scholarly journals Optimizing central pattern generators (CPG) controller for one legged hopping robot by using genetic algorithm (GA)

2018 ◽  
Vol 7 (2.14) ◽  
pp. 160 ◽  
Author(s):  
Arman Hadi Azahar ◽  
Chong Shin Horng ◽  
Anuar Mohamed Kassim ◽  
Amar Faiz Zainal Abidin ◽  
Mohamad Haniff Harun ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Stochastic Optimization ◽  
Central Pattern Generators ◽  
Optimization Method ◽  
Pattern Generator ◽  
Pi Controller ◽  
Optimum Parameters ◽  
Hopping Robot ◽  
Pattern Generators ◽  
The One

This paper presents the optimization process of Central Pattern Generator (CPG) controller for one legged hopping robot by using Genetic Algorithm (GA). To control the one legged hopping robot, a CPG controller is designed and integrated with a conventional Proportional-Integral (PI) controller. Conventionally, the CPG parameters are tuned manually. But by using this method, the parameters produced are not exactly the optimum parameters for the CPG. Therefore, a computational stochastic optimization method; GA is designed to optimize the CPG controller parameters. The GA is designed based on minimizing the error produced towards achieving the reference height. The re-sponse of the one legged hopping robot is compared and the results of the error towards reference height are analyzed.  

Behavior-Dependent Activities of a Central Pattern Generator in Freely Behaving Lymnaea stagnalis

1997 ◽  
Vol 78 (6) ◽  
pp. 3415-3427 ◽  
Author(s):  
Rene F. Jansen ◽  
Anton W. Pieneman ◽  
Andries ter Maat
Keyword(s):  
Electrical Activity ◽  
Central Pattern Generator ◽  
Lymnaea Stagnalis ◽  
Central Pattern Generators ◽  
Pattern Generator ◽  
Egg Laying ◽  
Buccal Ganglion ◽  
Level Of Activity ◽  
Freely Behaving ◽  
Pattern Generators

Jansen, Rene F., Anton W. Pieneman, and Andries ter Maat. Behavior-dependent activities of a central pattern generator in freely behaving Lymnaea stagnalis. J. Neurophysiol. 78: 3415–3427, 1997. Cyclic or repeated movements are thought to be driven by networks of neurons (central pattern generators) that are dynamic in their connectivity. During two unrelated behaviors (feeding and egg laying), we investigated the behavioral output of the buccal pattern generator as well as the electrical activity of a pair of identified interneurons that have been shown to be involved in setting the level of activity of this pattern generator (PG). Analysis of the quantile plots of the parameters that describe the behavior (movements of the buccal mass) reveals that during egg laying, the behavioral output of the PG is different compared with that during feeding. Comparison of the average durations of the different parts of the buccal movements showed that during egg laying, the duration of one specific part of buccal movement is increased. Correlated with these changes in the behavioral output of the PG were changes in the firing rate of the cerebral giant neurons (CGC), a pair of interneurons that have been shown to modulate the activity of the PG by means of multiple synaptic contacts with neurons in the buccal ganglion. Interval- and autocorrelation histograms of the behavioral output and CGC spiking show that both the PG output and the spiking properties of the CGCs are different when comparing egg-laying animals with feeding animals. Analysis of the timing relations between the CGCs and the behavioral output of the PG showed that both during feeding and egg laying, the electrical activity of the CGCs is largely in phase with the PG output, although small changes occur. We discuss how these results lead to specific predictions about the kinds of changes that are likely to occur when the animal switches the PG from feeding to egg laying and how the hormones that cause egg laying are likely to be involved.

Intrinsic and Extrinsic Modulation of a Single Central Pattern Generating Circuit

2000 ◽  
Vol 84 (3) ◽  
pp. 1186-1193 ◽  
Author(s):  
Peter T. Morgan ◽  
Ray Perrins ◽  
Philip E. Lloyd ◽  
Klaudiusz R. Weiss
Keyword(s):  
Neural Circuits ◽  
Central Pattern Generators ◽  
Motor Program ◽  
Pattern Generator ◽  
Motor Programs ◽  
Appetitive Behavior ◽  
Protraction Phase ◽  
Pattern Generators ◽  
Rhythmic Behaviors ◽  
Appetitive Behaviors

