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Detail publikačního výsledku
LIGOCKI, A.; ŽALUD, L.; JELÍNEK, A.
Originální název
Brno Urban Dataset - The New Data for Self-Driving Agents and Mapping Tasks
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
Autonomous driving is a dynamically growing field of research, where quality and amount of experimental data is critical. Although several rich datasets are available these days, the demands of researchers and technical possibilities are evolving. Through this paper, we bring a new dataset recorded in Brno, Czech Republic. It offers data from four WUXGA cameras, two 3D LiDARs, inertial measurement unit, infrared camera and especially differential RTK GNSS receiver with centimetre accuracy which, to the best knowledge of the authors, is not available from any other public dataset so far. In addition, all the data are precisely timestamped with sub-millisecond precision to allow wider range of applications. At the time of publishing of this paper, recordings of more than 350 km of rides in varying environment are shared at: https: //github.com/RoboticsBUT/Brno-Urban-Dataset.
Anglický abstrakt
Klíčová slova
dataset, mapping, self driving car, rgb camera, thermal camera, lidar, imu, rtk gnss
Klíčová slova v angličtině
Autoři
Rok RIV
2021
Vydáno
01.06.2020
Nakladatel
IEEE
ISBN
978-1-7281-7395-5
Kniha
Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA)
Strany od
3284
Strany do
3290
Strany počet
8
URL
https://ieeexplore.ieee.org/document/9197277
Plný text v Digitální knihovně
http://hdl.handle.net/11012/195617
BibTex
@inproceedings{BUT164210, author="Adam {Ligocki} and Luděk {Žalud} and Aleš {Jelínek}", title="Brno Urban Dataset - The New Data for Self-Driving Agents and Mapping Tasks", booktitle="Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA)", year="2020", pages="3284--3290", publisher="IEEE", doi="10.1109/ICRA40945.2020.9197277", isbn="978-1-7281-7395-5", url="https://ieeexplore.ieee.org/document/9197277" }
Dokumenty
ICRA2020_paper9197277-accepted