Classification of the Fish Inspired Robots: Comparison
View Latest Version
Please note this is a comparison between Version 3 by Jason Zhu and Version 2 by Jason Zhu.

Compared with traditional underwater vehicles, bio-inspired fish robots have the advantages of high efficiency, high maneuverability, low noise, and minor fluid disturbance. The propulsion ability of fish comes from the coordination between muscle groups, which gives its body uniform weight distribution and a more space-saving motion structure. A body that has evolved over billions of years also has an excellent hydrodynamic shape and a reasonable structural elastic modulus. At the same time, the organic combination of movement between muscle groups is also the reason to improve the overall efficiency of movement. Finally, fish have unique fluid sensing systems. A body and (or) caudal fin (BCF) swimmer bends its body into a backward propulsive wave that extends up to its caudal fin, while median and paired fin (MPF) swimmers use the median and paired fins to gain thrust. Similar to the classification of the biological systems, fish-inspired robots can also be divided into BCF-based and MPF-based robotic fish with a series of subcategories.

  • Classification
  • Fish Inspired Robots
  • fish swimming

1. Introduction

The ocean accounts for 71% of the earth’s total surface area and is also a critical resource pool for humankind. The vast amount of water, mineral, and biological resources in the ocean are essential to modern society, and their potential value is much more sufficient compared to the land resources [1][2]. Therefore, how to explore and exploit the ocean safely and efficiently has become one of the leading research interests of the scientific community.
The human development of ocean vehicles can be traced back to ancient times, and the initial ocean explorer mainly sailed on the water surface [3]. However, since the 1930s, scientists and engineers have made tremendous progress in underwater vehicles. After two generations of underwater vehicle iterations [4], the current multi-species and multi-functional submersibles can already work effectively at different depths, from shallow to full ocean depth [5][6][7][8][9][10][11]. The new development goals have shifted to performance optimization involving complex hydrodynamic effects, such as swimming efficiency and noise control, inspired by aquatic animals.
Unlike traditional submersibles that obtain mobility from propellers and rudders, fish have evolved over millions of years to use oscillatory motion to swim and maneuver. Studies have found that such an oscillatory motion could lead to a high propulsion efficiency, super-maneuverability, low noise, and minor disturbance to the flow field [12][13][14][15]. In addition, aquatic animals have evolved to obtain various flow sensing abilities to perceive the complicated underwater environments [16][17][18]. Inspired by nature, the learning of the fish bionics and the design of the robotic fish are of great interest and importance for developing next-generation submersibles.
In more detail, via biological observation, fluid and structure experimentation, and numerical simulation, research has shown how fish use their soft bodies and specially evolved sensory systems to swim, maneuver, and navigate in the complex underwater environment in a highly efficient and agile manner. In addition, many researchers have also made solid progress on the design, fabrication, and control of bio-inspired aquatic robotics. As a matter of fact, since the birth of the “Robo-Tuna” by Triantafyllou et al. [19], over the last 30 years, human have witnessed a significant number of bionic swimming robots of different shapes and sizes, and the creature they mimic varies from fish (listed in detail in the following article) to all kinds of aquatic organisms, such as frogs [20][21], octopuses [22][23][24], jellyfish [25][26], etc. Their performance and the techniques involving various disciplines are aligned with continuous progress and innovation in material science, fluid mechanics, and control theory.
Despite extensive research in related fields, many scientific and technological bottlenecks still remain. First of all, understanding the complex fluid–fish–body interaction phenomenon is a significant challenge, especially within unsteady flow conditions. Computational fluid dynamics (CFD) has become a major tool to assist the experimental investigation but still suffers problems, such as the extensive computation resources required [27]. The second is the difference in the driving structure of natural fish compared to its robotic counterpart. The propulsion ability of fish comes from the coordination between muscle groups [28], which gives its body uniform weight distribution and a more space-saving motion structure. A body that has evolved over billions of years also has an excellent hydrodynamic shape and a reasonable structural elastic modulus. At the same time, the organic combination of movement between muscle groups is also the reason to improve the overall efficiency of movement [29]. Finally, fish have unique fluid sensing systems, such as the lateral line system in satin fish and the bioelectric system in sharks [17][18]. These fluid perception systems allow the foil to perceive the perturbation information of the flow field and efficiently utilize the energy in the flow field to enhance efficiency.
In the past decade, researchers have made more progress in the above problems, including the understanding and control of the physics of rigid and flexible foils [30][31][32] (as a simplified model of swimming fish), and shedding some light on the complex interaction between fish fins and their moving bodies. Meanwhile, tremendous advances based on materials science and computer science also breathe new life into the robotic fish design. New flexible materials and actuators have laid the foundation for the soft bionic shape of the robot fish [33][34][35]. Artificial intelligence algorithms and the extraction and analysis of big data have also greatly enhanced the robot’s overall optimization, fine control, and information perception capabilities [36][37]. The addition of these new technologies leads the research of robot fish toward an interdisciplinary approach and makes the research field considerably broadened.

