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Titel:

OGM2PGBM

Dokumenttyp:
Forschungsdaten
Veröffentlichungsdatum:
29.07.2024
Verantwortlich:
Vega-Torres, Miguel A.
Autorinnen / Autoren:
Vega-Torres, Miguel A.; Braun, Alexander; Borrmann, André
Institutionszugehörigkeit:
TUM
Herausgeber:
TUM
Identifikator:
doi:10.14459/2024mp1749236
Enddatum der Datenerzeugung:
01.08.2022
Fachgebiet:
BAU Bauingenieurwesen, Vermessungswesen; DAT Datenverarbeitung, Informatik; TEC Technik, Ingenieurwissenschaften (allgemein)
Quellen der Daten:
Simulationen / simulations; Abbildungen von Objekten / image of objects
Datentyp:
Bilder / images ; mehrdimensionale Visualisierungen oder Modelle / models
Anderer Datentyp:
ROS Bag files (ROS1); 2D Occupancy grid maps in .pgm format with their respective .yaml file; 3D map in .obj format.
Methode der Datenerhebung:
The dataset was generated using the Gazebo simulation engine, simulating the properties of the RS-16 3D LiDAR.
Beschreibung:
The OGM2PGBM TUM CMS LiDAR long-term indoor localization dataset comprises raw LiDAR scan data simulated on a model of the offices at the Technical University of Munich, along with their corresponding 3D and 2D reference maps. The datasets were meticulously created using the Gazebo simulation engine, ensuring complete coverage of the space, as described in this paper
The dataset consists of six sequences, simulated in three different environments. Each environment introduces varying lev...     »
Links:
Related publication: https://doi.org/10.48550/arXiv.2308.05443
Schlagworte:
LiDAR; Localization; SLAM; OGM; BIM
Technische Hinweise:
View and download (31,2 GB total, 11 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1749236):
rsync rsync://m1749236@dataserv.ub.tum.de/m1749236/
Sprache:
en
Rechte:
by-nc, http://creativecommons.org/licenses/by-nc/4.0
Horizon 2020:
INTREPID Horizon 2020 Grant agreement ID: 883345
 BibTeX