The self-potential method responds to the electrokinetic phenomenon of streaming potential and has been applied in hydrogeologic and engineering investigations to aid in the evaluation of subsurface hydraulic conditions. Of specific interest is the application of the method to embankment dam seepage monitoring and detection. This demands a quantitative interpretation of seepage conditions from the geophysical data. To enable the study of variably saturated flow problems of complicated geometry, a three-dimensional finite volume algorithm is developed to evaluate the self-potential distribution resulting from subsurface fluid flow. The algorithm explicitly calculates the distribution of streaming current sources and solves for the self-potential given a model of hydraulic head and prescribed distributions of the streaming current cross-coupling conductivity and electrical resistivity. A new laboratory apparatus is developed to measure the streaming potential coupling coefficient and resistivity in unconsolidated soil samples. Measuring both of these parameters on the same sample under the same conditions enables us to properly characterize the streaming current cross-coupling conductivity coefficient. I present the results of a laboratory investigation to study the influence of soil and fluid parameters on the cross-coupling coefficient, and characterize this property for representative well-graded embankment soils. The streaming potential signals associated with preferential seepage through the core of a synthetic embankment dam model are studied using the forward modelling algorithm and measured electrical properties to assess the sensitivity of the self-potential method in detecting internal erosion. Maximum self-potential anomalies are shown to be linked to large localized hydraulic gradients that develop in response to piping, prior to any detectable increase in seepage flow through the dam. A linear inversion algorithm is developed to evaluate the three-dimensional distribution of hydraulic head from self-potential data, given a known distribution of the cross-coupling coefficient and electrical resistivity. The inverse problem is solved by minimizing an objective function, which consists of a data misfit that accounts for measurement error and a model objective function that incorporates a priori information. The algorithm is suitable for saturated flow problems or where the position of the phreatic surface is known.

The self-potential method responds to the electrokinetic phenomenon of streaming potential and has been applied in hydrogeologic and engineering investigations to aid in the evaluation of subsurface hydraulic conditions. Of specific interest is the application of the method to embankment dam seepage monitoring and detection. This demands a quantitative interpretation of seepage conditions from the geophysical data. To enable the study of variably saturated flow problems of complicated geometry, a three-dimensional finite volume algorithm is developed to evaluate the self-potential distribution resulting from subsurface fluid flow. The algorithm explicitly calculates the distribution of streaming current sources and solves for the self-potential given a model of hydraulic head and prescribed distributions of the streaming current cross-coupling conductivity and electrical resistivity. A new laboratory apparatus is developed to measure the streaming potential coupling coefficient and resistivity in unconsolidated soil samples. Measuring both of these parameters on the same sample under the same conditions enables us to properly characterize the streaming current cross-coupling conductivity coefficient. I present the results of a laboratory investigation to study the influence of soil and fluid parameters on the cross-coupling coefficient, and characterize this property for representative well-graded embankment soils. The streaming potential signals associated with preferential seepage through the core of a synthetic embankment dam model are studied using the forward modelling algorithm and measured electrical properties to assess the sensitivity of the self-potential method in detecting internal erosion. Maximum self-potential anomalies are shown to be linked to large localized hydraulic gradients that develop in response to piping, prior to any detectable increase in seepage flow through the dam. A linear inversion algorithm is developed to evaluate the three-dimensional distribution of hydraulic head from self-potential data, given a known distribution of the cross-coupling coefficient and electrical resistivity. The inverse problem is solved by minimizing an objective function, which consists of a data misfit that accounts for measurement error and a model objective function that incorporates a priori information. The algorithm is suitable for saturated flow problems or where the position of the phreatic surface is known.

Falkenberg area is located in southwest Sweden formed in the Sveconorwegian orogen and contains an extremely complex geological structure. Multiple geophysical datasets have been acquired and together with available petrophysical information, models corresponding to the subsurface geological structures were generated. The collected data comprise ground magnetic, AMT (Audio Magnetotelluric) and RMT (Radio Magnetotelluric) data. The available airborne magnetic and ground gravity data acquired by the Geological Survey of Sweden (SGU) as well as the reflection seismic section from a study made by Uppsala University further aids in obtaining substantially improved interpretation of the geometry of the structures along the AMT profile. The principal objective of this profile was to delineate and map the possible deformation zone crossed by the profile. The AMT study was expected to complement existing geophysical data and improve existing interpretations. The Ullared deformation zone contains decompressed eclogite facies rocks. The presented results were obtained by comparison of different geophysical methods along the profile. The susceptibility model and resistivity model show that eclogites have higher resistivity and susceptibility than the surrounding structures. However use of the Occam type of inversion on the AMT data, makes the resistivity model smoother than the susceptibility model and as a results it is difficult to estimate the dip of the structures. The AMT profile and the seismic section show the same dip direction (NE) for the eclogite bearing structures although due to the smoothing in the AMT model the dips seen in the seismic section cannot be recovered in the resistivity model.

