  • L Wen, Z Y Ren, V Di Santo, et al. Understanding fish linear acceleration using an undulatory biorobotic model with soft fluidic elastomer actuated morphing median fins. Soft Robotics, 2018, 5(4): 375-388.

    Article 

    Google Scholar
     

  • S Z Wang, X Zhang, G W He. Numerical simulation of a three-dimensional fish-like body swimming with finlets. Communications in Computational Physics, 2012, 11(4): 1323-1333.

    Article 

    Google Scholar
     

  • J L Tangorra, A P Mignano, G N Carryon, et al. Biologically derived models of the sunfish for experimental investigations of multi-fin swimming. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, California, September 25–30, 2011: 580–587.

  • R X Li, Q Xiao, Y C Liu, et al. Computational investigation on a self-propelled pufferfish driven by multiple fins. Ocean Engineering, 2020, 197: 106908.

    Article 

    Google Scholar
     

  • G Liu, Y Ren, H B Dong, et al. Computational analysis of vortex dynamics and performance enhancement due to body–fin and fin–fin interactions in fish-like locomotion. Journal of Fluid Mechanics, 2017, 829: 65-88.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • Z J Zhao, L Dou. Effects of the structural relationships between the fish body and caudal fin on the propulsive performance of fish. Ocean Engineering, 2019, 186: 106117.

    Article 

    Google Scholar
     

  • G J Liu, M M Wang, A Y Wang, et al. Research on flow field perception based on artificial lateral line sensor system. Sensors, 2018, 18(3): 838.

    Article 

    Google Scholar
     

  • Y G Jiang, Z Q Ma, D Y Zhang. Flow field perception based on the fish lateral line system. Bioinspiration & Biomimetics, 2019, 14(4): 041001.

    Article 

    Google Scholar
     

  • G J Liu, M M Wang, L Xu, et al. A new bionic lateral line system applied to pitch motion parameters perception for autonomous underwater vehicles. Applied Ocean Research, 2020, 99: 102142.

    Article 

    Google Scholar
     

  • G J Liu, H H Hao, T T Yang, et al. Flow field perception of a moving carrier based on an artificial lateral line system. Sensors, 2020, 20(5): 1512.

    Article 

    Google Scholar
     

  • S Verma, C Papadimitriou, N Lüthen, et al. Optimal sensor placement for artificial swimmers. Journal of Fluid Mechanics, 2020, 884: A24.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • G J Liu, S K Liu, S R Wang, et al. Research on artificial lateral line perception of flow field based on pressure difference matrix. Journal of Bionic Engineering, 2019, 16(6): 1007-1018.

    Article 

    Google Scholar
     

  • Z J Tang, Z Wang, J Q Lu, et al. Underwater robot detection system based on fish’s lateral line. Electronics, 2019, 8(5): 566.

    Article 

    Google Scholar
     

  • A P Maertens, M S Triantafyllou. The boundary layer instability of a gliding fish helps rather than prevents object identification. Journal of Fluid Mechanics, 2014, 757: 179-207.

    Article 

    Google Scholar
     

  • A A R Gao. Sensing and control for fishlike propulsion in unsteady environments. Cambridge MA: Massachusetts Institute of Technology, 2018.


    Google Scholar
     

  • R Venturelli, O Akanyeti, F Visentin, et al. Hydrodynamic pressure sensing with an artificial lateral line in steady and unsteady flows. Bioinspiration & Biomimetics, 2012, 7(3): 036004.

    Article 

    Google Scholar
     

  • X W Zheng, C Wang, R F Fan, et al. Artificial lateral line based local sensing between two adjacent robotic fish. Bioinspiration & Biomimetics, 2017, 13(1): 016002.

    Article 

    Google Scholar
     

  • O Akanyeti, L D Chambers, J Ježov, et al. Self-motion effects on hydrodynamic pressure sensing: Part I. Forward–backward motion. Bioinspiration & Biomimetics, 2013, 8(2): 026001.

