Thumbnail Figures from Complex Urban, NCLT, Oxford robotcar, KiTTi, Cityscapes datasets.
This 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. 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.
We provide several category for each access of the data.
- Add 4Seasons
- Add M2DGR
- Add Tartanair
- Add VECtor Dataset
- Add Hilti SLAM Dataset
- Add PennCosyVIO
- We add a new visual localization and mapping dataset named "ICL Dataset".
- Added OpenVINS evaulation toolbox link.
- We updated SLAMBench from version 2.0 to 3.0.
- We add FMDataset which consist on RGBD and IMU data for dense reconstruction of indoor environments
- In ICRA 2019 (Montreal), workshop on 'Dataset Generation and Benchmarking of SLAM Algorithms for Robotics and VR/AR' will be held!. We are pretty sure that there will be many 'new' and 'hot' datasets intruduced at the workshop.
- We add evaluation section (Tools for trajectory and SLAM methods evaluation)
- We add a new UAV dataset, UZH-FPV Drone Racing Dataset, which aims high speed state estimation using RGB, Event, and IMU.
- Complex Urban Dataset (KAIST) now includes stereo camera images! (published in IJRR 2019)
- Add datasets introduced in CVPR 2019
- Waymo (https://waymo.com/open)
- Nuscenes (https://www.nuscenes.org/)
- ...
- Add Simulation datast category
- CARLA
- Airsim
- Syncity
-
- Evaluation Methods of SLAM
-
- Odometry: Dataset for odometry Benchmark
- Mapping: Dataset for mapping task
- Place Recognition: Dataset gives correspondences of places (images)
- Localization: Dataset for metric-level localization
- Perception: Dataset with semantic labels / correspondences
-
- Large-scale: City-scale map, kilometer level Map
- Long-term: Multi-session, long-term data collection
- Map Complexity: Variation of mapping structures
- Extreme Condition: Extreme environment, motions
-
- Vehicle (Veh): Commercial Vehicle (Four-wheeled on the road)
- Mobile robot (Mob): Mobile Robots (Ex. Husky, Rover.. )
- Unmanned Aerial Vehicle (UAV): Unmanned aerial robots include drone.
- Autonomous Underwater Vehicle (AUV): Underwater robots include ROV for simplicity.
- Unmanned Surface Vehicle (USV): Water surface vehicle such as canoe and boat.
- Hand-held Device (Hand): Hand-held platform by human
-
- Urban: City, campus, town, and infrastructures
- Indoor: Indoor environment
- Terrain: Forest, Rough terrain, underground, lake and farm
- Underwater: Underwater floor, cave
- Simulation: Simulation Scene
| Shortname | Affiliation | Year | Platform | Publication | Environment | GT-Pose | GT-Map | IMU | GPS | Labels | Lidar | Cameras | RGBD | Event | Radar | Sonar | DVL | Other |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4Seasons Dataset | Technical University of Munich | 2020 | Veh | GCPR | Outdoor | O | O | O | O | O | O | O | O | |||||
| M2DGR | Shanghai Jiaotong University | 2021 | Mob | RA-L | Indoor + Outdoor | O | O | O | O | O | O | O | ||||||
| TartanAir | CMU | 2020 | UAV | IROS | Simulation | O | O | O | O | O | ||||||||
| VECtor Dataset | ShanghaiTech University | 2022 | Hand | RA-L | Indoor + Outdoor | O | O | O | O | O | O | |||||||
| Hilti SLAM Dataset | Hilti, Oxford, UZH | 2022 | Hand | Indoor + Outdoor | O | O | O | O | O | |||||||||
| MADMAX Mars Dataset | 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 | |||||||
| FinnForest Dataset | Tampere University | 2020 | Veh | RAS journal | Forest, Terrain | O | O | Multiple Stereo Pairs ; Sampling Rate(40, 13, and 8Hz) | ||||||||||
