Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben

2008 | Buch

Overview of Motor Systems. Types of Movements: Reflexes, Rhythmical and Voluntary Movements Kapitel lesen Erstes Kapitel lesen

Dynamical Systems, Wave-Based Computation and Neuro-Inspired Robots

herausgegeben von: Paolo Arena

Verlag: Springer Vienna

Buchreihe : CISM International Centre for Mechanical Sciences

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik"

Einloggen, um Zugang zu erhalten
insite
SUCHEN

Über dieses Buch

This volume is a special Issue on "Dynamical Systems, Wave based computation and neuro inspired robots'^ based on a Course carried out at the CISM in Udine (Italy), the last week of September, 2003. From the topics treated within that Course, several new ideas were f- mulated, which led to a new kind of approach to locomotion and p- ception, grounded both on biologically inspired issues and on nonlinear dynamics. The Course was characterised by a high degree of multi disciplinarity. In fact, in order to conceive, design and build neuro inspired machines, it is necessary to deeply scan into different d- ciplines, including neuroscience. Artificial Intelligence, Biorobotics, Dynamical Systems theory and Electronics. New types of moving machines should be more closely related to the biological rules, not discarding the real implementation issues. The recipe has to include neurobiological paradigms as well as behavioral aspects from the one hand, new circuit paradigms, able of real time control of multi joint robots on the other hand. These new circuit paradigms are based on the theory of complex nonlinear dynamical systems, where aggregates of simple non linear units into ensembles of lattices, have the pr- erty that the solution set is much richer than that one shown by the single units. As a consequence, new solutions ^'emerge'\ which are often characterized by order and harmony.

