A Soft Robotic Fish with Variable-stiffness Decoupled Mechanisms

Li, Kangkang; Jiang, Hongzhou; Wang, Siyu; Yu, Jinpeng

doi:10.1007/s42235-018-0049-1

Cited by 31 publications

(23 citation statements)

References 30 publications

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“…The Reynolds number (Re) and Strouhal number (St) are also important factors to assess the hydrodynamic performance of the fish's swimming. Several robotic fish platforms inspired from actual fish morphology and swimming, such as tuna, use the same metrics to assess their robots' performance [13,[21][22][23]. Another important factor is to analyze the efficiency of fish propulsion.…”

Section: Underwater Locomotionmentioning

confidence: 99%

Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control

et al. 2022

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Nature and biological creatures are some of the main sources of inspiration for humans. Engineers have aspired to emulate these natural systems. As rigid systems become increasingly limited in their capabilities to perform complex tasks and adapt to their environment like living creatures, the need for soft systems has become more prominent due to the similar complex, compliant, and flexible characteristics they share with intelligent natural systems. This review provides an overview of the recent developments in the soft robotics field, with a focus on the underwater application frontier.

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Section: Underwater Locomotionmentioning

confidence: 99%

Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control

et al. 2022

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“…Scholars have proposed multiple ways to alter the stiffness of bionic fish [7][8][9][10][11][12] and have proposed a variety of methods to achieve variable stiffness, as Table 1 shows. Zuo [7] proposed a planar model of oscillatory propulsor with variable stiffnesses using hyperredundant serial-parallel mechanisms.…”

Section: Introductionmentioning

confidence: 99%

“…Kobayashi [10] used a fin with a variable effective length spring to change the stiffness. Li [11] made mechanisms that could be considered as redundant planar rotational parallel mechanisms with antagonistic flexible elements. Xu [12] proposed a variable stiffness mechanism that is based on negative work.…”

Section: Introductionmentioning

confidence: 99%

Experimental Research on the Coupling Relationship between Fishtail Stiffness and Undulatory Frequency

et al. 2022

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Fish can swim in a variety of states. For example, they look flexible and perform low-frequency undulatory locomotion when cruising, but they seem very powerful and stiff and perform high-frequency undulatory when hunting. In the process of changing the motion state, the stiffness of the fish body affects the swimming performance of the fish. In this article, we imitated the change of stiffness by superimposing rubber sheets and used experimental methods to test its swimming performance under different swing frequencies. A series of rubber fish tails were made according to the analysis of the swimming movement of real fish, providing different stiffness values and changing the curves of the body. In the prototype experiments, the base of the fish tail was fixed to a platform via a force sensor, which can oscillate at various speeds, so that the fish tail was able to swing and the thrust could be tested at different frequencies. According to the experimental results, we found that with the change of the swing frequency, there were different optimal stiffnesses that could make the thrust reach the maximum value, and with the increase of stiffness, the envelope interval of the swing curve gradually widened, the amplitude increased, and the hysteresis of the tail fin relative to the end decreased.

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“…Wu [15] analyzed and optimized the stiffness of a coaxial spherical parallel manipulator. Li et al [16] analyzed a soft robotic fish with variable-stiffness decoupled mechanisms. He et al [17] proposed a new general stiffness model, which includes linear and nonlinear stiffness models, for serial mechanisms.…”

Section: Introductionmentioning

confidence: 99%

“…16 are 3D and two-dimensional (2D) SD diagrams of the six mechanisms. There are considerable similarities between their SDs.…”

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confidence: 99%

Modeling and Analysis of the Stiffness Distribution of Host–Parasite Robots

et al. 2021

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The stiffness distribution (SD) of robot has a great influence on the robot pose accuracy, but the calculation efficiency and accuracy of stiffness distribution are still low.This study presents a finite element fitting method with an extremely small number of computational cells. It was developed based on experimental results of robot stiffness. This method can be employed to establish single-and multi-source fitted SD (FSD) (S-FSD and M-FSD) models for host-parasite (H-P) robots. The computational efficiency and correctness of the FSD models were verified by case studies.The configurations of six evolutionary mechanisms of an H-P robot were subjected to an SD analysis. A comparison of the six configurations shows that adding parasitic branched chains can improve the SD of the H-P robot to varying degrees. In particular, the most notable improvement was for H-P mechanism. Specifically, by averaging the stiffness of all positions, the average-stiffnesses of H-P mechanism in the x-, y-, and z-directions were 104.10%, 1427.78%, and 1101.62% of those of the host mechanism, respectively. In the SD diagram, the mediumand high-stiffness regions of mechanism F are large and distributed in a banded pattern between the highest pose point and the furthest pose point, whereas its low-stiffness region is small and concentrated near the nearest pose point .

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A Soft Robotic Fish with Variable-stiffness Decoupled Mechanisms

Cited by 31 publications

References 30 publications

Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control

Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control

Experimental Research on the Coupling Relationship between Fishtail Stiffness and Undulatory Frequency

Modeling and Analysis of the Stiffness Distribution of Host–Parasite Robots

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