14 resultados para SELF-ORGANIZATION

em Cambridge University Engineering Department Publications Database


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Robotics researchers increasingly agree that ideas from biology and self-organization can strongly benefit the design of autonomous robots. Biological organisms have evolved to perform and survive in a world characterized by rapid changes, high uncertainty, indefinite richness, and limited availability of information. Industrial robots, in contrast, operate in highly controlled environments with no or very little uncertainty. Although many challenges remain, concepts from biologically inspired (bio-inspired) robotics will eventually enable researchers to engineer machines for the real world that possess at least some of the desirable properties of biological organisms, such as adaptivity, robustness, versatility, and agility.

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In mammals, the development of reflexes is often regarded as an innate process. However, recent findings show that fetuses are endowed with favorable conditions for ontogenetic development. In this article, we hypothesize that the circuitry of at least some mammalian reflexes can be self-organized from the sensory and motor interactions brought forth in a musculoskeletal system. We focus mainly on three reflexes: the myotatic reflex, the reciprocal inhibition reflex, and the reverse myotatic reflex. To test our hypothesis, we conducted a set of experiments on a simulated musculoskeletal system using pairs of agonist and antagonist muscles. The reflex connectivity is obtained by producing spontaneous motor activity in each muscle and by correlating the resulting sensor and motor signals. Our results show that, under biologically plausible conditions, the reflex circuitry thus obtained is consistent with that identified in relation to the analogous mammalian reflexes. In addition, they show that the reflex connectivity obtained depends on the morphology of the musculoskeletal system as well as on the environment that it is embedded in.

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Recent results in spinal research are challenging the historical view that the spinal reflexes are mostly hardwired and fixed behaviours. In previous work we have shown that three of the simplest spinal reflexes could be self-organised in an agonist-antagonist pair of muscles. The simplicity of these reflexes is given from the fact that they entail at most one interneuron mediating the connectivity between afferent inputs and efferent outputs. These reflexes are: the Myotatic, the Reciprocal Inibition and the Reverse Myotatic reflexes. In this paper we apply our framework to a simulated 2D leg model actuated by six muscles (mono- and bi-articular). Our results show that the framework is successful in learning most of the spinal reflex circuitry as well as the corresponding behaviour in the more complicated muscle arrangement. © 2012 Springer-Verlag.

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Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

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It is well-known that carbon nanotube (CNT) growth from a dense arrangement of catalyst nanoparticles creates a vertically aligned CNT forest. CNT forests offer attractive anisotropic mechanical, thermal, and electrical properties, and their anisotropic structure is enabled by the self-organization of a large number of CNTs. This process is governed by individual CNT diameter, spacing, and the CNT-to-CNT interaction. However, little information is known about the self-organization of CNTs within a forest. Insight into the self-organization is, however, essential for tailoring the properties of the CNT forests for applications such as electrical interconnects, thermal interfaces, dry adhesives and energy storage. We demonstrate that arrays of CNT micropillars having micron-scale diameters organize in a similar manner as individual CNTs within a forest. For example, as previously demonstrated for individual CNTs within a forest, entanglement of small-diameter CNT micropillars during the initial stage of growth creates a film of entwined pillars. This layer enables coordinated subsequent growth of the pillars in the vertical direction, in a case where isolated pillars would not grow in a self-supporting fashion. Finally, we provide a detailed overview of the self-organization as a function of the diameter, length and spacing of the CNT pillars. This study, which is applicable to many one-dimensional nanostructured films, demonstrates guidelines for tailoring the self-organization which can enable control of the collective mechanical, electrical and interfacial properties of the films. © 2009 Elsevier B.V. All rights reserved.

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Molecular self-organization has the potential to serve as an efficient and versatile tool for the spontaneous creation of low-dimensional nanostructures on surfaces. We demonstrate how the subtle balance between intermolecular interactions and molecule-surface interactions can be altered by modifying the environment or through manipulation by means of the tip in a scanning tunnelling microscope (STM) at room temperature. We show how this leads to the distinctive ordering and disordering of a triangular nanographene molecule, the trizigzag-hexa-peri-hexabenzocoronenes-phenyl-6 (trizigzagHBC-Ph6), on two different surfaces: graphite and Au(111). The assembly of submonolayer films on graphite reveals a sixfold packing symmetry under UHV conditions, whereas at the graphite-phenyloctane interface, they reorganize into a fourfold packing symmetry, mediated by the solvent molecules. On Au(111) under UHV conditions in the multilayer films we investigated, although disorder prevails with the molecules being randomly distributed, their packing behaviour can be altered by the scanning motion of the tip. The asymmetric diode-like current-voltage characteristics of the molecules are retained when deposited on both substrates. This paper highlights the importance of the surrounding medium and any external stimulus in influencing the molecular organization process, and offers a unique approach for controlling the assembly of molecules at a desired location on a substrate.