Inhaltsverzeichnis

Frontmatter

Foundations of Neurodynamics and wave based computation for locomotion modeling

Frontmatter
Overview of Motor Systems. Types of Movements: Reflexes, Rhythmical and Voluntary Movements
Abstract
One of the principal characteristics of the animal kingdom is the ability to move actively in space. Our movements are controlled by a set of motor systems that allow us to maintain posture, to move our body, head, limbs and eyes, to communicate through speech. Motor control is one of the most complex functions of the nervous system. During movement, dozens and even hundreds of muscles are contracting in a coordinated fashion. This coordination is a basis for a remarkable degree of motor skill demonstrated by dancers, tennis players and even by ordinary people when walking or writing a letter.
Tatiana G. Deliagina
Initiation and generation of Movements: 1. Central Pattern Generators
Abstract
The complexity of motor control is, to a great extent, overcome by hierarchical organization of the controlling system. Lower levels of this system contain a set of central pattern generators (CPGs). the neuronal networks capable of producing the basic spatio-temporal pattern underlying different “automatic” movements (rhythmic movements like locomotion, respiration, as well as non-rhythmic ones like swallowing and defense reactions) in the absence of peripheral sensory feedback. Instead of controlling individual muscles involved in generation of a definite motor pattern, higher centers (through command system) activate the corresponding CPG that generates this pattern. The most detailed analysis of CPGs has been performed for rhythmical movements. In these experiments, sensory feedback was abolished using in vitro (see Figures 1D; 2D; 3D), immobilized (see Figure 4B-D), or deafferented preparations.
To figure out how a CPG operates one has to address the following questions: First, what is the source of rhythmicity in the network? Second, what mechanisms determine the temporal pattern of the motor output, that is, its frequency and the relative duration of the cycle phases? Third, what mechanisms shape the motor output, that is determine the number of phases in the cycle and the transition from one phase to another?
In the majority of CPGs, two parts can usually be distinguished: a rhythm generator and an output stage. The rhythm generator is the neuronal network in which the rhythm originates; it also determines a relative duration of the cycle phases. This network is usually formed by interneurons and does not include motoneurons. The output stage is formed by interneurons and motoneurons; they receive inputs from the rhythm generator but do not affect the rhythm. The output stage produces a final shaping of the motor output.
Tatiana G. Deliagina
Initiation and Generation of Movements: 2. Command Systems
Abstract
In both vertebrates and invertebrates, the CPGs for different movements can be activated by relatively simple (tonic) signals provided by command systems.
Tatiana G. Deliagina
Stabilization of Posture
Abstract
Different species, from mollusk to man, actively maintain a basic body posture (that is a particular orientation of their body in space) due to the activity of postural control system. For example, marine mollusk Clione and man maintain the vertical (headup orientation), the fish and terrestrial quadrupeds maintain the dorsal side-up body orientation. Deviations in any plane from this orientation evoke corrective movements, which lead to a restoration of the initial orientation. The stabile posture also presents a basis on which voluntary movements of different parts of the body can be superimposed. Maintenance of body posture is a non-volitional activity that is based, in many species, on innate neural mechanisms. Postural systems differ from those for movement control in their behavioral goals. The systems for movement control cause a movement of the whole body or its segments from one position in space to the other, as in walking or reaching. The systems for postural control prevent movements. they stabilize a position (or orientation) of the body in space, or orientation of its segments in space and in relation to each other.
Two principal modes of postural activity can be distinguished: (1) The feedback mode is compensation for the deviation from the desired posture (see Figure 1A). (2) The feedforward mode is anticipatory postural adjustments aimed at counteracting the destabilizing consequences of voluntary movements (see Figure 1B). In this lecture I will focus on the feedback mode of postural activity.
Tatiana G. Deliagina
Locomotion as a Spatial-temporal Phenomenon: Models of the Central Pattern Generator
Abstract
The development of new approaches and new architectures for locomotion control in legged robots is of high interest in the area of robotic and intelligent motion systems, especially when the solution is easy both to conceive and to implement.
This first lecture emphasizes analog neural processing structures to realize artificial locomotion in mechatronic devices. The main inspiration comes from the biological paradigm of the Central Pattern Generator (CPG), used to model the neural populations responsible for locomotion planning and control in animals. The approach presented here starts by considering locomotion by legs as a complex spatio-temporal non linear dynamical system, modelled referring to particular types of reaction-diffusion non linear partial differential equations. In the following lecture these Spatio-temporal phenomena are obtained implementing the whole mathematical model on a new Reaction-Diffusion Cellular Neural Network (RD-CNN) architecture. Wave-like solutions as well as patterns are obtained, able to induce and control locomotion in some prototypes of biologically inspired walking machines. The design of the CNN structure is subsequently realized by analog circuits; this gives the possibility to generate locomotion in real time and also to control the transition among several types of locomotion. The methodology presented is applied referring to the experimental prototype of an hexapod robot. In the last lecture the same approach will be shown to be able to realize locomotion generation and control in a number of different robotic structures, such as ring worm-like robots or lamprey-like robots.
Paolo Arena
Design of CPGs via spatial distributed non linear dynamical systems
Abstract
The classical CNN architecture, in the particular case where each cell is defined as a nonlinear first order circuit is shown in Figure 1, in which u ij , y ij and x ij are the input, the output and the state variable of the cell C ij respectively; the cell non linearity lies in the relation between the state and the output variables by the Piece Wise Linear (PWL) equation (see Figure 1(c)):
$$ y_{ij} = f(x_{ij} ) = 0.5 \cdot (|x_{ij} + 1| - |x_{ij} - 1|) $$
Paolo Arena
Realization of bio-inspired locomotion machines via nonlinear dynamical circuits
Abstract
In the previous lecture some design guidelines for CPGs by means of CNNs were given, giving particular attention to the realization of the gaits in a hexapod structure. In this lecture it will be shonw that the same spatial-temporal dynamics can be also used to obtain patterns for other kinds of bio-inspired moving machines. For the sake of clarity, in the following section the basic cell dynamical model, formally identical to that one used in the previous lecture, is briefly recalled.
Paolo Arena
Using robots to model biological behaviour
Abstract
Robots can be used to instantiate and test hypotheses about biological systems. This approach to modelling can be described by a number of dimensions: relevance to biology; the level of representation; generality of the mechanisms; the amount of abstraction; the accuracy of the model; how well it matches the behaviour; and what medium is used to construct the model. This helps to clarify the potential advantages of this methodology for understanding how behaviour emerges from interactions between the animal, its task and the environment.
Barbara Webb

From sensing toward perception

Frontmatter
Spiking neuron controllers for a sound localising robot
Abstract
Female crickets can find a mate by recognising and walking or flying towards the male calling song. Using a robot to model this behaviour, we explore of the functionality of identified neurons in the insect, including the roles of multiple sensory fibres, mutually inhibitory connections, and brain neurons with pattern-filtering properties.
Barbara Webb
Combining several sensorimotor systems: from insects to robot implementations
Abstract
Animals and robots need to integrate different sensorimotor systems to behave successfully. We added an optomotor system to our sound-localising robot, and investigated algorithms for combining the two behaviours. It has been claimed that crickets simply ‘add’ the outputs of the two responses. We show that several other explanations equally account for the cricket data, and that inhibitory interactions between the behaviours are successful for robot control.
Barbara Webb
Sensory Feedback in locomotion control
Abstract
This chapter focuses on the sensing processes and their interactions with locomotion control. The analysis has been accomplished taking into account different levels of behavior. Moreover dynamic simulators and robotic structures have been used to investigate the biological principles governing the sensory feedback in the real world.
Paolo Arena, Luigi Fortuna, Mattia Frasca, Luca Patané
A looming detector for collision avoidance
Abstract
The visual system is one of the most complex sensory architecture used by animals. The incredible technological progresses in the electronic field, nowadays, have not been able to produce devices with performances comparable to the insect visual system in terms of resolution, speed acquisition and processing. In this chapter an algorithm for the collision detection, inspired to the locust visual system will be presented.
Paolo Arena, Luca Patané
Hearing: recognition and localization of sound
Abstract
In this chapter the problem of recognition and localization of a sound source is discussed. The starting point is the solution adopted by the cricket able to identify an auditory stimulus and to reach the sound source. The auditory process has been modelled with a network of neurons with the aim to realize a bio-inspired auditory system for robotic applications.
Paolo Arena, Luigi Fortuna, Mattia Frasca, Luca Patané
Perception and robot behavior
Abstract
The phenomenon of perception is a complex process including several distinct elements that will be described in this chapter. The principles of locomotion and sensing are here re-elaborated from the agent point of view. The sensory information is processed to perceive the environment in order to generate an action useful to accomplish a particular task. Some psychological principles are discussed and the paradigm of action-oriented perception is taken into account for the realization of a perceiving robot.
Paolo Arena, Davide Lombardo, Luca Patané

