{"id":13429985,"url":"https://github.com/youngguncho/awesome-slam-datasets","last_synced_at":"2025-03-26T00:42:00.169Z","repository":{"id":37339035,"uuid":"133256832","full_name":"youngguncho/awesome-slam-datasets","owner":"youngguncho","description":"A curated list of awesome datasets for SLAM","archived":false,"fork":false,"pushed_at":"2024-04-18T13:43:12.000Z","size":1423,"stargazers_count":1615,"open_issues_count":13,"forks_count":328,"subscribers_count":63,"default_branch":"master","last_synced_at":"2024-05-19T19:00:49.756Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/youngguncho.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2018-05-13T16:54:05.000Z","updated_at":"2024-05-16T10:11:05.000Z","dependencies_parsed_at":"2024-01-03T04:47:47.498Z","dependency_job_id":"e2e8dece-79f4-4fca-a57a-efa14c1021eb","html_url":"https://github.com/youngguncho/awesome-slam-datasets","commit_stats":{"total_commits":47,"total_committers":13,"mean_commits":"3.6153846153846154","dds":0.5319148936170213,"last_synced_commit":"05f0ab869f9077c529efd78de989efab645f814c"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/youngguncho%2Fawesome-slam-datasets","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/youngguncho%2Fawesome-slam-datasets/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/youngguncho%2Fawesome-slam-datasets/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/youngguncho%2Fawesome-slam-datasets/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/youngguncho","download_url":"https://codeload.github.com/youngguncho/awesome-slam-datasets/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245568579,"owners_count":20636803,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-07-31T02:00:48.839Z","updated_at":"2025-03-26T00:42:00.150Z","avatar_url":"https://github.com/youngguncho.png","language":null,"funding_links":[],"categories":["Datasets","Uncategorized","优秀开源项目汇总","Topics","7. Datasets","Others","二 优秀开源项目汇总","Dataset Collections","Other Lists","[Libraries](#awesome-robotics-libraries)","Awesome-list"],"sub_categories":["Sensors","Uncategorized","多相机拼接","Localization","6.4 Others","TeX Lists","[SLAM](#awesome-robotics-libraries)","LiDAR global localization"],"readme":"\n\n# Awesome SLAM Datasets [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\n![image](figs/awesome_datasets_thumbnails.png)\n\u003eThumbnail Figures from Complex Urban, NCLT, Oxford robotcar, KiTTi, Cityscapes datasets.  \n\n\nThis repository is the collection of SLAM-related datasets. Among various SLAM datasets, we've selected the datasets provide pose and map information. This repository is linked to the [google site](https://sites.google.com/view/awesome-slam-datasets/). In this repository, the overall dataset chart is represented as simplified version. You can use full version of the chart (made by google spreadsheet) in the [project page](https://sites.google.com/view/awesome-slam-datasets/).\n\nWe provide several category for each access of the data.\n\n## News !!\n\n## Update: 2024-07-31\n- Add FusionPortable Series (V1: Campus-scene with diverse platforms, V2: From Campus to Highway, scalable environments.)\n\n## Update: 2024-4-18\n- Add VBR SLAM Dataset\n \n## Update: 2023-06-20\n- Add 4Seasons\n- Add M2DGR\n- Add Tartanair\n  \n## Update: 2022-8-15\n- Add VECtor Dataset\n\n## Update: 2022-04-07\n- Add Hilti SLAM Dataset\n\n## Update: 2021-03-24\n- Add PennCosyVIO\n\n### Update: 2021-02-26\n- We add a new visual localization and mapping dataset named \"ICL Dataset\". \n- Added OpenVINS evaulation toolbox link.\n\n### Update: 2020-02-29\n- We updated SLAMBench from version 2.0 to 3.0. \n\n### Update: 2019-09-24\n- We add [FMDataset](https://github.com/zhuzunjie17/FastFusion) which consist on RGBD and IMU data for dense reconstruction of indoor environments\n- In ICRA 2019 (Montreal), workshop on ['Dataset Generation and Benchmarking of SLAM Algorithms for Robotics and VR/AR'](https://sites.google.com/view/icra-2019-workshop/home) will be held!. We  are pretty sure that there will be many 'new' and 'hot' datasets intruduced at the workshop.\n- We add [evaluation section](#evaluation) (Tools for trajectory and SLAM methods evaluation)\n- We add a new UAV dataset, [UZH-FPV Drone Racing Dataset](http://rpg.ifi.uzh.ch/uzh-fpv.html), which aims high speed state estimation using RGB, Event, and IMU.\n- [Complex Urban Dataset (KAIST)](https://sites.google.com/view/complex-urban-dataset) now includes stereo camera images! (published in IJRR 2019)\n\n## TODO\n- Add datasets introduced in CVPR 2019\n  - Waymo (https://waymo.com/open)\n  - Nuscenes (https://www.nuscenes.org/)\n  - ...\n- Add Simulation datast category\n  - CARLA\n  - Airsim\n  - Syncity\n\n## Category\n- [Awesome SLAM Datasets ](#awesome-slam-datasets-)\n  - [News !!](#news-)\n  - [Update: 2024-07-31](#update-2024-07-31)\n  - [Update: 2023-06-20](#update-2023-06-20)\n  - [Update: 2022-8-15](#update-2022-8-15)\n  - [Update: 2022-04-07](#update-2022-04-07)\n  - [Update: 2021-03-24](#update-2021-03-24)\n    - [Update: 2021-02-26](#update-2021-02-26)\n    - [Update: 2020-02-29](#update-2020-02-29)\n    - [Update: 2019-09-24](#update-2019-09-24)\n  - [TODO](#todo)\n  - [Category](#category)\n  - [Overall datasets chart (Simplified Version)](#overall-datasets-chart-simplified-version)\n  - [Evaluation](#evaluation)\n  - [Categorized By Topic](#categorized-by-topic)\n    - [Odometry](#odometry)\n    - [Mapping](#mapping)\n    - [Place Recognition](#place-recognition)\n    - [Localization](#localization)\n    - [Perception](#perception)\n  - [Categorized By Characteristics](#categorized-by-characteristics)\n    - [Large-scale](#large-scale)\n    - [Long-term](#long-term)\n    - [Map Complexity](#map-complexity)\n    - [Extreme Condition](#extreme-condition)\n  - [Categorized by Platform](#categorized-by-platform)\n    - [Vehicle](#vehicle)\n    - [Mobile Robot](#mobile-robot)\n    - [Unmanned Aerial Vehicle](#unmanned-aerial-vehicle)\n    - [Autonomous Underwater Vehicle](#autonomous-underwater-vehicle)\n    - [Unmanned Surface Vehicle](#unmanned-surface-vehicle)\n    - [Hand-held Device](#hand-held-device)\n  - [Categorized by Environment](#categorized-by-environment)\n    - [Urban](#urban)\n    - [Indoor](#indoor)\n    - [Terrain](#terrain)\n    - [Underwater](#underwater)\n    - [Simulation](#simulation)\n  - [Contributing](#contributing)\n  - [License](#license)\n\n## Overall datasets chart (Simplified Version)\n[Link to Full version](https://sites.google.com/view/awesome-slam-datasets/)\n\n| Shortname                                                                                                | Affiliation  | Year | Platform   | Publication | Environment           | GT-Pose | GT-Map | IMU | GPS | Labels | Lidar      | Cameras | RGBD | Event | Radar | Sonar | DVL | Other                   |\n|----------------------------------------------------------------------------------------------------------|--------------|------|------------|-------------|-----------------------|---------|--------|-----|-----|--------|------------|---------|------|-------|-------|-------|-----|-------------------------|\n| [VBR SLAM Dataset](https://www.rvp-group.net/slam-dataset.html) | Sapienza University of Rome| 2024 | Hand, Veh  | ICRA | Indoor + Outdoor | O  |  |O  |  |  |O  |O  |  |  |  |  |  |Stereo Cams; Multiple configuration; SLAM Benchmark  |\n| [4Seasons Dataset](https://www.4seasons-dataset.com/) | Technical University of Munich| 2020 | Veh    |  GCPR  | Outdoor                | O       |   O     | O   |    O |        | O          | O       |  O    |    O    |       |       |     |    \n| [M2DGR](https://github.com/SJTU-ViSYS/M2DGR/) | Shanghai Jiaotong University | 2021 | Mob     |  RA-L  | Indoor + Outdoor                | O       |        | O   |   O  |        | O          | O       |  O    |    O    |       |       |     |   \n| [TartanAir](https://theairlab.org/tartanair-dataset/)               |    CMU    | 2020 | UAV       | IROS  | Simulation                | O       |   O    | O   |   |        |            |  O     |     | O     |       |       |     |  |\n| [VECtor Dataset](https://star-datasets.github.io/vector/) | ShanghaiTech University | 2022 | Hand     |  RA-L  | Indoor + Outdoor                | O       |        | O   |     |        | O          | O       |  O    |    O    |       |       |     |                         |\n| [Hilti SLAM Dataset](https://hilti-challenge.com/)               | Hilti, Oxford, UZH     | 2022 | Hand     |    | Indoor + Outdoor                | O       | O      | O   |     |        | O          | O       |      |       |       |       |     |                         |\n| [MADMAX Mars Dataset](https://rmc.dlr.de/morocco2018/)               | German Aerospace Center (DLR)      | 2021 | Handheld Rover-Mockup     | JFR  | Rough Terrain, Planetary analog   | O       |       | O   | O    |        |            | O      | O    |      |       |       |     | Stereo Cams + Stereo Omnidirectional Cameras; Navigation Benchmark |\n| [FinnForest Dataset](http://urn.fi/urn:nbn:fi:att:9b8157a7-1e0f-47c2-bd4e-a19a7e952c0d)   | Tampere University   | 2020 | Veh     | RAS journal  | Forest,  Terrain   |     O    |       |        |      |       |            |    O    |      |      |       |       |     | Multiple Stereo Pairs ;  Sampling Rate(40, 13, and 8Hz) |\n| [PennCOSYVIO Dataset](https://daniilidis-group.github.io/penncosyvio/)               | University of Pennsylvania      | 2017 | Hand     | ICRA  | Indoor + Outdoor                | O       |       | O   |     |        |            | O      |     |      |       |       |     |  |\n| [ICL Dataset](https://peringlab.org/lmdata/)               | Imperial College       | 2019 | Hand, MAV       | ICRA  | Indoor                | O       |       |    |     |        |            | O      | O    |      |       |       |     |  |\n| [UZH-FPV Drone Racing](http://rpg.ifi.uzh.ch/uzh-fpv.html)               | UZH, ETH       | 2019 | UAV       | ICRA  | Indoor, Urban                | O       |       | O   |     |        |            |  O     |     | O     |       |       |     |  |\n| [FMDataset](https://github.com/zhuzunjie17/FastFusion)   | Hangzhou Dianzi / Tsinghua | 2019 | Hand | ICME | Indoor |   |   | O |   |   |   |   | O  |   |   |  |   |   |\n| [Rosario Dataset](http://www.cifasis-conicet.gov.ar/robot/doku.php) | CONICET-UNR      | 2019 | Mob  | IJRR | Terrain    | O |   | O |   |   |   | O |   |   |   |   |   | Encoder                                  |\n| [Collaborative SLAM Dataset (CSD)](https://github.com/torrvision/CollaborativeSLAMDataset)               | Oxford       | 2018 | Hand       | TVCG/ISMAR  | Indoor                | O       | O      | O   |     |        |            | O       | O    |       |       |       |     | Tango (Asus ZenFone AR)\n| [ADVIO Dataset](https://github.com/AaltoVision/ADVIO)               | Aalto U          | 2018 | Hand | ECCV                | Urban      | O | O | O |   |   |   | O |   |   |   |   |   | iPhone, Tango, Pixel                     |\n| [DeepIO Dataset](http://deepio.cs.ox.ac.uk/)                        | Oxford           | 2018 | Hand | Arxiv               | Indoor     | O |   | O |   |   |   |   |   |   |   |   |   |                                          |\n| [Aqualoc Dataset](http://www.lirmm.fr/aqualoc/)                     | ONERA-DTIS       | 2018 | ROV  | IROS WS             | Underwater | O |   | O |   |   |   | O |   |   |   |   |   | Pressure Sensor                          |\n| [InteriorNet](https://interiornet.org/)                             | Imperial College | 2018 | Hand | BMVC                | Indoor     | O | O | O |   | O |   | O | O | O |   |   |   | Texture, Lighting, Context, Optical Flow |\n| [SPO Dataset](https://www.hs-karlsruhe.de/odometry-data/)           | TUM, Karlsruhe   | 2018 | Hand | Arxiv               | Urban      | O |   |   |   |   |   | O |   |   |   |   |   | Plenoptic Camera                         |\n| [Complex Urban](https://sites.google.com/view/complex-urban-dataset)                                                        | KAIST-IRAP   | 2018 | Veh        | ICRA        | Urban                 | O       | O      | O   | O   |        | O          |         |      |       |       |       |     | Encoder                 |\n| [KAIST Day/Night](https://sites.google.com/view/multispectral/home)                                      | KAIST-RCV    | 2018 | Veh        | T-ITS       | Urban                 | O       |        | O   | O   | O      | O          | O       |      |       |       |       |     | Thermal Camera          |\n| [TUM-Visual-Inertial](https://vision.in.tum.de/data/datasets/visual-inertial-dataset)                    | TUM          | 2018 | Hand       | Arxiv       | Indoor, Urban         |         |        | O   |     |        |            |         | O    |       | O     |       |     |                         |\n| [Multi Vech Event](https://daniilidis-group.github.io/mvsec/)                                            | Upenn        | 2018 | Veh        | RA-L        | Urban                 | O       |        | O   | O   |        | O          | O       |      | O     |       |       |     |                         |\n| [VI Canoe](https://databank.illinois.edu/datasets/IDB-9342111)                                           | UIUC         | 2018 | USV        | IJRR        | Terrain               | O       |        | O   | O   |        |            | O       |      |       |       |       |     |                         |\n| [MPO-Japan](https://robotics.ait.kyushu-u.ac.jp/en/archives/research/db)                   | ETH-RPG      | 2017 | UAV / Hand | IJRR        | Indoor                | O       |        | O   |     |        |            | O       |      | O     |       |       |     |                         |\n| [Underwater Cave](http://cirs.udg.edu/caves-dataset/)                                                    | UDG          | 2017 | AUV        | IJRR        | Underwater            | O       |        | O   |     |        |            | O       |      |       |       | O     | O   | Profiling Sonar         |\n| [Robot @ Home](http://mapir.isa.uma.es/mapirwebsite/index.php/mapir-downloads/203-robot-at-home-dataset) | MRPT         | 2017 | Mob        | IJRR        | Indoor                | O       | O      |     |     | O      | O          |         | O    |       |       |       |     | Semantic Labels         |\n| [Zurich Urban MAV](http://rpg.ifi.uzh.ch/zurichmavdataset.html)                                          | ETH-RPG      | 2017 | UAV        | IJRR        | Urban                 | O       |        | O   | O   |        |            | O       |      |       |       |       |     | Streetview images       |\n| [Chilean Underground](http://dataset.amtc.cl/#)                                                          | Trimble      | 2017 | Mob        | IJRR        | Terrain (Underground) | O       |        |     |     |        | O          | O       |      |       | O     |       |     | Encoder                 |\n| [SceneNet RGB-D](https://robotvault.bitbucket.io/scenenet-rgbd.html)                                     | Imperial     | 2017 | Hand       | ICCV        | Indoor                | O       |        |     |     | O      |            |         | O    |       |       |       |     |                         |\n| [Symphony Lake](http://dream.georgiatech-metz.fr/?q=node/79)                                             | Georgia Tech | 2017 | USV        | IJRR        | Terrain (Lake)        |         |        | O   | O   |        | O          | O       |      |       |       |       |     | PTZ camera, Longterm    |\n| [Agricultural robot](http://www.ipb.uni-bonn.de/data/sugarbeets2016/)                                    | Bonn         | 2017 | Mob        | IJRR        | Terrain               | O       |        |     | O   | O      | O          | O       | O    |       |       |       |     | Multispectral camera    |\n| [Beach Rover](https://robotics.estec.esa.int/datasets/katwijk-beach-11-2015/)                            | TEC-MMA      | 2017 | Mob        |             | Terrain               | O       |        | O   | O   |        | O          | O       | O    |       |       |       |     | Encoder                 |\n| [EuRoC](http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets)                     | ETH-ASL      | 2016 | UAV        | IJRR        | Indoor                | O       | O      | O   |     |        |            | O       |      |       |       |       |     |                         |\n| [Cartographer](https://google-cartographer-ros.readthedocs.io/en/latest/data.html)                     | Google      | 2016 | Hand        | ICRA        | Indoor                |         |        | O   |     |        | O          | O       |      |       |       |       |     |                         |\n| [TUM-Mono](https://vision.in.tum.de/data/datasets/mono-dataset)                                          | TUM          | 2016 | Hand       | Arxiv       | Indoor, Urban         |         |        |     |     |        |            |         |      |       | O     |       |     | Photometric Calibration |\n| [Cityscape](https://www.cityscapes-dataset.com/)                                                         | Daimler AG   | 2016 | Veh        | CVPR        | Urban                 | O       |        |     | O   | O      |            | O       |      |       |       |       |     |                         |\n| [Solar-UAV](http://projects.asl.ethz.ch/datasets/doku.php?id=fsr2015)                                    | ETHZ         | 2016 | UAV        | CVPR        | Terrain               | O       | O      | O   | O   |        | O          |         |      |       |       |       |     |                         |\n| [CoRBS](http://corbs.dfki.uni-kl.de/?pagerd_tumlltzzf42zsv6de7b9)                                        | DFKI         | 2016 | Hand       | WACV        | Indoor                | O       | O      |     |     |        |            |         | O    |       |       |       |     |                         |\n| [Oxford-robotcar](http://robotcar-dataset.robots.ox.ac.uk)                                               | Oxford       | 2016 | Veh        | IJRR        | Urban                 | O       |        | O   | O   |        | O          | O       |      |       |       |       |     |                         |\n| [NCLT](http://robots.engin.umich.edu/nclt/)                                                              | UMich        | 2016 | Mob        | IJRR        | Urban                 | O       |        | O   | O   |        | O          |         |      |       |       |       |     | FOG                     |\n| [RPG-event](http://rpg.ifi.uzh.ch/davis_data.html)                                                       | Kyushu U     | 2016 | Veh        | IROS        | Urban, Terrain        |         |        | O   | O   |        | O          | O       |      |       |       |       |     | FARO 3D                 |\n| [CCSAD](http://aplicaciones.cimat.mx/Personal/jbhayet/ccsad-dataset)                                     | CIMAT        | 2015 | Veh        | CAIP        | Urban                 |         |        | O   | O   |        |            | O       |      |       |       |       |     |                         |\n| [TUM-Omni](https://vision.in.tum.de/data/datasets/omni-lsdslam)                                          | TUM          | 2015 | Hand       | IROS        | Indoor, Urban         |         |        |     |     |        |            | O       |      |       |       |       |     |                         |\n| [Augmented ICL-NUIM](http://redwood-data.org/indoor/index.html)                                          | Redwood      | 2015 | Hand       | CVPR        | Indoor                | O       | O      |     |     |        |            |         | O    |       |       |       |     |                         |\n| [Cambridge Landmark](http://mi.eng.cam.ac.uk/projects/relocalisation/)                                   | Cambridge    | 2015 | Hand       | ICCV        | Urban                 | O       | O      |     |     |        |            | O       |      |       |       |       |     |                         |\n| [ICL-NUIM](https://www.doc.ic.ac.uk/~ahanda/VaFRIC/iclnuim.html)                                         | Imperial     | 2014 | Hand       | ICRA        | Indoor                | O       | O      |     |     |        |            |         | O    |       |       |       |     |                         |\n| [MRPT-Malaga](https://www.mrpt.org/robotics_datasets)                                                    | MRPT         | 2014 | Veh        | AR          | Urban                 |         |        | O   | O   |        | O          | O       |      |       |       |       |     |                         |\n| [KITTI](http://www.cvlibs.net/datasets/kitti/index.php)                                                  | KIT          | 2013 | Veh        | IJRR        | Urban                 | O       |        | O   | O   | O      | O          | O       |      |       |       |       |     |                         |\n| [Canadian Planetary](http://asrl.utias.utoronto.ca/datasets/3dmap/#Datasets)                             | UToronto     | 2013 | Mob        | IJRR        | Terrain               | O       |        | O   | O   |        | O (sensor) | O       |      |       |       |       |     |                         |\n| [Microsoft 7 scenes](https://www.microsoft.com/en-us/research/project/rgb-d-dataset-7-scenes/)                               | Microsoft    | 2013 | Hand       | CVPR        | Indoor                | O       | O      |     |     |        |            | O       |      |       |       |       |     |                         |\n| [SeqSLAM](https://ieeexplore.ieee.org/document/6224623)                              | QUT          | 2012 | Veh        | ICRA        | Urban                 |         |        |     |     | O      |            | O       |      |       |       |       |     |                         |\n| [ETH-challenging](http://projects.asl.ethz.ch/datasets/doku.php?id=laserregistration:laserregistration)  | ETH-ASL      | 2012 | Hand       | IJRR        | Urban, Terrain        |         |        | O   | O   |        | O          | O       | O    |       |       |       |     |                         |\n| [TUM-RGBD](https://vision.in.tum.de/data/datasets/rgbd-dataset)                                          | TUM          | 2012 | Hand / Mob | IROS        | Indoor                | O       |        | O   |     |        |            |         | O    |       |       |       |     |                         |\n| [ASRL-Kagara-airborne](http://asrl.utias.utoronto.ca/~mdw/kagarudataset.html)                            | UToronto     | 2012 | UAV        | FSR         | Terrain               |         |        | O   | O   |        |            | O       |      |       |       |       |     |                         |\n| [Devon Island Rover](http://asrl.utias.utoronto.ca/datasets/devon-island-rover-navigation/)              | UToronto     | 2012 | Mob        | IJRR        | Terrain               | O       |        |     | O   |        |            | O       |      |       |       |       |     | Sunsensor, Inclinometer |\n| [ACFR Marine](http://marine.acfr.usyd.edu.au/datasets/)                                                  | ACFR         | 2012 | AUV        |             | Underwater            | O       |        | O   |     | O      |            | O       |      |       |       | O     |     |                         |\n| [UTIAS Multi-Robot](http://asrl.utias.utoronto.ca/datasets/mrclam/)                                      | UT-IAS       | 2011 | Mob        | IJRR        | Urban                 | O       |        |     |     | O      |            |         |      |       |       |       |     |                         |\n| [Ford Campus](http://robots.engin.umich.edu/SoftwareData/Ford)                                           | UMich        | 2011 | Veh        | IJRR        | Urban                 | O       |        | O   | O   |        | O          | O       |      |       |       |       |     |                         |\n| [San francisco](https://sites.google.com/site/chenmodavid/datasets)                                      | Stanford     | 2011 | Veh        | CVPR        | Urban                 | O       |        | O   | O   | O      |            | O       |      |       |       |       |     | DMI                     |\n| [Annotated-laser](https://journals.sagepub.com/doi/10.1177/0278364910389840)                                                       | NTU          | 2011 | Veh        | IJRR        | Urban                 | O       |        |     |     | O      | O          | O       |      |       |       |       |     |                         |\n| [MIT-DARPA](http://grandchallenge.mit.edu/wiki/index.php?title=PublicData)                               | MIT          | 2010 | Veh        | IJRR        | Urban                 | O       |        | O   | O   | O      | O          | O       |      |       |       |       |     |                         |\n| [St