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AG-LOAM Dataset

AG-LOAM dataset has been released to facilitate the evaluation of LiDAR-based odometry algorithms in agricultural environments. 1) It was collected by a wheeled mobile robot at the Agricultural Experimental Station of the University of California, Riverside, during Winter 2022 and Winter 2023. 2) It provides LiDAR point cloud data captured using a Velodyne VLP-16 sensor, along with ground-truth trajectories obtained from an RTK-GPS system. 3) It consists of 18 sequences collected over three phases, covering diverse planting environments, terrain conditions, path patterns, and robot motion profiles. 4) It spans a total operation...

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Data coverage

AG-LOAM dataset has been released to facilitate the evaluation of LiDAR-based odometry algorithms in agricultural environments. 1) It was collected by a wheeled mobile robot at the Agricultural Experimental Station of the University of California, Riverside, during Winter 2022 and Winter 2023. 2) It provides LiDAR point cloud data captured using a Velodyne VLP-16 sensor, along with ground-truth trajectories obtained from an RTK-GPS system. 3) It consists of 18 sequences collected over three phases, covering diverse planting environments, terrain conditions, path patterns, and robot motion profiles. 4) It spans a total operation time of 3 hours, covers a total distance of 7.5 km, and constitutes 150 GB of data.

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Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).

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