Toward biomorphic robotics: A review on swimming central pattern generators

Tsybina, Yu.A.; Gordleeva, Susanna; Zharinov, A.I.; Kastalskiy, Innokentiy; Ermolaeva, A.V.; Hramov, Alexander E.; Kazantsev, Victor B.

doi:10.1016/j.chaos.2022.112864

Cited by 10 publications

(3 citation statements)

References 77 publications

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“…A neuromorphic system describes the designing of an electronic circuitry that is emulate any capability of a living being, so various bio-inspired developments, which are transferred the biological mains to the engineering applications, are presented to the literature [22]- [24]. The pattern generator networks are one of the most critical application fields of the neuromorphic studies.…”

Section: Obtaining the Electrical Signals With Fpga For A Neuromorphi...mentioning

confidence: 99%

“…The dorsal fins affect the swimming speed and performance of the bioinspired underwater robots and a systematic dual dorsal fin design has been performed in [21] for swimming efficiency of a snake-like underwater robot. In these applications, it can be aimed to implement a neuromorphic emulator circuit by utilizing the rhythmic pattern generator models [22]- [24]. However, the realizations of the exponential boundary functions in these mentioned models are quite difficult directly with the digital equipment.…”

Section: Introductionmentioning

confidence: 99%

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A Digital Emulator Design for the Swimming Rhythmic Pattern Generator of a Lamprey

Korkmaz

2024

IEEE Access

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It is difficult to perform multiplication with digital devices and required to the more practical implementation methods. Thus, a well-known simpler transfer function adaptation to a swimming pattern generator is suggested for the digital implementation easiness in here. However, the direct adaptation of this function to this neural circuit is insufficient, so a control parameter is included in the laterally inhibitor neurons. Its fittest value is determined by a bifurcation diagram for getting a neural circuit that produces rhythmic patterns. Then, a four-segmented neural swimming pattern generator is constructed by using this simpler function and the anti-phase firings of neuron groups on the opposite sides is observed by the numerical simulations. Additionally, it is aimed to obtain an adjustable time delay between the neural segments, so the 'reciprocal inhibition' synaptic connections are adapted to this four-segmented structure. The effect of the reciprocal inhibition on time delays is observed by the standard deviation and numerical simulations. The final aim is to get the electrical signals with the digital device-based implementation for emulating the swimming pattern generator of a lamprey and a Field Programmable Gate Array-based realization is carried out by using the simpler transfer function. To see the achievement of this implementation, the anti-phase firings of neuron groups on the opposite sides and getting an adjustable time delay between neural segments are verified by the electrical signals. Moreover, the swimming pattern generator of a lamprey is realized with FPGA without using any multiplier blocks thanks to the simplification process.INDEX TERMS Swimming Pattern Generator, lamprey, reciprocal inhibition, time delay, Field Programmable Gate Array-FPGA

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Section: Obtaining the Electrical Signals With Fpga For A Neuromorphi...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Digital Emulator Design for the Swimming Rhythmic Pattern Generator of a Lamprey

Korkmaz

2024

IEEE Access

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“…In order to meet the growing performance demands of AUVs and to propose innovative design methods, a comprehensive review of the swimming modes of robotic fish, hydrodynamic modelling, advanced materials, and actuators is necessary. Previous studies have investigated various aspects of this field, including the hydrodynamics of flapping wings as analysed by Triantafyllou et al [ 23 ]; the control of robotic fish by Colgate et al [ 24 ]; the progress in fluid dynamics, neural-based control, and artificial muscle as summarized by Bandyopadhyay [ 25 ]; the kinematics and fluid dynamics of median and paired fins by Kato [ 26 ]; the use of smart materials, such as shape memory alloys (SMA), lead zirconate titanate (PZT), and ionic polymer metal composites (IPMCs), by Chu et al [ 27 ]; and the design and analysis of CPG (central pattern generator) model applied to swimming robots by Tsybina et al [ 28 ]. This article aims to provide a comprehensive overview of fish swimming modes and hydrodynamic modelling.…”

Section: Introductionmentioning

confidence: 99%

A Review of Robotic Fish Based on Smart Materials

Zhao

Ding

et al. 2023

Biomimetics

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The present study focuses on summarizing the recent advancements in the field of fish swimming mode research and bionic robotic fish prototypes based on smart materials. It has been widely acknowledged that fish exhibit exceptional swimming efficiency and manoeuvrability compared to conventional underwater vehicles. In the pursuit of developing autonomous underwater vehicles (AUVs), conventional experimental methods often prove to be complex and expensive. Hence, the utilization of computer simulations for hydrodynamic modelling provides a cost-effective and efficient approach for analysing the swimming behaviour of bionic robotic fish. Additionally, computer simulations can provide data that are difficult to obtain through experimental methods. Smart materials, which integrate perception, drive, and control functions, are increasingly being applied to bionic robotic fish research. However, the utilization of smart materials in this field is still an area of ongoing research and several challenges remain unresolved. This study provides an overview of the current state of research on fish swimming modes and the development of hydrodynamic modelling. The application of four distinct types of smart materials in bionic robotic fish is then reviewed, with a focus on analysing the advantages and disadvantages of each material in driving swimming behaviour. In conclusion, the paper highlights the key technical challenges that must be addressed for the practical implementation of bionic robotic fish and provides insights into the potential future directions of this field.

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