2. Robots in Anguilliform

The anguilliform caudal fin category represents animals that are highly flexible (due to a large number of vertebrae) and have a small turning radii [38][39]. Snake-like robots show the full body undulation as anguilliform and, hence are concluded. Moreover, some amphibious robots, which include Salamandra Robotica II [40] developed by Crespi et al., Series Elastic Actuated Snake [41], Mamba Waterproof Snake Robot [42], and amphibious snake-like robot developed by Yu et al. [43] also belong to this category, as they also perform anguilliform locomotion. Due to the hyper-redundant design comprising multiple serially connected links, anguilliform robots obtain relatively high maneuverability as the high degree of freedom of the robot. While the early efforts in this category are considered to be the Amphibot [44], which the actuators only allow for one degree of freedom, Stefanini et al. created the LAMPETRA [45], which has a more flexible body thanks to smaller sections and actuators. After that, Salamandra Robotica I [46] and II [40], as amphibious snake-like robots, were created with 18 and 20 degrees of freedom (DOF), respectively. However, the pseudo-rigid nature of the links leads to the maneuverability loss of the robots, compared with their biological counterparts.

3. Robots in Subcarangiform and Carangiform

The subcarangiform and carangiform classifications are highly similar and can be distinguished by a slightly different initiation point along the body. In particular, subcarangiform fish utilize slightly more back and forth head movement [47], while carangiform fish utilize one-third of their posterior body for undulation [48]. Due to the difficulty of discerning the robot’s variation in body undulation initiation between subcarangiform and carangiform, the robots in these categories are grouped based on their actuation mechanism. Researchers divide them into four parts: the three-link systems, four-linked systems, multi-linked systems, and the outliers [28]. Considering the three-link actuation robots, the G9 fish [49] is the most famous, which has a rigid body unit that houses components. For the four-link systems, Yu et al. proposed three different robots, namely Four-Joint Robotic Fish, Four-Link Robotic Fish Large Pectoral Fin Control Surfaces [50] and AmphiRobot-II [51] with a rigid body. Koca et al. [52] created a robot that has a small rigid body, where the caudal peduncle actuation unit is a majority of the body length. This robot has fixed pectoral fins and a sizable rigid tail. In 2005, multiple robots were created through the work of Essex MT1 Robotic Fish [53] for which the actuation mechanism is multi-linked peduncle units, where rigid components are used. Information on the construction of these robots is limited, but the Essex C-turn Robot [54] has a small head unit and a large peduncle section, where a multi-sectioned skin covers the peduncle section. Ichikizaki et al. [55] created a Carp-inspired robot, where the robot structure was contained within a mimetic body shell. Furthermore, Clapham et al. [56] created iSplash, which showed promise in body undulation mimicry. There are also a few robots that do not belong to the three- or four-link systems. For instance, a wire-driven shark was constructed by Lau et al. [57], with a multi-segmented tail, providing the capability for good peduncle flexion. Furthermore, a hydraulic actuated peduncle was created by Katzschmann et al. [58], of which the peduncle is made of soft materials. Katzschmann et al. [59] proposed an acoustically controlled soft robotic fish to explore underwater life. In a word, major robots in this category maintained rigidity during the locomotion, and therefore the body undulation is localized in the posterior portion, which causes an enhanced propulsive force [60]. Therefore, carangiform and subcarangiform locomotion robots are more likely to have higher speeds than those that are anguilliform.

4. Robots in Thunniform

With a very limited body undulation to the last quarter of the body, thunniform fish are usually very streamlined and extremely efficient fish, as they sustain top speed for a long duration to either pursue prey or avoid even larger predators [61][62]. The thunniform robots use a peduncle actuation unit and different actuation mechanisms to achieve a more concentrated tail actuation. An early effort in Thunniform robots was the RoboTuna created by MIT [63]. Thereafter, a robot mimicking a mackerel called Mackerel Robot [64] was created in 2012. These two robots were both equipped with a flexible, streamlined skin and fixed to a strut. Furthermore, inspired by the RoboTuna, a large vorticity control unmanned undersea vehicle (VCUUV) was created by Anderson et al. at the Draper Laboratory [65]. This design is capable of high-speed swimming; however, this is also a weighty hydraulic design. Chen et al. created an ionic polymer–metal composite (IPMC) peduncle-driven robot, where the body and pectoral fins are rigid structures with no complacent movement [66]. Moreover, a miniature robotic fish was created by Marras et al., where the body and peduncle could be considered two separate units controlled by a single motor and joint [67]. A relatively simple single-motor-actuated robotic fish called Single-Motor-Actuated Robotic Fish, was created by Yu et al. [68], in which the motor gives motion to an eccentric wheel that drives a connecting rod. In 2011, a multi-linked robotic dolphin was created by Shen et al., which has a polymer–metal peduncle unit composited of three links that allow for vertical flexion and a fourth for a smaller horizontal flexion [69]. In addition, a slider-crank robotic dolphin was created that gave actuation to two vertical pitch units and one yaw unit, which realizes a tail flexion with three degrees of freedom, and the pectoral fins are fixed surfaces [70]. Through efforts to increase the endurance, a gliding mode was conceived for a mechanical design by Wu et al., in which the robot incorporated a single joint for the movement of the peduncle with another joint for the movement of the caudal fin [71]. Yu et al. [72] created a dolphin robot that was capable of fast speed and leaping out of the water.