The self-potential method responds to the electrokinetic phenomenon of streaming potential and has been applied in hydrogeologic and engineering investigations to aid in the evaluation of subsurface hydraulic conditions. Of specific interest is the application of the method to embankment dam seepage monitoring and detection. This demands a quantitative interpretation of seepage conditions from the geophysical data. To enable the study of variably saturated flow problems of complicated geometry, a three-dimensional finite volume algorithm is developed to evaluate the self-potential distribution resulting from subsurface fluid flow. The algorithm explicitly calculates the distribution of streaming current sources and solves for the self-potential given a model of hydraulic head and prescribed distributions of the streaming current cross-coupling conductivity and electrical resistivity. A new laboratory apparatus is developed to measure the streaming potential coupling coefficient and resistivity in unconsolidated soil samples. Measuring both of these parameters on the same sample under the same conditions enables us to properly characterize the streaming current cross-coupling conductivity coefficient. I present the results of a laboratory investigation to study the influence of soil and fluid parameters on the cross-coupling coefficient, and characterize this property for representative well-graded embankment soils. The streaming potential signals associated with preferential seepage through the core of a synthetic embankment dam model are studied using the forward modelling algorithm and measured electrical properties to assess the sensitivity of the self-potential method in detecting internal erosion. Maximum self-potential anomalies are shown to be linked to large localized hydraulic gradients that develop in response to piping, prior to any detectable increase in seepage flow through the dam. A linear inversion algorithm is developed to evaluate the three-dimensional distribution of hydraulic head from self-potential data, given a known distribution of the cross-coupling coefficient and electrical resistivity. The inverse problem is solved by minimizing an objective function, which consists of a data misfit that accounts for measurement error and a model objective function that incorporates a priori information. The algorithm is suitable for saturated flow problems or where the position of the phreatic surface is known. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

This thesis explores the combination of influence maps and potential fields in two novel pathfinding algorithms, IM+PF and IM/PF, that allows AI agents to intelligently navigate an environment. The novel algorithms are compared to two established pathfinding algorithms, A* and A*+PF, in the real-time strategy (RTS) game StarCraft 2. The main focus of the thesis is to evaluate the pathfinding capabilities and real-time performance of the novel algorithms in comparison to the established pathfinding algorithms. Based on the results of the evaluation, general use cases of the novel algorithms are presented, as well as an assessment if the novel algorithms can be used in modern games. The novel algorithms’ pathfinding capabilities, as well as performance scalability, are compared to established pathfinding algorithms to evaluate the viability of the novel solutions. Several experiments are created, using StarCraft 2’s base game as a benchmarking tool, where various aspects of the algorithms are tested. The creation of influence maps and potential fields in real-time are highly parallelizable, and are therefore done in a GPGPU solution, to accurately assess all algorithms’ real-time performance in a game environment. The experiments yield mixed results, showing better pathfinding and scalability performance by the novel algorithms in certain situations. Since the algorithms utilizing potential fields enable agents to inherently avoid and engage units in the environment, they have an advantage in experiments where such qualities are assessed. Similarly, influence maps enable agents to traverse the map more efficiently than simple A*, giving agents inherent advantages. In certain use cases, where multiple agents require pathfinding to the same destination, creating a single influence map is more beneficial than generating separate A* paths for each agent. The main benefits of generating the influence map, compared to A*-based solutions, being the lower total compute time, more precise pathfinding and the possibility of pre-calculating the map. / Denna rapport utforskar kombinationen av influence maps och potential fields med två nya pathfinding algoritmer, IM+PF och IM/PF, som möjliggör intelligent navigation av AI agenter. De nya algoritmerna jämförs med två existerande pathfindingalgoritmer, A* och A*+PF, i realtidsstrategispelet StarCraft 2. Rapportens fokus är att utvärdera de nya algoritmernas pathfindingförmåga samt realtidsprestanda i förhållande till de två existerande algoritmerna, i sex olika experiment. Baserat på resultaten av experimenten presenteras generella användningsområden för algoritmerna tillsammans med en bedömning om algoritmerna kan användas i moderna spel. De fyra pathfindingalgoritmerna implementeras för att jämföra pathfindingförmåga och realtidsprestanda, för att dra slutsatser angående de nya algoritmernas livsduglighet. Med användningen av StarCraft 2 som ett benchmarkingvertyg skapas sex experiment där olika aspekter av algoritmerna testas. Genereringen av influence maps och potential fields i realtid är ett arbete som kan parallelliseras, och därför implementeras en GPGPU-lösning för att få en meningsfull representation av realtidsprestandan av algoritmerna i en spelmiljö. Experimenten visar att de nya algoritmerna presterar bättre i både pathfindingförmåga och skalbarhet under vissa förhållanden. Algoritmerna som använder potential fields har en stor fördel gentemot simpel A*, då agenterna kan naturligt undvika eller konfrontera enheter i miljön, vilket ger de algoritmerna stora fördelar i experiment där sådana förmågor utvärderas. Influence maps ger likväl egna fördelar gentemot A*, då agenter som utnyttjar influence maps kan traversera världen mer effektivt. Under förhållanden då flera AI agenter ska traversera en värld till samma mål kan det vara förmånligt att skapa en influence map, jämfört med att generera individuella A*-vägar till varje agent. De huvudsakliga fördelarna för de influence map-baserade algoritmerna är att de kräver lägre total beräkningstid och ger en merexakt pathfinding, samt möjligheten att förberäkna influence map-texturen.