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The self-organization of the helical structure of chiral nematic liquid crystals combined with their sensitivity to electric fields makes them particularly interesting for low-threshold, wavelength tunable laser devices. We have studied these organic lasers in detail, ranging from the influence specific macroscopic properties, such as birefringence and order parameter, have on the output characteristics, to practical systems in the form of two-dimensional arrays, double-pass geometries and paintable lasers. Furthermore, even though chiral nematics are responsive to electric fields there is no facile means by which the helix periodicity can be adjusted, thereby allowing laser wavelength tuning, without adversely affecting the optical quality of the resonator. Therefore, in addition to studying the liquid crystal lasers, we have focused on finding a novel method with which to alter the periodicity of a chiral nematic using electric fields without inducing defects and degrading the optical quality factor of the resonator. This paper presents an overview of our research, describing (i) the correlation between laser output and material properties,(ii) the importance of the gain medium,(iii) multicolor laser arrays, and (iv) high slope efficiency (>60%) silicon back-plane devices. Overall we conclude that these materials have great potential for use in versatile organic laser systems.

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Carbon nanotube (CNT) emitters were formed on line-patterned cathodes in microtrenches through a thermal CVD process. Single-walled carbon nanotubes (SWCNTs) self-organized along the trench lines with a submicron inter-CNT spacing. Excellent field emission (FE) properties were obtained: current densities at the anode (J(a)) of 1 microA cm(-2), 10 mA cm(-2) and 100 mA cm(-2) were recorded at gate voltages (V(g)) of 16, 25 and 36 V, respectively. The required voltage difference to gain a 1:10 000 contrast of the anode current was as low as 9 V, indicating that a very low operating voltage is possible for these devices. Not only a large number of emission sites but also the optimal combination of trench structure and emitter morphology are crucial to achieve the full FE potential of thin CNTs with a practical lifetime. The FE properties of 1D arrays of CNT emitters and their optimal design are discussed. Self-organization of thin CNTs is an attractive prospect to tailor preferable emitter designs in FE devices.

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The introduction of new materials and processes to microfabrication has, in large part, enabled many important advances in microsystems, labon- a-chip devices, and their applications. In particular, capabilities for cost-effective fabrication of polymer microstructures were transformed by the advent of soft lithography and other micromolding techniques 1,2, and this led a revolution in applications of microfabrication to biomedical engineering and biology. Nevertheless, it remains challenging to fabricate microstructures with well-defined nanoscale surface textures, and to fabricate arbitrary 3D shapes at the micro-scale. Robustness of master molds and maintenance of shape integrity is especially important to achieve high fidelity replication of complex structures and preserving their nanoscale surface texture. The combination of hierarchical textures, and heterogeneous shapes, is a profound challenge to existing microfabrication methods that largely rely upon top-down etching using fixed mask templates. On the other hand, the bottom-up synthesis of nanostructures such as nanotubes and nanowires can offer new capabilities to microfabrication, in particular by taking advantage of the collective self-organization of nanostructures, and local control of their growth behavior with respect to microfabricated patterns. Our goal is to introduce vertically aligned carbon nanotubes (CNTs), which we refer to as CNT "forests", as a new microfabrication material. We present details of a suite of related methods recently developed by our group: fabrication of CNT forest microstructures by thermal CVD from lithographically patterned catalyst thin films; self-directed elastocapillary densification of CNT microstructures; and replica molding of polymer microstructures using CNT composite master molds. In particular, our work shows that self-directed capillary densification ("capillary forming"), which is performed by condensation of a solvent onto the substrate with CNT microstructures, significantly increases the packing density of CNTs. This process enables directed transformation of vertical CNT microstructures into straight, inclined, and twisted shapes, which have robust mechanical properties exceeding those of typical microfabrication polymers. This in turn enables formation of nanocomposite CNT master molds by capillary-driven infiltration of polymers. The replica structures exhibit the anisotropic nanoscale texture of the aligned CNTs, and can have walls with sub-micron thickness and aspect ratios exceeding 50:1. Integration of CNT microstructures in fabrication offers further opportunity to exploit the electrical and thermal properties of CNTs, and diverse capabilities for chemical and biochemical functionalization 3. © 2012 Journal of Visualized Experiments.