5. Robots in Ostraciiform

The ostraciiform is a unique class because it uses an oscillatory thrust-generating mechanism. These fish gain propulsive power through the low hydrodynamic efficient, pendulum-like oscillations of the stiff caudal fin. However, these fish have good maneuverability in the tiny crevasses as their habitats [73]. Ostraciiform robots utilize fewer actuators because only the tail fin needs to oscillate. Moreover, these robots mainly have a rigid body with high maneuverability. For instance, the BoxyBot created by Lachat et al. [74] is a rigid component-based robot, and the body was separated into two sections. Kodati et al. [75] created a robot named the microautonomous robotic ostraciiform (MARCO). Wang [76] and his consultants created the Boxfish-like robot, which was slightly smaller but had the same capabilities. Mainong et al. [77] used their design to invest different aspect ratios and shapes for the pectoral fins. The body is a mimic of the boxfish, of which the caudal fin has 1 DOF, while the pectoral fins have 360° movement spaces.

6. Robots in Labriform

The species of labriform tend to be found in reefs and areas of coverage in which fish use a caudal fin occasionally when their pectoral muscles are at maximum endurance or when performing a burst acceleration [78]. Moreover, these fish may have low endurance when solely utilizing the pectoral fins [79]. As it is challenging to create a stable robot that solely uses fin oscillation, there are few robots belonging to this subcategory. Sitorus et al. [80] created the early labriform robot, called Wrasse robot, in 2009. Thereafter, by efforts by Behbahani et al. [81], a labriform swimming robot was proposed with flexible pectoral fins which could perform both the rowing and flapping motions. Moreover, a cross-over robot that drives its pectoral fins and a dual caudal fin for swimming was proposed by Zhang et al. [82]. The robot used a hybrid fin mode; the pectoral fins have 3 DOF, while the dual caudal fin has 1 DOF, and the whole kinematic system compresses the water when their strokes come together.

7. Robots in Rajiform

The body of individuals in rajiform comprises cartilage, which gives their whole body great flexibility. Furthermore, the fin ribs extend from the body into the pectoral fin [83]. In practical robot fish design, there are a variety of robots belonging to this class due to the advantage in efficiency and maneuverability. Here, researchers divide them into two parts, namely leading-edge rib-based robots and multi-ribbed-based robots. For the leading-edge rib-based robots, one crucial early effort to note is the manta ray robot, with a rigid unit as the body and fixed control surfaces as horizontal and vertical tails [84]. This robot was then upgraded into the Robo-Ray III, where the fixed control surfaces were replaced by functioning ones that increased stability and depth control [85]. Furthermore, a rigid encased skeleton design called flexible pectoral foil cownose ray was created by Cai et al. [86]. The skeleton was encased in a mimetic body resembling the manta ray. A soft material leading edge design called IPMC manta ray was created by Chen et al. [87], using the elastomer membrane fin as the front part of the body. Alvarado et al. [88] proposed a similar design called the soft body single–dual actuator ray with a body that contains more than 70% soft materials. In addition, Chew et al. [89] created a leading edge design named the bionic fin manta ray in 2015, which gave flapping actuation to a rigid, leading edge in the pectoral fin. There are also various bionic prototypes for the actively excited multi-ribbed rajiform category. The first robot to be considered is the cow-nosed ray-I created by Yang et al. [90] with an actuation skeleton that excites multiple ribs in a flexible membrane. Zhong et al. [91] designed RoMan-I with interlimb coordination of 14 DOF involved in the thrust generation, which can perform swimming and gliding locomotion in water driven by servomotors. Rowan-II was developed by Zhou et al. [92][93], which can perform diversified locomotion patterns in water by using a model of artificial central pattern generators (CPGs) constructed with coupled nonlinear oscillators. After that, a larger version called RoMan-III was proposed by Low et al. [85] based on RoMan-II; the size of the third version is much more compact while maintaining the velocity. Punning et al. [94] and Takagi et al. [95] designed relatively similar IPMC robots called IPMC chain ribbed ray and multi-ribbed IPMC, respectively. Moreover, Krishnamurthy et al. [96] created a RayBot which is a rajiform robot that uses a caudal fin for propulsion. The smallest robot considered is a soft-robotic ray combined with tissue engineering, which was created by Park et al. [97] with a metallic skeleton that transports electrical excitation to multiple ribs. Although rajiform fish have high maneuverability, the same ability of the robots inspired by rajiform locomotion varies from low to medium. The difference in performance should be attributed to the flexibility deficiency of the broad fins used in the robots compared to the fins of real fishes, resulting in lower degrees of freedom [60].

