%0 Journal Article
%T The Rosario dataset: Multisensor data for localization and mapping in agricultural environments
%A Ernesto Kofman
%A Javier Civera
%A Mart¨Ēn Mujica
%A Taih¨˛ Pire
%J The International Journal of Robotics Research
%@ 1741-3176
%D 2019
%R 10.1177/0278364919841437
%X 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/
%K Precision agriculture
%K SLAM
%K agricultural robotics
%U https://journals.sagepub.com/doi/full/10.1177/0278364919841437