993 resultados para Robots, Industrial


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This chapter will provide you with the some of the information you may need to make information on decisions in cases such as the one given above. In particular it will help you answer questions such as: 1. As Molly and Vikram are approaching the end of their shift, to attend will force them into overtime; could they refuse to attend the job on the basis of the refusal to do overtime outside of contracted hours? 2. Would their refusal be viewed as a breach of contract and therefore a disciplinary issue? 3. Why? 4. Does the need to attend this possibly gravely ill patient outweigh the demands of the paramedics to finish on time?

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The screen producer plays a vital role in shaping the creative, commercial and entrepreneurial dimensions of production. And yet Australian film history is most often presented as an appreciation of film directors or an examination of industrial governance measures. On the other hand, public funding agencies in Australia have, for the most part, supported independent film and television production as a producer-led, or producer-as-auteur production system, and as such the producer has played a critical role in shaping the broader independent production landscape. In recent years, fundamental changes to distribution and consumption practices have had a major impact on the nature of screen production. Screen producers are increasingly migrating into emerging online, transmedia and cross-media production; generating both opportunities and challenges for traditional producers. However, the production cultures and motivations of producers operating in these emergent spaces remain poorly understood. This presentation will focus on the largely unremarked role of the producer in Australian screen scholarship. It will explore the ways in which the practice of screen producing is evolving and the migratory pathways of traditional producers moving into digital/new media production. The presentation’s primary findings are drawn from the 2011 Australian Screen Producer Survey; a national study of the activities of Australian screen producers conducted by the ARC Centre of Excellence for Creative Industries and Innovation (CCI), Queensland University of Technology, with support from the Centre for Screen Business /Australian Film Television and Radio School (AFTRS). From longitudinal analysis, the presentation will compare and contrast data from the 2009 and 2011 survey across film, television, corporate production and new media industry segments. In so doing the presentation will delineate the practices, attitudes, strategies, and aspirations of screen producers operating in a convergent digital media marketplace and suggest ways forward for a more industrially cognisant approach to screen history.

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Student engagement tends to be viewed as a reflection of learning processes, and in the context of first year university studies, it is a crucial means of an educational process that establishes the foundations for successful later year studies (Krausse and Coates, 2008). In the context of first year design studio teaching in higher education, fostering students’ positive engagement poses challenges to design educators as current trends set these design studios to be large size classes that makes difficult to manage and follow up students’ individual learning experiences. At QUT’s first year industrial design studio classes we engage in a variety of teaching pedagogies from which we identify two of them as instrumental vehicles to foster positive student engagement. Concept bombs and the field trip experience provide such platform as shown in student responses through a learning experience survey.

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The Queensland government planning policies actively encourage increased dwelling density, sustainable infill development and transit oriented development to maximise land use and minimise urban sprawl. One of the detriments of such a policy is the potential for intensified residential development to create conflict between lawfully operating existing industrial uses and residences. In particular the government is concerned that intensified urban development will increase the risk of litigation from landowners and tenants detrimentally affected by the emission of aerosols, fumes, light, noise, odour, particles or smoke from existing industrial premises.

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This pilot study aimed to compare the effect of companion robots (PARO) to participation in an interactive reading group on emotions in people living with moderate to severe dementia in a residential care setting. A randomized crossover design, with PARO and reading control groups, was used. Eighteen residents with mid- to late-stage dementia from one aged care facility in Queensland, Australia, were recruited. Participants were assessed three times using the Quality of Life in Alzheimer’s Disease, Rating Anxiety in Dementia, Apathy Evaluation, Geriatric Depression, and Revised Algase Wandering Scales. PARO had a moderate to large positive influence on participants’ quality of life compared to the reading group. The PARO intervention group had higher pleasure scores when compared to the reading group. Findings suggest PARO may be useful as a treatment option for people with dementia; however, the need for a larger trial was identified.

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Reliable communications is one of the major concerns in wireless sensor networks (WSNs). Multipath routing is an effective way to improve communication reliability in WSNs. However, most of existing multipath routing protocols for sensor networks are reactive and require dynamic route discovery. If there are many sensor nodes from a source to a destination, the route discovery process will create a long end-to-end transmission delay, which causes difficulties in some time-critical applications. To overcome this difficulty, the efficient route update and maintenance processes are proposed in this paper. It aims to limit the amount of routing overhead with two-tier routing architecture and introduce the combination of piggyback and trigger update to replace the periodic update process, which is the main source of unnecessary routing overhead. Simulations are carried out to demonstrate the effectiveness of the proposed processes in improvement of total amount of routing overhead over existing popular routing protocols.

