{"url":"/dataset/conslam","name":"ConSLAM","full_name":"Construction Dataset for SLAM","description_markdown":"ConSLAM is a real-world dataset collected periodically on a construction site to measure the accuracy of mobile scanners' SLAM algorithms. \r\n\r\nThe dataset contains time-synchronized and spatially registered RGB and NIR images and 360-deg LiDAR scans, 9-axis IMU measurements, and professional ground-truth terrestrial laser scans.\r\nThis dataset reflects the periodic need to scan construction sites with the aim of accurately monitoring progress using a hand-held scanner.\r\nThe sensors used for data acquisition are:\r\n- LiDAR: Velodyne VLP-16.\r\n- RGB camera: Alvium U-319c, 3.2 MP. \r\n- NIR camera: Alvium 1800 U-501, 5.0 MP. \r\n- 9-axis IMU: Xsens MTi-610.","description_withheld":null,"homepage":"https://github.com/mac137/ConSLAM","introduced_date":"2023-10-22","introduced_date_note":null,"introduced_by":null,"license":{"name":"Copyright (C) 2023, University of Cambridge, all rights reserved.","url":"https://github.com/mac137/ConSLAM/blob/main/LICENCE.txt"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"3D","url":"/datasets/modality/3d"},{"name":"Point cloud","url":"/datasets/modality/point-cloud"},{"name":"Tracking","url":"/datasets/modality/tracking"},{"name":"RGB Video","url":"/datasets/modality/rgb-video"},{"name":"LiDAR","url":"/datasets/modality/lidar"}],"tasks":[{"name":"Pose Estimation","url":"/task/pose-estimation","datasets_with_task":"/datasets/task/pose-estimation"},{"name":"Depth Estimation","url":"/task/depth-estimation","datasets_with_task":"/datasets/task/depth-estimation"},{"name":"Pose Tracking","url":"/task/pose-tracking","datasets_with_task":"/datasets/task/pose-tracking"},{"name":"Camera Localization","url":"/task/camera-localization","datasets_with_task":"/datasets/task/camera-localization"},{"name":"2D Pose Estimation","url":"/task/2d-pose-estimation","datasets_with_task":"/datasets/task/2d-pose-estimation"},{"name":"Visual Odometry","url":"/task/visual-odometry","datasets_with_task":"/datasets/task/visual-odometry"},{"name":"Depth Completion","url":"/task/depth-completion","datasets_with_task":"/datasets/task/depth-completion"},{"name":"6D Pose Estimation","url":"/task/6d-pose-estimation-1","datasets_with_task":"/datasets/task/6d-pose-estimation-1"},{"name":"lidar absolute pose regression","url":"/task/lidar-absolute-pose-regression","datasets_with_task":"/datasets/task/lidar-absolute-pose-regression"},{"name":"3D Pose Estimation","url":"/task/3d-pose-estimation","datasets_with_task":"/datasets/task/3d-pose-estimation"},{"name":"Camera Relocalization","url":"/task/camera-relocalization","datasets_with_task":"/datasets/task/camera-relocalization"},{"name":"Indoor Localization","url":"/task/indoor-localization","datasets_with_task":"/datasets/task/indoor-localization"},{"name":"Simultaneous Localization and Mapping","url":"/task/simultaneous-localization-and-mapping","datasets_with_task":"/datasets/task/simultaneous-localization-and-mapping"},{"name":"Semantic SLAM","url":"/task/semantic-slam","datasets_with_task":"/datasets/task/semantic-slam"},{"name":"Camera Pose Estimation","url":"/task/camera-pose-estimation","datasets_with_task":"/datasets/task/camera-pose-estimation"},{"name":"Robot Pose Estimation","url":"/task/robot-pose-estimation","datasets_with_task":"/datasets/task/robot-pose-estimation"},{"name":"Monocular Visual Odometry","url":"/task/monocular-visual-odometry","datasets_with_task":"/datasets/task/monocular-visual-odometry"},{"name":"Object SLAM","url":"/task/object-slam","datasets_with_task":"/datasets/task/object-slam"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ConSLAM"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}