    Article 

    Google Scholar
     

  • D B Quinn, G V Lauder. Tunable stiffness in fish robotics: mechanisms and advantages. Bioinspiration & Biomimetics, 2021, 17(1): 011002.

    Article 

    Google Scholar
     

  • Q Zhong, J Zhu, F E Fish, et al. Tunable stiffness enables fast and efficient swimming in fish-like robots. Science Robotics, 2021, 6(57): eabe4088.

    Article 

    Google Scholar
     

  • T L Wang, Z Y Ren, W Q Hu, et al. Effect of body stiffness distribution on larval fish–like efficient undulatory swimming. Science Advances, 2021, 7(19): eabf7364.

    Article 

    Google Scholar
     

  • J H Long Jr, N M Krenitsky, S F Roberts, et al. Testing biomimetic structures in bioinspired robots: How vertebrae control the stiffness of the body and the behavior of fish-like swimmers. Integrative and Comparative Biology, 2011, 51(1): 158-175.

    Article 

    Google Scholar
     

  • B Wright, D M Vogt, R J Wood, et al. Soft sensors for curvature estimation under water in a soft robotic fish. 2019 2nd IEEE International Conference on Soft Robotics (RoboSoft), Seoul, South Korea, April 14–18, 2019: 367–371.

  • A Jusufi, D M Vogt, R J Wood, et al. Undulatory swimming performance and body stiffness modulation in a soft robotic fish-inspired physical model. Soft Robotics, 2017, 4(3): 202-210.

    Article 

    Google Scholar
     

  • Z Wolf, A Jusufi, D M Vogt, et al. Fish-like aquatic propulsion studied using a pneumatically-actuated soft-robotic model. Bioinspiration & Biomimetics, 2020, 15(4): 046008.

    Article 

    Google Scholar
     

  • E D Tytell, C Y Hsu, T L Williams, et al. Interactions between internal forces, body stiffness, and fluid environment in a neuromechanical model of lamprey swimming. Proceedings of the National Academy of Sciences, 2010, 107(46): 19832-19837.

    Article 

    Google Scholar
     

  • D Floryan, C W Rowley. Distributed flexibility in inertial swimmers. Journal of Fluid Mechanics, 2020, 888: A24.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • Y Luo, Q Xiao, G Y Shi, et al. The effect of variable stiffness of tuna-like fish body and fin on swimming performance. Bioinspiration & Biomimetics, 2020, 16(1): 016003.

    Article 

    Google Scholar
     

  • D Xu, H N Zeng, X Peng, et al. A stiffness adjustment mechanism based on negative work for high-efficient propulsion of robotic fish. Journal of Bionic Engineering, 2018, 15(2): 270-282.

    Article 

    Google Scholar
     

  • K K Li, H Z Jiang, S Y Wang, et al. A soft robotic fish with variable-stiffness decoupled mechanisms. Journal of Bionic Engineering, 2018, 15(4): 599-609.

    Article 

    Google Scholar
     

  • K K Li, H Z Jiang, J F H, et al. Variable-stiffness decoupling of redundant planar rotational parallel mechanisms with crossed legs. Journal of Vibration and Control, 2018, 24(23): 5525–5533.

  • B X Chen, H Z Jiang. Swimming performance of a tensegrity robotic fish. Soft Robotics, 2019, 6(4): 520-531.

    MathSciNet 
    Article 

    Google Scholar
     

  • D S Barrett. The design of a flexible hull undersea vehicle propelled by an oscillating foil. Cambridge MA: Massachusetts Institute of Technology, 1994.


    Google Scholar
     

  • J M Anderson, N K Chhabra. Maneuvering and stability performance of a robotic tuna. Integrative and Comparative Biology, 2002, 42(1): 118-126.