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This paper is concerned with the unsupervised learning of object representations by fusing visual and motor information. The problem is posed for a mobile robot that develops its representations as it incrementally gathers data. The scenario is problematic as the robot only has limited information at each time step with which it must generate and update its representations. Object representations are refined as multiple instances of sensory data are presented; however, it is uncertain whether two data instances are synonymous with the same object. This process can easily diverge from stability. The premise of the presented work is that a robot's motor information instigates successful generation of visual representations. An understanding of self-motion enables a prediction to be made before performing an action, resulting in a stronger belief of data association. The system is implemented as a data-driven partially observable semi-Markov decision process. Object representations are formed as the process's hidden states and are coordinated with motor commands through state transitions. Experiments show the prediction process is essential in enabling the unsupervised learning method to converge to a solution - improving precision and recall over using sensory data alone.

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Our everyday environment is full of text but this rich source of information remains largely inaccessible to mobile robots. In this paper we describe an active text spotting system that uses a small number of wide angle views to locate putative text in the environment and then foveates and zooms onto that text in order to improve the reliability of text recognition. We present extensive experimental results obtained with a pan/tilt/zoom camera and a ROS-based mobile robot operating in an indoor environment.

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Current state of the art robot mapping and navigation systems produce impressive performance under a narrow range of robot platform, sensor and environmental conditions, in contrast to animals such as rats that produce “good enough” maps that enable them to function under an incredible range of situations. In this paper we present a rat-inspired featureless sensor-fusion system that assesses the usefulness of multiple sensor modalities based on their utility and coherence for place recognition during a navigation task, without knowledge as to the type of sensor. We demonstrate the system on a Pioneer robot in indoor and outdoor environments with abrupt lighting changes. Through dynamic weighting of the sensors, the system is able to perform correct place recognition and mapping where the static sensor weighting approach fails.

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This paper proposes an efficient and online learning control system that uses the successful Model Predictive Control (MPC) method in a model based locally weighted learning framework. The new approach named Locally Weighted Learning Model Predictive Control (LWL-MPC) has been proposed as a solution to learn to control complex and nonlinear Elastic Joint Robots (EJR). Elastic Joint Robots are generally difficult to learn to control due to their elastic properties preventing standard model learning techniques from being used, such as learning computed torque control. This paper demonstrates the capability of LWL-MPC to perform online and incremental learning while controlling the joint positions of a real three Degree of Freedom (DoF) EJR. An experiment on a real EJR is presented and LWL-MPC is shown to successfully learn to control the system to follow two different figure of eight trajectories.

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Most high-power ultrasound applications are driven by two-level inverters. However, the broad spectral content of the two-level pulse results in undesired harmonics that can decrease the performance of the system significantly. On the other hand, it is crucial to excite the piezoelectric devices at their main resonant frequency in order to have maximum energy conversion. Therefore a high-quality, low-distorted power signal is needed to excite the high-power piezoelectric transducer at its resonant frequency. This study proposes an efficient approach to develop the performance of high-power ultrasonic applications using multilevel inverters along with a frequency estimation algorithm. In this method, the resonant frequencies are estimated based on relative minimums of the piezoelectric impedance frequency response. The algorithm follows the resonant frequency variation and adapts the multilevel inverter reference frequency to drive an ultrasound transducer at high power. Extensive simulation and experimental results indicate the effectiveness of the proposed approach.

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The security of industrial control systems in critical infrastructure is a concern for the Australian government and other nations. There is a need to provide local Australian training and education for both control system engineers and information technology professionals. This paper proposes a postgraduate curriculum of four courses to provide knowledge and skills to protect critical infrastructure industrial control systems. Our curriculum is unique in that it provides security awareness but also the advanced skills required for security specialists in this area. We are aware that in the Australian context there is a cultural gap between the thinking of control system engineers who are responsible for maintaining and designing critical infrastructure and information technology professionals who are responsible for protecting these systems from cyber attacks. Our curriculum aims to bridge this gap by providing theoretical and practical exercises that will raise the awareness and preparedness of both groups of professionals.

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We introduce a new image-based visual navigation algorithm that allows the Cartesian velocity of a robot to be defined with respect to a set of visually observed features corresponding to previously unseen and unmapped world points. The technique is well suited to mobile robot tasks such as moving along a road or flying over the ground. We describe the algorithm in general form and present detailed simulation results for an aerial robot scenario using a spherical camera and a wide angle perspective camera, and present experimental results for a mobile ground robot.

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A dual-scale model of the torrefaction of wood was developed and used to study industrial configurations. At the local scale, the computational code solves the coupled heat and mass transfer and the thermal degradation mechanisms of the wood components. At the global scale, the two-way coupling between the boards and the stack channels is treated as an integral component of the process. This model is used to investigate the effect of the stack configuration on the heat treatment of the boards. The simulations highlight that the exothermic reactions occurring in each single board can be accumulated along the stack. This phenomenon may result in a dramatic eterogeneity of the process and poses a serious risk of thermal runaway, which is often observed in industrial plants. The model is used to explain how thermal runaway can be lowered by increasing the airflow velocity, the sticker thickness or by gas flow reversal.