# The Newer College Dataset: Handheld LiDAR, Inertial and Vision with Ground Truth Source: [The Newer College Dataset: Handheld LiDAR, Inertial and Vision with Ground Truth]() Collection index: [llms.txt]() Data updated: 2025-10-26T00:21:36.840Z Authors: Milad Ramezani, Yiduo Wang, Marco Camurri, David Wisth, Matias Mattamala, Maurice Fallon Published: 2020-03-12T10:17:16.000Z ## Abstract In this paper we present a large dataset with a variety of mobile mapping sensors collected using a handheld device carried at typical walking speeds for nearly 2.2 km through New College, Oxford. The dataset includes data from two commercially available devices - a stereoscopic-inertial camera and a multi-beam 3D LiDAR, which also provides inertial measurements. Additionally, we used a tripod-mounted survey grade LiDAR scanner to capture a detailed millimeter-accurate 3D map of the test location (containing $\\sim$290 million points). Using the map we inferred centimeter-accurate 6 Degree of Freedom (DoF) ground truth for the position of the device for each LiDAR scan to enable better evaluation of LiDAR and vision localisation, mapping and reconstruction systems. This ground truth is the particular novel contribution of this dataset and we believe that it will enable systematic evaluation which many similar datasets have lacked. The dataset combines both built environments, open spaces and vegetated areas so as to test localization and mapping systems such as vision-based navigation, visual and LiDAR SLAM, 3D LIDAR reconstruction and appearance-based place recognition. The dataset is available at: ori.ox.ac.uk/datasets/newer-college-dataset ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [LiDAR-Inertial Odometry on Newer-College (quad-D, quad-M, quad-H, math-H)](): LiDAR-Inertial Odometry; Newer-College (quad-D, quad-M, quad-H, math-H); RMSE ATE (quad-D): 0.135. - [LiDAR-Inertial Odometry on Authors' Custom Dataset (CW, CCW, mid)](): LiDAR-Inertial Odometry; Authors' Custom Dataset (CW, CCW, mid); ATE RMSE (CCW): 21.62. - [LiDAR-Inertial Odometry on NTU-VIRAL](): LiDAR-Inertial Odometry; NTU-VIRAL; EEE: 51.84. - [LiDAR-Inertial Odometry on NTU-VIRAL (eee, nya, rtp, sbs, tnp, spms)](): LiDAR-Inertial Odometry; NTU-VIRAL (eee, nya, rtp, sbs, tnp, spms); ATE RMSE (m): not recorded. ## Original sources and implementation [Original paper]() [PDF]()