Artículos y presentaciones en Congresos

URI https://digital.cic.gba.gob.ar/handle/11746/1637

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  • Artículo
    Acceso Abierto
    ECOPAMPA: A new tool for automatic fish schools detection and assessment from echo data
    (2021) Villar, Sebastián; Madirolas, Adrián; Cabreira, Ariel; Rozenfeld, Alejandro F.; Acosta, Gerardo G.
    Accurate identification of aquatic organisms and their numerical abundance calculation using echo detection techniques remains a great challenge for marine researchers. A software architecture for echo data processing is presented in this article. Within it, it is discussed how to obtain energetic, morphometric and bathymetric fish school descriptors to accurately identify different fish-species. To accomplish this task it was necessary to have a development platform that allowed reading echo data from a particular echosounder, to detect fish aggregations and then to calculate fish school descriptors that would be used for fish-species identification, in an automatic way. This article also describes thoroughly the digital processing algorithms for this automatic detection and classification, as well as the automatic process required for surface and bottom line detection, which is necessary to determine the exploration range. These algorithms are implemented within the ECOPAMPA software, which is the first Argentinean system for marine species identification. Finally, a comparative result over experimental data of ECOPAMPA against EchoviewTM Software Pty Ltd (formerly Myriax Software Pty Ltd), is carefully examined.
  • Documento de conferencia
    Acceso Abierto
    Optimización y control del flujo de materiales en procesos de producción flexibles utilizando aprendizaje profundo
    (2021) Saavedra Sueldo, Carolina; Perez Colo, Ivo; De Paula, Mariano; Villar, Sebastián; Acosta, Gerardo G.
    Industry 4.0, currently on the rise, demandsincreasing flexibility and adaptation of production systems tochanging products demands and external factors. The adaptationof the production systems implies frequent and often abruptchanges in the configurations of the shop floors and consequentlythe movement of materials must be re-planned. Materialhandlingis significant in terms of operative costs and times and it doesnot add value to the end products. It is desired to optimize theperformance of the system based onthe degree of movements,buffer usage and waiting times, such that the combinationof these minimizes the impact on the process costs. Machinelearning algorithms incombination with powerful computationalsimulators can be mutually leveraged to give rise to solvethese kinds of real-world problems, typical of smart factories.In this work, for the optimization approach, we develop aclosed-loop decision-making system with a deep reinforcementlearning algorithm based on a discrete-event simulation modelfor material handling. In addition, our proposed approach usesthe communication architecture Simulai, which allows interfacinga computational discrete-event simulator and the proposed deep learning-based decision-making algorithm. The functionality ofour proposal is evidenced through the obtained results and anoptimal solution for the problem stated is reached, proving thatan intelligent agentcan collaborate in making multiple decisionsfor smart factories.
  • Documento de conferencia
    Acceso Abierto
    A robust version of the Lee filter for speckle reduction and contrast enhancement applied to side scan sonar images
    (2020) Ferraggine, Viviana; Villar, Sebastián
    Sonar images are typically affected by a granular pattern interference known as speckle noise, which degrades image contrast. To aid in object detection and recognition for speckled imagery, a robust version of the Lee filter is presented. The new method essentially combines robust statistics with an adaptive approach to achieve an effective balance between contrast stretching and speckle reduction. Tests were performed on real sonar images, where objective metrics and direct visual perception were used to evaluate the results. Experiments have shown that this easy-to-implement filter remarkably highlights edges and details with apparent speckle reduction, offering a promising simple tool that may be useful in segmentation and classification applications.
  • Artículo
    Acceso Abierto
    Particle Filter based Autonomous Underwater Vehicle Navigation System aided thru acoustic communication ranging
    (2020) Menna, Bruno V.; Villar, Sebastián; Acosta, Gerardo G.
    Autonomous Underwater Vehicles (AUVs) are platforms suitable for a wide variety of applications in the marine environment with economic and operational advantages. In these applications an AUV performs a given task as a mission. During the mission execution, the AUV will move around the environment following paths that allow it to fulfill the mission's objectives. To achieve this, a reliable Navigation System (NS) is required. In addition to this, the current operating concept includes the deployment of multiple AUVs on a given area, thus a communication system between vehicles is also required. In the underwater environment both navigation and communication systems deals with the particular characteristics of the medium that limits the use of conventional techniques. In this work, a complete NS for an AUV is presented. The developed NS is based on an inertial navigation scheme with velocity and position aiding. The position aiding takes advantage of the communication system onboard the vehicle, which avoids the use of additional positioning systems. The fundamentals of the applied solutions are described and experimental results and implementation details are provided. Also conclusions and future works are presented.
  • Documento de conferencia
    Acceso Abierto
    Integración de ROS y Tecnomatix para el desarrollo de gemelos digitales en sistemas de manufactura flexible
    (2020) Saavedra Sueldo, Carolina; Villar, Sebastián; De Paula, Mariano; Urrutia, Silvia B.; Acosta, Gerardo G.
    Los gemelos digitales emplean la simulación en conjunto con una variedad de datos provenientes de diferentes equipos y sistemas físicos de planta, para mantener actualizados continuamente sus modelos digitales del mundo en un esquema de retroalimentación en un entorno virtual que facilita la toma de decisiones. La heterogeneidad de hardware y software existente requiere del desarrollo de arquitecturas de software para que los diversos componentes se integren e interactúen mediante el intercambio de información. En este trabajo se propone el diseño y construcción de una arquitectura de software que integra un simulador de procesos de manufactura con el sistema operativo de robots (ROSRobot Operating System). La propuesta se prueba con el simulador Tecnomatix de Siemens® y la distribución libre ROS Melodic. Se presenta una instancia de la arquitectura de software para un caso de estudio complejo típico de plantas de manufactura y se demuestra su fácil integración con un sistema autónomo de toma de decisiones.