93 research outputs found

    Hierarchical motion planning with kinodynamic feasibility guarantees: Local trajectory planning via model predictive control

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    Copyright © 2012 IEEEPresented at 2012 IEEE International Conference on Robotics and Automation (ICRA)DOI: dx.doi.org/10.1109/ICRA.2012.6224895Motion planners for autonomous vehicles often involve a two-level hierarchical structure consisting of a high-level, discrete planner and a low-level trajectory generation scheme. To ensure compatibility between these two levels of planning, we previously introduced a motion planning framework based on multiple-edge transition costs in the graph used by the discrete planner. This framework is enabled by a special local trajectory generation problem, which we address in this paper. In particular, we discuss a trajectory planner based on model predictive control for complex vehicle dynamical models. We demonstrate the efficacy of our overall motion planning approach via examples involving non-trivial vehicle models and complex environments, and we offer comparisons of our motion planner with state-of-the-art randomized sampling-based motion planners

    Generalização de modelos digitais de terreno com base em transformada wavelet

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    Os sistemas de laser scanner permitem a obtenção de modelos digitais de terreno de alta resolução e exatidão. Porém, quando se necessita trabalhar em aplicações com uma resolução menor que a originalmente gerada, a grande quantidade de dados acarreta a necessidade de generalização. Este trabalho tem por objetivo verificar o comportamento da transformada wavelet na generalização de modelos digitais do terreno sob a forma de grades regulares, obtidas a partir de dados do laser scanner. As transformadas wavelets foram implementadas em programas na linguagem Matlab. Foram utilizadas as wavelets de Haar, Daubechies e Symlet. A generalização por krigagem foi utilizada para a comparação dos resultados. Os resultados obtidos nos experimentos realizados permitem afirmar que a transformada wavelet pode ser utilizada como alternativa para a generalização de MDT em razão da facilidade de programação, baixo custo computacional, alta velocidade de processamento e exatidão compatível com a resolução obtida no MDT generalizado, além de ser um método natural de análise multirresolução

    Hierarchical motion planning for autonomous aerial and terrestrial vehicles

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    Autonomous mobile robots - both aerial and terrestrial vehicles - have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory. Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle. Although simple and efficient, such hierarchical separation suffers a serious drawback: the geometric path planner has no information of the kinematic and dynamic constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates altogether the geometric planner by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption concerning the vehicle kinematic model. In this thesis, we propose a hierarchical motion planning framework based on a novel mode of interaction between these two levels of planning. This interaction rests on the solution of a special shortest-path problem on graphs, namely, one using costs defined on multiple edge transitions in the path instead of the usual single edge transition costs. These costs are provided by a local trajectory generation algorithm, which we implement using model predictive control and the concept of effective target sets for simplifying the non-convex constraints involved in the problem. The proposed motion planner ensures "consistency" between the two levels of planning, i.e., a guarantee that the higher level geometric path is always associated with a kinematically and dynamically feasible trajectory. We show that the proposed motion planning approach offers distinct advantages in comparison with the competing approaches of discretization of the state space, of randomized sampling-based motion planning, and of local feedback-based, decoupled hierarchical motion planning. Finally, we propose a multi-resolution implementation of the proposed motion planner, which requires accurate descriptions of the environment and the vehicle only for short-term, local motion planning in the immediate vicinity of the vehicle.Ph.D

    Supporting Survivors of Sexual Assault: A Feminist Perspective

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    Sexual assault continues to be a serious problem in the United States and in Utah; one that exacts a heavy toll on the survivors as well as society in general. While the issue is an old one, there is still considerable debate around it. Indeed, the myths, misperceptions, and ignorance about the causes and effects of rape and sexual assault impede the recovery process for the survivors of sexual assault. The goal of this thesis is to support survivors of sexual assault in their recovery. The core of the thesis is a manual written for professionals who work with survivors in Utah. Issues and problems resulting from rape and sexual assault are discussed in detail and the manual includes advocacy tips on dealing with specific circumstances. Emphasis is placed on providing multifaceted and comprehensive care to facilitate long-term healing for the survivor. The manual is the first of its kind for the State of Utah. The introduction and conclusion view and analyze the manual through a feminist lens. A theoretical basis for the manual is presented. Finally, a postmodern framework is used to question the status quo and provide the basis for new thought and theory

    Reshaping Role of State Governments in Industrial Development

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    Multiresolution Aircraft Guidance in a Spatiotemporally-varying Threat Field

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    Unifying Artificial Intelligence and Trajectory Optimization for UAV Guidance

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