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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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Taihú Pire
Consejo Nacional de Investigaciones Científicas y Técnicas
Martín Mujica
Centre National de la Recherche Scientifique
Javier Civera
Karlsruhe Institute of Technology
The International Journal of Robotics Research
Consejo Nacional de Investigaciones Científicas y Técnicas
Universidad de Zaragoza
Centro Internacional Franco-Argentino de Ciencias de la Información y de Sistemas
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Pire et al. (Mon,) studied this question.
synapsesocial.com/papers/69d6fc0f5413bc3de5ab322c — DOI: https://doi.org/10.1177/0278364919841437