| PennCOSYVIO Dataset | University of Pennsylvania | 2017 | Hand | ICRA | Indoor + Outdoor | O | O | O | ||||||||||
| ICL Dataset | Imperial College | 2019 | Hand, MAV | ICRA | Indoor | O | O | O | ||||||||||
| UZH-FPV Drone Racing | UZH, ETH | 2019 | UAV | ICRA | Indoor, Urban | O | O | O | O | |||||||||
| FMDataset | Hangzhou Dianzi / Tsinghua | 2019 | Hand | ICME | Indoor | O | O | |||||||||||
| Rosario Dataset | CONICET-UNR | 2019 | Mob | IJRR | Terrain | O | O | O | Encoder | |||||||||
| Collaborative SLAM Dataset (CSD) | Oxford | 2018 | Hand | TVCG/ISMAR | Indoor | O | O | O | O | O | Tango (Asus ZenFone AR) | |||||||
| ADVIO Dataset | Aalto U | 2018 | Hand | ECCV | Urban | O | O | O | O | iPhone, Tango, Pixel | ||||||||
| DeepIO Dataset | Oxford | 2018 | Hand | Arxiv | Indoor | O | O | |||||||||||
| Aqualoc Dataset | ONERA-DTIS | 2018 | ROV | IROS WS | Underwater | O | O | O | Pressure Sensor | |||||||||
| InteriorNet | Imperial College | 2018 | Hand | BMVC | Indoor | O | O | O | O | O | O | O | Texture, Lighting, Context, Optical Flow | |||||
| SPO Dataset | TUM, Karlsruhe | 2018 | Hand | Arxiv | Urban | O | O | Plenoptic Camera | ||||||||||
| Complex Urban | KAIST-IRAP | 2018 | Veh | ICRA | Urban | O | O | O | O | O | Encoder | |||||||
| KAIST Day/Night | KAIST-RCV | 2018 | Veh | T-ITS | Urban | O | O | O | O | O | O | Thermal Camera | ||||||
| TUM-Visual-Inertial | TUM | 2018 | Hand | Arxiv | Indoor, Urban | O | O | O | ||||||||||
| Multi Vech Event | Upenn | 2018 | Veh | RA-L | Urban | O | O | O | O | O | O | |||||||
| VI Canoe | UIUC | 2018 | USV | IJRR | Terrain | O | O | O | O | |||||||||
| MPO-Japan | ETH-RPG | 2017 | UAV / Hand | IJRR | Indoor | O | O | O | O | |||||||||
| Underwater Cave | UDG | 2017 | AUV | IJRR | Underwater | O | O | O | O | O | Profiling Sonar | |||||||
| Robot @ Home | MRPT | 2017 | Mob | IJRR | Indoor | O | O | O | O | O | Semantic Labels | |||||||
| Zurich Urban MAV | ETH-RPG | 2017 | UAV | IJRR | Urban | O | O | O | O | Streetview images | ||||||||
| Chilean Underground | Trimble | 2017 | Mob | IJRR | Terrain (Underground) | O | O | O | O | Encoder | ||||||||
| SceneNet RGB-D | Imperial | 2017 | Hand | ICCV | Indoor | O | O | O | ||||||||||
| Symphony Lake | Georgia Tech | 2017 | USV | IJRR | Terrain (Lake) | O | O | O | O | PTZ camera, Longterm | ||||||||
| Agricultural robot | Bonn | 2017 | Mob | IJRR | Terrain | O | O | O | O | O | O | Multispectral camera | ||||||
| Beach Rover | TEC-MMA | 2017 | Mob | Terrain | O | O | O | O | O | O | Encoder | |||||||
| EuRoC | ETH-ASL | 2016 | UAV | IJRR | Indoor | O | O | O | O | |||||||||
| Cartographer | 2016 | Hand | ICRA | Indoor | O | O | O | |||||||||||
| TUM-Mono | TUM | 2016 | Hand | Arxiv | Indoor, Urban | O | Photometric Calibration | |||||||||||
| Cityscape | Daimler AG | 2016 | Veh | CVPR | Urban | O | O | O | O | |||||||||
| Solar-UAV | ETHZ | 2016 | UAV | CVPR | Terrain | O | O | O | O | O | ||||||||
| CoRBS | DFKI | 2016 | Hand | WACV | Indoor | O | O | O | ||||||||||
| Oxford-robotcar | Oxford | 2016 | Veh | IJRR | Urban | O | O | O | O | O | ||||||||
| NCLT | UMich | 2016 | Mob | IJRR | Urban | O | O | O | O | FOG | ||||||||
| RPG-event | Kyushu U | 2016 | Veh | IROS | Urban, Terrain | O | O | O | O | FARO 3D | ||||||||
| CCSAD | CIMAT | 2015 | Veh | CAIP | Urban | O | O | O | ||||||||||
| TUM-Omni | TUM | 2015 | Hand | IROS | Indoor, Urban | O | ||||||||||||
