924 resultados para Factory automation
Resumo:
This paper is directed towards providing an answer to the question, ”Can you control the trajectory of a Lagrangian float?” Being a float that has minimal actuation (only buoyancy control), their horizontal trajectory is dictated through drifting with ocean currents. However, with the appropriate vertical actuation and utilising spatio-temporal variations in water speed and direction, we show here that broad controllabilty results can be met such as waypoint following to keep a float inside of a bay or out of a designated region. This paper extends theory experimen- tally evaluted on horizontally actuated Autonomous Underwater Vehicles (AUVs) for trajectory control utilising ocean forecast models and presents an initial investi- gation into the controllability of these minimally actuated drifting AUVs. Simulated results for offshore coastal and within highly dynamic tidal bays illustrate two tech- niques with the promise for an affirmative answer to the posed question above.
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Autonomous guidance of agricultural vehiclesis vital as mechanized farming production becomes more prevalent. It is crucial that tractor-trailers are guided with accuracy in both lateral and longitudinal directions, whilst being affected by large disturbance forces, or slips, owing to uncertain and undulating terrain. Successful research has been concentrated on trajectory control which can provide longitudinal and lateral accuracy if the vehicle moves without sliding, and the trailer is passive. In this paper, the problem of robust trajectory tracking along straight and circular paths of a tractor-steerable trailer is addressed. By utilizing a robust combination of backstepping and nonlinear PI control, a robust, nonlinear controller is proposed. For vehicles subjected to sliding, the proposed controller makes the lateral deviations and the orientation errors of the tractor and trailer converge to a neighborhood near the origin. Simulation results are presented to illustrate that the suggested controller ensures precise trajectory tracking in the presence of slip.
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This paper presents a method for automatic terrain classification, using a cheap monocular camera in conjunction with a robot’s stall sensor. A first step is to have the robot generate a training set of labelled images. Several techniques are then evaluated for preprocessing the images, reducing their dimensionality, and building a classifier. Finally, the classifier is implemented and used online by an indoor robot. Results are presented, demonstrating an increased level of autonomy.
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This paper presents an approach to building an observation likelihood function from a set of sparse, noisy training observations taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process framework. To validate the approach experimentally, a model of an environment is built using observations from an omni-directional camera. After a model has been built from the training data, a particle filter is used to localise while traversing this environment
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This paper presents a general, global approach to the problem of robot exploration, utilizing a topological data structure to guide an underlying Simultaneous Localization and Mapping (SLAM) process. A Gap Navigation Tree (GNT) is used to motivate global target selection and occluded regions of the environment (called “gaps”) are tracked probabilistically. The process of map construction and the motion of the vehicle alters both the shape and location of these regions. The use of online mapping is shown to reduce the difficulties in implementing the GNT.
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This paper is about planning paths from overhead imagery, the novelty of which is taking explicit account of uncertainty in terrain classification and spatial variation in terrain cost. The image is first classified using a multi-class Gaussian Process Classifier which provides probabilities of class membership at each location in the image. The probability of class membership at a particular grid location is then combined with a terrain cost evaluated at that location using a spatial Gaussian process. The resulting cost function is, in turn, passed to a planner. This allows both the uncertainty in terrain classification and spatial variations in terrain costs to be incorporated into the planned path. Because the cost of traversing a grid cell is now a probability density rather than a single scalar value, we can produce not only the most-likely shortest path between points on the map, but also sample from the cost map to produce a distribution of paths between the points. Results are shown in the form of planned paths over aerial maps, these paths are shown to vary in response to local variations in terrain cost.
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In this paper, we examine the use of a Kalman filter to aid in the mission planning process for autonomous gliders. Given a set of waypoints defining the planned mission and a prediction of the ocean currents from a regional ocean model, we present an approach to determine the best, constant, time interval at which the glider should surface to maintain a prescribed tracking error, and minimizing time on the ocean surface. We assume basic parameters for the execution of a given mission, and provide the results of the Kalman filter mission planning approach. These results are compared with previous executions of the given mission scenario.