In car racing simulation games, finishing first is the main goal. To reach that goal, it is required to go around a racing track, competing against other cars aiming for the same goal. Implementing a bot for doing so may have its difficulties, although using a technique called multi-agent systems combined with artificial potential field, let- ting the agents take care of subtasks like keeping the car on the track, minimize how much the car turns in a curvature and basics in navigation around the track, has showed that artificial potential fields very well fit the problem of driving a car in simulated car racing in a competitive way. / Mobiltelefon: 0707422666

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With the advancements in acquisition and processing of seismic reflection data recorded over crystalline rocks, building three-dimensional geologic models becomes increasingly favorable. Because of little available petrophysical data, interpretations of seismic reflection data in hardrock terrains are often speculative. Potential field data modeling are sometimes performed in order to reduce the ambiguity of seismic reflection interpretations. The Kristineberg mining area in the western part of the Paleoproterozoic Skellefte Ore District was chosen to construct a pilot three-dimensional geologic model in an attempt to understand the crustal architecture in the region and how the major mineral systems operated in this architecture. To contribute to this aim, two parallel seismic reflection profiles were acquired in 2003 and processed to 20 sec with special attention to the top 4 sec of data. Several reflections were imaged and interpreted by the aid of reflector modeling, borehole data, 2.5D and 3D potential field modeling, and geological observations. Interpretations are informative at the crustal scale and help to construct a three-dimensional geologic model of the Kristineberg mining area. The three-dimensional geologic model covers an area of 30×30 km2 down to a depth of 12 km. The integrations help to interpret a structural basement to the Skellefte volcanic rocks, possibly with Bothnian Basin metasedimentary affinity. The contact is a shear-zone that separates the two units, generating large fold structures, which can be observed in the region. The interpretations help to divide the Revsund granitic rocks into two major groups based on their present shape and thickness. A large gravity low in the south is best represented by the intrusion of thick dome of Revsund granite. In the north, the low-gravity corresponds to the intrusion of sheet-like Revsund granites. In general, the structure associated with the Skellefte volcanics and the overlying metasedimentary rocks are two thrusts exposing the Skellefte volcanic rocks in the cores of hanging wall anticlinal structures. Lack of coherent reflectivity in the seismic reflection data may be due to complex faulting and folding systems observed in the Skellefte volcanics. Ultramafic sills within the metasedimentary rocks are interpreted to extend down to depths of about 5-6 km. The interpretations are helpful for targeting new VHMS deposits and areas with gold potential. For VHMS deposits, these are situated in the southern limb of a local synformal structure south of the Kristineberg mine, on the contact between the Revsund granite and the Skellefte volcanic rocks. A combination of metasedimentary and mafic-ultramafic rocks are highly gold prospective in the west, similar to observations elsewhere in the region. There are still questions that remain unanswered and need more work. New data in the study area will help to answer questions related to e.g., an enigmatic diffraction seismic signal in Profile 5 and the structural relationship between the Skellefte volcanic rocks and the Malå volcanics. Although the derived 3D geologic model is preliminary and constructed at the crustal scale, it provides useful information to better understand the tectonic evolution of the Kristineberg mining area.

