Research Development on Fish Swimming

Jiang, Hongzhou

doi:10.1186/s10033-022-00791-4

Cited by 17 publications

(4 citation statements)

References 250 publications

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“…could be conducive to sustaining the Cr into Mg(Cr, Al) 2 O 4 spinel phase precipitated from slag. The research of Liu et al [6][7][8] exhibit the influence of slag composition on the dissolution of chromium ore which shows that the dissolution of chromium ore increases with the decrease of slag basicity under high basicity condition (B = 0.8-1.6). Moreover, the increase in mass fraction of Al 2 O 3 and MgO results in the reduction of chromium ore dissolution.…”

Section: Influence Of Slag Chemistry On the Dissolution Of Fecr 2 O 4...mentioning

confidence: 99%

Influence of Slag Chemistry on the Dissolution of FeCr2O4 in CaO–SiO2–Al2O3–MgO Slag with Graphite Crucible

et al. 2023

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Section: Influence Of Slag Chemistry On the Dissolution Of Fecr 2 O 4...mentioning

confidence: 99%

Influence of Slag Chemistry on the Dissolution of FeCr2O4 in CaO–SiO2–Al2O3–MgO Slag with Graphite Crucible

et al. 2023

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“…By combining deep reinforcement learning and fluid simulation, an energy-saving strategy was proposed, which enabled followers to save energy by using vortices in the leader’s wake [ 17 ]. More studies can be found in [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

Target-Following Control of a Biomimetic Autonomous System Based on Predictive Reinforcement Learning

Wang,

Kang

et al. 2024

Biomimetics

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Biological fish often swim in a schooling manner, the mechanism of which comes from the fact that these schooling movements can improve the fishes’ hydrodynamic efficiency. Inspired by this phenomenon, a target-following control framework for a biomimetic autonomous system is proposed in this paper. Firstly, a following motion model is established based on the mechanism of fish schooling swimming, in which the follower robotic fish keeps a certain distance and orientation from the leader robotic fish. Second, by incorporating a predictive concept into reinforcement learning, a predictive deep deterministic policy gradient-following controller is provided with the normalized state space, action space, reward, and prediction design. It can avoid overshoot to a certain extent. A nonlinear model predictive controller is designed and can be selected for the follower robotic fish, together with the predictive reinforcement learning. Finally, extensive simulations are conducted, including the fix point and dynamic target following for single robotic fish, as well as cooperative following with the leader robotic fish. The obtained results indicate the effectiveness of the proposed methods, providing a valuable sight for the cooperative control of underwater robots to explore the ocean.

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“…In the past few decades, various bionic robotic fish with BCF mode have been developed [ 11 , 12 ]. From the perspective of bioinspired design, these robots can be roughly classified into the discrete mechanism with multiple joints and the continuous compliant mechanism [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of a Novel Bionic Tensegrity Robotic Fish with a Continuum Body

Chen,

Wang,

Xiong

et al. 2024

Biomimetics

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Biological fish exhibit remarkable adaptability and exceptional swimming performance through their powerful and flexible bodies. Therefore, designing a continuum flexible body is significantly important for the development of a robotic fish. However, it is still challenging to replicate these functions of a biological body due to the limitations of actuation and material. In this paper, based on a tensegrity structure, we propose a bionic design scheme for a continuum robotic fish body with a property of stiffness variation. Its detailed structures and actuation principles are also presented. A mathematical model was established to analyze the bending characteristics of the tensegrity structure, which demonstrates the feasibility of mimicking the fish-like oscillation propulsion. Additionally, the stiffness variation mechanism is also exhibited experimentally to validate the effectiveness of the designed tensegrity fish body. Finally, a novel bionic robotic fish design scheme is proposed, integrating an electronic module-equipped fish head, a tensegrity body, and a flexible tail with a caudal fin. Subsequently, a prototype was developed. Extensive experiments were conducted to explore how control parameters and stiffness variation influence swimming velocity and turning performance. The obtained results reveal that the oscillation amplitude, frequency, and stiffness variation of the tensegrity robotic fish play crucial roles in swimming motions. With the stiffness variation, the developed tensegrity robotic fish achieves a maximum swimming velocity of 295 mm/s (0.84 body length per second, BL/s). Moreover, the bionic tensegrity robotic fish also performs a steering motion with a minimum turning radius of 230 mm (0.68 BL) and an angular velocity of 46.6°/s. The conducted studies will shed light on the novel design of a continuum robotic fish equipped with stiffness variation mechanisms.

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Research Development on Fish Swimming

Cited by 17 publications

References 250 publications

Influence of Slag Chemistry on the Dissolution of FeCr<sub>2</sub>O<sub>4</sub> in CaO–SiO<sub>2</sub>–Al<sub>2</sub>O<sub>3</sub>–MgO Slag with Graphite Crucible

Influence of Slag Chemistry on the Dissolution of FeCr<sub>2</sub>O<sub>4</sub> in CaO–SiO<sub>2</sub>–Al<sub>2</sub>O<sub>3</sub>–MgO Slag with Graphite Crucible

Target-Following Control of a Biomimetic Autonomous System Based on Predictive Reinforcement Learning

Design and Analysis of a Novel Bionic Tensegrity Robotic Fish with a Continuum Body

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