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We present an iterative hierarchical algorithm for multi-view stereo. The algorithm attempts to utilise as much contextual information as is available to compute highly accurate and robust depth maps. There are three novel aspects to the approach: 1) firstly we incrementally improve the depth fidelity as the algorithm progresses through the image pyramid; 2) secondly we show how to incorporate visual hull information (when available) to constrain depth searches; and 3) we show how to simultaneously enforce the consistency of the depth-map by continual comparison with neighbouring depth-maps. We show that this approach produces highly accurate depth-maps and, since it is essentially a local method, is both extremely fast and simple to implement.
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In this article we identify how computational automation achieved through programming has enabled a new class of music technologies with generative music capabilities. These generative systems can have a degree of music making autonomy that impacts on our relationships with them; we suggest that this coincides with a shift in the music-equipment relationship from tool use to a partnership. This partnership relationship can occur when we use technologies that display qualities of agency. It raises questions about the kinds of skills and knowledge that are necessary to interact musically in such a partnership. These are qualities of musicianship we call eBility. In this paper we seek to define what eBility might consist of and how consideration of it might effect music education practice. The 'e' in eBility refers not only to the electronic nature of computing systems but also to the ethical, enabling, experiential and educational dimensions of the creative relationship with technologies with agency. We hope to initiate a discussion around differentiating what we term representational technologies from those with agency and begin to uncover the implications of these ideas for music educators in schools and communities. We hope also to elucidate the emergent theory and practice that has enabled the development of strategies for optimising this kind of eBility where the tool becomes partner. The identification of musical technologies with agency adds to the authors’ list of metaphors for technology use in music education that previously included tool, medium and instrument. We illustrate these ideas with examples and with data from our work with the jam2jam interactive music system. In this discussion we will outline our experiences with jam2jam as an example of a technology with agency and describe the aspects of eBility that interaction with it promotes.
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A history and introduction to civil unmanned aircraft systems in Australia. Discussion is provided on some of the current challenges facing the civil UAS sector and the research being undertaken to address these challenges.
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This presentation explores the requirements and capabilities of Unmanned Aircraft Systems (UAS) for applications in Law Enforcement and Search and Rescue.
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High Speed Rail (HSR) is rapidly gaining popularity worldwide as a safe and efficient transport option for long-distance travel. Designed to win market shares from air transport, HSR systems optimise their productivity between increasing speeds and station spacing to offer high quality service and gain ridership. Recent studies have investigated the effects that the deployment of HSR infrastructure has on spatial distribution and the economic development of cities and regions. Findings appear mostly positive at higher geographical scales, where HSR links connect major urban centres several hundred kilometres apart and already well positioned within a national or international context. Also, at the urban level, studies have shown regeneration and concentration effects around HSR station areas with positive returns on city’s image and economy. However, doubts persist on the effects of HSR at an intermediate scale, where the accessibility trade off on station spacing limits access to many small and medium agglomerations. Thereby, their ability to participate in the development opportunities facilitated by HSR infrastructure is significantly reduced. The locational advantages deriving from transport improvements appear contrasting especially in regions that tend to have a polycentric structure, where cities may present greater accessibility disparities between those served by HSR and those left behind. This thesis fits in this context where intermediate and regional cities do not directly enjoy the presence of an HSR station while having an existing or planned proximate HSR corridor. With the aim of understanding whether there might be a solution to this apparent incongruity, the research investigates strategies to integrate HSR accessibility at the regional level. While current literature recommends to commit with ancillary investments to the uplift of station areas and the renewal of feeder systems, I hypothesised the interoperability between the HSR and the conventional networks to explore the possibilities offered by mixed traffic and infrastructure sharing. Thus, I developed a methodology to quantify the exchange of benefits deriving from this synergistic interaction. In this way, it was possible to understand which level of service quality offered by alternative transit strategies best facilitates the distribution of accessibility benefits for areas far from actual HSR stations. Therefore, strategies were selected for their type of service capable of regional extensions and urban penetrations, while incorporating a combination of specific advantages (e.g. speed, sub-urbanity, capacity, frequency and automation) in order to emulate HSR quality with increasingly efficient services. The North-eastern Italian macro region was selected as case study to ground the research offering concurrently a peripheral polycentric metropolitan form, the presence of a planned HSR corridor with some portions of HSR infrastructure implementation, and the project to develop a suburban rail service extended regionally. Results show significant distributive potential, in terms of network effects produced in relation with HSR, in increasing proportions for all the strategies considered: a regional metro rail strategy (abbreviated RMR), a regional high speed rail strategy (abbreviated RHSR), a regional light rail transit (abbreviated LRT) strategy, and a non-stopping continuous railway system (abbreviated CRS) strategy. The provision of additional tools to value HSR infrastructure against its accessibility benefits and their regional distribution through alternative strategies beyond the actual HSR stations, would have great implications, both politically and technically, in moving towards new dimensions of HSR evaluation and development.
