862 resultados para Path Planning Under Uncertainty


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Este estudo exploratório teve como objetivo investigar os principais mecanismos de gestão utilizados no planejamento na indústria cinematográfica. Para tanto, foi realizado um estudo de casos múltiplos, envolvendo quatro produtoras cinematográficas, das quais três estão localizadas no estado do Rio de Janeiro e uma em São Paulo. Os dados foram obtidos a partir de entrevistas focalizadas com profissionais dessas quatro empresas. Os casos foram analisados sob à luz de teorias sobre planejamento e controle em ambientes incertos e nas indústrias culturais. Os resultados indicam que o orçamento e controle dos filmes é feito de forma rigorosa. Todas as produtoras efetuam revisões orçamentárias durante a produção dos filmes. A maior incerteza relatada por todas as empresas foi a estimativa da receita e para isso, duas produtoras indicaram o uso de cenários para auxiliá-los nesta tarefa. Além disso, duas produtoras relataram a elaboração de carteiras de projetos a fim de reduzir o risco das produções. Por fim, um caso especificamente trouxe um elemento novo em relação aos demais casos ao incluir sócio em busca de investimento de risco na composição acionária do filme. Este modelo de negócio acarretou orçamentos em patamares menores do que nos demais casos.

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This work presents the localization and path planning systems for two robots: a non-instrumented humanoid and a slave wheeled robot. The localization of wheeled robot is made using odometry information and landmark detection. These informations are fused using a Extended Kalman Filter. The relative position of humanoid is acquired fusing (using another Kalman Filter) the wheeled robot pose with the characteristics of the landmark on the back of humanoid. Knowing the wheeled robot position and the humanoid relative position in relation to it, we acquired the absolute position of humanoid. The path planning system was developed to provide the cooperative movement of the two robots,incorporating the visibility restrictions of the robotic system

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This work introduces a new method for environment mapping with three-dimensional information from visual information for robotic accurate navigation. Many approaches of 3D mapping using occupancy grid typically requires high computacional effort to both build and store the map. We introduce an 2.5-D occupancy-elevation grid mapping, which is a discrete mapping approach, where each cell stores the occupancy probability, the height of the terrain at current place in the environment and the variance of this height. This 2.5-dimensional representation allows that a mobile robot to know whether a place in the environment is occupied by an obstacle and the height of this obstacle, thus, it can decide if is possible to traverse the obstacle. Sensorial informations necessary to construct the map is provided by a stereo vision system, which has been modeled with a robust probabilistic approach, considering the noise present in the stereo processing. The resulting maps favors the execution of tasks like decision making in the autonomous navigation, exploration, localization and path planning. Experiments carried out with a real mobile robots demonstrates that this proposed approach yields useful maps for robot autonomous navigation

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The main task and one of the major mobile robotics problems is its navigation process. Conceptualy, this process means drive the robot from an initial position and orientation to a goal position and orientation, along an admissible path respecting the temporal and velocity constraints. This task must be accomplished by some subtasks like robot localization in the workspace, admissible path planning, trajectory generation and motion control. Moreover, autonomous wheeled mobile robots have kinematics constraints, also called nonholonomic constraints, that impose the robot can not move everywhere freely in its workspace, reducing the number of feasible paths between two distinct positions. This work mainly approaches the path planning and trajectory generation problems applied to wheeled mobile robots acting on a robot soccer environment. The major dificulty in this process is to find a smooth function that respects the imposed robot kinematic constraints. This work proposes a path generation strategy based on parametric polynomials of third degree for the 'x' and 'y' axis. The 'theta' orientation is derived from the 'y' and 'x' relations in such a way that the generated path respects the kinematic constraint. To execute the trajectory, this work also shows a simple control strategy acting on the robot linear and angular velocities

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Enterprises need continuous product development activities to remain competitive in the marketplace. Their product development process (PDP) must manage stakeholders' needs - technical, financial, legal, and environmental aspects, customer requirements, Corporate strategy, etc. -, being a multidisciplinary and strategic issue. An approach to use real option to support the decision-making process at PDP phases in taken. The real option valuation method is often presented as an alternative to the conventional net present value (NPV) approach. It is based on the same principals of financial options: the right to buy or sell financial values (mostly stocks) at a predetermined price, with no obligation to do so. In PDP, a multi-period approach that takes into account the flexibility of, for instance, being able to postpone prototyping and design decisions, waiting for more information about technologies, customer acceptance, funding, etc. In the present article, the state of the art of real options theory is prospected and a model to use the real options in PDP is proposed, so that financial aspects can be properly considered at each project phase of the product development. Conclusion is that such model can provide more robustness to the decisions processes within PDP.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Geologia Regional - IGCE

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Reasoning under uncertainty is a human capacity that in software system is necessary and often hidden. Argumentation theory and logic make explicit non-monotonic information in order to enable automatic forms of reasoning under uncertainty. In human organization Distributed Cognition and Activity Theory explain how artifacts are fundamental in all cognitive process. Then, in this thesis we search to understand the use of cognitive artifacts in an new argumentation framework for an agent-based artificial society.

