921 resultados para 090602 Control Systems Robotics and Automation
Resumo:
The continuum model is a key paradigm describing the behavior of electromechanical transients in power systems. In the past two decades, much research work has been done on applying the continuum model to analyze the electromechanical wave in power systems. In this work, the uniform and non-uniform continuum models are first briefly described, and some explanations borrowing concepts and tools from other fields are given. Then, the existing approaches of investigating the resulting wave equations are summarized. An application named the zero reflection controller based on the idea of the wave equations is next presented.
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The effect of nitrogen on the growth of vertically oriented graphene nanosheets on catalyst-free silicon and glass substrates in a plasma-assisted process is studied. Different concentrations of nitrogen were found to act as versatile control knobs that could be used to tailor the length, number density and structural properties of the nanosheets. Nanosheets with different structural characteristics exhibit markedly different optical properties. The nanosheet samples were treated with a bovine serum albumin protein solution to investigate the effects of this variation on the optical properties for biosensing through confocal micro-Raman spectroscopy and UV-Vis spectrophotometry. © 2012 Optical Society of America.
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The possibility of effective control of morphology and electrical properties of self-organized graphene structures on plasma-exposed Si surfaces is demonstrated. The structures are vertically standing nanosheets and can be grown without any catalyst and any external heating upon direct contact with high-density inductively coupled plasmas at surface temperatures not exceeding 673–723 K. Study of nucleation and growth dynamics revealed the possibility to switch-over between the two most common (turnstile- and maze-like) morphologies on the same substrates by a simple change of the plasma parameters. This change leads to the continuous or discontinuous native oxide layer that supports self-organized patterns of small carbon nanoparticles on which the structures nucleate. It is shown that by tailoring the nanoparticle arrangement one can create various three-dimensional architectures and networks of graphene nanosheet structures. We also demonstrate effective control of the degree of graphitization of the graphene nanosheet structures from the initial through the final growth stages. This makes it possible to tune the electrical resistivity properties of the produced three-dimensional patterns/networks from strongly dielectric to semiconducting. Our results contribute to enabling direct integration of graphene structures into presently dominant Si-based nanofabrication platform for next-generation nanoelectronic, sensor, biomedical, and optoelectronic components and nanodevices.
Resumo:
Plasma nanoscience is an emerging multidisciplinary research field at the cutting edge of a large number of disciplines including but not limited to physics and chemistry of plasmas and gas discharges, materials science, surface science, nanoscience and nanotechnology, solid-state physics, space physics and astrophysics, photonics, optics, plasmonics, spintronics, quantum information, physical chemistry, biomedical sciences and related engineering subjects. This paper examines the origin, progress and future perspectives of this research field driven by the global scientific and societal challenges. The future potential of plasma nanoscience to remain a highly topical area in the global research and technological agenda in the age of fundamental-level control for a sustainable future is assessed using a framework of the five Grand Challenges for Basic Energy Sciences recently mapped by the US Department of Energy. It is concluded that the ongoing research is very relevant and is expected to substantially expand to competitively contribute to the solution of all of these Grand Challenges. The approach to controlling energy and matter at nano- and subnanoscales is based on identifying the prevailing carriers and transfer mechanisms of the energy and matter at the spatial and temporal scales that are most relevant to any particular nanofabrication process. Strong accent is made on the competitive edge of the plasma-based nanotechnology in applications related to the major socio-economic issues (energy, food, water, health and environment) that are crucial for a sustainable development of humankind. Several important emerging topics, opportunities and multidisciplinary synergies for plasma nanoscience are highlighted. The main nanosafety issues are also discussed and the environment- and human health-friendly features of plasma-based nanotech are emphasized.
Resumo:
The approach to control the elementary processes of plasma–surface interactions to direct the fluxes of energy and matter at nano- and subnanometer scales is introduced. This ability is related to the solution of the grand challenge of directing energy and matter at nanoscales and is critical for the renewable energy and energy-efficient technologies for a sustainable future development. The examples of deterministic synthesis of self-organized arrays of metastable nanostructures in the size range beyond the reach of the present-day nanofabrication are considered to illustrate this possibility. By using precisely controlled and kinetically fast nanoscale transfer of energy and matter under nonequilibrium conditions and harnessing numerous plasma-specific controls of species creation, delivery to the surface,nucleation, and large-scale self-organization of nuclei and nanostructures, the arrays of metastable nanostructures can be created, arranged, stabilized, and further processed to meet the specific requirements of the envisaged applications.
