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

Author:

Pire Taihú1ORCID,Mujica Martín1,Civera Javier2,Kofman Ernesto1

Affiliation:

1. CIFASIS, French Argentine International Center for Information and Systems Sciences (CONICET-UNR), Argentina

2. I3A, University of Zaragoza, Spain

Abstract

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/ .

Funder

gobierno de aragón

Gobierno Español

Consejo Nacional de Investigaciones Científicas y Técnicas

Publisher

SAGE Publications

Subject

Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modelling and Simulation,Software

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