Intrinsic and extrinsic neuromodulation are both thought to be responsible for the flexibility of the neural circuits (central pattern generators) that control rhythmic behaviors. Because the two forms of modulation have been studied in different circuits, it has been difficult to compare them directly. We find that the central pattern generator for biting in Aplysia is modulated both extrinsically and intrinsically. Both forms of modulation increase the frequency of motor programs and shorten the duration of the protraction phase. Extrinsic modulation is mediated by the serotonergic metacerebral cell (MCC) neurons and is mimicked by application of serotonin. Intrinsic modulation is mediated by the cerebral peptide-2 (CP-2) containing CBI-2 interneurons and is mimicked by application of CP-2. Since the effects of CBI-2 and CP-2 occlude each other, the modulatory actions of CBI-2 may be mediated by CP-2 release. Although the effects of intrinsic and extrinsic modulation are similar, the neurons that mediate them are active predominantly at different times, suggesting a specialized role for each system. Metacerebral cell (MCC) activity predominates in the preparatory (appetitive) phase and thus precedes the activation of CBI-2 and biting motor programs. Once the CBI-2s are activated and the biting motor program is initiated, MCC activity declines precipitously. Hence extrinsic modulation prefacilitates biting, whereas intrinsic modulation occurs during biting. Since biting inhibits appetitive behavior, intrinsic modulation cannot be used to prefacilitate biting in the appetitive phase. Thus the sequential use of extrinsic and intrinsic modulation may provide a means for premodulation of biting without the concomitant disruption of appetitive behaviors.

Head Motion Stabilization During Quadruped Robot Locomotion

2011 ◽  
Vol 2 (1) ◽  
pp. 39-62 ◽  
Author(s):  
Miguel Oliveira ◽  
Cristina P. Santos ◽  
Lino Costa ◽  
Ana Rocha ◽  
Manuel Ferreira
Keyword(s):  
Global Optimization ◽  
Head Movement ◽  
Nonlinear Dynamical Systems ◽  
Fitness Function ◽  
Central Pattern Generators ◽  
Quadruped Robot ◽  
Biologically Inspired ◽  
Nonlinear Dynamical ◽  
Pattern Generators ◽  
The One

In this work, the authors propose a combined approach based on a controller architecture that is able to generate locomotion for a quadruped robot and a global optimization algorithm to generate head movement stabilization. The movement controllers are biologically inspired in the concept of Central Pattern Generators (CPGs) that are modelled based on nonlinear dynamical systems, coupled Hopf oscillators. This approach allows for explicitly specified parameters such as amplitude, offset and frequency of movement and to smoothly modulate the generated oscillations according to changes in these parameters. The overall idea is to generate head movement opposed to the one induced by locomotion, such that the head remains stabilized. Thus, in order to achieve this desired head movement, it is necessary to appropriately tune the CPG parameters. Three different global optimization algorithms search for this best set of parameters. In order to evaluate the resulting head movement, a fitness function based on the Euclidean norm is investigated. Moreover, a constraint-handling technique based on tournament selection was implemented.

scholarly journals Three-dimensional walking of a simulated muscle-driven quadruped robot with neuromorphic two-level central pattern generators

2019 ◽  
Vol 16 (6) ◽  
pp. 172988141988528
Author(s):  
Yasushi Habu ◽  
Keiichiro Uta ◽  
Yasuhiro Fukuoka
Keyword(s):  
Three Dimensional ◽  
Central Pattern Generators ◽  
Pattern Generator ◽  
Quadruped Robot ◽  
Neural Systems ◽  
Rhythm Generation ◽  
Pattern Generators ◽  
Cat Model ◽  
Muscle Models ◽  
Leg Mechanisms

We aim to design a neuromorphic controller for the locomotion of a quadruped robot with muscle-driven leg mechanisms. To this end, we use a simulated cat model; each leg of the model is equipped with three joints driven by six muscle models incorporating two-joint muscles. For each leg, we use a two-level central pattern generator consisting of a rhythm generation part to produce basic rhythms and a pattern formation part to synergistically activate a different set of muscles in each of the four sequential phases (swing, touchdown, stance, and liftoff). Conventionally, it was difficult for a quadruped model with such realistic neural systems and muscle-driven leg mechanisms to walk even on flat terrain, but because of our improved neural and mechanical components, our quadruped model succeeds in reproducing motoneuron activations and leg trajectories similar to those in cats and achieves stable three-dimensional locomotion at a variety of speeds. Moreover, the quadruped is capable of walking upslope and over irregular terrains and adapting to perturbations, even without adjusting the parameters.

