Articles producció científica> Enginyeria Informàtica i Matemàtiques

Online human assisted and cooperative pose estimation of 2D cameras

  • Identification data

    Identifier: imarina:5633353
    Authors:
    Manzo, GaetanoSerratosa, FrancescVento, Mario
    Abstract:
    © 2016 Elsevier B.V. All rights reserved. Autonomous robots performing cooperative tasks need to know the relative pose of the other robots in the fleet. Deducing these poses might be performed through structure from motion methods in the applications where there are no landmarks or GPS, for instance, in non-explored indoor environments. Structure from motion is a technique that deduces the pose of cameras only given only the 2D images. This technique relies on a first step that obtains a correspondence between salient points of images. For this reason, the weakness of this method is that poses cannot be estimated if a proper correspondence is not obtained due to low quality of the images or images that do not share enough salient points. We propose, for the first time, an interactive structure-from-motion method to deduce the pose of 2D cameras. Autonomous robots with embedded cameras have to stop when they cannot deduce their position because the structure-from-motion method fails. In these cases, a human interacts by simply mapping a pair of points in the robots' images. Performing this action the human imposes the correct correspondence between them. Then, the interactive structure from motion is capable of deducing the robots' lost positions and the fleet of robots can continue their high level task. From the practical point of view, the interactive method allows the whole system to achieve more complex tasks in more complex environments since the human interaction can be seen as a recovering or a reset process.
  • Others:

    Author, as appears in the article.: Manzo, Gaetano; Serratosa, Francesc; Vento, Mario
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: Serratosa Casanelles, Francesc d'Assís
    Keywords: Structure from motion Spect Social robots Robots Robot cooperation Mri Image registration Human-robot interaction Framework Features Computation Brisk Alignment Algorithm 2d pose estimation
    Abstract: © 2016 Elsevier B.V. All rights reserved. Autonomous robots performing cooperative tasks need to know the relative pose of the other robots in the fleet. Deducing these poses might be performed through structure from motion methods in the applications where there are no landmarks or GPS, for instance, in non-explored indoor environments. Structure from motion is a technique that deduces the pose of cameras only given only the 2D images. This technique relies on a first step that obtains a correspondence between salient points of images. For this reason, the weakness of this method is that poses cannot be estimated if a proper correspondence is not obtained due to low quality of the images or images that do not share enough salient points. We propose, for the first time, an interactive structure-from-motion method to deduce the pose of 2D cameras. Autonomous robots with embedded cameras have to stop when they cannot deduce their position because the structure-from-motion method fails. In these cases, a human interacts by simply mapping a pair of points in the robots' images. Performing this action the human imposes the correct correspondence between them. Then, the interactive structure from motion is capable of deducing the robots' lost positions and the fleet of robots can continue their high level task. From the practical point of view, the interactive method allows the whole system to achieve more complex tasks in more complex environments since the human interaction can be seen as a recovering or a reset process.
    Thematic Areas: Química Operations research & management science Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Interdisciplinar Geociências General engineering Farmacia Engineering, electrical & electronic Engineering (miscellaneous) Engineering (all) Engenharias iv Engenharias iii Engenharias ii Engenharias i Enfermagem Educação Economia Direito Computer science, artificial intelligence Computer science applications Ciências sociais aplicadas i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência da computação Biotecnología Biodiversidade Astronomia / física Artificial intelligence Arquitetura, urbanismo e design Administração, ciências contábeis e turismo Administração pública e de empresas, ciências contábeis e turismo
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: francesc.serratosa@urv.cat
    Author identifier: 0000-0001-6112-5913
    Record's date: 2024-10-12
    Papper version: info:eu-repo/semantics/acceptedVersion
    Link to the original source: https://www.sciencedirect.com/science/article/pii/S0957417416302305?via%3Dihub
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Expert Systems With Applications. 60 258-268
    APA: Manzo, Gaetano; Serratosa, Francesc; Vento, Mario (2016). Online human assisted and cooperative pose estimation of 2D cameras. Expert Systems With Applications, 60(), 258-268. DOI: 10.1016/j.eswa.2016.05.012
    Article's DOI: 10.1016/j.eswa.2016.05.012
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2016
    Publication Type: Journal Publications
  • Keywords:

    Artificial Intelligence,Computer Science Applications,Computer Science, Artificial Intelligence,Engineering (Miscellaneous),Engineering, Electrical & Electronic,Operations Research & Management Science
    Structure from motion
    Spect
    Social robots
    Robots
    Robot cooperation
    Mri
    Image registration
    Human-robot interaction
    Framework
    Features
    Computation
    Brisk
    Alignment
    Algorithm
    2d pose estimation
    Química
    Operations research & management science
    Medicina iii
    Medicina ii
    Medicina i
    Materiais
    Matemática / probabilidade e estatística
    Interdisciplinar
    Geociências
    General engineering
    Farmacia
    Engineering, electrical & electronic
    Engineering (miscellaneous)
    Engineering (all)
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Enfermagem
    Educação
    Economia
    Direito
    Computer science, artificial intelligence
    Computer science applications
    Ciências sociais aplicadas i
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência da computação
    Biotecnología
    Biodiversidade
    Astronomia / física
    Artificial intelligence
    Arquitetura, urbanismo e design
    Administração, ciências contábeis e turismo
    Administração pública e de empresas, ciências contábeis e turismo
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