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Negli ultimi decenni la Politica Agricola Comune (PAC) è stata sottoposta a diverse revisioni, più o meno programmate, che ne hanno modificato gli obiettivi operativi e gli strumenti per perseguirli. In letteratura economica agraria sono state eseguite diverse ricerche che affrontano analisi ex-ante sui possibili impatti delle riforme politiche, in particolare al disaccoppiamento, riguardo all’allocazione dei terreni alle diverse colture e all’adozione di tecniche di coltivazione più efficienti. Ma tale argomento, nonostante sia di grande importanza, non è stato finora affrontato come altri temi del mondo agricolo. Le principali lacune si riscontrano infatti nella carenza di analisi ex-ante, di modelli che includano le preferenze e le aspettative degli agricoltori. Questo studio valuta le scelte di investimento in terreno di un’azienda agricola di fronte a possibili scenari PAC post-2013, in condizioni di incertezza circa le specifiche condizioni in cui ciascuno scenario verrebbe a verificarsi. L’obiettivo è di ottenere indicazioni utili in termini di comprensione delle scelte di investimento dell’agricoltore in presenza di incertezza sul futuro. L’elemento maggiormente innovativo della ricerca consiste nell’applicazione di un approccio real options e nell’interazione tra la presenza di diversi scenari sul futuro del settore agricolo post-2013, e la componente di incertezza che incide e gravita su di essi. La metodologia adottata nel seguente lavoro si basa sulla modellizzazione di un’azienda agricola, in cui viene simulato il comportamento dell’azienda agricola in reazione alle riforme della PAC e alla variazione dei prezzi dei prodotti in presenza di incertezza. Mediante un modello di Real Option viene valutata la scelta della tempistica ottimale per investire nell’acquisto di terreno (caratterizzato da incertezza e irreversibilità). Dai risultati emerge come in presenza di incertezza all’agricoltore convenga rimandare la decisione a dopo il 2013 e in base alle maggiori informazioni disponibili eseguire l’investimento solo in presenza di condizioni favorevoli. La variazione dei prezzi dei prodotti influenza le scelte più dell’incertezza dei contributi PAC. Il Real Option sembra interpretare meglio il comportamento dell’agricoltore rispetto all’approccio classico del Net Present Value.

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Accurate seasonal to interannual streamflow forecasts based on climate information are critical for optimal management and operation of water resources systems. Considering most water supply systems are multipurpose, operating these systems to meet increasing demand under the growing stresses of climate variability and climate change, population and economic growth, and environmental concerns could be very challenging. This study was to investigate improvement in water resources systems management through the use of seasonal climate forecasts. Hydrological persistence (streamflow and precipitation) and large-scale recurrent oceanic-atmospheric patterns such as the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the Pacific North American (PNA), and customized sea surface temperature (SST) indices were investigated for their potential to improve streamflow forecast accuracy and increase forecast lead-time in a river basin in central Texas. First, an ordinal polytomous logistic regression approach is proposed as a means of incorporating multiple predictor variables into a probabilistic forecast model. Forecast performance is assessed through a cross-validation procedure, using distributions-oriented metrics, and implications for decision making are discussed. Results indicate that, of the predictors evaluated, only hydrologic persistence and Pacific Ocean sea surface temperature patterns associated with ENSO and PDO provide forecasts which are statistically better than climatology. Secondly, a class of data mining techniques, known as tree-structured models, is investigated to address the nonlinear dynamics of climate teleconnections and screen promising probabilistic streamflow forecast models for river-reservoir systems. Results show that the tree-structured models can effectively capture the nonlinear features hidden in the data. Skill scores of probabilistic forecasts generated by both classification trees and logistic regression trees indicate that seasonal inflows throughout the system can be predicted with sufficient accuracy to improve water management, especially in the winter and spring seasons in central Texas. Lastly, a simplified two-stage stochastic economic-optimization model was proposed to investigate improvement in water use efficiency and the potential value of using seasonal forecasts, under the assumption of optimal decision making under uncertainty. Model results demonstrate that incorporating the probabilistic inflow forecasts into the optimization model can provide a significant improvement in seasonal water contract benefits over climatology, with lower average deficits (increased reliability) for a given average contract amount, or improved mean contract benefits for a given level of reliability compared to climatology. The results also illustrate the trade-off between the expected contract amount and reliability, i.e., larger contracts can be signed at greater risk.