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There has been an increasing interest in applying biological principles to the design and control of robots. Unlike industrial robots that are programmed to execute a rather limited number of tasks, the new generation of bio-inspired robots is expected to display a wide range of behaviours in unpredictable environments, as well as to interact safely and smoothly with human co-workers. In this article, we put forward some of the properties that will characterize these new robots: soft materials, flexible and stretchable sensors, modular and efficient actuators, self-organization and distributed control. We introduce a number of design principles; in particular, we try to comprehend the novel design space that now includes soft materials and requires a completely different way of thinking about control. We also introduce a recent case study of developing a complex humanoid robot, discuss the lessons learned and speculate about future challenges and perspectives.

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It is still not known how the 'rudimentary' movements of fetuses and infants are transformed into the coordinated, flexible and adaptive movements of adults. In addressing this important issue, we consider a behavior that has been perennially viewed as a functionless by-product of a dreaming brain: the jerky limb movements called myoclonic twitches. Recent work has identified the neural mechanisms that produce twitching as well as those that convey sensory feedback from twitching limbs to the spinal cord and brain. In turn, these mechanistic insights have helped inspire new ideas about the functional roles that twitching might play in the self-organization of spinal and supraspinal sensorimotor circuits. Striking support for these ideas is coming from the field of developmental robotics: when twitches are mimicked in robot models of the musculoskeletal system, the basic neural circuitry undergoes self-organization. Mutually inspired biological and synthetic approaches promise not only to produce better robots, but also to solve fundamental problems concerning the developmental origins of sensorimotor maps in the spinal cord and brain.

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Legged locomotion of biological systems can be viewed as a self-organizing process of highly complex system-environment interactions. Walking behavior is, for example, generated from the interactions between many mechanical components (e.g., physical interactions between feet and ground, skeletons and muscle-tendon systems), and distributed informational processes (e.g., sensory information processing, sensory-motor control in central nervous system, and reflexes) [21]. An interesting aspect of legged locomotion study lies in the fact that there are multiple levels of self-organization processes (at the levels of mechanical dynamics, sensory-motor control, and learning). Previously, the self-organization of mechanical dynamics was nicely demonstrated by the so-called Passive Dynamic Walkers (PDWs; [18]). The PDW is a purely mechanical structure consisting of body, thigh, and shank limbs that are connected by passive joints. When placed on a shallow slope, it exhibits natural bipedal walking dynamics by converting potential to kinetic energy without any actuation. An important contribution of these case studies is that, if designed properly, mechanical dynamics can generate a relatively complex locomotion dynamics, on the one hand, and the mechanical dynamics induces self-stability against small disturbances without any explicit control of motors, on the other. The basic principle of the mechanical self-stability appears to be fairly general that there are several different physics models that exhibit similar characteristics in different kinds of behaviors (e.g., hopping, running, and swimming; [2, 4, 9, 16, 19]), and a number of robotic platforms have been developed based on them [1, 8, 13, 22]. © 2009 Springer London.

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Passive dynamics plays an important role in legged locomotion of the biological systems. The use of passive dynamics provides a number of advantages in legged locomotion such as energy efficiency, self-stabilization against disturbances, and generating gait patterns and behavioral diversity. Inspired from the theoretical and experimental studies in biomechanics, this paper presents a novel bipedal locomotion model for walking and running behavior which uses compliant legs. This model consists of three-segment legs, two servomotors, and four passive joints that are constrained by eight tension springs. The self-organization of two gait patterns (walking and running) is demonstrated in simulation and in a real-world robot. The analysis of joint kinematics and ground reaction force explains how a minimalistic control architecture can exploit the particular leg design for generating different gait patterns. Moreover, it is shown how the proposed model can be extended for controlling locomotion velocity and gait patterns with the simplest control architecture. © 2007 IEEE.