8. Robots in Amiiform

The fish in amiiform are not extremely fast, but they can move forward and backward by switching the direction of the wave motion in the fin, which shows decent agility [98]. Compared to the subcategory above, the robots designed in amiiform are relatively few. Hu et al. [99] proposed the RoboGrilos with a very slender rigid body that contains the necessary actuation mechanisms to carry the translational undulation wave. Moreover, a remarkably similar dorsal undulation fin design called the Dorsal Undulation Fin Robot was implemented with a rigid shell encasement akin to the torpedo by Xie et al. [100]

9. Robots in Gymnotiform

Gymnotiform fish are experts in complex maneuvering. In particular, fish in this subcategory bend the body at a significant angle, allowing the fin even to be in a vertical axis, which can permit them to move with a higher degree of freedom [101]. Similar to amiiform, the gymnotiform class has few robot systems to be classified. Siahmansouri et al. [102] incorporated a knifefish robot with pitch and yaw actuation joints that connect to the multi-ribbed propulsion fin. Curet et al. [103] created a robot that has an actuation mechanism encased in a rigid tubular shell. Furthermore, Liu et al. [104] proposed a robot that uses a passive fin design, where a rib on the nose and tail of the robot gives excitation to the flexible fin membrane stretched between them.

10. Summary

From the above introduction, it is obvious that each swimming mode of fish has its unique characteristics, advantages, appropriate flow field environment, and the corresponding designs of fish-inspired robots often make trade-offs in these different properties. It should be noted that the caudal fin-propelled BCF swimming mode is still the dominant driving mode in this period for high-speed fish and bionic fish, but researchers have also paid attention to the synergy between different fins and the hydrodynamic effects generated by the overall flexible deformation of the fish. However, most bionic attempts at this stage are still relatively crude imitations, rarely supported by quantitative and complete hydrodynamic theories, and are hard to be further optimized. It is foreseeable that future bionic fish should consider the characteristics of flexible deformation and the design introducing artificial intelligence to achieve better hydrodynamic performance.