| Augmented ICL-NUIM | Redwood | 2015 | Hand | CVPR | Indoor | O | O | O | ||||||||||
| Cambridge Landmark | Cambridge | 2015 | Hand | ICCV | Urban | O | O | O | ||||||||||
| ICL-NUIM | Imperial | 2014 | Hand | ICRA | Indoor | O | O | O | ||||||||||
| MRPT-Malaga | MRPT | 2014 | Veh | AR | Urban | O | O | O | O | |||||||||
| KITTI | KIT | 2013 | Veh | IJRR | Urban | O | O | O | O | O | O | |||||||
| Canadian Planetary | UToronto | 2013 | Mob | IJRR | Terrain | O | O | O | O (sensor) | O | ||||||||
| Microsoft 7 scenes | Microsoft | 2013 | Hand | CVPR | Indoor | O | O | O | ||||||||||
| SeqSLAM | QUT | 2012 | Veh | ICRA | Urban | O | O | |||||||||||
| ETH-challenging | ETH-ASL | 2012 | Hand | IJRR | Urban, Terrain | O | O | O | O | O | ||||||||
| TUM-RGBD | TUM | 2012 | Hand / Mob | IROS | Indoor | O | O | O | ||||||||||
| ASRL-Kagara-airborne | UToronto | 2012 | UAV | FSR | Terrain | O | O | O | ||||||||||
| Devon Island Rover | UToronto | 2012 | Mob | IJRR | Terrain | O | O | O | Sunsensor, Inclinometer | |||||||||
| ACFR Marine | ACFR | 2012 | AUV | Underwater | O | O | O | O | O | |||||||||
| UTIAS Multi-Robot | UT-IAS | 2011 | Mob | IJRR | Urban | O | O | |||||||||||
| Ford Campus | UMich | 2011 | Veh | IJRR | Urban | O | O | O | O | O | ||||||||
| San francisco | Stanford | 2011 | Veh | CVPR | Urban | O | O | O | O | O | DMI | |||||||
| Annotated-laser | NTU | 2011 | Veh | IJRR | Urban | O | O | O | O | |||||||||
| MIT-DARPA | MIT | 2010 | Veh | IJRR | Urban | O | O | O | O | O | O | |||||||
| St Lucia Stereo | UToronto | 2010 | Veh | ACRA | Urban | O | O | O | ||||||||||
| St Lucia Multiple Times | QUT | 2010 | Veh | ICRA | Urban | O | O | |||||||||||
| Marulan | ACFR | 2010 | Mob | IJRR | Terrain | O | O | O | O | O | O | IR | ||||||
| COLD | KTH | 2009 | Hand | IJRR | Indoor | O | O | O | O | |||||||||
| NewCollege | Oxford-Robot | 2009 | Mob | IJRR | Urban | O | O | O | O | O | ||||||||
| Rawseeds-indoor | Milano | 2009 | Mob | IROSW | Indoor | O | O | O | O | O | O | |||||||
| Rawseeds-outdoor | Milano | 2009 | Mob | IROSW | Urban | O | O | O | O | O | O | O | ||||||
| FABMAP | Oxford-Robot | 2008 | Veh | IJRR | Urban | O | O |
Evaluation methods for SLAM benchmarks
- Trajectory Evaluation with Alignment [Paper], [Code]
- Python package for the evaluation of odometry and SLAM [Code]
- SLAMBench 3.0: Systematic Automated Reproducible Evaluation of SLAM Systems for Robot Vision Challenges and Scene Understanding [Paper], [Code]
- OpenVINS ov_eval Trajectory Evaulation and Alignment, Timing, and Plotting [Paper], [Docs], [Code]
Dataset for odometry Benchmark
- FinnForest Dataset
- ICL Dataset
- UZH-FPV Drone Racing
- TUM-Visual-Inertial
- Visual-Inertial Canoe Dataset
- Multi Vehicle Stereo Event Camera Dataset
- Zurich Urban Micro Aerial Vehicle Dataset
- EuRoC MAV Dataset
- TUM Monocular Cameras Dataset
- Event-Camera Dataset and Simulator
- TUM Omnidirectional Cameras Dataset
- ICL-NUIM RGBD Dataset
- TUM RGB-D SLAM Dataset and Benchmark
- Google Cartographer
- ADVIO Dataset
- Deep Inertial Odometry Dataset
- Aqualoc Underwater Dataset
- Rosario Agricultural Dataset
- Stereo Plenoptic Odometry Dataset
- MADMAX Mars Dataset
- Hilti SLAM Dataset
- VECtor Dataset
Dataset for mapping task
- Collaborative SLAM Dataset (CSD)
- Complex Urban
- Multi-modal Panoramic 3D Outdoor Dataset (MPO)
- Underwater Caves SONAR and Vision Dataset
- Chilean Underground Mine Dataset
- Oxford Robotcar Dataset
- University of Michigan North Campus Long-Term (NCLT) Vision and LIDAR Dataset
