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dc.contributor.author
Pire, Taihú Aguará Nahuel
dc.contributor.author
Baravalle, Rodrigo Guillermo
dc.contributor.author
D'alessandro, Ariel
dc.contributor.author
Civera Sancho, Javier
dc.date.available
2020-01-08T20:33:15Z
dc.date.issued
2018-10
dc.identifier.citation
Pire, Taihú Aguará Nahuel; Baravalle, Rodrigo Guillermo; D'alessandro, Ariel; Civera Sancho, Javier; Real-time dense map fusion for stereo SLAM; Cambridge University Press; Robotica; 36; 10; 10-2018; 1510-1526
dc.identifier.issn
0263-5747
dc.identifier.uri
http://hdl.handle.net/11336/94018
dc.description.abstract
A robot should be able to estimate an accurate and dense 3D model of its environment (a map), along with its pose relative to it, all of it in real time, in order to be able to navigate autonomously without collisions. As the robot moves from its starting position and the estimated map grows, the computational and memory footprint of a dense 3D map increases and might exceed the robot capabilities in a short time. However, a global map is still needed to maintain its consistency and plan for distant goals, possibly out of the robot field of view. In this work, we address such problem by proposing a real-time stereo mapping pipeline, feasible for standard CPUs, which is locally dense and globally sparse and accurate. Our algorithm is based on a graph relating poses and salient visual points, in order to maintain a long-term accuracy with a small cost. Within such framework, we propose an efficient dense fusion of several stereo depths in the locality of the current robot pose. We evaluate the performance and the accuracy of our algorithm in the public datasets of Tsukuba and KITTI, and demonstrate that it outperforms single-view stereo depth. We release the code as open-source, in order to facilitate the system use and comparisons.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Cambridge University Press
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
DENSE MAPPING
dc.subject
STEREO VISION
dc.subject
VISUAL SLAM
dc.subject.classification
Control Automático y Robótica
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Real-time dense map fusion for stereo SLAM
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-10-17T14:55:21Z
dc.journal.volume
36
dc.journal.number
10
dc.journal.pagination
1510-1526
dc.journal.pais
Reino Unido
dc.journal.ciudad
Cambridge
dc.description.fil
Fil: Pire, Taihú Aguará Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
dc.description.fil
Fil: Baravalle, Rodrigo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
dc.description.fil
Fil: D'Alessandro, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina
dc.description.fil
Fil: Civera, Javier. Universidad de Zaragoza; España
dc.journal.title
Robotica
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1017/S0263574718000528
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.cambridge.org/core/journals/robotica/article/realtime-dense-map-fusion-for-stereo-slam/0A200FD65A1614E712954184E930D745
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