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Perth-WA Localization Dataset in 3D Point Cloud Maps
- Citation Author(s):
- Submitted by:
- Muhammad Ibrahim
- Last updated:
- Wed, 03/15/2023 - 03:59
- DOI:
- 10.21227/s2p2-2e66
- Research Article Link:
- License:
- Categories:
- Keywords:
Abstract
Perth-WA is the localization dataset that provides 6DoF annotations in 3D point cloud maps. The data comprises a LiDAR map of 4km square region of Perth Central Business District (CBD) in Western Australia. The scenes contain commercial structures, residential areas, food streets, complex routes, and hospital building etc. The data was collected in three different two-hour sessions under day/night conditions with sunny and cloudy weather. Unlike the existing related dataset, Apollo-SouthBay and Oxford Radar RobotCar Dataset, Perth-WA dataset annotations do not rely on Inertial Measurement Unit (IMU). Instead, the labeling comes directly from the LiDAR frames themselves. To extract the ground-truth poses for Perth-WA dataset, we exploit the map creation process itself. Within a loop, a moving LiDAR frame is registered with a static point cloud, which generates a transformation matrix for the moving frame. To compute the transformation matrix of a frame, we multiply the previous frame's transformation to the transformation matrix of that frame
A dataloader is attached to the dataset. Please provide the dataset path like in the Main function of the loader. The dataset contains two main folders- train and test. Each folder comprises loop data with LiDAR frames and their pose ground truth labels in a text file by the name GT.txt.
Dataset Files
- Dataset1.zip (21.50 GB)
- ICRA23Video.mp4 (18.86 MB)
- Dataloader is coded in Pytorch. Datasetloader.py (2.00 kB)