1000 resultados para Path formulation


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Robot Path Planning (RPP) in dynamic environments is a search problem based on the examination of collision-free paths in the presence of dynamic and static obstacles. Many techniques have been developed to solve this problem. Trapping in a local minima and maintaining a Real-Time performance are known as the two most important challenges that these techniques face to solve such problem. This study presents a comprehensive survey of the various techniques that have been proposed in this domain. As part of this survey, we include a classification of the approaches and identify their methods.

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Algorithms for planning quasistatic attitude maneuvers based on the Jacobian of the forward kinematic mapping of fully-reversed (FR) sequences of rotations are proposed in this paper. An FR sequence of rotations is a series of finite rotations that consists of initial rotations about the axes of a body-fixed coordinate frame and subsequent rotations that undo these initial rotations. Unlike the Jacobian of conventional systems such as a robot manipulator, the Jacobian of the system manipulated through FR rotations is a null matrix at the identity, which leads to a total breakdown of the traditional Jacobian formulation. Therefore, the Jacobian algorithm is reformulated and implemented so as to synthesize an FR sequence for a desired rotational displacement. The Jacobian-based algorithm presented in this paper identifies particular six-rotation FR sequences that synthesize desired orientations. We developed the single-step and the multiple-step Jacobian methods to accomplish a given task using six-rotation FR sequences. The single-step Jacobian method identifies a specific FR sequence for a given desired orientation and the multiple-step Jacobian algorithm synthesizes physically feasible FR rotations on an optimal path. A comparison with existing algorithms verifies the fast convergence ability of the Jacobian-based algorithm. Unlike closed-form solutions to the inverse kinematics problem, the Jacobian-based algorithm determines the most efficient FR sequence that yields a desired rotational displacement through a simple and inexpensive numerical calculation. The procedure presented here is useful for those motion planning problems wherein the Jacobian is singular or null.

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Formulation of quantum first passage problem is attempted in terms of a restricted Feynman path integral that simulates an absorbing barrier as in the corresponding classical case. The positivity of the resulting probability density, however, remains to be demonstrated.

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The specific objective of this paper is to develop a state space model of a tubular ammonia reactor which is the heart of an ammonia plant in a fertiliser complex. A ninth order model with three control inputs and two disturbance inputs is generated from the nonlinear distributed model using linearization and lumping approximations. The lumped model is chosen such that the steady state temperature at the exit of the catalyst bed computed from the simplified state space model is close enough to the one computed from the nonlinear steady state model. The model developed in this paper is very useful for the design of continuous/discrete versions of single variable/multivariable control algorithms.

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We propose four variants of recently proposed multi-timescale algorithm in [1] for ant colony optimization and study their application on a multi-stage shortest path problem. We study the performance of the various algorithms in this framework. We observe, that one of the variants consistently outperforms the algorithm [1].

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This paper deals with the optimal load flow problem in a fixed-head hydrothermal electric power system. Equality constraints on the volume of water available for active power generation at the hydro plants as well as inequality constraints on the reactive power generation at the voltage controlled buses are imposed. Conditions for optimal load flow are derived and a successive approximation algorithm for solving the optimal generation schedule is developed. Computer implementation of the algorithm is discussed, and the results obtained from the computer solution of test systems are presented.

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Database management systems offer a very reliable and attractive data organization for fast and economical information storage and processing for diverse applications. It is much more important that the information should be easily accessible to users with varied backgrounds, professional as well as casual, through a suitable data sublanguage. The language adopted here (APPLE) is one such language for relational database systems and is completely nonprocedural and well suited to users with minimum or no programming background. This is supported by an access path model which permits the user to formulate completely nonprocedural queries expressed solely in terms of attribute names. The data description language (DDL) and data manipulation language (DML) features of APPLE are also discussed. The underlying relational database has been implemented with the help of the DATATRIEVE-11 utility for record and domain definition which is available on the PDP-11/35. The package is coded in Pascal and MACRO-11. Further, most of the limitations of the DATATRIEVE-11 utility have been eliminated in the interface package.