- Málaga Stereo and Laser Urban Data Set
- KITTI Vision Benchmark Suite
- Challenging data sets for point cloud registration algorithms
- ACFR Marine Robotics Dataset
- Ford Campus Vision and Lidar Dataset
- InteriorNet
- FMDataset
- MADMAX Mars Dataset
Dataset gives correspondences of places (images)
- Visual-Inertial Canoe Dataset
- Symphony Lake Dataset
- Alderley Day/Night Dataset
- St Lucia Multiple Times of Day
- New College Vision and Laser Data Set
- FABMAP Dataset
Dataset for metric-level localization
- ICL Dataset
- Cambridge Landmark Dataset
- KITTI Vision Benchmark Suite
- Microsoft 7 scenes
- San Francisco Landmark Dataset
- MADMAX Mars Dataset
Dataset with semantic labels / correspondences
- KAIST Day/Night Dataset
- Robot @ Home Dataset
- SceneNet RBG-D Dataset
- Sugar Beets 2016, Agricultural Robot Dataset
- CityScapes Dataset
- KITTI Vision Benchmark Suite
- Multi-Sensor Perception (Marulan) Dataset
- InteriorNet
City-scale map, kilometer level Map
- Complex Urban
- Multi Vehicle Stereo Event Camera Dataset
- Multi-modal Panoramic 3D Outdoor Dataset (MPO)
- CityScapes Dataset
- Solar-powered UAV Sensing and Mapping Dataset
- Oxford Robotcar Dataset
- CCSAD (Stereo Urban) Dattaset
- Málaga Stereo and Laser Urban Data Set
- KITTI Vision Benchmark Suite
- Kagaru Airborne Stereo Dataset Dataset
- ACFR Marine Robotics Dataset
Multi-session, long-term data collection
- FinnForest Dataset
- KAIST Day/Night Dataset
- Visual-Inertial Canoe Dataset
- Symphony Lake Dataset
- Oxford Robotcar Dataset
- University of Michigan North Campus Long-Term (NCLT) Vision and LIDAR Dataset
- Alderley Day/Night Dataset
- St Lucia Multiple Times of Day
Variation of mapping structures
- Complex Urban
- Multi Vehicle Stereo Event Camera Dataset
- Multi-modal Panoramic 3D Outdoor Dataset (MPO)
- Málaga Stereo and Laser Urban Data Set
- KITTI Vision Benchmark Suite
- Challenging data sets for point cloud registration - algorithms
Extreme environment, motions
- FinnForest Dataset
- UZH-FPV Drone Racing
- Underwater Caves SONAR and Vision Dataset: Underwater Environment
- Chilean Underground Mine Dataset: Underground Environment
- CityScapes Dataset: Foggy Scene
- EuRoC MAV Dataset: Fast motion
- Multi-Sensor Perception (Marulan) Dataset : Smoky, dust, and Rain condition
Commercial Vehicle (Four-wheeled on the road)
- FinnForest Dataset
- Complex Urban Dataset
- Multi Vehicle Stereo Event Camera Dataset
- KAIST Day/Night Dataset
- Multi-modal Panoramic 3D Outdoor Dataset (MPO)
- Oxford Robotcar Dataset
- CityScapes Dataset
- CCSAD (Stereo Urban) Dattaset
- Málaga Stereo and Laser Urban Data Set
- KITTI Vision Benchmark Suite
- Day and Night with Lateral Pose Change Dataset
- Alderley Day/Night Dataset
- Annotated-laser Dataset (Link Broken)
- San Francisco Landmark Dataset
- Ford Campus Vision and Lidar Dataset
- St Lucia Stereo Vehicular Dataset
- St Lucia Multiple Times of Day
- MIT DARPA Urban Challenge Dataset
- FABMAP Dataset
Mobile Robots (Ex. Husky, Rover.. )
- Rosario Dataset
- Sugar Beets 2016, Agricultural Robot Dataset
- Chilean Underground Mine Dataset
- Katwijk Beach Planetary Rover Dataset
- Robot @ Home Dataset
- University of Michigan North Campus Long-Term (NCLT) Vision and LIDAR Dataset
- Rawseeds In/Outdoor Dataset
- Canadian Planetary Emulation Terrain 3D Mapping Dataset
- Devon Island Rover Navigation Dataset
- Multi-Robot Cooperative Localization and Mapping Dataset