References

  1. Trujillo, A.P.; Thurman, H.V. Essentials of Oceanography; Pearson: London, UK, 2017.
  2. Garrison, T.S. Oceanography: An Invitation to Marine Science. Cengage Learning: Boston, MA, USA, 2012.
  3. Jackson, S. Argo: The first ship? Rhein. Mus. Philol. 1997, 140, 249–257.
  4. Cui, W.C. An overview of submersible research and development in China. J. Mar. Sci. Appl. 2018, 17, 459–470.
  5. Takagawa, S.; Takahashi, K.; Sano, T. 6500 m deep manned research submersible Shinkai 6500 system. In Proceedings of the OCEANS’89, Hamilton, OH, USA, 18–21 September 1989.
  6. Boillot, G.; Comas, M.C.; Girardeau, J.; Kornprobst, J.; Loreau, J.P.; Malod, J.; Mougenot, D.; Moullade, M. Preliminary results of the Galinaute cruise: Dives of the submersible Nautile on the western Galicia margin, Spain. In Proceedings of the Ocean Drilling Program Scientific Results; Boillot, G., Winterer, E.L., Eds.; 1988; Volume 103, pp. 37–51. Available online: https://www.researchgate.net/publication/265264256_Preliminary_Results_of_the_Galinaute_Cruise_Dives_of_the_Submersible_Nautile_on_the_Western_Galicia_Margin_Spain (accessed on 12 April 2022).
  7. Cui, W. Development of the Jiaolong deep manned submersible. Mar. Technol. Soc. J. 2013, 47, 37–54.
  8. Cui, W.; Hu, Y.; Guo, W. Chinese journey to the challenger deep: The development and first phase of sea trial of an 11,000-m Rainbowfish ARV. Mar. Technol. Soc. J. 2017, 51, 23–35.
  9. Wu, J.; Shi, K.; Liu, J.; Xu, H.; Wang, Y.; Li, Y.; Xu, C. Development and experimental research on the variable buoyancy system for the 6000m rated class “Qianlong I” AUV. J. Ocean Technol. 2014, 33, 1–7.
  10. YANG, B.; LIU, Y.; LIAO, J. Manned Submersibles—Deep-sea Scientific Research and Exploitation of Marine Resources. Bull. Chin. Acad. Sci. 2021, 36, 622–631.
  11. Yu, J.c.; Zhang, A.q.; Jin, W.m.; Chen, Q.; Tian, Y.; Liu, C.j. Development and experiments of the sea-wing underwater glider. China Ocean Eng. 2011, 25, 721–736.
  12. Williams, S.B.; Newman, P.; Rosenblatt, J.; Dissanayake, G.; Durrant-Whyte, H. Autonomous underwater navigation and control. Robotica 2001, 19, 481–496.
  13. Blidberg, D.R. Autonomous underwater vehicles: A tool for the ocean. Unmanned Syst. 1991, 9, 10–15.
  14. Sfakiotakis, M.; Lane, D.M.; Davies, J.B.C. Review of fish swimming modes for aquatic locomotion. IEEE J. Ocean. Eng. 1999, 24, 237–252.
  15. Anderson, J.M. The vorticity control unmanned undersea vehicle. In Proceeding of the International Symposium on Seawater Drag Reduction, Newport, RI, USA, 22–23 July 1998; pp. 479–484.
  16. Montgomery, J.; Coombs, S.; Halstead, M. Biology of the mechanosensory lateral line in fishes. Rev. Fish Biol. Fish. 1995, 5, 399–416.
  17. Hino, H.; Miles, N.; Bandoh, H.; Ueda, H. Molecular biological research on olfactory chemoreception in fishes. J. Fish Biol. 2009, 75, 945–959.
  18. Kramer, B. Electroreception and Communication in Fishes; Gustav Fischer: Stuttgart, Germany, 1996; Volume 42.
  19. Triantafyllou, M.S.; Triantafyllou, G.S. An efficient swimming machine. Sci. Am. 1995, 272, 64–70.
  20. Soomro, A.M.; Memon, F.H.; Lee, J.W.; Ahmed, F.; Kim, K.H.; Kim, Y.S.; Choi, K.H. Fully 3D printed multi-material soft bio-inspired frog for underwater synchronous swimming. Int. J. Mech. Sci. 2021, 210, 106725.
  21. Fan, J.; Wang, S.; Yu, Q.; Zhu, Y. Swimming performance of the frog-inspired soft robot. Soft Robot. 2020, 7, 615–626.
  22. Cianchetti, M.; Calisti, M.; Margheri, L.; Kuba, M.; Laschi, C. Bioinspired locomotion and grasping in water: The soft eight-arm OCTOPUS robot. Bioinspiration Biomim. 2015, 10, 035003.
  23. Fras, J.; Noh, Y.; Macias, M.; Wurdemann, H.; Althoefer, K. Bio-inspired octopus robot based on novel soft fluidic actuator. In Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia, 21–25 May 2018; pp. 1583–1588.
  24. Wu, Q.; Yang, X.; Wu, Y.; Zhou, Z.; Wang, J.; Zhang, B.; Luo, Y.; Chepinskiy, S.A.; Zhilenkov, A.A. A novel underwater bipedal walking soft robot bio-inspired by the coconut octopus. Bioinspiration Biomim. 2021, 16, 046007.
  25. Godaba, H.; Li, J.; Wang, Y.; Zhu, J. A soft jellyfish robot driven by a dielectric elastomer actuator. IEEE Robot. Autom. Lett. 2016, 1, 624–631.
  26. Cheng, T.; Li, G.; Liang, Y.; Zhang, M.; Liu, B.; Wong, T.W.; Forman, J.; Chen, M.; Wang, G.; Tao, Y.; et al. Untethered soft robotic jellyfish. Smart Mater. Struct. 2018, 28, 015019.
  27. Norton, T.; Sun, D.W. Computational fluid dynamics (CFD)–an effective and efficient design and analysis tool for the food industry: A review. Trends Food Sci. Technol. 2006, 17, 600–620.
  28. Salazar, R.; Fuentes, V.; Abdelkefi, A. Classification of biological and bioinspired aquatic systems: A review. Ocean Eng. 2018, 148, 75–114.
  29. Gray, J. Studies in animal locomotion: VI. The propulsive powers of the dolphin. J. Exp. Biol. 1936, 13, 192–199.