Lucia Stereo](http://asrl.utias.utoronto.ca/~mdw/uqstluciadataset.html)                              | UToronto     | 2010 | Veh        | ACRA        | Urban                 |         |        | O   | O   |        |            | O       |      |       |       |       |     |                         |\n| [St Lucia Multiple Times](https://ieeexplore.ieee.org/abstract/document/5509547)          | QUT          | 2010 | Veh        | ICRA        | Urban                 |         |        |     | O   |        |            | O       |      |       |       |       |     |                         |\n| [Marulan](http://sdi.acfr.usyd.edu.au/)                                                                  | ACFR         | 2010 | Mob        | IJRR        | Terrain               | O       |        | O   | O   |        | O          | O       |      |       | O     |       |     | IR                      |\n| [COLD](https://www.nada.kth.se/cas/COLD/)                                                                   | KTH          | 2009 | Hand       | IJRR        | Indoor                | O       |        |     |     | O      | O          | O       |      |       |       |       |     |                         |\n| [NewCollege](http://www.robots.ox.ac.uk/NewCollegeData/)                                                 | Oxford-Robot | 2009 | Mob        | IJRR        | Urban                 | O       |        |   O  | O   |        | O          | O       |      |       |       |       |     |                         |\n| [Rawseeds-indoor](http://www.rawseeds.org/home/category/benchmarking-toolkit/datasets/)                  | Milano       | 2009 | Mob        | IROSW       | Indoor                | O       | O      | O   |     |        | O          | O       |      |       |       | O     |     |                         |\n| [Rawseeds-outdoor](http://www.rawseeds.org/home/category/benchmarking-toolkit/datasets/)                 | Milano       | 2009 | Mob        | IROSW       | Urban                 | O       | O      | O   | O   |        | O          | O       |      |       |       | O     |     |                         |\n| [FABMAP](http://www.robots.ox.ac.uk/~mobile/IJRR_2008_Dataset/)                                          | Oxford-Robot | 2008 | Veh        | IJRR        | Urban                 |         |        |     | O   |        |            | O       |      |       |       |       |     |                         |\n\n\n## Evaluation\n_Evaluation methods for SLAM benchmarks_\n- Trajectory Evaluation with Alignment [[Paper](http://rpg.ifi.uzh.ch/docs/IROS18_Zhang.pdf)], [[Code](https://github.com/uzh-rpg/rpg_trajectory_evaluation)]\n- Python package for the evaluation of odometry and SLAM [[Code](https://michaelgrupp.github.io/evo/)]\n- SLAMBench 3.0: Systematic Automated Reproducible Evaluation of SLAM Systems for Robot Vision Challenges and Scene Understanding [[Paper](https://www.sajad-saeedi.ca/uploads/3/8/5/9/38597021/sb3.pdf)], [[Code](https://github.com/mihaibujanca/slambench3)]\n- OpenVINS ov_eval Trajectory Evaulation and Alignment, Timing, and Plotting [[Paper](http://udel.edu/~pgeneva/downloads/papers/c10.pdf)], [[Docs](https://docs.openvins.com/evaluation.html)], [[Code](https://github.com/rpng/open_vins/)]\n\n## Categorized By Topic\n\n### Odometry\n_Dataset for odometry Benchmark_\n- [FusionPortable](https://fusionportable.github.io/dataset/fusionportable/)\n- [VBR SLAM Dataset](https://www.rvp-group.net/slam-dataset.html)\n- [FinnForest Dataset](http://urn.fi/urn:nbn:fi:att:9b8157a7-1e0f-47c2-bd4e-a19a7e952c0d)\n- [ICL Dataset](https://peringlab.org/lmdata/)\n- [UZH-FPV Drone Racing](http://rpg.ifi.uzh.ch/uzh-fpv.html)\n- [TUM-Visual-Inertial](https://vision.in.tum.de/data/datasets/visual-inertial-dataset)\n- [Visual-Inertial Canoe Dataset](https://databank.illinois.edu/datasets/IDB-9342111)\n- [Multi Vehicle Stereo Event Camera Dataset](https://docs.google.com/spreadsheets/d/1mudM7LxXv09ywuQGDp3t_RlIjIdwzg_ZaMu78agLmH4/edit#gid=0)\n- [Zurich Urban Micro Aerial Vehicle Dataset](http://rpg.ifi.uzh.ch/zurichmavdataset.html)\n- [EuRoC MAV Dataset](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets)\n- [TUM Monocular Cameras Dataset](https://vision.in.tum.de/data/datasets/mono-dataset)\n- [Event-Camera Dataset and Simulator](http://rpg.ifi.uzh.ch/davis_data.html)\n- [TUM Omnidirectional Cameras Dataset](https://vision.in.tum.de/data/datasets/omni-lsdslam)\n- [ICL-NUIM RGBD Dataset](https://www.doc.ic.ac.uk/~ahanda/VaFRIC/iclnuim.html)\n- [TUM RGB-D SLAM Dataset and Benchmark](https://vision.in.tum.de/data/datasets/rgbd-dataset)\n- [Google Cartographer](https://google-cartographer-ros.readthedocs.io/en/latest/data.html)\n- [ADVIO Dataset](https://github.com/AaltoVision/ADVIO)\n- [Deep Inertial Odometry Dataset](http://deepio.cs.ox.ac.uk/)\n- [Aqualoc Underwater Dataset](http://www.lirmm.fr/aqualoc/)\n- [Rosario Agricultural Dataset](http://www.cifasis-conicet.gov.ar/robot/doku.php)\n- [Stereo Plenoptic Odometry Dataset](https://www.hs-karlsruhe.de/odometry-data/)\n- [MADMAX Mars Dataset](https://rmc.dlr.de/morocco2018/) \n- [Hilti SLAM Dataset](https://hilti-challenge.com/)  \n- [VECtor Dataset](https://star-datasets.github.io/vector/)\n### Mapping\n_Dataset for mapping task_\n- [FusionPortable](https://fusionportable.github.io/dataset/fusionportable/)\n- [Collaborative SLAM Dataset (CSD)](https://github.com/torrvision/CollaborativeSLAMDataset)\n- [Complex Urban](https://sites.google.com/view/complex-urban-dataset)\n- [Multi-modal Panoramic 3D Outdoor Dataset (MPO)](https://robotics.ait.kyushu-u.ac.jp/en/archives/research/db)\n- [Underwater Caves SONAR and Vision Dataset](http://cirs.udg.edu/caves-dataset/)\n- [Chilean Underground Mine Dataset](http://dataset.amtc.cl/#)\n- [Oxford Robotcar Dataset](http://robotcar-dataset.robots.ox.ac.uk/)\n- [University of Michigan North Campus Long-Term (NCLT) Vision and LIDAR Dataset](http://robots.engin.umich.edu/nclt/)\n- [Málaga Stereo and Laser Urban Data Set](https://www.mrpt.org/MalagaUrbanDataset)\n- [KITTI Vision Benchmark Suite](http://www.cvlibs.net/datasets/kitti/index.php)\n- [Challenging data sets for point cloud registration algorithms](https://projects.asl.ethz.ch/datasets/doku.php?id=laserregistration:laserregistration)\n- [ACFR Marine Robotics