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The possibility to control the morphology and nucleation density of quasi-one-dimensional, single-crystalline α -Fe2 O3 nanostructures by varying the electric potential of iron surfaces exposed to reactive oxygen plasmas is demonstrated experimentally. A systematic increase in the oxygen ion flux through rf biasing of otherwise floating substrates and then an additional increase of the ion/neutral density resulted in remarkable structural transformations of straight nanoneedles into nanowires with controlled tapering/aspect ratio and also in larger nucleation densities. Multiscale numerical simulations relate the microscopic ion flux topographies to the nanostructure nucleation and morphological evolution. This approach is applicable to other metal-oxide nanostructures.
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This paper is concerned with how a localised and energy-constrained robot can maximise its time in the field by taking paths and tours that minimise its energy expenditure. A significant component of a robot's energy is expended on mobility and is a function of terrain traversability. We estimate traversability online from data sensed by the robot as it moves, and use this to generate maps, explore and ultimately converge on minimum energy tours of the environment. We provide results of detailed simulations and parameter studies that show the efficacy of this approach for a robot moving over terrain with unknown traversability as well as a number of a priori unknown hard obstacles.
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The growing number of potential applications of Unmanned Aircraft Systems (UAS) in civilian operations and national security is putting pressure of National Airworthiness Authorities to provide a path for certification and allow UAS integration into the national airspace. The success of this integration depends not only on developments in improved UAS reliability and safety, but also on regulations for certification, and methodologies for operational performance and safety assessment. This paper focuses on the latter and describes progress in relation to a previously proposed framework for evaluating robust autonomy of UAS. The paper draws parallels between the proposed evaluation framework and the evaluation of pilots during the licensing process. It discusses how the data from the proposed evaluation can be used as an aid for decision making in certification and UAS designs. Finally, it discusses challenges associated with the evaluation.
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This paper evaluates the performance of different text recognition techniques for a mobile robot in an indoor (university campus) environment. We compared four different methods: our own approach using existing text detection methods (Minimally Stable Extremal Regions detector and Stroke Width Transform) combined with a convolutional neural network, two modes of the open source program Tesseract, and the experimental mobile app Google Goggles. The results show that a convolutional neural network combined with the Stroke Width Transform gives the best performance in correctly matched text on images with single characters whereas Google Goggles gives the best performance on images with multiple words. The dataset used for this work is released as well.
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Vision-based underwater navigation and obstacle avoidance demands robust computer vision algorithms, particularly for operation in turbid water with reduced visibility. This paper describes a novel method for the simultaneous underwater image quality assessment, visibility enhancement and disparity computation to increase stereo range resolution under dynamic, natural lighting and turbid conditions. The technique estimates the visibility properties from a sparse 3D map of the original degraded image using a physical underwater light attenuation model. Firstly, an iterated distance-adaptive image contrast enhancement enables a dense disparity computation and visibility estimation. Secondly, using a light attenuation model for ocean water, a color corrected stereo underwater image is obtained along with a visibility distance estimate. Experimental results in shallow, naturally lit, high-turbidity coastal environments show the proposed technique improves range estimation over the original images as well as image quality and color for habitat classification. Furthermore, the recursiveness and robustness of the technique allows implementation onboard an Autonomous Underwater Vehicle for improving navigation and obstacle avoidance performance.
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This paper describes the development and experimental evaluation of a novel vision-based Autonomous Surface Vehicle with the purpose of performing coordinated docking manoeuvres with a target, such as an Autonomous Underwater Vehicle, on the water’s surface. The system architecture integrates two small processor units; the first performs vehicle control and implements a virtual force obstacle avoidance and docking strategy, with the second performing vision-based target segmentation and tracking. Furthermore, the architecture utilises wireless sensor network technology allowing the vehicle to be observed by, and even integrated within an ad-hoc sensor network. The system performance is demonstrated through real-world experiments.