Càlcul, disseny i fabricació d'una carrosseria autoportant en material compòsit per al vehicle de baix consum Àliga

El projecte és l’inici de la creació d’un nou prototip per a poder competir la temporada 2008 a la cursa de vehicles de baix consum Shell Eco-Marathon. El principal objectiu és aconseguir un xassís que redueixi, en la mesura del possible, el pes del prototip a la vegada que asseguri una millor rigidesa i millori l’ergonomia de tot el conjunt. Es dissenyarà tota la part estructural de la carrosseria, que serà sotmesa a càlcul mitjançant la tècnica dels elements finits i posteriorment es realitzarà una guia de producció per tal de guiar els membres de l’equip que en realitzin la producció

A mission control system for an autonomous underwater vehicle

The presented work focuses on the theoretical and practical aspects concerning the design and development of a formal method to build a mission control system for autonomous underwater vehicles bringing systematic design principles for the formal description of missions using Petri nets. The proposed methodology compounds Petri net building blocks within it to de_ne a mission plan for which it is proved that formal properties, such as reachability and reusability, hold as long as these same properties are also guaranteed by each Petri net building block. To simplify the de_nition of these Petri net blocks as well as their composition, a high level language called Mission Control Language has been developed. Moreover, a methodology to ensure coordination constraints for teams of multiple robots as well as the de_nition of an interface between the proposed system and an on-board planner able to plan/replan sequences of prede_ned mission plans is included as well. Results of experiments with several real underwater vehicles and simulations involving an autonomous surface craft and an autonomous underwater vehicles are presented to show the system's capabilities.

A proposal to estimate the motion of an underwater vehicle through visual mosaicking

This thesis proposes a solution to the problem of estimating the motion of an Unmanned Underwater Vehicle (UUV). Our approach is based on the integration of the incremental measurements which are provided by a vision system. When the vehicle is close to the underwater terrain, it constructs a visual map (so called "mosaic") of the area where the mission takes place while, at the same time, it localizes itself on this map, following the Concurrent Mapping and Localization strategy. The proposed methodology to achieve this goal is based on a feature-based mosaicking algorithm. A down-looking camera is attached to the underwater vehicle. As the vehicle moves, a sequence of images of the sea-floor is acquired by the camera. For every image of the sequence, a set of characteristic features is detected by means of a corner detector. Then, their correspondences are found in the next image of the sequence. Solving the correspondence problem in an accurate and reliable way is a difficult task in computer vision. We consider different alternatives to solve this problem by introducing a detailed analysis of the textural characteristics of the image. This is done in two phases: first comparing different texture operators individually, and next selecting those that best characterize the point/matching pair and using them together to obtain a more robust characterization. Various alternatives are also studied to merge the information provided by the individual texture operators. Finally, the best approach in terms of robustness and efficiency is proposed. After the correspondences have been solved, for every pair of consecutive images we obtain a list of image features in the first image and their matchings in the next frame. Our aim is now to recover the apparent motion of the camera from these features. Although an accurate texture analysis is devoted to the matching pro-cedure, some false matches (known as outliers) could still appear among the right correspon-dences. For this reason, a robust estimation technique is used to estimate the planar transformation (homography) which explains the dominant motion of the image. Next, this homography is used to warp the processed image to the common mosaic frame, constructing a composite image formed by every frame of the sequence. With the aim of estimating the position of the vehicle as the mosaic is being constructed, the 3D motion of the vehicle can be computed from the measurements obtained by a sonar altimeter and the incremental motion computed from the homography. Unfortunately, as the mosaic increases in size, image local alignment errors increase the inaccuracies associated to the position of the vehicle. Occasionally, the trajectory described by the vehicle may cross over itself. In this situation new information is available, and the system can readjust the position estimates. Our proposal consists not only in localizing the vehicle, but also in readjusting the trajectory described by the vehicle when crossover information is obtained. This is achieved by implementing an Augmented State Kalman Filter (ASKF). Kalman filtering appears as an adequate framework to deal with position estimates and their associated covariances. Finally, some experimental results are shown. A laboratory setup has been used to analyze and evaluate the accuracy of the mosaicking system. This setup enables a quantitative measurement of the accumulated errors of the mosaics created in the lab. Then, the results obtained from real sea trials using the URIS underwater vehicle are shown.