Dataset](http://marine.acfr.usyd.edu.au/datasets/)\n- [Ford Campus Vision and Lidar Dataset](http://robots.engin.umich.edu/SoftwareData/Ford)\n- [InteriorNet](https://interiornet.org/)\n- [FMDataset](https://github.com/zhuzunjie17/FastFusion)\n- [MADMAX Mars Dataset](https://rmc.dlr.de/morocco2018/) \n\n### Place Recognition\n_Dataset gives correspondences of places (images)_\n- [Visual-Inertial Canoe Dataset](https://databank.illinois.edu/datasets/IDB-9342111)\n- [Symphony Lake Dataset](http://dream.georgiatech-metz.fr/?q=node/79)\n- [Alderley Day/Night Dataset](https://wiki.qut.edu.au/pages/viewpage.action?pageId=181178395)\n- [St Lucia Multiple Times of Day](https://wiki.qut.edu.au/display/cyphy/St+Lucia+Multiple+Times+of+Day)\n- [New College Vision and Laser Data Set](http://www.robots.ox.ac.uk/NewCollegeData/)\n- [FABMAP Dataset](http://www.robots.ox.ac.uk/~mobile/IJRR_2008_Dataset/)\n\n### Localization\n_Dataset for metric-level localization_\n- [FusionPortable](https://fusionportable.github.io/dataset/fusionportable/)\n- [VBR SLAM Dataset](https://www.rvp-group.net/slam-dataset.html)\n- [ICL Dataset](https://peringlab.org/lmdata/)\n- [Cambridge Landmark Dataset](http://mi.eng.cam.ac.uk/projects/relocalisation/)\n- [KITTI Vision Benchmark Suite](http://www.cvlibs.net/datasets/kitti/index.php)\n- [Microsoft 7 scenes](https://www.microsoft.com/en-us/research/project/rgb-d-dataset-7-scenes/)\n- [San Francisco Landmark Dataset](https://sites.google.com/site/chenmodavid/datasets)\n- [MADMAX Mars Dataset](https://rmc.dlr.de/morocco2018/) \n\n\n### Perception\n_Dataset with semantic labels / correspondences_\n- [KAIST Day/Night Dataset](https://sites.google.com/view/multispectral/home)\n- [Robot @ Home Dataset](http://mapir.isa.uma.es/mapirwebsite/index.php/mapir-downloads/203-robot-at-home-dataset)\n- [SceneNet RBG-D Dataset](https://robotvault.bitbucket.io/scenenet-rgbd.html)\n- [Sugar Beets 2016, Agricultural Robot Dataset](http://www.ipb.uni-bonn.de/data/sugarbeets2016/)\n- [CityScapes Dataset](https://www.cityscapes-dataset.com/)\n- [KITTI Vision Benchmark Suite](http://www.cvlibs.net/datasets/kitti/index.php)\n- [Multi-Sensor Perception (Marulan) Dataset ](http://sdi.acfr.usyd.edu.au/)\n- [InteriorNet](https://interiornet.org/)\n- [FusionPortableV2](https://fusionportable.github.io/dataset/fusionportable_v2/)\n\n## Categorized By Characteristics\n\n### Large-scale\n_City-scale map, kilometer level Map_\n- [FusionPortableV2](https://fusionportable.github.io/dataset/fusionportable_v2/)\n- [VBR SLAM Dataset](https://www.rvp-group.net/slam-dataset.html)\n- [Complex Urban](https://sites.google.com/view/complex-urban-dataset)\n- [Multi Vehicle Stereo Event Camera Dataset](https://docs.google.com/spreadsheets/d/1mudM7LxXv09ywuQGDp3t_RlIjIdwzg_ZaMu78agLmH4/edit#gid=0)\n- [Multi-modal Panoramic 3D Outdoor Dataset (MPO)](https://robotics.ait.kyushu-u.ac.jp/en/archives/research/db)\n- [CityScapes Dataset](https://www.cityscapes-dataset.com/)\n- [Solar-powered UAV Sensing and Mapping Dataset](https://projects.asl.ethz.ch/datasets/doku.php?id=fsr2015)\n- [Oxford Robotcar Dataset](http://robotcar-dataset.robots.ox.ac.uk/)\n- [CCSAD (Stereo Urban) Dattaset](http://aplicaciones.cimat.mx/Personal/jbhayet/ccsad-dataset)\n- [Málaga Stereo and Laser Urban Data Set](https://www.mrpt.org/MalagaUrbanDataset)\n- [KITTI Vision Benchmark Suite](http://www.cvlibs.net/datasets/kitti/index.php)\n- [Kagaru Airborne Stereo Dataset Dataset](http://asrl.utias.utoronto.ca/~mdw/kagarudataset.html)\n- [ACFR Marine Robotics Dataset](http://marine.acfr.usyd.edu.au/datasets/)\n\n### Long-term\n_Multi-session, long-term data collection_\n- [FinnForest Dataset](http://urn.fi/urn:nbn:fi:att:9b8157a7-1e0f-47c2-bd4e-a19a7e952c0d)\n- [KAIST Day/Night Dataset](https://sites.google.com/view/multispectral/home)\n- [Visual-Inertial Canoe Dataset](https://databank.illinois.edu/datasets/IDB-9342111)\n- [Symphony Lake Dataset](http://dream.georgiatech-metz.fr/?q=node/79)\n- [Oxford Robotcar Dataset](http://robotcar-dataset.robots.ox.ac.uk/)\n- [University of Michigan North Campus Long-Term (NCLT) Vision and LIDAR Dataset](http://robots.engin.umich.edu/nclt/)\n- [Alderley Day/Night Dataset](https://wiki.qut.edu.au/pages/viewpage.action?pageId=181178395)\n- [St Lucia Multiple Times of Day](https://wiki.qut.edu.au/display/cyphy/St+Lucia+Multiple+Times+of+Day)\n\n### Map Complexity\n_Variation of mapping structures_\n- [VBR SLAM Dataset](https://www.rvp-group.net/slam-dataset.html)\n- [Complex Urban](https://sites.google.com/view/complex-urban-dataset/)\n- [Multi Vehicle Stereo Event Camera Dataset](https://docs.google.com/spreadsheets/d/1mudM7LxXv09ywuQGDp3t_RlIjIdwzg_ZaMu78agLmH4/edit#gid=0)\n- [Multi-modal Panoramic 3D Outdoor Dataset (MPO)](https://robotics.ait.kyushu-u.ac.jp/en/archives/research/db)\n- [Málaga Stereo and Laser Urban Data Set](https://www.mrpt.org/MalagaUrbanDataset)\n- [KITTI Vision Benchmark Suite](http://www.cvlibs.net/datasets/kitti/index.php)\n- [Challenging data sets for point cloud registration - algorithms](https://projects.asl.ethz.ch/datasets/doku.php?id=laserregistration:laserregistration)\n\n### Extreme Condition\n_Extreme environment, motions_\n- [FinnForest Dataset](http://urn.fi/urn:nbn:fi:att:9b8157a7-1e0f-47c2-bd4e-a19a7e952c0d)\n- [UZH-FPV Drone Racing](http://rpg.ifi.uzh.ch/uzh-fpv.html)\n- [Underwater Caves SONAR and Vision Dataset](http://cirs.udg.edu/caves-dataset/): Underwater Environment\n- [Chilean Underground Mine Dataset](http://dataset.amtc.cl/#): Underground Environment\n- [CityScapes Dataset](https://www.cityscapes-dataset.com/): Foggy Scene\n- [EuRoC MAV Dataset](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets): Fast motion\n- [Multi-Sensor Perception (Marulan) Dataset ](http://sdi.acfr.usyd.edu.au/):  Smoky, dust, and Rain condition\n\n## Categorized by Platform\n\n### Vehicle\n_Commercial Vehicle (Four-wheeled on the road)_\n- [FusionPortableV2 Dataset](https://fusionportable.github.io/dataset/fusionportable_v2/)\n- [VBR SLAM Dataset](https://www.rvp-group.net/slam-dataset.html)\n- [FinnForest Dataset](http://urn.fi/urn:nbn:fi:att:9b8157a7-1e0f-47c2-bd4e-a19a7e952c0d)\n- [Complex Urban Dataset](https://sites.google.com/view/complex-urban-dataset/)\n- [Multi Vehicle Stereo Event Camera