CPG-based Sensory Feedback Control for Bio-inspired Multimodal Swimming

Wang, Ming; Yu, Junzhi; Tan, Min

doi:10.5772/59186

Cited by 26 publications

(13 citation statements)

References 30 publications

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“…1 Among underwater robots, swimming robots have significant potential for study of marine life, monitoring oceanic environments, and underwater operations. [2][3][4][5][6][7] As a specific sea creature, jellyfish has a soft body, which is found in the waters all over the world. Owing to low metabolic rate, jellyfish has the ability to move vertically without expending much energy, while it passively depends on ocean current, tides, and wind for horizontal movements.…”

Section: Introductionmentioning

confidence: 99%

Towards a miniature self-propelled jellyfish-like swimming robot

Xiao

et al. 2016

International Journal of Advanced Robotic Systems

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Jellyfish uses jet propulsion to achieve a diversity of propulsion modes in the water. In this article, a miniature jellyfish-inspired swimming robot is designed and built, which is capable of executing horizontal and vertical propulsion and maneuvers. In order to imitate the jellyfish in terms of morphology and kinematics, the robotic jellyfish is designed to be comprised of a streamlined head, a cavity shell, four separate drive units with bevel gears, and a soft outer skin encasing the drive units. A combination of four six-bar linkage mechanisms that are centrally symmetric is adopted as the driver to regulate the phases of contraction and relaxation of the bell-shaped body. Furthermore, a triangle wave generator is incorporated to generate rhythmic drive signals, which is implemented on the microcontroller. Through independent and coordinated control of the four drive units, the robotic jellyfish is able to replicate various propulsion modes similar to real jellyfish. Aquatic tests on the actual robot verify the effectiveness of the formed design scheme along with the proposed control methods.

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Section: Introductionmentioning

confidence: 99%

Towards a miniature self-propelled jellyfish-like swimming robot

Xiao

et al. 2016

International Journal of Advanced Robotic Systems

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“…For example, a fly could produce inphase rhythms to provide the general control of head-cleaning movements but the sensory feedback from various parts of the head could adjust these movements to optimize the efficiency of cleaning of those parts. The concept of sensory feedback playing a role in stabilizing and adjusting rhythmic behaviors has been explored in robotics (Wang, 2014, Sartoretti, G., 2018 and in walking mice (Mayer W. P., 2018, Santuz, A., 2019, as well as in computational modeling of CPGs (Yu, Z., 2021).…”

Section: Discussionmentioning

confidence: 99%

Behavioral evidence for nested central pattern generator control ofDrosophilagrooming

Ravbar

Zhang

Simpson

2020

Preprint

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Central pattern generators (CPGs) are neurons or neural circuits that produce periodic output without requiring patterned input. More complex behaviors can be assembled from simpler subroutines, and nested CPGs have been proposed to coordinate their repetitive elements, simplifying control over different time-scales. Here, we use behavioral experiments to establish that Drosophila grooming may be controlled by nested CPGs. On the short time-scale (5-7 Hz), flies execute periodic leg sweeps and rubs. More surprisingly, transitions between bouts of head cleaning and leg rubbing are also periodic on a longer time-scale (0.3 - 0.6 Hz). We examine grooming at a range of temperatures to show that the frequencies of both oscillations increase – a hallmark of CPG control – and also that the two time-scales increase at the same rate, indicating that the nested CPGs may be linked. This relationship also holds when sensory drive is held constant using optogenetic activation, but the rhythms decouple in spontaneously grooming flies, showing that alternative control modes are possible. Nested CPGs simplify generation of complex but repetitive behaviors, and identifying them in Drosophila grooming presents an opportunity to map the neural circuits that constitute them.

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“…In Yu et al ( 2020 ), the frequency of the CPG oscillation is temporarily increased as a part of reflexive behavior, where the leg performs fast spiral motions. Switching the topology of coupling between CPGs changes the gait pattern, which is used in Wang et al ( 2014 ) where CPG network generates multiple gaits for a fish-like robot, such as forward and backward swimming and turning. Besides the motor signal generation, a CPG can also be used as a sensory phase estimator.…”

Section: Related Workmentioning

confidence: 99%

Self-Learning Event Mistiming Detector Based on Central Pattern Generator

2021

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A repetitive movement pattern of many animals, a gait, is controlled by the Central Pattern Generator (CPG), providing rhythmic control synchronous to the sensed environment. As a rhythmic signal generator, the CPG can control the motion phase of biomimetic legged robots without feedback. The CPG can also act in sensory synchronization, where it can be utilized as a sensory phase estimator. Direct use of the CPG as the estimator is not common, and there is little research done on its utilization in the phase estimation. Generally, the sensory estimation augments the sensory feedback information, and motion irregularities can reveal from comparing measurements with the estimation. In this work, we study the CPG in the context of phase irregularity detection, where the timing of sensory events is disturbed. We propose a novel self-supervised method for learning mistiming detection, where the neural detector is trained by dynamic Hebbian-like rules during the robot walking. The proposed detector is composed of three neural components: (i) the CPG providing phase estimation, (ii) Radial Basis Function neuron anticipating the sensory event, and (iii) Leaky Integrate-and-Fire neuron detecting the sensory mistiming. The detector is integrated with the CPG-based gait controller. The mistiming detection triggers two reflexes: the elevator reflex, which avoids an obstacle, and the search reflex, which grasps a missing foothold. The proposed controller is deployed and trained on a hexapod walking robot to demonstrate the mistiming detection in real locomotion. The trained system has been examined in the controlled laboratory experiment and real field deployment in the Bull Rock cave system, where the robot utilized mistiming detection to negotiate the unstructured and slippery subterranean environment.

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CPG-based Sensory Feedback Control for Bio-inspired Multimodal Swimming

Cited by 26 publications

References 30 publications

Towards a miniature self-propelled jellyfish-like swimming robot

Towards a miniature self-propelled jellyfish-like swimming robot

Behavioral evidence for nested central pattern generator control ofDrosophilagrooming

Self-Learning Event Mistiming Detector Based on Central Pattern Generator

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