  30. Alben, S.; Witt, C.; Baker, T.V.; Anderson, E.; Lauder, G.V. Dynamics of freely swimming flexible foils. Phys. Fluids 2012, 24, 051901.
  31. Shelton, R.M.; Thornycroft, P.J.; Lauder, G.V. Undulatory locomotion of flexible foils as biomimetic models for understanding fish propulsion. J. Exp. Biol. 2014, 217, 2110–2120.
  32. Deng, J.; Sun, L.; Teng, L.; Pan, D.; Shao, X. The correlation between wake transition and propulsive efficiency of a flapping foil: A numerical study. Phys. Fluids 2016, 28, 094101.
  33. Lee, C.; Kim, M.; Kim, Y.J.; Hong, N.; Ryu, S.; Kim, H.J.; Kim, S. Soft robot review. Int. J. Control. Autom. Syst. 2017, 15, 3–15.
  34. Sun, K.; Cui, W.; Chen, C. Review of Underwater Sensing Technologies and Applications. Sensors 2021, 21, 7849.
  35. De Greef, A.; Lambert, P.; Delchambre, A. Towards flexible medical instruments: Review of flexible fluidic actuators. Precis. Eng. 2009, 33, 311–321.
  36. Fan, D.; Yang, L.; Wang, Z.; Triantafyllou, M.S.; Karniadakis, G.E. Reinforcement learning for bluff body active flow control in experiments and simulations. Proc. Natl. Acad. Sci. USA 2020, 117, 26091–26098.
  37. Fan, D.; Jodin, G.; Consi, T.; Bonfiglio, L.; Ma, Y.; Keyes, L.; Karniadakis, G.E.; Triantafyllou, M.S. A robotic intelligent towing tank for learning complex fluid-structure dynamics. Sci. Robot. 2019, 4, eaay5063.
  38. Gillis, G.B. Undulatory locomotion in elongate aquatic vertebrates: Anguilliform swimming since Sir James Gray. Am. Zool. 1996, 36, 656–665.
  39. Graham, J.B.; Lowell, W.R.; RUBINOFF, I.; MOTTA, J. Surface and subsurface swimming of the sea snake Pelamis platurus. J. Exp. Biol. 1987, 127, 27–44.
  40. Crespi, A.; Karakasiliotis, K.; Guignard, A.; Ijspeert, A.J. Salamandra robotica II: An amphibious robot to study salamander-like swimming and walking gaits. IEEE Trans. Robot. 2013, 29, 308–320.
  41. Rollinson, D.; Bilgen, Y.; Brown, B.; Enner, F.; Ford, S.; Layton, C.; Rembisz, J.; Schwerin, M.; Willig, A.; Velagapudi, P.; et al. Design and architecture of a series elastic snake robot. In Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA, 14–18 September 2014; pp. 4630–4636.
  42. Liljebäck, P.; Stavdahl, Ø.; Pettersen, K.Y.; Gravdahl, J.T. Mamba-A waterproof snake robot with tactile sensing. In Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA, 14–18 September 2014; pp. 294–301.
  43. Yu, S.; Ma, S.; Li, B.; Wang, Y. An amphibious snake-like robot: Design and motion experiments on ground and in water. In Proceedings of the 2009 International Conference on Information and Automation, Zhuhai/Macau, China, 22–24 June 2009; pp. 500–505.
  44. Crespi, A.; Badertscher, A.; Guignard, A.; Ijspeert, A.J. AmphiBot I: An amphibious snake-like robot. Robot. Auton. Syst. 2005, 50, 163–175.
  45. Stefanini, C.; Orofino, S.; Manfredi, L.; Mintchev, S.; Marrazza, S.; Assaf, T.; Capantini, L.; Sinibaldi, E.; Grillner, S.; Wallen, P.; et al. A compliant bioinspired swimming robot with neuro-inspired control and autonomous behavior. In Proceedings of the 2012 IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA, 14–18 May 2012; pp. 5094–5098.
  46. Crespi, A.; Ijspeert, A.J. Salamandra robotica: A biologically inspired amphibious robot that swims and walks. In Artificial life Models in Hardware; Springer: Berlin/Heidelberg, Germany, 2009; pp. 35–64.
  47. Hammond, L.; Altringham, J.D.; Wardle, C.S. Myotomal slow muscle function of rainbow trout Oncorhynchus mykiss during steady swimming. J. Exp. Biol. 1998, 201, 1659–1671.
  48. Altringham, J.; Wardle, C.; Smith, C. Myotomal muscle function at different locations in the body of a swimming fish. J. Exp. Biol. 1993, 182, 191–206.
  49. Hu, H.; Liu, J.; Dukes, I.; Francis, G. Design of 3D swim patterns for autonomous robotic fish. In Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, 9–15 October 2006; pp. 2406–2411.
  50. Yu, J.; Wang, K.; Tan, M.; Zhang, J. Design and control of an embedded vision guided robotic fish with multiple control surfaces. Sci. World J. 2014, 2014.
  51. Yu, J.; Ding, R.; Yang, Q.; Tan, M.; Wang, W.; Zhang, J. On a bio-inspired amphibious robot capable of multimodal motion. IEEE/ASME Trans. Mechatron. 2011, 17, 847–856.
  52. Koca, G.O.; Korkmaz, D.; Bal, C.; Akpolat, Z.H.; Ay, M. Implementations of the route planning scenarios for the autonomous robotic fish with the optimized propulsion mechanism. Measurement 2016, 93, 232–242.
  53. Liu, J.; Dukes, I.; Hu, H. Novel mechatronics design for a robotic fish. In Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, Edmonton, AB, Canada, 2–6 August 2005; pp. 807–812.
  54. Liu, J.; Hu, H. Mimicry of sharp turning behaviours in a robotic fish. In Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, 18–22 April 2005; pp. 3318–3323.
  55. Ichikizaki, T.; Yamamoto, I. Development of robotic fish with various swimming functions. In Proceedings of the 2007 Symposium on Underwater Technology and Workshop on Scientific Use of Submarine Cables and Related Technologies, Tokyo, Japan, 17–20 April 2007; pp. 378–383.