Practical Issues

Frontmatter
Practical Issues of “Dynamical Systems, Wave based Computation and Neuro-Inspired Robots” — Introduction
Abstract
This Chapter introduces the topics covered during the practice hours of the course “Dynamical Systems, Wave based Computation and Neuro-Inspired Robots”. These practice hours were divided into two parts. Firstly, the course participants were asked to learn the basics on CNNs by using a CNN simulator. Then, they were divided in several groups and a project was assigned to each group. In this Chapter the project objectives are introduced, while in the following Chapters the projects are detailed in the contributions given by the course participants.
Adriano Basile, Mattia Frasca
Locomotion control of a hexapod by Turing patterns
Abstract
In this paper, the reflexive behavior of a biomorphic adaptive robot is analyzed. The motion generation of the robot is governed by a Reaction-Diffusion Cellular Neural Network (RD-CNN) that evolves towards a Turing pattern representing the action pattern of the robot. The initial conditions of this RD-CNN are given by the sensor input. The proposed approach is particularly valuable when the number of sensors is high, being able to perform data compression in real-time through analog parallel processing. An experiment using a small 6-legged robot realized in Lego MindStorms™ with three sensors is presented to validate the approach. A simulated 3×3 CNN is used to control this hexapod.
Marco Pavone, Michael Stich, Bernhard Streibl
Visual Control of a Roving Robot based on Turing Patterns
Abstract
Turing Patterns (TP) could be useful in robot control. In particular, using a webcam on board the robot, a snapshot of the environment could be set as initial condition of a CNN that will generate TP. Analysing the TP aroused is possible to control the robot avoiding obstacles.
Paola Brunetto, Arturo Buscarino, Alberta Latteri
Wave-based control of a bio-inspired hexapod robot
Abstract
The main idea of this work is to merge locomotion based on neural approach of Rexabot robot and real-time wave-based navigation in a complex, dynamically changing environment.
Fabio Danieli, Donato Melita
Cricket phonotaxis: simple Lego implementation
Abstract
Female crickets are able to recognise and localise their mates, using a simple neural structure that implements phonotaxis. In this paper we show simple Lego implementation of this biological model.
Paolo Crucitti, Gaetana Ganci
CNN-based control of a robot inspired to snakeboard locomotion
Abstract
This paper wants to emphasize the role of analog neural processing structures to realize artificial locomotion in mechatronic devices. The approach presented starts by considering locomotion as a complex spatio-temporal phenomena, modelled referring to particular types of reaction-diffusion nonlinear partial differential equations implemented on a Reaction-Diffusion Cellular Neural Network architecture (RD-CNN). Several examples in literature show the usefulness of this methodology applied to generate and control the locomotion in real-time in a number of different robotic structures as multi-legged or worm-like robots. In this paper we apply this technique, using wave-like solutions, obtained by a ring of RD-CNN cells, to generate and control locomotion in a mechanic wheeled structure that exploits the inertia of two masses.
Peppe Aprile, Matthieu Porez, Marcus Wrabel
Cooperative behavior of robots controlled by CNN autowaves
Abstract
In this paper we will discuss in some details how the wave-based approach can be applied to roving robots. Two slightly different implementations are shown and experimental results obtained are discussed. The wave-controlled robots have only local information coming from the on-board cameras, but a simple cooperation strategy shown in the following allows to overcome the limits of local information.
Paolo Crucitti, Giuseppe Dimartino, Marco Pavone, Calogero D. Presti
Metadaten
Titel
Dynamical Systems, Wave-Based Computation and Neuro-Inspired Robots
herausgegeben von
Paolo Arena
Copyright-Jahr
2008
Verlag
Springer Vienna
Electronic ISBN
978-3-211-78775-5
Print ISBN
978-3-211-78774-8
DOI
https://doi.org/10.1007/978-3-211-78775-5

Neuer Inhalt

    Bildnachweise