    Article 

    Google Scholar
     

  • J H Liang, T M Wang, Wang S, et al. Experiment of robofish aided underwater archaeology. 2005 IEEE International Conference on Robotics and Biomimetics (ROBIO), Shatin, HK, China, July 5–9, 2005: 499–504.

  • J D Liu. Modelling and online optimisation of robotic fish behaviours. Saarbrücken: LAMBERT Academic Publishing, 2013.


    Google Scholar
     

  • T M Wang, L Wen, J H Liang, et al. Fuzzy vorticity control of a biomimetic robotic fish using a flapping lunate tail. Journal of Bionic Engineering, 2010, 7(1): 56-65.

    Article 

    Google Scholar
     

  • Z S Su, J Z Yu, M Tan, et al. Implementing flexible and fast turning maneuvers of a multijoint robotic fish. IEEE/ASME Transactions on Mechatronics, 2013, 19(1): 329-338.

    Article 

    Google Scholar
     

  • R X Du, Z Li, K Youcef-Toumi, et al. Robot fish: Bio-inspired fishlike underwater robots. Berlin: Springer Science & Business Media, 2015.

    MATH 
    Book 

    Google Scholar
     

  • L Li, Lv J, W Chen, et al. Application of Taguchi method in the optimization of swimming capability for robotic fish. International Journal of Advanced Robotic Systems, 2016, 13(3): 102.

    Article 

    Google Scholar
     

  • C H White, G V Lauder, H Bart-Smith. Tunabot flex: A tuna-inspired robot with body flexibility improves high-performance swimming. Bioinspiration & Biomimetics, 2021, 16(2): 026019.

    Article 

    Google Scholar
     

  • Y Zhong, Z Li, R X Du. A novel robot fish with wire-driven active body and compliant tail. IEEE/ASME Transactions on Mechatronics, 2017, 22(4): 1633-1643.

    Article 

    Google Scholar
     

  • P L Nguyen, B R Lee, K K Ahn. Thrust and swimming speed analysis of fish robot with non-uniform flexible tail. Journal of Bionic Engineering, 2016, 13(1): 73-83.

    Article 

    Google Scholar
     

  • V Kopman, J Laut, F Acquaviva, et al. Dynamic modeling of a robotic fish propelled by a compliant tail. IEEE Journal of Oceanic Engineering, 2014, 40(1): 209-221.

    Article 

    Google Scholar
     

  • J X Wang, P K McKinley, X B Tan. Dynamic modeling of robotic fish with a base-actuated flexible tail. Journal of Dynamic Systems, Measurement, and Control, 2015, 137(1): 011004.

    Article 

    Google Scholar
     

  • H El Daou, T Salumäe, L D Chambers, et al. Modelling of a biologically inspired robotic fish driven by compliant parts. Bioinspiration & Biomimetics, 2014, 9(1): 016010.

    Article 

    Google Scholar
     

  • A J Wahab. A framework for design, modeling, and identification of compliant biomimetic swimmers. Cambridge MA: Massachusetts Institute of Technology, 2008.


    Google Scholar
     

  • W Zhou, Y Q Li. Modeling and analysis of soft pneumatic actuator with symmetrical chambers used for bionic robotic fish. Soft Robotics, 2020, 7(2): 168-178.

    Article 

    Google Scholar
     

  • T Wang, Y C Zhang, Y P Zhu, et al. A computationally efficient dynamical model of fluidic soft actuators and its experimental verification. Mechatronics, 2019, 58: 1-8.

    Article 

    Google Scholar
     

  • T Wang, Y C Zhang, Z Chen, et al. Parameter identification and model-based nonlinear robust control of fluidic soft bending actuators. IEEE/ASME Transactions on Mechatronics, 2019, 24(3): 1346-1355.

    Article 

    Google Scholar
     

  • W P Hu, R Mutlu, W H Li, et al. A structural optimisation method for a soft pneumatic actuator. Robotics, 2018, 7(2): 24.