  56. Clapham, R.J.; Hu, H. iSplash-I: High performance swimming motion of a carangiform robotic fish with full-body coordination. In Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 31 May–7 June 2014; pp. 322–327.
  57. Lau, W.P.; Zhong, Y.; Du, R.; Li, Z. Bladderless swaying wire-driven robot shark. In Proceedings of the 2015 IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), Siem Reap, Cambodia, 15–17 July 2015; pp. 155–160.
  58. Katzschmann, R.K.; Marchese, A.D.; Rus, D. Hydraulic autonomous soft robotic fish for 3D swimming. In Proceedings of the Experimental Robotics; Springer: Berlin/Heidelberg, Germany, 2016; pp. 405–420.
  59. Katzschmann, R.K.; DelPreto, J.; MacCurdy, R.; Rus, D. Exploration of underwater life with an acoustically controlled soft robotic fish. Sci. Robot. 2018, 3, eaar3449.
  60. Raj, A.; Thakur, A. Fish-inspired robots: Design, sensing, actuation, and autonomy—A review of research. Bioinspiration Biomimetics 2016, 11, 031001.
  61. Guinet, C.; Domenici, P.; de Stephanis, R.; Barrett-Lennard, L.; Ford, J.; Verborgh, P. Killer whale predation on bluefin tuna: Exploring the hypothesis of the endurance-exhaustion technique. Mar. Ecol. Prog. Ser. 2007, 347, 111–119.
  62. Syme, D.A.; Shadwick, R.E. Red muscle function in stiff-bodied swimmers: There and almost back again. Philos. Trans. R. Soc. B 2011, 366, 1507–1515.
  63. Tolkoff, S.W. Robotics and Power Measurements of the RoboTuna. Ph.D. Thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, 1999.
  64. Wen, L.; Wang, T.; Wu, G.; Liang, J. Quantitative thrust efficiency of a self-propulsive robotic fish: Experimental method and hydrodynamic investigation. IEEE/Asme Trans. Mechatron. 2012, 18, 1027–1038.
  65. Anderson, J.M.; Chhabra, N.K. Maneuvering and stability performance of a robotic tuna. Integr. Comp. Biol. 2002, 42, 118–126.
  66. Mbemmo, E.; Chen, Z.; Shatara, S.; Tan, X. Modeling of biomimetic robotic fish propelled by an ionic polymer-metal composite actuator. In Proceedings of the 2008 IEEE International Conference on Robotics and Automation, Pasadena, CA, USA, 19–23 May 2008; pp. 689–694.
  67. Kopman, V.; Porfiri, M. Design, modeling, and characterization of a miniature robotic fish for research and education in biomimetics and bioinspiration. IEEE/ASME Trans. Mechatron. 2012, 18, 471–483.
  68. Yu, J.; Sun, F.; Xu, D.; Tan, M. Embedded vision-guided 3-D tracking control for robotic fish. IEEE Trans. Ind. Electron. 2015, 63, 355–363.
  69. Shen, F.; Wei, C.; Cao, Z.; Xu, D.; Yu, J.; Zhou, C. Implementation of a multi-link robotic dolphin with two 3-DOF flippers. J. Comput. Inform. Syst. 2011, 7, 2601–2607.
  70. Yu, J.; Wei, C. Towards development of a slider-crank centered self-propelled dolphin robot. Adv. Robot. 2013, 27, 971–977.
  71. Wu, Z.; Yu, J.; Yuan, J.; Tan, M.; Zhang, J. Mechatronic design and implementation of a novel gliding robotic dolphin. In Proceedings of the 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO), Zhuhai, China, 6–9 December 2015; pp. 267–272.
  72. Yu, J.; Su, Z.; Wu, Z.; Tan, M. Development of a fast-swimming dolphin robot capable of leaping. IEEE/ASME Trans. Mechatron. 2016, 21, 2307–2316.
  73. Hove, J.; O’Bryan, L.; Gordon, M.S.; Webb, P.W.; Weihs, D. Boxfishes (Teleostei: Ostraciidae) as a model system for fishes swimming with many fins: Kinematics. J. Exp. Biol. 2001, 204, 1459–1471.
  74. Lachat, D.; Crespi, A.; Ijspeert, A.J. Boxybot: A swimming and crawling fish robot controlled by a central pattern generator. In Proceedings of the The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics 2006, BioRob, Pisa, Italy, 20–26 February 2006; pp. 643–648.
  75. Kodati, P.; Hinkle, J.; Winn, A.; Deng, X. Microautonomous robotic ostraciiform (MARCO): Hydrodynamics, design, and fabrication. IEEE Trans. Robot. 2008, 24, 105–117.
  76. Wang, W.; Xie, G. CPG-based locomotion controller design for a boxfish-like robot. Int. J. Adv. Robot. Syst. 2014, 11, 87.
  77. Mainong, A.; Ayob, A.; Arshad, M. Investigating pectoral shapes and locomotive strategies for conceptual designing bio-inspired robotic fish. J. Eng. Sci. Technol. 2017, 12, 001–014.
  78. Korsmeyer, K.E.; Steffensen, J.F.; Herskin, J. Energetics of median and paired fin swimming, body and caudal fin swimming, and gait transition in parrotfish (Scarus schlegeli) and triggerfish (Rhinecanthus aculeatus). J. Exp. Biol. 2002, 205, 1253–1263.
  79. Behbahani, S.B.; Tan, X. Bio-inspired flexible joints with passive feathering for robotic fish pectoral fins. Bioinspiration Biomim. 2016, 11, 036009.
  80. Sitorus, P.E.; Nazaruddin, Y.Y.; Leksono, E.; Budiyono, A. Design and implementation of paired pectoral fins locomotion of labriform fish applied to a fish robot. J. Bionic Eng. 2009, 6, 37–45.
