Simulació mitjançant tècniques CFD d'una culata per al motor del vehicle de baix consum "Àliga-EPS-UdG"

El projecte pretén estudiar i quantificar les restriccions creades al fluid en circular pels conductes d’admissió i escapament de la culata del motor del vehicle Àliga. L’estudi consta de quatre etapes: estudi de les restriccions actuals dels sistemes d’admissió i escapament; anàlisi dels resultats de la culata de sèrie i proposta de millores aplicables al model real; càlcul de les restriccions creades pels models millorats, i finalment, estudi comparatiu dels resultats obtinguts, interpretant els resultats dels principals paràmetres a analitzar

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.

Process scheduling by output considerations

In multi-tasking systems when it is not possible to guarantee completion of all activities by specified times, the scheduling problem is not straightforward. Examples of this situation in real-time programming include the occurrence of alarm conditions and the buffering of output to peripherals in on-line facilities. The latter case is studied here with the hope of indicating one solution to the general problem.

Graphical tracking systems revisited: a practical approach to computer scheduling in horticulture

Graphical tracking is a technique for crop scheduling where the actual plant state is plotted against an ideal target curve which encapsulates all crop and environmental characteristics. Management decisions are made on the basis of the position of the actual crop against the ideal position. Due to the simplicity of the approach it is possible for graphical tracks to be developed on site without the requirement for controlled experimentation. Growth models and graphical tracks are discussed, and an implementation of the Richards curve for graphical tracking described. In many cases, the more intuitively desirable growth models perform sub-optimally due to problems with the specification of starting conditions, environmental factors outside the scope of the original model and the introduction of new cultivars. Accurate specification for a biological model requires detailed and usually costly study, and as such is not adaptable to a changing cultivar range and changing cultivation techniques. Fitting of a new graphical track for a new cultivar can be conducted on site and improved over subsequent seasons. Graphical tracking emphasises the current position relative to the objective, and as such does not require the time consuming or system specific input of an environmental history, although it does require detailed crop measurement. The approach is flexible and could be applied to a variety of specification metrics, with digital imaging providing a route for added value. For decision making regarding crop manipulation from the observed current state, there is a role for simple predictive modelling over the short term to indicate the short term consequences of crop manipulation.

Developing protocols for nursery based scheduling trials

Most existing crop scheduling models are cultivar specific and are developed using academic resources. As such they rarely meet the particular needs of a grower. A series of protocols have been created to generate effective schedules for a changing product range using data generated on site at a commercial nursery. A screening programme has been developed to help determine a cultivar's photoperiod sensitivity and vernalisation requirement. Experimental conditions were obtained using a cold store facility set to 5degreesC and photoperiod cloches. Eight and 16 hour photoperiod treatments were achieved at low cost by growing plants in cloches of opaque plastic with a motorised rolling screen. Natural light conditions were extended where necessary using a high pressure sodium lamp. Batches of plants were grown according to different schedules based on these treatments. The screening programme found Coreopsis grandiflora 'Flying Saucers' to be a long day plant. Data to form the basis of graphical tracks was taken using variations on commercial schedules. The work provides a nursery based approach to the continuous improvement of crop scheduling practises.

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.