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.

Head Motion Stabilization During Quadruped Robot Locomotion

2014 ◽  
pp. 41-65
Author(s):  
Miguel Oliveira ◽  
Cristina P. Santos ◽  
Lino Costa ◽  
Ana Maria A. C. 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 Evolution of central pattern generators for the control of a five-link bipedal walking mechanism

2012 ◽  
Vol 3 (1) ◽  
Author(s):  
Atılım Güneş Baydin
Keyword(s):  
Robot Control ◽  
Central Pattern Generators ◽  
Legged Locomotion ◽  
Bipedal Walking ◽  
Biologically Inspired ◽  
Neurophysiological Studies ◽  
Real Robot ◽  
Pattern Generators ◽  
And Performance ◽  
Walking Mechanism

AbstractCentral pattern generators (CPGs), with a basis is neurophysiological studies, are a type of neural network for the generation of rhythmic motion. While CPGs are being increasingly used in robot control, most applications are hand-tuned for a specific task and it is acknowledged in the field that generic methods and design principles for creating individual networks for a given task are lacking. This study presents an approach where the connectivity and oscillatory parameters of a CPG network are determined by an evolutionary algorithm with fitness evaluations in a realistic simulation with accurate physics. We apply this technique to a five-link planar walking mechanism to demonstrate its feasibility and performance. In addition, to see whether results from simulation can be acceptably transferred to real robot hardware, the best evolved CPG network is also tested on a real mechanism. Our results also confirm that the biologically inspired CPG model is well suited for legged locomotion, since a diverse manifestation of networks have been observed to succeed in fitness simulations during evolution.

Growth Phenomena — Algebraic and Geometric Descriptions

2001 ◽  
Vol 08 (01) ◽  
pp. 63-71
Author(s):  
Andrzej Jamiołkowski
Keyword(s):  
Vector Fields ◽  
Nonlinear Dynamical Systems ◽  
Polynomial Systems ◽  
Polynomial Vector ◽  
Finsler Spaces ◽  
Polynomial Vector Fields ◽  
Associative Algebras ◽  
Nonlinear Dynamical ◽  
Volterra Systems ◽  
The One

An enormous variety of nonlinear dynamical systems can be — by suitable introduction of new coordinates — represented in the form of polynomial systems and then can be reduced to Volterra systems, where the nonlinearities are at most quadratic. In this paper, we discuss a link between systems of differential equations with homogeneous quadratic polynomial vector fields and non-associative algebras on the one hand and the question of representation of such systems as geodesics in some Finsler spaces on the other hand.

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.

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.  

scholarly journals Adaptive and Energy-Efficient Optimal Control in CPGs Through Tegotae-Based Feedback

2021 ◽  
Vol 8 ◽  
Author(s):  
Riccardo Zamboni ◽  
Dai Owaki ◽  
Mitsuhiro Hayashibe
Keyword(s):  
Energy Efficiency ◽  
Force Feedback ◽  
Central Pattern Generators ◽  
The State ◽  
Proprioceptive Information ◽  
Robotic Control ◽  
Periodic Patterns ◽  
Biologically Inspired ◽  
Optimal Energy ◽  
Pattern Generators

To obtain biologically inspired robotic control, the architecture of central pattern generators (CPGs) has been extensively adopted to generate periodic patterns for locomotor control. This is attributed to the interesting properties of nonlinear oscillators. Although sensory feedback in CPGs is not necessary for the generation of patterns, it plays a central role in guaranteeing adaptivity to environmental conditions. Nonetheless, its inclusion significantly modifies the dynamics of the CPG architecture, which often leads to bifurcations. For instance, the force feedback can be exploited to derive information regarding the state of the system. In particular, the Tegotae approach can be adopted by coupling proprioceptive information with the state of the oscillation itself in the CPG model. This paper discusses this policy with respect to other types of feedback; it provides higher adaptivity and an optimal energy efficiency for reflex-like actuation. We believe this is the first attempt to analyse the optimal energy efficiency along with the adaptivity of the Tegotae approach.

