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Concept

.NET Framework

Résumé

Le .NET Framework (abr. NetFx) est un cadriciel (framework) pouvant être utilisé par un système d'exploitation Microsoft Windows et Microsoft Windows Mobile depuis la version 5 (.NET Compact Framework). Une version légère et limitée fournie avec un moteur d'exécution fonctionnant à l'intérieur d'un navigateur ou d'un périphérique mobile est disponible sous le nom de Silverlight. La version 3.0 du framework est intégrée à Windows Vista et à la plupart des versions de Windows Server 2008 ou téléchargeable depuis le site de l'éditeur Microsoft. La version 4.5.1 du framework est intégrée à Windows 8. La version 4.6 est intégrée à Windows 10. L'infrastructure de développement .NET framework s'appuie sur la norme Common Language Infrastructure (CLI) qui est indépendante du langage de programmation utilisé. Ainsi tous les langages compatibles respectant la norme CLI ont accès à toutes les bibliothèques installées (installables) dans l'environnement d'exécution. Le cadriciel .NET framework e

Source officielle

https://fr.wikipedia.org/wiki/.NET_Framework

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This course covers methods for the analysis and control of systems with multiple inputs and outputs, which are ubiquitous in modern technology and industry. Special emphasis will be given to discrete-time systems, due to their relevance for digital and embedded control architectures.

This course gives an introduction to the fundamental concepts and methods of the Digital Humanities, both from a theoretical and applied point of view. The course introduces the Digital Humanities circle of processing and interpretation, from data acquisition to new understandings.

The course will discuss classic material as well as recent advances in computer vision and machine learning relevant to processing visual data with a primary focus on embodied intelligence and vision for active agents.

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Séances de cours associées (28)

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Publications associées (100)

The development of robot motion planning algorithms is inherently a challenging task. This is more than ever true when the latest trends in motion planning are considered. Some motion planners can deal with kinematic and dynamic constraints induced by the mechanical structure of the robot. Another class of motion planners fulfill various types of optimality conditions, yet others include means of dealing with uncertainty about the robot and its environment. Sensor-based motion planners gather information typically afflicted with errors about a partially known environment in order to plan a trajectory therein. In another research area it is investigated how multiple robots best cooperate to solve a common task. In order to deal with the complexity of developing motion planning algorithms, it is proposed in this document to resort to a simulation environment. The advantages of doing so are outlined and a system named Ibex presented which is well suited to support motion planner development. The developed framework makes use of rigid body dynamics algorithms as simulation kernel. Further, various components are included which integrate the simulation into existing engineering environments. Simulation content can be conveniently developed through extensions of well-established 3D modelling tools. The co-simulation with components from other domains of physics is provided by the integration into a leading dynamic modelling environment. Robotic actuator models can be combined with a rigid body dynamics simulation using this mechanism. The same configuration also allows to conveniently develop control algorithms for a rigid body dynamics setup and offers powerful tools for handling and analysing simulation data. The developed simulation framework also offers physics-based models for simulating various sensors, most prominently a model for sensor types based on wave propagation, such as laser range finding devices. Application examples of the simulation framework are presented from the mobile robotics rough-terrain motion planning domain. Three novel rough-terrain planning algorithms are presented which are extensions of known approaches. To quantify the navigational difficulty on rough terrain, a new generic measure named "obstacleness" is proposed which forms the basis of the proposed algorithms. The first algorithm is based on Randomised Potential Field Planners (RPP) and consequently is a local algorithm. The second proposed planner extends RRTconnect , a bi-directional Rapidly Exploring Random Tree (RRT) algorithm and biases exploration of the search space towards easily traversable regions. The third planner is an extension of the second approach and uses the same heuristic to grow a series of additional local RRTs. This allows it to plan trajectories through complex distributions of navigational difficulty benefitting from easy regions throughout the motion plan. A complete example is shown in which the proposed algorithms form the basis for sensor-based dynamic re-planning simulated in the presented framework. In the scenario, a simulated planetary rover navigates a long distance over rough terrain while gathering sensor data about the terrain topography. Where obstacles are sensed which interfere with the original motion plan, dynamic re-planning routines are applied to circumnavigate the hindrances. In the course of this document a complete simulation environment is presented by means of a theoretical background and application examples which can significantly support the development of robot motion planning algorithms. The framework is capable of simulating setups which fulfil the requirements posed by stateof-the-art motion planning algorithm development.

