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Your search keyword '"specific hardware"' showing total 4 results
Start Over Descriptor "specific hardware" Topic computer science
4 results on '"specific hardware"'

1. Automatized Switchgear Wiring: An Outline of the WIRES Experiment Results

Author

Riccardo Zanella, Maurizio Indovini, Claudio Melchiorri, Gianluca Palli, Daniele De Gregorio, Salvatore Pirozzi, Palli G., Pirozzi S., Indovini M., De Gregorio D., Zanella R., Melchiorri C., Antoni Grau • Yannick Morel • Ana Puig-Pey • Francesca Cecchi, Palli, G., Pirozzi, S., Indovini, M., De Gregorio, D., Zanella, R., and Melchiorri, C.

Subjects
Computer vision system, Manipulation task, Computer science, business.industry, Specific hardware, Robot end effector, Pipeline (software), Switchgear, Task (project management), law.invention, Software, law, Deformable linear object, Electric screwdriver, Hardware_INTEGRATEDCIRCUITS, Robot, Wire manipulation, Routing (electronic design automation), business, Tactile sensor, Computer hardware, Occlusion problem, Electromechanical component
Abstract

This chapter reports an overview of the experience and the results achieved during the development of the robotized system for switchgear wiring carried out in the WIRES experiment. This specific application is particularly challenging for a robotic system due to the complexity of the manipulation task. As a matter of fact, in this task deformable linear objects, such as electric wires, are involved. Moreover, the precision requested during the assembly task and the typical crowded space inside the switchgear imply, on one side, the development of specific hardware and software tools and, on the other side, high adaptability and flexibility of the robotic system. In the WIRES experiment, a software package to extract the wiring information and to generate the robot task sequence directly from the switchgear CAD files has been developed. Additionally, a computer vision system able to recognize the location of the wires and of the electromechanical components inside the switchgear has been developed. To deal with the wire deformability and occlusion problems during the wire insertion, machine learning and sensor fusion techniques have been adopted to enable the wire manipulation by means of tactile sensors and 2D cameras feedback. From the hardware point of view, a specific end effector has been developed to manipulate and connect the wire to the components. This end effector is equipped with an electric screwdriver and a customized tactile sensor used to evaluate the wire shape, the wire end pose and its interaction with the environment during the manipulation. The entire task pipeline, going from the switchgear information extraction, to the wire grasp and manipulation, its connection and the routing along the desired wire path is presented in this chapter. The preliminary experimental results show that the developed system can achieve a success rate of about 95% in the wire insertion and connection task.

Published
2020

2. Bayesian time-domain multiple sound source localization for a stochastic machine

Author

Emmanuel Mazer, Laurent Girin, Marvin Faix, Raphael Frisch, Jacques Droulez, Techniques of Informatics and Microelectronics for integrated systems Architecture (TIMA), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Interaction située avec les objets et environnements intelligents (PERVASIVE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'Informatique de Grenoble (LIG), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Institut des Systèmes Intelligents et de Robotique (ISIR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CRISSP (GIPSA-CRISSP), Département Parole et Cognition (GIPSA-DPC), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-GIPSA Pôle Parole et Cognition (GIPSA-PPC), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Stendhal - Grenoble 3-Université Joseph Fourier - Grenoble 1 (UJF)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Techniques de l'Informatique et de la Microélectronique pour l'Architecture des systèmes intégrés (TIMA), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'Informatique de Grenoble (LIG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), GIPSA - Cognitive Robotics, Interactive Systems, & Speech Processing (GIPSA-CRISSP), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])

Subjects
[INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR], Signal processing, Computer science, Bayesian probability, 020206 networking & telecommunications, Statistical model, specific hardware, 02 engineering and technology, Acoustic source localization, Bayesian stochastic machine, time-domain processing, Bayesian inference, Robustness (computer science), [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD], 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Multiple sound source localization, Time domain, Algorithm, ComputingMilieux_MISCELLANEOUS
Abstract

We propose a time-domain multiple sound source localization (SSL) method based on Bayesian inference. This method is specifically designed to run on the stochastic machines (SM) that we are currently developing to perform efficient low-level sensor signal processing with ultra-low power consumption. The proposed SSL method is divided into two main parts. First, a probabilistic model is run on 50 very short time frames (3. 75ms each) of multichannel recorded signals. Second, the results obtained on the different frames are fused to obtain a final localization map. Using the system in a supervised way allows to extract estimated source locations by selecting as many maxima as there are sources in the room. We explain how this method is implemented on a SM. Experiments are presented to illustrate the performance and robustness of the resulting system.