The Effects of Symmetry Breaking Perturbation on the Dynamics of a Novel Chaotic System with Cyclic Symmetry: Theoretical Analysis and Circuit Realization

2021 ◽  
Vol 31 (14) ◽  
Author(s):  
Jacques Kengne ◽  
Sandrine Zoulewa Dountsop ◽  
Jean Chamberlain Chedjou ◽  
Khabibullo Nosirov
Keyword(s):  
Nonlinear Dynamical Systems ◽  
Period Doubling ◽  
Cyclic Symmetry ◽  
Multiple Attractors ◽  
Circuit Realization ◽  
Analog Device ◽  
Nonlinear Dynamical ◽  
The One ◽  
Parameter Ranges ◽  
New System

Symmetry is an important property shared by a large number of nonlinear dynamical systems. Although the study of nonlinear systems with a symmetry property is very well documented, the literature has no sufficient investigation on the important issues concerning the behavior of such systems when their symmetry is broken or altered. In this work, we introduce a novel autonomous 3D system with cyclic symmetry having a piecewise quadratic nonlinearity [Formula: see text] where parameter [Formula: see text] is fixed and parameter [Formula: see text] controls the symmetry and the nonlinearity of the model. Obviously, for [Formula: see text] the system presents both cyclic and inversion symmetries while the inversion symmetry is explicitly broken for [Formula: see text]. We consider in detail the dynamics of the new system for both two regimes of operation by using classical nonlinear analysis tools (e.g. bifurcation diagrams, plots of largest Lyapunov exponents, phase space trajectory plots, etc.). Several nonlinear patterns are reported such as period doubling, periodic windows, parallel bifurcation branches, hysteresis, transient chaos, and the coexistence of multiple attractors of different topologies as well. One of the most gratifying features of the new system introduced in this work is the existence of several parameter ranges for which up to twelve disconnected periodic and chaotic attractors coexist. This latter feature is rarely reported, at least for a simple system like the one discussed in this work. An electronic analog device of the new cyclic system is designed and implemented in PSpice. A very good agreement is observed between PSpice simulation and the theoretical results.

Parallel Spine Design and CPG Motion Test of Quadruped Robot

2019 ◽  
Vol 34 (05) ◽  
pp. 2059013
Author(s):  
Binrui Wang ◽  
Yixuan Liu ◽  
Zhongwen Li ◽  
Dijian Chen ◽  
Ruizi Ma ◽  
...  
Keyword(s):  
Lateral Displacement ◽  
Central Pattern Generators ◽  
Quadruped Robot ◽  
Model Based ◽  
Biological Phenomena ◽  
Parallel Kinematic Mechanism ◽  
Physical Prototype ◽  
Spine Model ◽  
Pattern Generators ◽  
The Stability

The spine of mammals aids in the stability of locomotion. Central Pattern Generators (CPGs) located in spinal cord can rapidly provide a rhythmic output signal during loss of sensory feedback on the basis of a simulated quadruped agent. In this paper, active spine of quadruped robot is shown to be extremely effective in motion. An active spine model based on the Parallel Kinematic Mechanism (PKM) system and biological phenomena is described. The general principles involved in constructing a neural network coupled with limbs and spine to solve specific problems are discussed. A CPG mathematical model based on Hopf nonlinear oscillators produces rhythmic signal during locomotion is described, where many parameters to be solved must be formulated in terms of desired stability, often subject to vertical stability analysis. Our simulations demonstrate that active spine with setting reasonable CPG parameters can reduce unnecessary lateral displacement during trot gait, improving the stability of quadruped robot. In addition, we demonstrate that physical prototype mechanism provides a framework which shows correctness of simulation, and stability can thus be easily embodied within locomotion.

Sign in / Sign up

Export Citation Format

Share Document