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Using the promeasure technique, we give an alternative evaluation of a path integral corresponding to a quadratic action with a generalized memory.

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An exact expression for the calculation of gaussian path integrals involving non-local potentials is given. Its utility is demonstrated by using it to evaluate a path integral arising in the study of an electron gas in a random potential.

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The power of projects has been demonstrated by the growth in their use across an increasing range of industries and workplaces in recent years. Not only has the number of people involved in project management increased, but the qualifications and backgrounds of those people have also broadened, with engineering no longer being the only path to project management (PM). Predicting the career trajectories in Project Management has become more important for both organisations employing project managers and project managers building career portfolios. Our research involved interviewing more than 75 project officers and project managers across a range of industries to explore their career journey. We used Wittgenstein’s family resemblance theory is to analyse the information from the transcripts to identify the extent to which the roles of participants fit with the commonly accepted definition of project management. Findings demonstrate diversity of project manager backgrounds and experiences and relational competencies across these backgrounds that form and shape PM careers.

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Systems of learning automata have been studied by various researchers to evolve useful strategies for decision making under uncertainity. Considered in this paper are a class of hierarchical systems of learning automata where the system gets responses from its environment at each level of the hierarchy. A classification of such sequential learning tasks based on the complexity of the learning problem is presented. It is shown that none of the existing algorithms can perform in the most general type of hierarchical problem. An algorithm for learning the globally optimal path in this general setting is presented, and its convergence is established. This algorithm needs information transfer from the lower levels to the higher levels. Using the methodology of estimator algorithms, this model can be generalized to accommodate other kinds of hierarchical learning tasks.

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In an effort to develop a fully computerized approach for structural synthesis of kinematic chains the steps involved in the method of structural synthesis based on transformation of binary chains [38] have been recast in a format suitable for implementation on a digital computer. The methodology thus evolved has been combined with the algebraic procedures for structural analysis [44] to develop a unified computer program for structural synthesis and analysis of simple jointed kinematic chains with a degree of freedom 0. Applications of this program are presented in the succeeding parts of the paper.

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Using the promeasure technique, we give an alternative evaluation of a path integral corresponding to a quadratic action with a generalized memory.

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Kafirin, a protein extracted from sorghum grain, has been formulated into microparticles and proposed for use as a delivery system owing to the resistance of kafirin to upper gastrointestinal digestion. However, extracting kafirin from sorghum distillers dried grains with solubles (DDGS) may be more efficient, because the carbohydrate component has been removed by fermentation. This study investigated the properties and use of kafirin extracted from DDGS to formulate microparticles. Prednisolone, an anti-inflammatory drug that could benefit from a delayed and targeted delivery system to the colon, was loaded into DDGS kafirin microparticles by phase separation with sodium chloride. Scanning electron micrographs revealed that the empty and prednisolone-loaded microparticles were round in shape and varied in size. Surface binding studies indicated prednisolone was loaded within the microparticles rather than being solely bound on the surface. These findings demonstrate DDGS kafirin can be formulated into microparticles and loaded with medication. Future studies could investigate the potential applications of DDGS kafirin microparticles as an orally administered targeted drug-delivery system.

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Numerically discretized dynamic optimization problems having active inequality and equality path constraints that along with the dynamics induce locally high index differential algebraic equations often cause the optimizer to fail in convergence or to produce degraded control solutions. In many applications, regularization of the numerically discretized problem in direct transcription schemes by perturbing the high index path constraints helps the optimizer to converge to usefulm control solutions. For complex engineering problems with many constraints it is often difficult to find effective nondegenerat perturbations that produce useful solutions in some neighborhood of the correct solution. In this paper we describe a numerical discretization that regularizes the numerically consistent discretized dynamics and does not perturb the path constraints. For all values of the regularization parameter the discretization remains numerically consistent with the dynamics and the path constraints specified in the, original problem. The regularization is quanti. able in terms of time step size in the mesh and the regularization parameter. For full regularized systems the scheme converges linearly in time step size.The method is illustrated with examples.