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Multi-Camera LiDAR Inertial Extension to the Newer College Dataset

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arxiv 2112.08854 v3 pith:FJUL3OX5 submitted 2021-12-16 cs.RO cs.CV

Multi-Camera LiDAR Inertial Extension to the Newer College Dataset

Lintong Zhang , Marco Camurri , David Wisth , Maurice Fallon This is my paper
classification cs.RO cs.CV
keywords datasetlidarmulti-cameracollegeexpansioninertialnewerabrupt
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We present a multi-camera LiDAR inertial dataset of 4.5 km walking distance as an expansion of the Newer College Dataset. The global shutter multi-camera device is hardware synchronized with both the IMU and LiDAR, which is more accurate than the original dataset with software synchronization. This dataset also provides six Degrees of Freedom (DoF) ground truth poses at LiDAR frequency (10 Hz). Three data collections are described and an example use case of multi-camera visual-inertial odometry is demonstrated. This expansion dataset contains small and narrow passages, large scale open spaces, as well as vegetated areas, to test localization and mapping systems. Furthermore, some sequences present challenging situations such as abrupt lighting change, textureless surfaces, and aggressive motion. The dataset is available at: https://ori-drs.github. io/newer-college-dataset/

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Cited by 5 Pith papers

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    cs.RO 2026-04 unverdicted novelty 5.0

    BIEVR-LIO improves robustness of LiDAR-inertial odometry by representing maps as voxel-wise oriented height images and sampling points only from geometrically informative regions.

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