Dataset](https://docs.google.com/spreadsheets/d/1mudM7LxXv09ywuQGDp3t_RlIjIdwzg_ZaMu78agLmH4/edit#gid=0)\n- [KAIST Day/Night Dataset](https://sites.google.com/view/multispectral/home)\n- [Multi-modal Panoramic 3D Outdoor Dataset (MPO)](https://robotics.ait.kyushu-u.ac.jp/en/archives/research/db)\n- [Oxford Robotcar Dataset](http://robotcar-dataset.robots.ox.ac.uk/)\n- [CityScapes Dataset](https://www.cityscapes-dataset.com/)\n- [CCSAD (Stereo Urban) Dattaset](http://aplicaciones.cimat.mx/Personal/jbhayet/ccsad-dataset)\n- [Málaga Stereo and Laser Urban Data Set](https://www.mrpt.org/MalagaUrbanDataset)\n- [KITTI Vision Benchmark Suite](http://www.cvlibs.net/datasets/kitti/index.php)\n- [Day and Night with Lateral Pose Change Dataset](https://wiki.qut.edu.au/display/cyphy/Day+and+Night+with+Lateral+Pose+Change+Datasets)\n- [Alderley Day/Night Dataset](https://wiki.qut.edu.au/pages/viewpage.action?pageId=181178395)\n- [Annotated-laser Dataset](http://any.csie.ntu.edu.tw/data) (Link Broken)\n- [San Francisco Landmark Dataset](https://sites.google.com/site/chenmodavid/datasets)\n- [Ford Campus Vision and Lidar Dataset](http://robots.engin.umich.edu/SoftwareData/Ford)\n- [St Lucia Stereo Vehicular Dataset](http://asrl.utias.utoronto.ca/~mdw/uqstluciadataset.html)\n- [St Lucia Multiple Times of Day](https://wiki.qut.edu.au/display/cyphy/St+Lucia+Multiple+Times+of+Day)\n- [MIT DARPA Urban Challenge Dataset](http://grandchallenge.mit.edu/wiki/index.php?title=PublicData)\n- [FABMAP Dataset](http://www.robots.ox.ac.uk/~mobile/IJRR_2008_Dataset/)\n\n\n### Mobile Robot\n_Mobile Robots (Ex. Husky, Rover.. )_\n- [Rosario Dataset](http://www.cifasis-conicet.gov.ar/robot/doku.php)\n- [Sugar Beets 2016, Agricultural Robot Dataset](http://www.ipb.uni-bonn.de/data/sugarbeets2016/)\n- [Chilean Underground Mine Dataset](http://dataset.amtc.cl/#)\n- [Katwijk Beach Planetary Rover Dataset](https://robotics.estec.esa.int/datasets/katwijk-beach-11-2015/)\n- [Robot @ Home Dataset](http://mapir.isa.uma.es/mapirwebsite/index.php/mapir-downloads/203-robot-at-home-dataset)\n- [University of Michigan North Campus Long-Term (NCLT) Vision and LIDAR Dataset](http://robots.engin.umich.edu/nclt/)\n- [Rawseeds In/Outdoor Dataset](http://www.rawseeds.org/home/category/benchmarking-toolkit/datasets/)\n- [Canadian Planetary Emulation Terrain 3D Mapping Dataset](http://asrl.utias.utoronto.ca/datasets/3dmap/#Datasets)\n- [Devon Island Rover Navigation Dataset](http://asrl.utias.utoronto.ca/datasets/devon-island-rover-navigation/)\n- [Multi-Robot Cooperative Localization and Mapping Dataset](http://asrl.utias.utoronto.ca/datasets/mrclam/)\n- [Multi-Sensor Perception (Marulan) Dataset ](http://sdi.acfr.usyd.edu.au/)\n- [TUM RGB-D SLAM Dataset and Benchmark](https://vision.in.tum.de/data/datasets/rgbd-dataset)\n- [New College Vision and Laser Data Set](http://www.robots.ox.ac.uk/NewCollegeData/)\n- [MADMAX Mars Dataset](https://rmc.dlr.de/morocco2018/) \n\n### Unmanned Aerial Vehicle\n_Unmanned aerial robots include drone_\n- [ICL Dataset](https://peringlab.org/lmdata/)\n- [UZH-FPV Drone Racing](http://rpg.ifi.uzh.ch/uzh-fpv.html)\n- [Zurich Urban Micro Aerial Vehicle Dataset](http://rpg.ifi.uzh.ch/zurichmavdataset.html)\n- [Event-Camera Dataset and Simulator](http://rpg.ifi.uzh.ch/davis_data.html)\n- [Solar-powered UAV Sensing and Mapping Dataset](https://projects.asl.ethz.ch/datasets/doku.php?id=fsr2015)\n- [EuRoC MAV Dataset](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets)\n- [Kagaru Airborne Stereo Dataset Dataset](http://asrl.utias.utoronto.ca/~mdw/kagarudataset.html)\n\n\n\n\n### Autonomous Underwater Vehicle\n_Underwater robots include ROV for simplicity_\n- [Aqualoc Underwater Dataset](http://www.lirmm.fr/aqualoc/)\n- [Underwater Caves SONAR and Vision Dataset](http://cirs.udg.edu/caves-dataset/)\n- [ACFR Marine Robotics Dataset](http://marine.acfr.usyd.edu.au/datasets/)\n\n\n### Unmanned Surface Vehicle\n_Water surface vehicle such as canoe and boat_\n- [Visual-Inertial Canoe Dataset](https://databank.illinois.edu/datasets/IDB-9342111)\n- [Symphony Lake Dataset](http://dream.georgiatech-metz.fr/?q=node/79)\n\n\n### Hand-held Device\n_Hand-held platform by human_\n- [VBR SLAM Dataset](https://www.rvp-group.net/slam-dataset.html)\n- [Collaborative SLAM Dataset (CSD)](https://github.com/torrvision/CollaborativeSLAMDataset)\n- [SceneNet RBG-D Dataset](https://robotvault.bitbucket.io/scenenet-rgbd.html)\n- [Event-Camera Dataset and Simulator](http://rpg.ifi.uzh.ch/davis_data.html)\n- [Comprehensive RGB-D Benchmark (CoRBS)](http://corbs.dfki.uni-kl.de/?pagerd_tumlltzzf42zsv6de7b9)\n- [Augmented ICL-NUIM Reconstruction Dataset](http://redwood-data.org/indoor/index.html)\n- [ICL-NUIM RGBD Dataset](https://www.doc.ic.ac.uk/~ahanda/VaFRIC/iclnuim.html)\n- [Challenging data sets for point cloud registration algorithms](https://projects.asl.ethz.ch/datasets/doku.php?id=laserregistration:laserregistration)\n- [Cosy Localization Database (COLD)](https://www.pronobis.pro/#data)\n- [ADVIO Dataset](https://github.com/AaltoVision/ADVIO)\n- [Deep Inertial Odometry Dataset](http://deepio.cs.ox.ac.uk/)\n- [InteriorNet](https://interiornet.org/)\n- [Stereo Plenoptic Dataset](https://www.hs-karlsruhe.de/odometry-data/)\n- [FMDataset](https://github.com/zhuzunjie17/FastFusion)\n- [Hilti SLAM Dataset](https://hilti-challenge.com/)  \n\n\n## Categorized by Environment\n### Urban\n_City, campus, town, and infrastructures\n- [VBR SLAM Dataset](https://www.rvp-group.net/slam-dataset.html)\n- [UZH-FPV Drone Racing](http://rpg.ifi.uzh.ch/uzh-fpv.html)\n- [ADVIO Dataset](https://github.com/AaltoVision/ADVIO)\n- [Stereo Plenoptic Dataset](https://www.hs-karlsruhe.de/odometry-data/)\n- [KAIST Day/Night Dataset](https://sites.google.com/view/multispectral/home)\n- [TUM-Visual-Inertial](https://vision.in.tum.de/data/datasets/visual-inertial-dataset)\n- [Complex Urban](https://sites.google.com/view/complex-urban-dataset/)\n- [Multi Vehicle Stereo Event Camera Dataset](https://docs.google.com/spreadsheets/d/1mudM7LxXv09ywuQGDp3t_RlIjIdwzg_ZaMu78agLmH4/edit#gid=0)\n- [Zurich Urban Micro Aerial Vehicle Dataset](http://rpg.ifi.uzh.ch/zurichmavdataset.html)\n- [TUM Monocular Cameras Dataset](https://vision.in.tum.de/data/datasets/mono-dataset)\n- [CityScapes Dataset](https://www.cityscapes-dataset.com/)\n- [Oxford