132 resultados para Robots, Industrial


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This paper introduces a minimalistic approach to produce a visual hybrid map of a mobile robot’s working environment. The proposed system uses omnidirectional images along with odometry information to build an initial dense posegraph map. Then a two level hybrid map is extracted from the dense graph. The hybrid map consists of global and local levels. The global level contains a sparse topological map extracted from the initial graph using a dual clustering approach. The local level contains a spherical view stored at each node of the global level. The spherical views provide both an appearance signature for the nodes, which the robot uses to localize itself in the environment, and heading information when the robot uses the map for visual navigation. In order to show the usefulness of the map, an experiment was conducted where the map was used for multiple visual navigation tasks inside an office workplace.

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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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This paper presents a full system demonstration of dynamic sensorbased reconfiguration of a networked robot team. Robots sense obstacles in their environment locally and dynamically adapt their global geometric configuration to conform to an abstract goal shape. We present a novel two-layer planning and control algorithm for team reconfiguration that is decentralised and assumes local (neighbour-to-neighbour) communication only. The approach is designed to be resource-efficient and we show experiments using a team of nine mobile robots with modest computation, communication, and sensing. The robots use acoustic beacons for localisation and can sense obstacles in their local neighbourhood using IR sensors. Our results demonstrate globally-specified reconfiguration from local information in a real robot network, and highlight limitations of standard mesh networks in implementing decentralised algorithms.

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This thesis focuses on providing reliable data transmissions in large-scale industrial wireless sensor networks through improving network layer protocols. It addresses three major problems: scalability, dynamic industrial environments and coexistence of multiple types of data traffic in a network. Theoretical developments are conducted, followed by simulation studies for verification of theoretic results. The approach proposed in this thesis has been shown to be effective for large-scale network implementation and to provide improved data transmission reliability for both periodic and sporadic traffic.

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"This work considers a mobile service robot which uses an appearance-based representation of its workplace as a map, where the current view and the map are used to estimate the current position in the environment. Due to the nature of real-world environments such as houses and offices, where the appearance keeps changing, the internal representation may become out of date after some time. To solve this problem the robot needs to be able to adapt its internal representation continually to the changes in the environment. This paper presents a method for creating an adaptive map for long-term appearance-based localization of a mobile robot using long-term and short-term memory concepts, with omni-directional vision as the external sensor."--publisher website

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Throughout a lifetime of operation, a mobile service robot needs to acquire, store and update its knowledge of a working environment. This includes the ability to identify and track objects in different places, as well as using this information for interaction with humans. This paper introduces a long-term updating mechanism, inspired by the modal model of human memory, to enable a mobile robot to maintain its knowledge of a changing environment. The memory model is integrated with a hybrid map that represents the global topology and local geometry of the environment, as well as the respective 3D location of objects. We aim to enable the robot to use this knowledge to help humans by suggesting the most likely locations of specific objects in its map. An experiment using omni-directional vision demonstrates the ability to track the movements of several objects in a dynamic environment over an extended period of time.

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This study analyzes the management of air pollutant substance in Chinese industrial sectors from 1998 to 2009. Decomposition analysis applying the logarithmic mean divisia index is used to analyze changes in emissions of air pollutants with a focus on the following five factors: coal pollution intensity (CPI), end-of-pipe treatment (EOP), the energy mix (EM), productive efficiency change (EFF), and production scale changes (PSC). Three pollutants are the main focus of this study: sulfur dioxide (SO2), dust, and soot. The novelty of this paper is focusing on the impact of the elimination policy on air pollution management in China by type of industry using the scale merit effect for pollution abatement technology change. First, the increase in SO2 emissions from Chinese industrial sectors because of the increase in the production scale is demonstrated. However, the EOP equipment that induced this change and improvements in energy efficiency has prevented an increase in SO2 emissions that is commensurate with the increase in production. Second, soot emissions were successfully reduced and controlled in all industries except the steel industry between 1998 and 2009, even though the production scale expanded for these industries. This reduction was achieved through improvements in EOP technology and in energy efficiency. Dust emissions decreased by nearly 65% between 1998 and 2009 in the Chinese industrial sectors. This successful reduction in emissions was achieved by implementing EOP technology and pollution prevention activities during the production processes, especially in the cement industry. Finally, pollution prevention in the cement industry is shown to result from production technology development rather than scale merit. © 2013 Elsevier Ltd. All rights reserved.

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This study measures productive inefficiency within the context of multi-environmental pollution (eco-efficiency) in the Chinese industrial sector. The weighted Russell directional distance model is applied to measure eco-efficiency using production technology. The objective is to clarify how external factors affect eco-efficiency. The major findings are that both foreign direct investment and investment for pollution abatement improve eco-efficiency as measured by air pollutant substances. A levy system for wastewater discharge improves eco-efficiency as measured by wastewater pollutant substances. However, an air pollutant levy does not significantly affect eco-efficiency as measured by air pollutants.