EPFL2006

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Architectural Sampling: A Formal Basis for Machine-Learnable Architecture

Immanuel Chee Beng Koh

The spatial and formal conception of architecture, and thus its modes of design perception and representation, directly contributes to its machine-learnability; and consequently, its capacity in leveraging today's machine learning apparatus for design innovation. If text can be sampled and synthesized in Natural Language Processing, image in Image Processing and sound in Audio Signal Processing, how can architectural forms and spaces be likewise sampled for generating new designs? The thesis endeavours to construct such a theoretical and technical framework with the concept of architectural sampling -- defined as the exemplar-learning (pedagogical), the machinic encoding (technological) and probabilistic generation (aesthetical) of architectural forms. Foundational to this technical leap is the overcoming of architecture's own longstanding set of conceptual and perceptual assumptions, namely figure/ground, parts/whole and shapes/grammars; and replaced with one that is ontologically 'flattened', 'resolutional' and 'probabilistic'. The thesis samples precursory works from the history of architecture, alongside machine learning approaches, to build its theoretical claims; while algorithmically demonstrating and technically validating them through a series of design research projects organized according to their structural characteristics (grid, sequence and hierarchy). The contribution of the work lies in its fundamental reformulation of seeing, thinking and making architectural forms through the lens of machinic sampling.

EPFL2019

Chargement

Ergonomic Simulation Revisited Using Parametric Virtual Humans in the Biomechanical Framework

Hareesh Puthiya Veettil

The conventional CAD/CAM approach to design does not show the essential spatial relationships between user and product that are crucial for intuitive design analysis. As populations age and the home appliance market stagnates, Universal Design principles implemented with computerized virtual worlds become more important for meeting the ergonomic problems of heterogeneous populations that are increasingly difficult to adequately test with real-world subjects. Digital Human Modelling (DHM) is an emerging area that bridges computer-aided engineering design, human factors engineering and applied ergonomics. The most advanced forms of this technology are being used by many researchers for practical applications, including ergonomic analysis. However, a state of the art model of this technology has never been conceived for the conceptual design stage of a product development cycle as most conventional DHM techniques lack real time interaction, require considerable user intervention, and have inefficient control facilities and non-adequate validation techniques, all contributing to slow production pipelines. They have also not addressed the needs of the growing ageing population in many societies across the globe. The focus of this dissertation is to introduce a complete framework for ergonomic simulation at the conceptual design stage of a product development cycle based on parametric virtual humans in a prioritized inverse kinematics framework while taking biomechanical knowledge in to account. Using an intuitive control facility, design engineers can input a simple CAD model, design variables and human factors in to the system. The evaluation engine generates the required simulation in real-time by making use of an Anthropometric Database, Physical Characteristic Database and Prioritized Inverse Kinematics architecture. The key components of the total system are described and the results are demonstrated with a few applications such as kitchen, wash-basin and bath-tub. By introducing a quantitative estimation of ageing algorithm for anthropometric digital human models, products can be designed from the start to suit the ergonomic needs of the user rather than the biases and assumptions of the designer. Also, by creating a tool that can be used intuitively by non-specialists in a dynamic, real-time environment, designers can stop relying on specialists to test the safety of their ideas and start to effectively use data about populations to discover designs that can be used more easily by more people. Results have been validated with real human subjects indicating the practical implication of the total system as an ergonomic design tool for the conceptual design stage of a product development cycle.

EPFL2011

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EPFL2006

Ergonomic Simulation Revisited Using Parametric Virtual Humans in the Biomechanical Framework

Hareesh Puthiya Veettil

EPFL2011