Robotcar Dataset](http://robotcar-dataset.robots.ox.ac.uk/)\n- [University of Michigan North Campus Long-Term (NCLT) Vision and LIDAR Dataset](http://robots.engin.umich.edu/nclt/)\n- [Event-Camera Dataset and Simulator](http://rpg.ifi.uzh.ch/davis_data.html)\n- [CCSAD (Stereo Urban) Dattaset](http://aplicaciones.cimat.mx/Personal/jbhayet/ccsad-dataset)\n- [TUM Omnidirectional Cameras Dataset](https://vision.in.tum.de/data/datasets/omni-lsdslam)\n- [Cambridge Landmark Dataset](http://mi.eng.cam.ac.uk/projects/relocalisation/)\n- [Málaga Stereo and Laser Urban Data Set](https://www.mrpt.org/MalagaUrbanDataset)\n- [KITTI Vision Benchmark Suite](http://www.cvlibs.net/datasets/kitti/index.php)\n- [Alderley Day/Night Dataset](https://wiki.qut.edu.au/pages/viewpage.action?pageId=181178395)\n- [Challenging data sets for point cloud registration algorithms](https://projects.asl.ethz.ch/datasets/doku.php?id=laserregistration:laserregistration)\n- [Multi-Robot Cooperative Localization and Mapping Dataset](http://asrl.utias.utoronto.ca/datasets/mrclam/)\n- [Ford Campus Vision and Lidar Dataset](http://robots.engin.umich.edu/SoftwareData/Ford)\n- [San Francisco Landmark Dataset](https://sites.google.com/site/chenmodavid/datasets)\n- [Annotated-laser Dataset](http://any.csie.ntu.edu.tw/data) (Link Broken)\n- [MIT DARPA Urban Challenge Dataset](http://grandchallenge.mit.edu/wiki/index.php?title=PublicData)\n- [St Lucia Stereo Vehicular Dataset](http://asrl.utias.utoronto.ca/~mdw/uqstluciadataset.html)\n- [St Lucia Multiple Times of Day](https://wiki.qut.edu.au/display/cyphy/St+Lucia+Multiple+Times+of+Day)\n- [New College Vision and Laser Data Set](http://www.robots.ox.ac.uk/NewCollegeData/)\n- [Rawseeds In/Outdoor Dataset](http://www.rawseeds.org/home/category/benchmarking-toolkit/datasets/)\n- [FABMAP Dataset](http://www.robots.ox.ac.uk/~mobile/IJRR_2008_Dataset/)\n\n### Indoor\n_Indoor environment_\n- [VBR SLAM Dataset](https://www.rvp-group.net/slam-dataset.html)\n- [ICL Dataset](https://peringlab.org/lmdata/)\n- [FMDataset](https://github.com/zhuzunjie17/FastFusion)\n- [UZH-FPV Drone Racing](http://rpg.ifi.uzh.ch/uzh-fpv.html)\n- [Collaborative SLAM Dataset (CSD)](https://github.com/torrvision/CollaborativeSLAMDataset)\n- [InteriorNet](https://interiornet.org/)\n- [TUM-Visual-Inertial](https://vision.in.tum.de/data/datasets/visual-inertial-dataset)\n- [Multi-modal Panoramic 3D Outdoor Dataset (MPO)](https://robotics.ait.kyushu-u.ac.jp/en/archives/research/db)\n- [Robot @ Home Dataset](http://mapir.isa.uma.es/mapirwebsite/index.php/mapir-downloads/203-robot-at-home-dataset)\n- [SceneNet RBG-D Dataset](https://robotvault.bitbucket.io/scenenet-rgbd.html)\n- [EuRoC MAV Dataset](https://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets)\n- [TUM Monocular Cameras Dataset](https://vision.in.tum.de/data/datasets/mono-dataset)\n- [Comprehensive RGB-D Benchmark (CoRBS)](http://corbs.dfki.uni-kl.de/?pagerd_tumlltzzf42zsv6de7b9)\n- [TUM Omnidirectional Cameras Dataset](https://vision.in.tum.de/data/datasets/omni-lsdslam)\n- [Augmented ICL-NUIM Reconstruction Dataset](http://redwood-data.org/indoor/index.html)\n- [ICL-NUIM RGBD Dataset](https://www.doc.ic.ac.uk/~ahanda/VaFRIC/iclnuim.html)\n- [Microsoft 7 scenes](https://www.microsoft.com/en-us/research/project/rgb-d-dataset-7-scenes/)\n- [TUM RGB-D SLAM Dataset and Benchmark](https://vision.in.tum.de/data/datasets/rgbd-dataset)\n- [Cosy Localization Database (COLD)](https://www.pronobis.pro/#data)\n- [Rawseeds In/Outdoor Dataset](http://www.rawseeds.org/home/category/benchmarking-toolkit/datasets/)\n- [Google Cartographer](https://google-cartographer-ros.readthedocs.io/en/latest/data.html)\n\n\n### Terrain\n_Rough terrain, underground, lake and farm_\n- [VBR SLAM Dataset](https://www.rvp-group.net/slam-dataset.html)\n- [FinnForest Dataset](http://urn.fi/urn:nbn:fi:att:9b8157a7-1e0f-47c2-bd4e-a19a7e952c0d)\n- [Rosario Agricultural Dataset](http://www.cifasis-conicet.gov.ar/robot/doku.php)\n- [Visual-Inertial Canoe Dataset](https://databank.illinois.edu/datasets/IDB-9342111)\n- [Chilean Underground Mine Dataset](http://dataset.amtc.cl/#)\n- [Symphony Lake Dataset](http://dream.georgiatech-metz.fr/?q=node/79)\n- [Sugar Beets 2016, Agricultural Robot Dataset](http://www.ipb.uni-bonn.de/data/sugarbeets2016/)\n- [Katwijk Beach Planetary Rover Dataset](https://robotics.estec.esa.int/datasets/katwijk-beach-11-2015/)\n- [Solar-powered UAV Sensing and Mapping Dataset](https://projects.asl.ethz.ch/datasets/doku.php?id=fsr2015)\n- [Event-Camera Dataset and Simulator](http://rpg.ifi.uzh.ch/davis_data.html)\n- [Canadian Planetary Emulation Terrain 3D Mapping Dataset](http://asrl.utias.utoronto.ca/datasets/3dmap/#Datasets)\n- [Challenging data sets for point cloud registration - algorithms](https://projects.asl.ethz.ch/datasets/doku.php?id=laserregistration:laserregistration)\n- [Kagaru Airborne Stereo Dataset Dataset](http://asrl.utias.utoronto.ca/~mdw/kagarudataset.html)\n- [Devon Island Rover Navigation Dataset](http://asrl.utias.utoronto.ca/datasets/devon-island-rover-navigation/)\n- [Multi-Sensor Perception (Marulan) Dataset ](http://sdi.acfr.usyd.edu.au/)\n- [MADMAX Mars Dataset](https://rmc.dlr.de/morocco2018/) \n\n### Underwater\n_Underwater floor, cave_\n- [Aqualoc Underwater Dataset](http://www.lirmm.fr/aqualoc/)\n- [Underwater Caves SONAR and Vision Dataset](http://cirs.udg.edu/caves-dataset/)\n- [ACFR Marine Robotics Dataset](http://marine.acfr.usyd.edu.au/datasets/)\n\n### Simulation\n_Simulation Scene_\n- [TartanAir](https://theairlab.org/tartanair-dataset/)\n## Contributing\nPlease Feel free to send a [pull request](https://github.com/youngguncho/awesome-slam-datasets/pulls) to modify the list or add datasets.\n\n\n## License\n[![CC0](http://mirrors.creativecommons.org/presskit/buttons/88x31/svg/cc-zero.svg)](https://creativecommons.org/publicdomain/zero/1.0/)\n\nTo the extent possible under law, [Younggun Cho](https://github.com/youngguncho) has waived all copyright and related or neighboring rights to this work.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyoungguncho%2Fawesome-slam-datasets","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyoungguncho%2Fawesome-slam-datasets","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyoungguncho%2Fawesome-slam-datasets/lists"}