The International Journal of Robotics Research · 2019 · 85 citations · 30 references
Precision AgricultureEngineeringMultisensor DataLand UseAgricultural RobotField RoboticsAgricultural EconomicsAgricultural RoboticsLocalizationSocial SciencesMappingGeospatial MappingSensor FusionCartographyMachine VisionSensor DataVision RoboticsGeographySpatial Data AcquisitionVehicle LocalizationAgricultural EnvironmentsAutonomous NavigationRosario DatasetComputer VisionLand Cover MapOdometryAgricultural ScenesRemote SensingRoboticsGeospatial Data
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/ .
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