    Article 

    Google Scholar
     

  • F Yang, Q Ruan, Y M Man, et al. Design and optimize of a novel segmented soft pneumatic actuator. IEEE Access, 2020, 8: 122304-122313.

    Article 

    Google Scholar
     

  • H L Li, J T Yao, P Zhou, et al. High-force soft pneumatic actuators based on novel casting method for robotic applications. Sensors and Actuators A: Physical, 2020, 306: 111957.

    Article 

    Google Scholar
     

  • H Feng, Y Sun, P A Todd, et al. Body wave generation for anguilliform locomotion using a fiber-reinforced soft fluidic elastomer actuator array toward the development of the eel-inspired underwater soft robot. Soft Robotics, 2020, 7(2): 233-250.

    Article 

    Google Scholar
     

  • J Frame, N Lopez, O Curet, et al. Thrust force characterization of free-swimming soft robotic jellyfish. Bioinspiration & Biomimetics, 2018, 13(6): 064001.

    Article 

    Google Scholar
     

  • A Joshi, A Kulkarni, Y Tadesse. FludoJelly: Experimental study on jellyfish-like soft robot enabled by soft pneumatic composite (SPC). Robotics, 2019, 8(3): 56.

    Article 

    Google Scholar
     

  • J Shintake, V Cacucciolo, H Shea, et al. Soft biomimetic fish robot made of dielectric elastomer actuators. Soft Robotics, 2018, 5(4): 466-474.

    Article 

    Google Scholar
     

  • T F Li, G R Li, Y M Liang, et al. Fast-moving soft electronic fish. Science Advances, 2017, 3(4): e1602045.


    Google Scholar
     

  • J J U Hubbard. Design and characterization of sectored (Patterned) IPMC actuators for propulsion and maneuvering in bio-inspired underwater systems. Reno: University of Nevada, 2011.


    Google Scholar
     

  • Z Q Ye, P Q Hou, Z Chen. 2D maneuverable robotic fish propelled by multiple ionic polymer–metal composite artificial fins. International Journal of Intelligent Robotics and Applications, 2017, 1(2): 195-208.

    Article 

    Google Scholar
     

  • X J Chen, H Shigemune, H Sawada. An untethered bionic robotic fish using SMA actuators. 2020 IEEE International Conference on Mechatronics and Automation (ICMA), Beijing, China, October 13–16, 2020: 1768–1773.

  • Z L Wang, G R Hang, J Li, et al. A micro-robot fish with embedded SMA wire actuated flexible biomimetic fin. Sensors and Actuators A: Physical, 2008, 144(2): 354-360.

    Article 

    Google Scholar
     

  • D A Paley, N M Wereley. Bioinspired sensing, actuation, and control in underwater soft robotic systems. Cham: Springer Nature Switzerland AG, 2021. https://doi.org/10.1007/978-3-030-50476-2.

    Book 

    Google Scholar
     

  • R Salazar, A Campos, V Fuentes, et al. A review on the modeling, materials, and actuators of aquatic unmanned vehicles. Ocean Engineering, 2019, 172: 257-285.

    Article 

    Google Scholar
     

  • F B Zhu, C L Zhang, J Qian, et al. Mechanics of dielectric elastomers: materials, structures, and devices. Journal of Zhejiang University-Science A, 2016, 17(1): 1-21.


    Google Scholar
     

  • J Z Yu, M Wang, H F Dong, et al. Motion control and motion coordination of bionic robotic fish: A review. Journal of Bionic Engineering, 2018, 15(4): 579-598.

    Article 

    Google Scholar
     

  • R Tong, Z X Wu, J Wang, et al. Online optimization of normalized CPGs for a multi-joint robotic fish. 2021 40th Chinese Control Conference (CCC), Shanghai, China, July 26–28, 2021: 4205–4210.

  • F R Xie, R X Du. Central pattern generator control for a biomimetic robot fish in maneuvering. 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO), Kuala Lumpur, Malaysia, December 12–15, 2018: 268–273.