En route to disentangle the impact and neurobiological substrates of early vocalizations: Learning from Rett syndrome

2014 ◽  
Vol 37 (6) ◽  
pp. 562-563 ◽  
Author(s):  
Peter B. Marschik ◽  
Walter E. Kaufmann ◽  
Sven Bölte ◽  
Jeff Sigafoos ◽  
Christa Einspieler
Keyword(s):  
Rett Syndrome ◽  
Acoustic Communication ◽  
Neurodevelopmental Disorders ◽  
Central Pattern Generators ◽  
Pattern Generator ◽  
Neurological Development ◽  
Neurobiological Substrates ◽  
Pattern Generators ◽  
The Impact

AbstractResearch on acoustic communication and its underlying neurobiological substrates has led to new insights about the functioning of central pattern generators (CPGs). CPG-related atypicalities may point to brainstem irregularities rather than cortical malfunctions for early vocalizations/babbling. The “vocal pattern generator,” together with other CPGs, seems to have great potential in disentangling neurodevelopmental disorders and potentially predict neurological development.

scholarly journals An autonomous tail-beating cycle period expressed by a region-specific swimming pattern generator in the Ciona larva

2021 ◽  
Author(s):  
Takashi Hara ◽  
Shuya Hasegawa ◽  
Yasushi Iwatani ◽  
Atsuo S. Nishino
Keyword(s):  
Central Pattern Generators ◽  
Sister Group ◽  
Pattern Generator ◽  
The Body ◽  
Periodic Pattern ◽  
Cycle Period ◽  
Swimming Pattern ◽  
Aquatic Vertebrates ◽  
Pattern Generators ◽  
Region 10

Swimming locomotion in aquatic vertebrates, such as fish and tadpoles, is expressed through orchestrated operations of central pattern generators. These parallel neuronal circuits are ubiquitously distributed and mutually coupled along the spinal cord to express undulation patterns accommodated to efferent and afferent inputs. While such sets of schemes have been shown in vertebrates, the evolutionary origin of those mechanisms along the chordate phylogeny remains unclear. Ascidians, representing a sister group of vertebrates, give rise to tadpole larvae that freely swim in seawater. In this study, we tried to locate the swimming pattern generator in larvae of the ascidian Ciona by examining locomotor ability of segmented body fragments. Our experiments demonstrated necessary and sufficient pattern generator activity in a short region (~10% of the body length as the longest estimation) including the trunk-tail junction but excluding most of the trunk and tail with major sensory apparatuses therein. Moreover, we found that these "mid-piece" body fragments express periodic tail beating bursts with ~20-s intervals without any exogenous stimuli. Comparisons among temporal patterns of tail beating bursts expressed by the mid-piece fragments and by whole larvae placed under different sensory conditions suggested that the presence of parts other than the critical mid-piece had effects to shorten swimming burst intervals, especially in the dark, and also to expand the variance in burst durations. We propose that Ciona larvae perform swimming as modified representations of autonomous and periodic pattern generator drives, which operate locally in the region of the trunk-tail junction.

scholarly journals Performance Comparisons of Bio-Micro Genetic Algorithms on Robot Locomotion

2020 ◽  
Vol 10 (11) ◽  
pp. 3863
Author(s):  
Francisco A. Chávez-Estrada ◽  
Jacobo Sandoval-Gutiérrez ◽  
Juan C. Herrera-Lozada ◽  
Mauricio Olguín-Carbajal ◽  
Daniel L. Martínez-Vázquez ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Embedded System ◽  
Computing Time ◽  
Central Pattern Generators ◽  
Quadruped Robot ◽  
Robot Locomotion ◽  
Real Performance ◽  
Pattern Generators ◽  
The Individual ◽  
Computational Resources

This paper presents a comparison of four algorithms and identifies the better one in terms of convergence to the best performance for the locomotion of a quadruped robot designed. Three algorithms found in the literature review: a standard Genetic Algorithm (GA), a micro-Genetic Algorithm ( μ GA), and a micro-Artificial Immune System ( μ AIS); the fourth algorithm is a novel micro-segmented Genetic Algorithm ( μ sGA). This research shows how the computing time affects the performance in different algorithms of the gait on the robot physically; this contribution complements other studies that are limited to simulation. The μ sGA algorithm uses less computing time since the individual is segmented into specific bytes. In contrast, the use of a computer and the high demand in computational resources for the GA are avoided. The results show that the performance of μ sGA is better than the other three algorithms (GA, μ GA and μ AIS). The quadruped robot prototype guarantees the same conditions for each test. The structure of the platform was developed by 3D printing. This structure was used to accommodate the mechanisms, sensors and servomechanisms as actuators. It also has an internal battery and a multicore Embedded System (mES) to process and control the robot locomotion. The computing time was reduced using an mES architecture that enables parallel processing, meaning that the requirements for resources and memory were reduced. For example, in the experiment of a one-second gait cycle, GA uses 700% of computing time, μ GA (76%), μ AIS (32%) and μ sGA (13%). This research solves the problem of quadruped robot’s locomotion and gives a feasible solution (Central Pattern Generators, (CPGs)) with real performance parameters using a μ sGA bio-micro algorithm and a mES architecture.