Estimates of Avian Mortality Attributed to Vehicle Collisions in Canada

Although mortality of birds from collisions with vehicles is estimated to be in the millions in the USA, Europe, and the UK, to date, no estimates exist for Canada. To address this, we calculated an estimate of annual avian mortality attributed to vehicular collisions during the breeding and fledging season, in Canadian ecozones, by applying North American literature values for avian mortality to Canadian road networks. Because owls are particularly susceptible to collisions with vehicles, we also estimated the number of roadkilled Barn owls (Tyto alba) in its last remaining range within Canada. (This species is on the IUCN red list and is also listed federally as threatened; Committee on the Status of Endangered Wildlife in Canada 2010, International Union for the Conservation of Nature 2012). Through seven Canadian studies in existence, 80 species and 2,834 specimens have been found dead on roads representing species from 14 orders of birds. On Canadian 1 and 2-lane paved roads outside of major urban centers, the unadjusted number of bird mortalities/yr during an estimated 4-mo (122-d) breeding and fledging season for most birds in Canada was 4,650,137 on roads traversing through deciduous, coniferous, cropland, wetlands and nonagricultural landscapes with less than 10% treed area. On average, this represents 1,167 birds killed/100 km in Canada. Adjusted for scavenging, this estimate was 13,810,906 (3,462 dead birds/100 km). For barn owls, the unadjusted number of birds killed annually on 4-lane roads during the breeding and fledging season, within the species geographic range in southern British Columbia, was estimated as 244 owls and, when adjusted for scavenging and observer bias (3.6 factor), the total was 851 owls.

A Generic Deformable Model for Vehicle Recognition

This paper reports the development of a highly parameterised 3-D model able to adopt the shapes of a wide variety of different classes of vehicles (cars, vans, buses, etc), and its subsequent specialisation to a generic car class which accounts for most commonly encountered types of car (includng saloon, hatchback and estate cars). An interactive tool has been developed to obtain sample data for vehicles from video images. A PCA description of the manually sampled data provides a deformable model in which a single instance is described as a 6 parameter vector. Both the pose and the structure of a car can be recovered by fitting the PCA model to an image. The recovered description is sufficiently accurate to discriminate between vehicle sub-classes.

Model-based vehicle detection and classification using orthographic approximations

This paper reports the current state of work to simplify our previous model-based methods for visual tracking of vehicles for use in a real-time system intended to provide continuous monitoring and classification of traffic from a fixed camera on a busy multi-lane motorway. The main constraints of the system design were: (i) all low level processing to be carried out by low-cost auxiliary hardware, (ii) all 3-D reasoning to be carried out automatically off-line, at set-up time. The system developed uses three main stages: (i) pose and model hypothesis using 1-D templates, (ii) hypothesis tracking, and (iii) hypothesis verification, using 2-D templates. Stages (i) & (iii) have radically different computing performance and computational costs, and need to be carefully balanced for efficiency. Together, they provide an effective way to locate, track and classify vehicles.

Optimal kinematic control of an autonomous underwater vehicle

This note investigates the motion control of an autonomous underwater vehicle (AUV). The AUV is modeled as a nonholonomic system as any lateral motion of a conventional, slender AUV is quickly damped out. The problem is formulated as an optimal kinematic control problem on the Euclidean Group of Motions SE(3), where the cost function to be minimized is equal to the integral of a quadratic function of the velocity components. An application of the Maximum Principle to this optimal control problem yields the appropriate Hamiltonian and the corresponding vector fields give the necessary conditions for optimality. For a special case of the cost function, the necessary conditions for optimality can be characterized more easily and we proceed to investigate its solutions. Finally, it is shown that a particular set of optimal motions trace helical paths. Throughout this note we highlight a particular case where the quadratic cost function is weighted in such a way that it equates to the Lagrangian (kinetic energy) of the AUV. For this case, the regular extremal curves are constrained to equate to the AUV's components of momentum and the resulting vector fields are the d'Alembert-Lagrange equations in Hamiltonian form.

Learning enhanced 3D models for vehicle tracking

This paper presents an enhanced hypothesis verification strategy for 3D object recognition. A new learning methodology is presented which integrates the traditional dichotomic object-centred and appearance-based representations in computer vision giving improved hypothesis verification under iconic matching. The "appearance" of a 3D object is learnt using an eigenspace representation obtained as it is tracked through a scene. The feature representation implicitly models the background and the objects observed enabling the segmentation of the objects from the background. The method is shown to enhance model-based tracking, particularly in the presence of clutter and occlusion, and to provide a basis for identification. The unified approach is discussed in the context of the traffic surveillance domain. The approach is demonstrated on real-world image sequences and compared to previous (edge-based) iconic evaluation techniques.

Production and evaluation of dry alginate-chitosan microcapsules as an enteric delivery vehicle for probiotic bacteria

This study investigates the production of alginate microcapsules, which have been coated with the polysaccharide chitosan, and evaluates some of their properties with the intention of improving the gastrointestinal viability of a probiotic (Bifidobacterium breve) by encapsulation in this system. The microcapsules were dried by a variety of methods, and the most suitable was chosen. The work described in this Article is the first report detailing the effects of drying on the properties of these microcapsules and the viability of the bacteria within relative to wet microcapsules. The pH range over which chitosan and alginate form polyelectrolyte complexes was explored by spectrophotometry, and this extended into swelling studies on the microcapsules over a range of pHs associated with the gastrointestinal tract. It was shown that chitosan stabilizes the alginate microcapsules at pHs above 3, extending the stability of the capsules under these conditions. The effect of chitosan exposure time on the coating thickness was investigated for the first time by confocal laser scanning microscopy, and its penetration into the alginate matrix was shown to be particularly slow. Coating with chitosan was found to increase the survival of B. breve in simulated gastric fluid as well as prolong its release upon exposure to intestinal pH.

