The Rosario dataset: Multisensor data for localization and mapping in agricultural environments

Pire, T. ; Mujica, M. ; Civera, J. (Universidad de Zaragoza) ; Kofman, E.

Resumen: In this paper we present the Rosario dataset, a collection of sensor data for autonomous mobile robotics in agricultural scenes. The dataset is motivated by the lack of realistic sensor readings gathered by a mobile robot in such environments. It consists of six sequences recorded in soybean fields showing real and challenging cases: highly repetitive scenes, reflection, and burned images caused by direct sunlight and rough terrain among others. The dataset was conceived in order to provide a benchmark and contribute to the agricultural simultaneous localization and mapping (SLAM)/odometry and sensor fusion research. It contains synchronized readings of several sensors: wheel odometry, inertial measurement unit (IMU), stereo camera, and a Global Positioning System real-time kinematics (GPS-RTK) system. The dataset is publicly available from http://www.cifasis-conicet.gov.ar/robot/.

Idioma: Inglés

DOI: 10.1177/0278364919841437

Año: 2019

Publicado en: International Journal of Robotics Research 38, 6 (2019), 633 - 641
ISSN: 0278-3649

Factor impacto JCR: 4.703 (2019)

Categ. JCR: ROBOTICS rank: 5 / 28 = 0.179 (2019) - Q1 - T1

Factor impacto SCIMAGO: 3.212 - Applied Mathematics (Q1) - Artificial Intelligence (Q1) - Software (Q1) - Mechanical Engineering (Q1) - Modeling and Simulation (Q1) - Electrical and Electronic Engineering (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/T45-17R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2015-67275

Tipo y forma: Artículo (PostPrint)

Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)