Coupling effect analysis between the central nervous system and the CPG network with proprioception

He, Bin; Lu, Qiang; Wang, Zhipeng

doi:10.1017/s0263574714000708

Cited by 11 publications

(6 citation statements)

References 27 publications

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“…Each cell (motor neuron) is assumed to activate a single actuator in the motor system; the number of cells of the CPG is thus equal to the number of actuators for a structure with n actuators. The synaptic connections among the neurons in the CPG are elastic, and the CPG network can therefore provide a variety of output modes and control the animals to achieve different movement patterns [ 24 – 26 ].…”

Section: Cpg Controlmentioning

confidence: 99%

Motion Simulation of Ionic Liquid Gel Soft Actuators Based on CPG Control

Zhang

Ding

et al. 2019

Computational Intelligence and Neuroscience

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The ionic liquid gel (ILG), a new type of soft actuator material, is a mixture of 1-butyl-3-methylimidazolium tetrafluoroborate (BMIMBF4), hydroxyethyl methacrylate (HEMA), diethoxyacetophenone (DEAP), and ZrO2 polymerized into a gel state under ultraviolet (UV) light irradiation. The soft actuator structure consists of a layer of ionic liquid polymer gel sandwiched between two layers of activated carbon capped with gold foil. The volume of the cationic BMIM+ in the ionic liquid BMIMBF4 is much larger than that of the anionic BF4−. When voltages are applied to both sides of the actuator, the anions and cations move toward the anode and cathode of the electrode, respectively, under the electric field. The volume of the ILG cathode side therefore expands, and the volume of the ILG anode side shrinks, hence bending the entire actuator toward the anode side. The Ogden model was selected as the hyperelastic constitutive model to study the mechanical properties of the ILG by nonlinear analysis. As the ILG is an ideal material for the preparation of a supercapacitor, the equivalent circuit of the ILG can be modeled by the supercapacitor theory to identify the transfer function of the soft actuator. The central pattern generator (CPG) control is widely used in the area of biology, and CPGs based on bioinspired control methods have attracted great attention from researchers worldwide. After the continuum soft actuator is discretized, the CPG-based bioinspired method can be used to control the soft robot drivers. According to the simulation analysis results, the soft actuator can be smooth enough to reach the specified location.

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Section: Cpg Controlmentioning

confidence: 99%

Motion Simulation of Ionic Liquid Gel Soft Actuators Based on CPG Control

Zhang

Ding

et al. 2019

Computational Intelligence and Neuroscience

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“…With the CPG model, cheetah-cub realized a stable trotting both in simulation and experiment. He et al (2015) used the proprioception system to capture the actual output joint angles produced by the CPG. And then, the achieved data were transferred to the cerebellum for comparison with the parameter values from the cerebral cortex.…”

Section: Introductionmentioning

confidence: 99%

Bio-inspired control strategy study for the quadruped robot with a segmented spine

Wang

Zhang

Wei

et al. 2017

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Purpose This study aims to establish a bio-inspired controller for realizing the bounding gait of a quadruped robot system presented in this paper. Design/methodology/approach The bio-inspired controller is divided into three levels to mimic the biological patterns of animals. First, the high-level sub-controller is equivalent to the cerebellum, which could plan and control the motion of animals. Second, the effect of the middle-level sub-controller corresponds to the central nervous system. The central pattern generators in the spine generate the stable and cyclic signals as the fundamental rhythm for periodic motion of the leg and spine joints. Third, the low-level sub-controller is equal to the end effector, which adopts the simple proportional-derivative (PD) control to realize the specific motion trajectory of the legs and spine. Findings Combined with the stability criterion presented previously and the delayed feedback control method, the bounding gait of the cheetah virtual prototype could be actuated and stabilized by the bio-inspired controller. Moreover, the bio-inspired controller is applied to realize the bounding gait of an SQBot, which is a quadruped robot with a spine joint. Meanwhile, the validity and practicability of the bio-inspired controller for the control of quadruped robot have been verified against different forward velocities. Originality/value The bio-inspired controller and bionic quadruped robot system are instructive for the designing and actuating of the real quadruped robot.

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“…As known, cerebellum controls the balance and locomotion of the animals [ 1 ]. Meanwhile, the vestibular system and proprioception system also play vital roles for stabilizing the posture and movement of human [ 2 , 3 ]. The vestibular system could detect the linear and angular acceleration of body in three dimensions [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

“…The effects of the bioinspired control were verified in some robotic systems. He et al [ 2 ] employed the proprioception to capture the output joint angles produced by the central pattern generator (CPG). And then, the achieved data was transferred to the cerebellum for comparing with the parameter values from the cerebral cortex.…”

Section: Introductionmentioning

confidence: 99%

Bionic Control of Cheetah Bounding with a Segmented Spine

Wang

2016

Applied Bionics and Biomechanics

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A cheetah model is built to mimic real cheetah and its mechanical and dimensional parameters are derived from the real cheetah. In particular, two joints in spine and four joints in a leg are used to realize the motion of segmented spine and segmented legs which are the key properties of the cheetah bounding. For actuating and stabilizing the bounding gait of cheetah, we present a bioinspired controller based on the state-machine. The controller mainly mimics the function of the cerebellum to plan the locomotion and keep the body balance. The haptic sensor and proprioception system are used to detect the trigger of the phase transition. Besides, the vestibular modulation could perceive the pitching angle of the trunk. At last, the cerebellum acts as the CPU to operate the information from the biological sensors. In addition, the calculated results are transmitted to the low-level controller to actuate and stabilize the cheetah bounding. Moreover, the delay feedback control method is employed to plan the motion of the leg joints to stabilize the pitching motion of trunk with the stability criterion. Finally, the cyclic cheetah bounding with biological properties is realized. Meanwhile, the stability and dynamic properties of the cheetah bounding gait are analyzed elaborately.

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Coupling effect analysis between the central nervous system and the CPG network with proprioception

Cited by 11 publications

References 27 publications

Motion Simulation of Ionic Liquid Gel Soft Actuators Based on CPG Control

Motion Simulation of Ionic Liquid Gel Soft Actuators Based on CPG Control

Bio-inspired control strategy study for the quadruped robot with a segmented spine

Bionic Control of Cheetah Bounding with a Segmented Spine

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