Intake fraction of nonreactive motor vehicle exhaust in HongKong

The intake fraction (iF) of nonreactive constituents of exhaust from mobile vehicles in the urban area of HongKong is investigated using available monitoring data for carbon monoxide (CO) as a tracer of opportunity. Correcting for regional transport of carbon monoxide into HongKong, the annual-average iF for nonreactive motor vehicle emissions within the city is estimated to be around 270 per million. This estimated iF is much higher than values previously reported for vehicle emissions in US urban areas, Helsinki and Beijing, and somewhat lower than those reported for a densely populated street canyon in downtown Manhattan, New York City, or for emissions into indoor environments. The reported differences in intakefractions in various cities mainly result from the differences in local population densities. Our analysis highlights the importance of accounting for the influence of upwind transport of pollutants when using ambient data to estimate iF for an urban area. For vehicleexhaust in HongKong, it is found that the in/near vehicle microenvironment contributes similarly to the indoor home environment when accounting for the overall iF for children and adults. Keywords Intakefraction; Vehicle emission; Regional pollutant transport; Carbon monoxide; Exposure

A framework for English? Or a vehicle for literacy? English teaching in England in the age of the Strategy

This article considers the evolution and impact on schools in England of the "Framework for English" since its introduction in 2001, a national initiative that follows on from the National Literacy Strategy, which focused on primary schools. Whilst acknowledging that the Framework is part of a whole school policy, "The Key Stage Three Strategy", I concentrate on its direct impact on the school subject "English" and on standards within that subject. Such a discussion must incorporate some consideration of the rise of "Literacy" as a dominant term and theme in England (and globally) and its challenge to a politically controversial and much contested curriculum area, i.e. "English". If the Framework is considered within the context of the Literacy drive since the mid-1990s then it can be see to be evolving within a much changed policy context and therefore likely to change substantially in the next few years. In a global context England has been regarded for some time as at the extreme edge of standards-driven policy and practice. It is hoped that the story of "English" in England may be salutary to educators from other countries.

Multi-vehicle planning using RRT-connect

The problem of planning multiple vehicles deals with the design of an effective algorithm that can cause multiple autonomous vehicles on the road to communicate and generate a collaborative optimal travel plan. Our modelling of the problem considers vehicles to vary greatly in terms of both size and speed, which makes it suboptimal to have a faster vehicle follow a slower vehicle or for vehicles to drive with predefined speed lanes. It is essential to have a fast planning algorithm whilst still being probabilistically complete. The Rapidly Exploring Random Trees (RRT) algorithm developed and reported on here uses a problem specific coordination axis, a local optimization algorithm, priority based coordination, and a module for deciding travel speeds. Vehicles are assumed to remain in their current relative position laterally on the road unless otherwise instructed. Experimental results presented here show regular driving behaviours, namely vehicle following, overtaking, and complex obstacle avoidance. The ability to showcase complex behaviours in the absence of speed lanes is characteristic of the solution developed.

Motion planning of autonomous vehicles in a non-autonomous vehicle environment without speed lanes

Planning is one of the key problems for autonomous vehicles operating in road scenarios. Present planning algorithms operate with the assumption that traffic is organised in predefined speed lanes, which makes it impossible to allow autonomous vehicles in countries with unorganised traffic. Unorganised traffic is though capable of higher traffic bandwidths when constituting vehicles vary in their speed capabilities and sizes. Diverse vehicles in an unorganised exhibit unique driving behaviours which are analysed in this paper by a simulation study. The aim of the work reported here is to create a planning algorithm for mixed traffic consisting of both autonomous and non-autonomous vehicles without any inter-vehicle communication. The awareness (e.g. vision) of every vehicle is restricted to nearby vehicles only and a straight infinite road is assumed for decision making regarding navigation in the presence of multiple vehicles. Exhibited behaviours include obstacle avoidance, overtaking, giving way for vehicles to overtake from behind, vehicle following, adjusting the lateral lane position and so on. A conflict of plans is a major issue which will almost certainly arise in the absence of inter-vehicle communication. Hence each vehicle needs to continuously track other vehicles and rectify plans whenever a collision seems likely. Further it is observed here that driver aggression plays a vital role in overall traffic dynamics, hence this has also been factored in accordingly. This work is hence a step forward towards achieving autonomous vehicles in unorganised traffic, while similar effort would be required for planning problems such as intersections, mergers, diversions and other modules like localisation.