- Multi-Sensor Perception (Marulan) Dataset
- TUM RGB-D SLAM Dataset and Benchmark
- New College Vision and Laser Data Set
- MADMAX Mars Dataset
Unmanned aerial robots include drone
- ICL Dataset
- UZH-FPV Drone Racing
- Zurich Urban Micro Aerial Vehicle Dataset
- Event-Camera Dataset and Simulator
- Solar-powered UAV Sensing and Mapping Dataset
- EuRoC MAV Dataset
- Kagaru Airborne Stereo Dataset Dataset
Underwater robots include ROV for simplicity
Water surface vehicle such as canoe and boat
Hand-held platform by human
- Collaborative SLAM Dataset (CSD)
- SceneNet RBG-D Dataset
- Event-Camera Dataset and Simulator
- Comprehensive RGB-D Benchmark (CoRBS)
- Augmented ICL-NUIM Reconstruction Dataset
- ICL-NUIM RGBD Dataset
- Challenging data sets for point cloud registration algorithms
- Cosy Localization Database (COLD)
- ADVIO Dataset
- Deep Inertial Odometry Dataset
- InteriorNet
- Stereo Plenoptic Dataset
- FMDataset
- Hilti SLAM Dataset
City, campus, town, and infrastructures
- UZH-FPV Drone Racing
- ADVIO Dataset
- Stereo Plenoptic Dataset
- KAIST Day/Night Dataset
- TUM-Visual-Inertial
- Complex Urban
- Multi Vehicle Stereo Event Camera Dataset
- Zurich Urban Micro Aerial Vehicle Dataset
- TUM Monocular Cameras Dataset
- CityScapes Dataset
- Oxford Robotcar Dataset
- University of Michigan North Campus Long-Term (NCLT) Vision and LIDAR Dataset
- Event-Camera Dataset and Simulator
- CCSAD (Stereo Urban) Dattaset
- TUM Omnidirectional Cameras Dataset
- Cambridge Landmark Dataset
- Málaga Stereo and Laser Urban Data Set
- KITTI Vision Benchmark Suite
- Alderley Day/Night Dataset
- Challenging data sets for point cloud registration algorithms
- Multi-Robot Cooperative Localization and Mapping Dataset
- Ford Campus Vision and Lidar Dataset
- San Francisco Landmark Dataset
- Annotated-laser Dataset (Link Broken)
- MIT DARPA Urban Challenge Dataset
- St Lucia Stereo Vehicular Dataset
- St Lucia Multiple Times of Day
- New College Vision and Laser Data Set
- Rawseeds In/Outdoor Dataset
- FABMAP Dataset
Indoor environment
- ICL Dataset
- FMDataset
- UZH-FPV Drone Racing
- Collaborative SLAM Dataset (CSD)
- InteriorNet
- TUM-Visual-Inertial
- Multi-modal Panoramic 3D Outdoor Dataset (MPO)
- Robot @ Home Dataset
- SceneNet RBG-D Dataset
- EuRoC MAV Dataset
- TUM Monocular Cameras Dataset
- Comprehensive RGB-D Benchmark (CoRBS)
- TUM Omnidirectional Cameras Dataset
- Augmented ICL-NUIM Reconstruction Dataset
- ICL-NUIM RGBD Dataset
- Microsoft 7 scenes
- TUM RGB-D SLAM Dataset and Benchmark
- Cosy Localization Database (COLD)
- Rawseeds In/Outdoor Dataset
- Google Cartographer
Rough terrain, underground, lake and farm
- FinnForest Dataset
- Rosario Agricultural Dataset
- Visual-Inertial Canoe Dataset
- Chilean Underground Mine Dataset
- Symphony Lake Dataset
- Sugar Beets 2016, Agricultural Robot Dataset
- Katwijk Beach Planetary Rover Dataset
- Solar-powered UAV Sensing and Mapping Dataset
- Event-Camera Dataset and Simulator
- Canadian Planetary Emulation Terrain 3D Mapping Dataset
- Challenging data sets for point cloud registration - algorithms
- Kagaru Airborne Stereo Dataset Dataset
- Devon Island Rover Navigation Dataset
- Multi-Sensor Perception (Marulan) Dataset
- MADMAX Mars Dataset
Underwater floor, cave
Simulation Scene
Please Feel free to send a pull request to modify the list or add datasets.
To the extent possible under law, Younggun Cho has waived all copyright and related or neighboring rights to this work.