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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

Lintong Zhang , Marco Camurri , David Wisth , Maurice Fallon This is my paper · ORCID
classification cs.ROcs.CV
keywords datasetlidarmulti-cameracollegeexpansioninertialnewerabrupt
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Forward citations

Cited by 6 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Multi-LVI-SAM: A Robust LiDAR-Visual-Inertial Odometry for Multiple Fisheye Cameras

    cs.CV 2025-09 conditional novelty 6.0 of 10

    Multi-LVI-SAM fuses multiple fisheye cameras, LiDAR, and IMU using a unified panoramic feature model and an extrinsic compensation step, improving odometry accuracy on public benchmarks.

  2. A Comprehensive Evaluation of LiDAR Odometry Techniques

    cs.RO 2025-07 conditional novelty 6.0 of 10

    A seven-dataset ablation shows planar features with plane-to-plane residuals, IMU dewarping, and constant velocity initialization work best for LiDAR odometry.

  3. CURL-SLAM: Continuous and Compact LiDAR Mapping

    cs.RO 2025-06 conditional novelty 6.0 of 10

    A full LiDAR SLAM pipeline with loop closure and local bundle adjustment based on spherical-harmonic patch maps achieves compact, globally consistent, continuously resolvable 3D mapping in real time on a CPU.

  4. From Distances to Trajectories: Real-Time Signed Distance Function Mapping and Distance-Accelerated Motion Planning for UAVs

    cs.RO 2026-07 conditional novelty 5.0 of 10

    OREN-Bubble* reconstructs a continuous signed distance field online and plans safe quadrotor trajectories through overlapping collision-free balls, demonstrating onboard flight in real time.

  5. Kernel-SDF: An Open-Source Library for Real-Time Signed Distance Function Estimation using Kernel Regression

    cs.RO 2026-03 conditional novelty 5.0 of 10

    An open-source robot mapping library estimates signed distance fields and uncertainties online by combining Bayesian Hilbert maps with Gaussian process regression.

  6. PG-LIO: Photometric-Geometric fusion for Robust LiDAR-Inertial Odometry

    cs.RO 2025-06 conditional novelty 5.0 of 10

    PG-LIO fuses intensity-patch (photometric) and geometric LiDAR constraints with IMU preintegration in a factor graph, improving odometry accuracy in geometrically self-similar environments.

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