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The importance of the isoform CYP2E1 of the human cytochrome P-450 superfamily of enzymes for occupational and environmental medicine is derived from its unique substrate spectrum that includes a number of highly important high-production chemicals, such as aliphatic and aromatic hydrocarbons, solvents and industrial monomers (i.a. alkanes, alkenes, aromatic and halogenated hydrocarbons). Many polymorphic genes, such as CYP2E1, show considerable differences in allelic distribution between different human populations. The polymorphic nature of the human CYP2E1 gene is significant for inter-individual differences in toxicity of its substrates. Since the substrate spectrum of CYP2E1 includes many compounds of basic relevance to industrial toxicology, a rationale for metabolic interactions of different CYP2E1 substrates is provided. In-depth research into the inter-individual phenotypic differences of human CYP2E1 enzyme activities was enabled by the recognition that the 6-hydroxylation of the drug chlorzoxazone is mediated by CYP2E1. Studies on CYP2E1 phenotyping have pointed to inter-individual variations in enzyme activities. There are consistent ethnic differences in CYP2E1 enzyme expression, mostly demonstrated between European and Japanese populations, which point to a major impact of genetic factors. The most frequently studied genetic polymorphisms are the restriction fragment length polymorphisms PstI/RsaI (mutant allele: CYP2E1*5B) located in the 5′-flanking region of the gene, as well as the DraI polymorphism (mutant allele: CYP2E1*6) located in intron 6. These polymorphisms are partly related, as they form the common allele designated CYP2E1*5A. Striking inter-ethnic differences between Europeans and Asians appear with respect to the frequencies of the CYP2E1*5A allele (only approximately 5% of Europeans are heterozygous, but 37% of Asians are, whilst 6% of Asians are homozygous). Available studies indicate a wide variation in human CYP2E1 expression, which are very likely based on complex gene-environment interactions. Major inter-ethnic differences are apparent on the genotyping and the phenotyping levels. Selected cases are presented where inter-ethnic variations of CYP2E1 may provide likely explanations for unexplained findings concerning industrial chemicals that are CYP2E1 substrates. Possible consequences of differential inter-individual and inter-ethnic susceptibilities are related to individual expressions of clinical symptoms of chemical toxicity, to results of biological monitoring of exposed workers, and to the interpretation of results of epidemiological or molecular-epidemiological studies.

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Since the 1980s the calls for further criminalisation of organisational conduct causing harm to workers, the public and the environment have intensified in Australia, Canada and England and Wales.' One focal point of this movement has been the criminal law's response to organisations (and their personnel) failing to comply with occupational health and safety ('OHS') standards, particularly when physical harm (death and serious injury) has resulted from those breaches. Some governments have responded with proposals to enable manslaughter prosecutions to be initiated 'more effectively' against organisations causing the deaths of workers or, in some cases, members of the public (Archibald et al, 2004; Haines and Hall, 2004; Hall et al, 2004; Tombs and Whyte, 2003). In Australia governments have also increased monetary penalties for regulatory OHS offences, a few have introduced other contemporary organisational sanctions, and some have initiated OHS prosecutions more vigorously and with larger fines.

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The institutional and regulatory interlinkages between industrial relations (IR) and occupational health and safety (OHS) are seldom explored in the IR literature. This article begins to address this gap by examining regulatory initiatives in Australia during a period of neoliberal government. It examines the laws enacted by the federal government during this period and events and cases arising from these laws that go some way to illustrating their effects. Evidence is also drawn from detailed research on a number of state OHS inspectorates between 2004 and 2006. It is argued that de-collectivist changes to IR laws exacerbated problems posed by the growth of flexible work arrangements and a drop in union density, weakening participatory provisions in OHS laws and promoting work arrangements that undermined OHS standards. The study provides evidence of the implications of a divergence in the trajectory of IR and OHS laws and the importance of better integrating worker protection laws.

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Designed for undergraduate and postgraduate students, academic researchers and industrial practitioners, this book provides comprehensive case studies on numerical computing of industrial processes and step-by-step procedures for conducting industrial computing. It assumes minimal knowledge in numerical computing and computer programming, making it easy to read, understand and follow. Topics discussed include fundamentals of industrial computing, finite difference methods, the Wavelet-Collocation Method, the Wavelet-Galerkin Method, High Resolution Methods, and comparative studies of various methods. These are discussed using examples of carefully selected models from real processes of industrial significance. The step-by-step procedures in all these case studies can be easily applied to other industrial processes without a need for major changes and thus provide readers with useful frameworks for the applications of engineering computing in fundamental research problems and practical development scenarios.

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We present a framework and first set of simulations for evolving a language for communicating about space. The framework comprises two components: (1) An established mobile robot platform, RatSLAM, which has a "brain" architecture based on rodent hippocampus with the ability to integrate visual and odometric cues to create internal maps of its environment. (2) A language learning system based on a neural network architecture that has been designed and implemented with the ability to evolve generalizable languages which can be learned by naive learners. A study using visual scenes and internal maps streamed from the simulated world of the robots to evolve languages is presented. This study investigated the structure of the evolved languages showing that with these inputs, expressive languages can effectively categorize the world. Ongoing studies are extending these investigations to evolve languages that use the full power of the robots representations in populations of agents.