The Rosario Dataset: Multisensor Data for Localization and Mapping in Agricultural Environments
This dataset provides a benchmark for agricultural SLAM and sensor fusion research, but it is incremental as it adds to existing datasets in the field.
The authors introduced The Rosario Dataset, a collection of multisensor data from a mobile robot in soybean fields, addressing the lack of realistic agricultural sensor data for robotics. The dataset includes 6 sequences with challenging conditions like repetitive scenes and sunlight issues, and it is publicly available for research.
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 6 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 SLAM/odometry and sensor fusion research. It contains synchronized readings of several sensors: wheel odometry, IMU, stereo camera and a GPS-RTK system. The dataset is publicly available in http://www.cifasis-conicet.gov.ar/robot/.