  • F R Xie, Y Zhong, R X Du, et al. Central pattern generator (CPG) control of a biomimetic robot fish for multimodal swimming. Journal of Bionic Engineering, 2019, 16(2): 222-234.

    Article 

    Google Scholar
     

  • J Y Chen, B Yin, C C Wang, et al. Bioinspired closed-loop CPG-based control of a robot fish for obstacle avoidance and direction tracking. Journal of Bionic Engineering, 2021, 18(1): 171-183.

    Article 

    Google Scholar
     

  • J C Liu, C Zhang, Z N Liu, et al. Design and analysis of a novel tendon-driven continuum robotic dolphin. Bioinspiration & Biomimetics, 2021, 16(6): 065002.

    Article 

    Google Scholar
     

  • L Zhang, W Zhao, Y H Hu, et al. Development and depth control of biomimetic robotic fish. 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, California, October 29–November 2, 2007: 3560–3565.

  • F Shen, Z Q Cao, C Zhou, et al. Depth control for robotic dolphin based on fuzzy PID control. International Journal of Offshore and Polar Engineering, 2013, 23(03): 166-171.


    Google Scholar
     

  • J Z Yu, J C Liu, Z X Wu, et al. Depth control of a bioinspired robotic dolphin based on sliding-mode fuzzy control method. IEEE Transactions on Industrial Electronics, 2017, 65(3): 2429-2438.

    Article 

    Google Scholar
     

  • J Yuan, Z X Wu, J Z Yu, et al. Sliding mode observer-based heading control for a gliding robotic dolphin. IEEE Transactions on Industrial Electronics, 2017, 64(8): 6815-6824.

    Article 

    Google Scholar
     

  • Z Q Cao, F Shen, C Zhou, et al. Heading control for a robotic dolphin based on a self-tuning fuzzy strategy. International Journal of Advanced Robotic Systems, 2016, 13(1): 28.

    Article 

    Google Scholar
     

  • C Meurer, A Simha, Ü Kotta, et al. Nonlinear orientation controller for a compliant robotic fish based on asymmetric actuation. 2019 International Conference on Robotics and Automation (ICRA), Montreal, Quebec, May 20–24, 2019: 4688–4694.

  • R Y Tian, L Li, W Wang, et al. CFD based parameter tuning for motion control of robotic fish. Bioinspiration & Biomimetics, 2020, 15(2): 026008.

    Article 

    Google Scholar
     

  • J Z Yu, M Tan, Wang S, et al. Development of a biomimetic robotic fish and its control algorithm. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2004, 34(4): 1798-1810.

    Article 

    Google Scholar
     

  • Y H Hu, W Zhao, L Wang. Vision-based target tracking and collision avoidance for two autonomous robotic fish. IEEE Transactions on Industrial Electronics, 2009, 56(5): 1401-1410.

    Article 

    Google Scholar
     

  • S L Chen, J X Wang, X B Tan. Backstepping-based hybrid target tracking control for a carangiform robotic fish. Dynamic Systems and Control Conference, Palo Alto, California, October 21–23, 2013: V002T32A005.

  • J Z Yu, F H Sun, D Xu, et al. Embedded vision-guided 3-D tracking control for robotic fish. IEEE Transactions on Industrial Electronics, 2015, 63(1): 355-363.

    Article 

    Google Scholar
     

  • S Verma, J X Xu, Q Y Ren, et al. A comparison of robotic fish speed control based on analytical and empirical models. IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society, Florence, Italy, October 23–26, 2016: 6055–6060.

  • X F Li, Q Y Ren, J X Xu. Precise speed tracking control of a robotic fish via iterative learning control. IEEE Transactions on Industrial Electronics, 2015, 63(4): 2221-2228.