NONLINEAR DYNAMICS OF AN OSCILLATORY NEURAL NETWORK ACTING AS A MOTOR CENTRAL PATTERN GENERATOR

2013 ◽  
Vol 23 (08) ◽  
pp. 1350142 ◽  
Author(s):  
J. HURTADO-LÓPEZ ◽  
D. F. RAMÍREZ-MORENO
Keyword(s):  
Neural Network ◽  
Nonlinear Dynamics ◽  
Central Pattern Generator ◽  
Bifurcation Analysis ◽  
Central Pattern Generators ◽  
Pattern Generator ◽  
Reduced Model ◽  
Quadruped Locomotion ◽  
Oscillatory Neural Network ◽  
Pattern Generators

In this work, we present a bifurcation analysis of a network of symmetrically coupled units modeling central pattern generators for quadruped locomotion. Here, we show a reduced model and characterize its dynamics and the dependence of the model behavior when one of the parameters is varied.

Walking quality guaranteed central pattern generator control method

2013 ◽  
Vol 228 (3) ◽  
pp. 569-579
Author(s):  
Jiaqi Zhang ◽  
Xiaolei Han ◽  
Xueying Han
Keyword(s):  
Central Pattern Generator ◽  
Control Method ◽  
Central Pattern Generators ◽  
Pattern Generator ◽  
Walking Robots ◽  
High Quality ◽  
Traditional Methods ◽  
Walking Gait ◽  
Pattern Generators ◽  
Periodic Inputs

Creating effective locomotion for a legged robot is a challenging task. Central pattern generators have been widely used to control robot locomotion. However, one significant disadvantage of the central pattern generator method is its inability to design high-quality walks because it only produces sine or quasi-sine signals for motor control as compared to most cases in which the expected control signals are more advanced. Control accuracy is therefore diminished when traditional methods are replaced by central pattern generators resulting in unaesthetically pleasing walking robots. In this paper, we present a set of solutions, based on testings of Sony’s four-legged robotic dog (AIBO), which produces the same walking quality as traditional methods. First, we designed a method based on both evolution and learning to optimize the walking gait. Second, a central pattern generator model was put forth to enabled AIBO to learn from arbitrary periodic inputs, which resulted in the replication of the optimized gait to ensure high-quality walking. Lastly, an accelerator sensor feedback was introduced so that AIBO could detect uphill and downhill terrains and change its gait according to the surrounding environment. Simulations were performed to verify this method.

Control of Central Pattern Generators by an Identified Neurone in Crustacea: Activation of the Gastric Mill Motor Pattern by a Neurone Known to Modulate the Pyloric Network

1988 ◽  
Vol 136 (1) ◽  
pp. 53-87
Author(s):  
PATSY S. DICKINSON ◽  
FRÉDÉRIC NAGY ◽  
MAURICE MOULINS
Keyword(s):  
Central Pattern Generator ◽  
Motor Pattern ◽  
Central Pattern Generators ◽  
Rhythmic Activity ◽  
Pattern Generator ◽  
Gastric Mill ◽  
Pyloric Network ◽  
Single Burst ◽  
Pattern Generators ◽  
Synaptic Drive

In the red lobster (Palinurus vulgaris), an identified neurone, the anterior pyloric modulator neurone (APM), which has previously been shown to modulate the output of the pyloric central pattern generator, was shown to modulate the output of the gastric mill central pattern generator. APM activity induced a rhythm when the network was silent and increased rhythmic activity when the network was already active. Rhythmic activity was induced whether APM fired in single bursts, tonically or in repetitive bursts. A single burst in APM induced a rhythm which considerably outlasted the burst, whereas repetitive bursts effectively entrained the gastric oscillator. These modulations involved two major mechanisms. (1) APM induced or enhanced plateau properties in some of the gastric mill neurones. (2) APM activated the extrinsic inputs to the network, thus increasing the excitatory synaptic drive to most of the neurones of the network. As a result, when APM was active, all the neurones of the pattern generator actively participated in the rhythmic activity. By its actions on two separate but behaviourally related neural networks, the APM neurone may be able to control an entire concert of related types of behaviour.

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