Visual-aid positioning using point cloud compression and RGB-D cameras for robotic manipulators

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dc.contributor.authorCisternas Velásquez, Estefan Iván
dc.contributor.authorDel Río Caldumbide, Julio Andrés
dc.contributor.authorPrado Romo, Álvaro Javier
dc.contributor.authorMenéndez Granizo, Oswaldo Aníbal
dc.date.accessioned2025-04-08T00:57:44Z
dc.date.available2025-04-08T00:57:44Z
dc.date.issued2023
dc.descriptionIndexación: Scopus.
dc.description.abstractOver the last decade, optimization of a massive set of industrial tasks has been achieved by taking advantage of repeatability and precision of robotic arms. While the new era of robotic arms introduces high-tech tools to fix positioning and tracking issues, upgrading older units is a significant challenge due to hardware incompatibilities, outdated mechanisms, and operation restrictions. This work introduces a new visual system to determine the position of a robotic arm using a two-stereo-cameras array. The visual-positioning system estimates the position of the end-effector using an inverse model of the robot and the full point cloud acquired with the stereo cameras. An Iterative Point Cloud algorithm merges the partial point clouds of each depth sensor, and with a yellow color detector, the algorithm extracts the Region of Interest (ROI). Experimental results show that the proposed device can estimate the relative position of the end-effector with respect to the robotic arm base with errors in the longitudinal, lateral, and vertical positions of around 19.6%, 15.7% and 9.2%, respectively. © 2023, Universidad de Tarapaca. All rights reserved
dc.description.urihttps://www.scielo.cl/pdf/ingeniare/v31/0718-3305-ingeniare-31-16.pdf
dc.identifier.doi10.4067/s0718-33052023000100216
dc.identifier.issn07183291
dc.identifier.urihttps://repositorio.unab.cl/handle/ria/64007
dc.language.isoen
dc.publisherIngeniare, Volume 312023 Article number 16
dc.rights.licenseAttribution 4.0 International CC BY 4.0 Deed
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectComputer vision
dc.subjectmachine learning
dc.subjectpoint cloud compression
dc.subjectrobotic manipulators
dc.subjectstereo vision
dc.titleVisual-aid positioning using point cloud compression and RGB-D cameras for robotic manipulators
dc.typeArtículo
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