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At the same time, the organic combination of movement between muscle groups is also the reason to improve the overall efficiency of movement. A body that has evolved over billions of years also has an excellent hydrodynamic shape and a reasonable structural elastic modulus. 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. The second is the difference in the driving structure of natural fish compared to its robotic counterpart.
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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. First of all, understanding the complex fluid–fish–body interaction phenomenon is a significant challenge, especially within unsteady flow conditions. Their performance and the techniques involving various disciplines are aligned with continuous progress and innovation in material science, fluid mechanics, and control theory.ĭespite extensive research in related fields, many scientific and technological bottlenecks still remain. , over the last 30 years, we 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, octopuses, jellyfish, etc.
As a matter of fact, since the birth of the “Robo-Tuna” by Triantafyllou et al.
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In addition, many researchers have also made solid progress on the design, fabrication, and control of bio-inspired aquatic robotics. 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. By introducing recent progress in related fields, we summarize the advantages and challenges of soft robotic control and multi-phase robotics, guiding the further development of bionic aquatic robots. Multi-phase robots provide a broader scope of application compared to ordinary bionic robot fish, with the ability of operating in air or on land outside the fluid. The hybrid dynamic control of soft robotic systems combines the accuracy of model-based control and the efficiency of model-free control, and is considered the proper way to optimize the classical control model with the intersection of multiple machine learning algorithms. In addition, we select two pioneering directions about soft robotic control and multi-phase robotics. Like the natural fish species they imitate, different types of bionic fish have different morphological structures and distinctive hydrodynamic properties. In this review, we first highlight our enhanced scientific understanding of bio-inspired propulsion and sensing underwater and then present the research progress and performance characteristics of different bio-inspired robot fish, classified by the propulsion method. Therefore, they have gained an increasing research interest, which has led to a great deal of remarkable progress theoretically and practically in recent years. Compared with traditional underwater vehicles, bio-inspired fish robots have the advantages of high efficiency, high maneuverability, low noise, and minor fluid disturbance.