    Google Scholar
     

  • T Yuan, Z Y Ren, K N Hu, et al. A Kalman filter based force-feedback control system for hydrodynamic investigation of unsteady aquatic propulsion. 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO), Macau, China, December 5–8, 2017: 1214–1219.

  • P F Zhang, Z X Wu, Y Meng, et al. Nonlinear model predictive position control for a tail-actuated robotic fish. Nonlinear Dynamics, 2020, 101(4): 2235-2247.

    Article 

    Google Scholar
     

  • J Pan, J C Liu, J Z Yu. Path-following control of an amphibious robotic fish using fuzzy-linear model predictive control approach. 2020 IEEE International Conference on Mechatronics and Automation (ICMA), Beijing, China, October 13–16, 2020: 886–891.

  • S Du, C Zhou, J Z Yu, et al. A modified line-of-sight method for path tracking applied to robotic fish. 2020 IEEE International Conference on Mechatronics and Automation (ICMA), Beijing, China, October 13–16, 2020: 809–814.

  • R Wang, S Wang, Y Wang, et al. Path following for a biomimetic underwater vehicle based on ADRC. 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 29–June 3, 2017: 3519–3524.

  • R Wang, S Wang, Y Wang, et al. A paradigm for path following control of a ribbon-fin propelled biomimetic underwater vehicle. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 49(3): 482-493.

    Article 

    Google Scholar
     

  • J Z Yu, M Tan. Motion control of biomimetic swimming robots. Singapore: Springer Nature Singapore Pte Ltd., 2020. https://doi.org/10.1007/978-981-13-8771-5.

    Book 

    Google Scholar
     

  • H Cheng, H D Liu, X Q Wang, et al. Approximate piecewise constant curvature equivalent model and their application to continuum robot configuration estimation. 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Toronto, Ontario, October 11–14, 2020: 1929–1936.

  • M Luo. Pressure-operated soft robotic snake modeling, control, and motion planning. Worcester MA: Worcester Polytechnic Institute, 2017.

  • M Gazzola, B Hejazialhosseini, P Koumoutsakos. Reinforcement learning and wavelet adapted vortex methods for simulations of self-propelled swimmers. SIAM Journal on Scientific Computing, 2014, 36(3): B622-B639.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • S L Brunton, B R Noack, P Koumoutsakos. Machine learning for fluid mechanics. Annual Review of Fluid Mechanics, 2020, 52: 477-508.

    MATH 
    Article 

    Google Scholar
     

  • M Raissi, Z C Wang, M S Triantafyllou, et al. Deep learning of vortex-induced vibrations. Journal of Fluid Mechanics, 2019, 861: 119-137.

    MathSciNet 
    MATH 
    Article 

    Google Scholar
     

  • J Rabault, F Ren, W Zhang, et al. Deep reinforcement learning in fluid mechanics: A promising method for both active flow control and shape optimization. Journal of Hydrodynamics, 2020, 32(2): 234-246.

    Article 

    Google Scholar
     

  • H Xu, W Zhang, J Deng, et al. Active flow control with rotating cylinders by an artificial neural network trained by deep reinforcement learning. Journal of Hydrodynamics, 2020, 32(2): 254-258.

    Article 

    Google Scholar
     

  • Y S Jiao, F Ling, S Heydari, et al. Learning to swim in potential flow. Physical Review Fluids, 2021, 6(5): 050505.

    Article 

    Google Scholar
     

  • N Nedjah, L D S Coelho, L D M Mourelle. Mobile robots: The evolutionary approach. Berlin: Springer Science & Business Media, 2007.

    MATH 
    Book 

    Google Scholar
     

  • T G Thuruthel. Machine learning approaches for control of soft robots. Pisa: Sant’Anna School of Advanced Studies, 2019.


    Google Scholar
     

  • Y Cho, S Manzoor, Y Choi. Adaptation to environmental change using reinforcement learning for robotic salamander. Intelligent Service Robotics, 2019, 12(3): 209-218.

    Article 

    Google Scholar
     

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