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The literature supporting the notion that active, student-centered learning is superior to passive, teacher-centered instruction is encyclopedic (Bonwell & Eison, 1991; Bruning, Schraw, & Ronning, 1999; Haile, 1997a, 1997b, 1998; Johnson, Johnson, & Smith, 1999). Previous action research demonstrated that introducing a learning activity in class improved the learning outcomes of students (Mejias, 2010). People acquire knowledge and skills through practice and reflection, not by watching and listening to others telling them how to do something. In this context, this project aims to find more insights about the level of interactivity in the curriculum a class should have and its alignment with assessment so the intended learning outcomes (ILOs) are achieved. In this project, interactivity is implemented in the form of problem- based learning (PBL). I present the argument that a more continuous formative feedback when implemented with the correct amount of PBL stimulates student engagement bringing enormous benefits to student learning. Different levels of practical work (PBL) were implemented together with two different assessment approaches in two subjects. The outcomes were measured using qualitative and quantitative data to evaluate the levels of student engagement and satisfaction in the terms of ILOs.
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In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application specific evolutionary algorithm (EA) implemented entirely on a field programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, compliments it to be an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and three-dimensional terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment and mission profiles. The architecture has been successfully synthesised for a target Xilinx Virtex-4 FPGA platform with 32% logic slices utilisation. Results obtained from case studies for a small UAV helicopter with environment derived from LIDAR (Light Detection and Ranging) data verify the effectiveness of the proposed FPGA-based path planner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.
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In the university education arena, it is becoming apparent that traditional methods of conducting classes are not the most effective ways to achieve desired learning outcomes. The traditional class/method involves the instructor verbalizing information for passive, note-taking students who are assumed to be empty receptacles waiting to be filled with knowledge. This method is limited in its effectiveness, as the flow of information is usually only in one direction. Furthermore, “It has been demonstrated that students in many cases can recite and apply formulas in numerical problems, but the actual meaning and understanding of the concept behind the formula is not acquired (Crouch & Mazur)”. It is apparent that memorization is the main technique present in this approach. A more effective method of teaching involves increasing the students’ level of activity during, and hence their involvement in the learning process. This technique stimulates self- learning and assists in keeping these students’ levels of concentration more uniform. In this work, I am therefore interested in studying the influence of a particular TLA on students’ learning-outcomes. I want to foster high-level understanding and critical thinking skills using active learning (Silberman, 1996) techniques. The TLA in question aims to promote self-study by students and to expose them to a situation where their learning-outcomes can be tested. The motivation behind this activity is based on studies which suggest that some sensory modalities are more effective than others. Using various instruments for data collection and by means of a thorough analysis I present evidence of the effectiveness of this action research project which aims to improve my own teaching practices, with the ultimate goal of enhancing student’s learning.