Autor segons l'article: Manzo G; Serratosa F; Vento M
Departament: Enginyeria Informàtica i Matemàtiques
Autor/s de la URV: Serratosa Casanelles, Francesc d'Assís
Paraules clau: Structure from motion Spect Social robots Robots Robot cooperation Mri Image registration Human-robot interaction Framework Features Computation Brisk Alignment Algorithm 2d pose estimation
Resum: © 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.
Àrees temàtiques: 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
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: francesc.serratosa@urv.cat
Identificador de l'autor: 0000-0001-6112-5913
Data d'alta del registre: 2023-02-18
Versió de l'article dipositat: info:eu-repo/semantics/acceptedVersion
Enllaç font original: https://www.sciencedirect.com/science/article/pii/S0957417416302305?via%3Dihub
Referència a l'article segons font original: Expert Systems With Applications. 60 258-268
Referència de l'ítem segons les normes APA: Manzo G; Serratosa F; Vento M (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
URL Document de llicència: http://repositori.urv.cat/ca/proteccio-de-dades/
DOI de l'article: 10.1016/j.eswa.2016.05.012
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2016
Tipus de publicació: Journal Publications
Repositori URV