Published
2019
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3. Fuzzy markup language: A new solution for transparent intelligent agents

Author

Vincenzo Loia, Giovanni Acampora, Acampora, Giovanni, Loia, Vincenzo, and Information Systems IE&IS

Subjects
Fuzzy markup language, Exploit, Virtual organization, Fuzzy Control Language, Computer science, System controller, Virtual organization, Computer hardware, Fuzzy control, computer.software_genre, Development proce, High level language, Controller, Markup languages, Intelligent agents, Intelligent agent, Development time, computer.programming_language, Structure (mathematical logic), Programming language, Multi-agent system, Specific hardware, Hardware constraint, Fuzzy control system, New solution, Application problem, Computer language, computer
Abstract

From an industrial and technological point of view, fuzzy control theory deals with the development of a particular system controller on a specific hardware by means of an open or legacy programming language that is useful to address, in a high-level fashion, the hardware constraints. Independently from the complexity of the addressed application problem, the development time may be very expensive if the designers want to exploit the possibility to collect different controllers in terms of an active, cooperative and heterogeneous virtual organization. In order to bridge this gap, we introduce the Fuzzy Markup Language (FML), a novel specific-purpose computer language that defines a detailed structure of fuzzy control independent from its legacy representation. This choice allows systems' designers to to express their ideas in fast and simple way and, as a consequence, speeds up the whole development process of a given complex system. © 2011 IEEE.

Published
2011

4. Real-time task reconfiguration support applied to an UAV-based surveillance system

Author

Carlos Eduardo Pereira, A. Stork, Tony Larsson, Alécio Pedro Delazari Binotto, and E.P. de Freitas

Subjects
Specific tasks, Re-configurable, Computer science, High-performance platforms, Design phase, Radar image processing, Remotely operated underwater vehicle, Task (project management), Non-functional, Teknik och teknologier, Resource allocation (computer), High-performance computers, Load-Balancing, Computational resources, Flexibility (engineering), Heterogeneous clusters, business.industry, Reconfigurable computing, Specific hardware, Workload balancing, Control reconfiguration, Mobile robot, Workload, Surveillance systems, System platforms, Run-time reconfigurable, Embedded system, Engineering and Technology, Aspect-oriented, Time requirements, business, Real-time tasks, Reconfiguration requirement, Resource information, Task allocation
Abstract

Modern surveillance systems, such as those based on the use of Unmanned Aerial Vehicles, require powerful high- performance platforms to deal with many different algorithms that make use of massive calculations. At the same time, low- cost and high-performance specific hardware (e.g., GPU, PPU) are rising and the CPUs turned to multiple cores, characteriz- ing together an interesting and powerful heterogeneous execu- tion platform. Therefore, reconfigurable computing is a poten- tial paradigm for those scenarios as it can provide flexibility to explore the computational resources on heterogeneous cluster attached to a high-performance computer system platform. As the first step towards a run-time reconfigurable workload bal- ancing framework targeting that kind of platform, application time requirements and its crosscutting behavior play an impor- tant role for task allocation decisions. This paper presents a strategy to reallocate specific tasks in a surveillance system composed by a fleet of Unmanned Aerial Vehicles using aspect- oriented paradigms in order to address non-functional applica- tion timing constraints in the design phase. An aspect support from a framework called DERAF is used to support reconfigu- ration requirements and provide the resource information needed by the reconfigurable load-balancing strategy. Finally, for the case study, a special attention on Radar Image Process- ing will be given.

Published
2008

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