This thesis deals with safety verification analysis of collision avoidance systems for unmanned vehicles. The safety of the vehicle is dependent on collision avoidance algorithms and associated control laws, and it must be proven that the collision avoidance algorithms and controllers are functioning correctly in all nominal conditions, various failure conditions and in the presence of possible variations in the vehicle and operational environment. The current widely used exhaustive search based approaches are not suitable for safety analysis of autonomous vehicles due to the large number of possible variations and the complexity of algorithms and the systems. To address this topic, a new optimisation-based verification method is developed to verify the safety of collision avoidance systems. The proposed verification method formulates the worst case analysis problem arising the verification of collision avoidance systems into an optimisation problem and employs optimisation algorithms to automatically search the worst cases. Minimum distance to the obstacle during the collision avoidance manoeuvre is defined as the objective function of the optimisation problem, and realistic simulation consisting of the detailed vehicle dynamics, the operational environment, the collision avoidance algorithm and low level control laws is embedded in the optimisation process. This enables the verification process to take into account the parameters variations in the vehicle, the change of the environment, the uncertainties in sensors, and in particular the mismatching between model used for developing the collision avoidance algorithms and the real vehicle. It is shown that the resultant simulation based optimisation problem is non-convex and there might be many local optima. To illustrate and investigate the proposed optimisation based verification process, the potential field method and decision making collision avoidance method are chosen as an obstacle avoidance candidate technique for verification study. Five benchmark case studies are investigated in this thesis: static obstacle avoidance system of a simple unicycle robot, moving obstacle avoidance system for a Pioneer 3DX robot, and a 6 Degrees of Freedom fixed wing Unmanned Aerial Vehicle with static and moving collision avoidance algorithms. It is proven that although a local optimisation method for nonlinear optimisation is quite efficient, it is not able to find the most dangerous situation. Results in this thesis show that, among all the global optimisation methods that have been investigated, the DIviding RECTangle method provides most promising performance for verification of collision avoidance functions in terms of guaranteed capability in searching worst scenarios.

O desenvolvimento de arquiteturas de controle para múltiplos robôs em ambientes dinâmicos tem sido tema de pesquisas na área de robótica. A complexidade deste tema varia de acordo com as necessidades exigidas da equipe de robôs. Em geral, espera-se que os robôs colaborem uns com os outros na execução de uma tarefa. Além disso, cada robô deve ser capaz de planejar trajetórias e replanejá-las em caso de situações inesperadas. No presente trabalho, propomos uma Arquitetura de Controle Inteligente para múltiplos robôs denominada ACIn. Para esta finalidade, foram investigadas algumas técnicas utilizadas para o controle inteligente de robôs, tais como, Redes Neurais Artificiais, Campos Potenciais e Campos Potenciais baseados em Problema do Valor de Contorno (PVC). Tais técnicas, normalmente utilizadas para um único robô, foram adaptadas para tornar possível o controle de múltiplos robôs sob arquitetura ACIn. Uma outra contribuição deste trabalho refere-se ao aperfeiçoamento da técnica de Campos Potenciais baseada PVC denominada Campos Potenciais Localmente Orientados (CPLO). Este aperfeiçoamento foi proposto para suprir a deficiência das técnicas baseadas em PVC quando estas são aplicadas em ambientes com múltiplos robôs. Além disso, um Sistema Baseado em Regras (SBR) também foi proposto como parte integrante da arquitetura ACIn. O objetivo do SBR é caracterizar a funcionalidade de cada robô para uma determinada tarefa. Isto se faz necessário para que o comportamento dos integrantes da equipe de robôs não seja competitivo e sim colaborativo. Por fim, através dos experimentos utilizando o simulador oficial de futebol de robôs da FIRA, observou-se que a arquitetura de controle inteligente (ACIn) implementada com a técnica de planejamento CPLO e SBR propostos, mostrou-se robusta e eficiente no controle de múltiplos robôs / In this work, an intelligent control architecture for multi-robots denominated ACIn was proposed. With this objective, some techniques considered intelligent were studied for the planning of trajectories, such as Artificial Neural Networks, Potential Fields and Potential Fields based on the boundary value problem (BVP). Such techniques, normally used for a single robot, were adapted to function with multi-robots inside the ACIn architecture. Another contribution of this work refers to the improvement of the Potential Fields based on the boundary value problem (BVP) technique. This improvement was proposed to supply the drawback of the BVP based techniques when they are applied to multi robots environments. Besides, a Rule Based System (RBS) was also proposed as part of the ACIn architecture. The objective of the RBS is to characterize the functionality of each robot for a determined task. This is necessary for the behavior of the equip members not to be competitive, but collaborative. Finally, it was observed through the experiments with the robot soccer simulated environment, that our intelligent control architecture (ACIn) proposal, integrating planning and RBS for the control of multi-robots was satisfactory