  81. Behbahani, S.B.; Tan, X. Design and modeling of flexible passive rowing joint for robotic fish pectoral fins. IEEE Trans. Robot. 2016, 32, 1119–1132.
  82. Zhang, S.; Qian, Y.; Liao, P.; Qin, F.; Yang, J. Design and control of an agile robotic fish with integrative biomimetic mechanisms. IEEE/ASME Trans. Mechatron. 2016, 21, 1846–1857.
  83. Rosenberger, L.J. Pectoral fin locomotion in batoid fishes: Undulation versus oscillation. J. Exp. Biol. 2001, 204, 379–394.
  84. Gao, J.; Bi, S.; Xu, Y.; Liu, C. Development and design of a robotic manta ray featuring flexible pectoral fins. In Proceedings of the 2007 IEEE international conference on robotics and biomimetics (ROBIO), Sanya, China, 15–18 December 2007; pp. 519–523.
  85. Low, K.; Zhou, C.; Seet, G.; Bi, S.; Cai, Y. Improvement and testing of a robotic manta ray (RoMan-III). In Proceedings of the 2011 IEEE International Conference on Robotics and Biomimetics, Karon Beach, Thailand, 7–11 December 2011; pp. 1730–1735.
  86. Cai, Y.; Bi, S.; Zhang, L.; Gao, J. Design of a robotic fish propelled by oscillating flexible pectoral foils. In Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, USA, 10–15 October 2009; pp. 2138–2142.
  87. Chen, Z.; Um, T.I.; Bart-Smith, H. Bio-inspired robotic manta ray powered by ionic polymer–metal composite artificial muscles. Int. J. Smart Nano Mater. 2012, 3, 296–308.
  88. y Alvarado, P.V.; Chin, S.; Larson, W.; Mazumdar, A.; Youcef-Toumi, K. A soft body under-actuated approach to multi degree of freedom biomimetic robots: A stingray example. In Proceedings of the 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, Tokyo, Japan, 26–29 September 2010; pp. 473–478.
  89. Chew, C.M.; Lim, Q.Y.; Yeo, K. Development of propulsion mechanism for Robot Manta Ray. In Proceedings of the 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO), Zhuhai, China, 6–9 December 2015; pp. 1918–1923.
  90. Yang, S.b.; Qiu, J.; Han, X.y. Kinematics modeling and experiments of pectoral oscillation propulsion robotic fish. J. Bionic Eng. 2009, 6, 174–179.
  91. Zhong, Y.; Zhang, D.; Zhou, C.; Chong, C.; Hu, T.; Shen, L.; Low, K. Better endurance and load capacity: An underwater vehicle inspired by manta ray. In Proceedings of the The Fourth International Symposium on Aero Aqua Bio-Mechanisms (ISABMEC2009), Shanghai, China, 9 August–2 September 2009.
  92. Zhou, C.; Low, K.H. Better endurance and load capacity: An improved design of manta ray robot (RoMan-II). J. Bionic Eng. 2010, 7, S137–S144.
  93. Zhou, C.; Low, K. Design and locomotion control of a biomimetic underwater vehicle with fin propulsion. IEEE/ASME Trans. Mechatron. 2011, 17, 25–35.
  94. Punning, A.; Anton, M.; Kruusmaa, M.; Aabloo, A. A biologically inspired ray-like underwater robot with electroactive polymer pectoral fins. In Proceedings of the International IEEE Conference on Mechatronics and Robotics, Chengdu, China, 26–31 August 2004; Volume 2004, pp. 241–245.
  95. Takagi, K.; Yamamura, M.; Luo, Z.W.; Onishi, M.; Hirano, S.; Asaka, K.; Hayakawa, Y. Development of a rajiform swimming robot using ionic polymer artificial muscles. In Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, 9–15 October 2006; pp. 1861–1866.
  96. Krishnamurthy, P.; Khorrami, F.; De Leeuw, J.; Porter, M.; Livingston, K.; Long, J. An electric ray inspired biomimetic autonomous underwater vehicle. In Proceedings of the 2010 American Control Conference, Baltimore, MD, USA, 30 June–2 July 2010; pp. 5224–5229.
  97. Park, S.J.; Gazzola, M.; Park, K.S.; Park, S.; Di Santo, V.; Blevins, E.L.; Lind, J.U.; Campbell, P.H.; Dauth, S.; Capulli, A.K.; et al. Phototactic guidance of a tissue-engineered soft-robotic ray. Science 2016, 353, 158–162.
  98. Jagnandan, K.; Sanford, C.P. Kinematics of ribbon-fin locomotion in the bowfin, Amia calva. J. Exp. Zool. Part A 2013, 319, 569–583.
  99. Hu, T.; Shen, L.; Lin, L.; Xu, H. Biological inspirations, kinematics modeling, mechanism design and experiments on an undulating robotic fin inspired by Gymnarchus niloticus. Mech. Mach. Theory 2009, 44, 633–645.
  100. Xie, H.; Zhou, H.; Shen, L.; Yin, D. Mechanism design, dynamics modelling and experiments of bionic undulating fins. Int. J. Robot. Autom. 2016, 31.
  101. Youngerman, E.D.; Flammang, B.E.; Lauder, G.V. Locomotion of free-swimming ghost knifefish: Anal fin kinematics during four behaviors. Zoology 2014, 117, 337–348.
  102. Siahmansouri, M.; Ghanbari, A.; Fakhrabadi, M.M.S. Design, implementation and control of a fish robot with undulating fins. Int. J. Adv. Robot. Syst. 2011, 8, 60.
  103. Curet, O.M.; Patankar, N.A.; Lauder, G.V.; MacIver, M.A. Mechanical properties of a bio-inspired robotic knifefish with an undulatory propulsor. Bioinspiration Biomim. 2011, 6, 026004.
  104. Liu, F.; Lee, K.M.; Yang, C.J. Hydrodynamics of an undulating fin for a wave-like locomotion system design. IEEE/ASME Trans. Mechatron. 2011, 17, 554–562.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
Feedback