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1 | Configuration | Ground Truth | Sensor Information | External Information | |||||||||||||||||||||
2 | Shortname | Affiliation | Year | Platform | Publication | Environment | Pose | Map | IMU | GPS | Labels | 2D Lidar | 3D Lidar | Mono | Stereo | Omni | RGBD | Event | Radar | Sonar | DVL | Other | Link | Ref | |
3 | ADVIO Dataset | Aalto U | 2018 | Hand | ECCV | Urban | O | O | O | O | iPhone, Tango, Pixel | https://github.com/AaltoVision/ADVIO | Saraee, Elham, Mona Jalal, and Margrit Betke. "SAVOIAS: A Diverse, Multi-Category Visual Complexity Dataset." arXiv preprint arXiv:1810.01771 (2018). | ||||||||||||
4 | DeepIO Dataset | Oxford | 2018 | Hand | Arxiv | Indoor | O | O | http://deepio.cs.ox.ac.uk/ | Chen, Changhao, et al. "OxIOD: The Dataset for Deep Inertial Odometry." arXiv preprint arXiv:1809.07491 (2018). | |||||||||||||||
5 | Aqualoc Dataset | ONERA-DTIS | 2018 | ROV | IROS WS | Underwater | O | O | O | Pressure Sensor | http://www.lirmm.fr/aqualoc/ | Ferrera, Maxime, et al. "The Aqualoc Dataset: Towards Real-Time Underwater Localization from a Visual-Inertial-Pressure Acquisition System." arXiv preprint arXiv:1809.07076 (2018). | |||||||||||||
6 | Rosario Dataset | CONICET-UNR | 2018 | Mob | IJRR (Under Review) | Terrain | O | O | O | O | Encoder | http://www.cifasis-conicet.gov.ar/robot/doku.php | Taihú Pire, Martín Mujica, Javier Civera and Ernesto Kofman. The Rosario Dataset: Multisensor Data for Localization and Mapping in Agricultural Environments. In: International Journal of Research Robotics, 2018. (Under Revision) | ||||||||||||
7 | InteriorNet | Imperial College | 2018 | Hand | BMVC | Indoor | O | O | O | O | O | O | O | Texture, Lighting, Context, Optical Flow | https://interiornet.org/ | Li, Wenbin, et al. "InteriorNet: Mega-scale multi-sensor photo-realistic indoor scenes dataset." arXiv preprint arXiv:1809.00716 (2018). | |||||||||
8 | SPO Dataset | TUM, Karlsruhe | 2018 | Hand | Arxiv | Urban | O | O | O | Plenoptic Camera | https://www.hs-karlsruhe.de/odometry-data/ | N. Zeller, F. Quint, U. Stilla (2018): A Synchronized Stereo and Plenoptic Visual Odometry Dataset, arXiv:1807.09372. | |||||||||||||
9 | KAIST Day/Night | KAIST-RCV | 2018 | Veh | T-ITS | Urban | O | O | O | O | O | O | Thermal Camera | https://sites.google.com/view/multispectral/home | Choi, Yukyung, et al. "KAIST Multi-Spectral Day/Night Data Set for Autonomous and Assisted Driving." IEEE Transactions on Intelligent Transportation Systems 19.3 (2018): 934-948. | ||||||||||
10 | TUM-Visual-Inertial | TUM | 2018 | Hand | Arxiv | Indoor, Urban | O | O | O | https://vision.in.tum.de/data/datasets/visual-inertial-dataset | Schubert, David, et al. "The TUM VI Benchmark for Evaluating Visual-Inertial Odometry." arXiv preprint arXiv:1804.06120 (2018). | ||||||||||||||
11 | Complex Urban | KAIST-IRAP | 2018 | Veh | ICRA | Urban | O | O | O | O | O | O | Encoder | http://irap.kaist.ac.kr/dataset/ | Complex Urban LiDAR Data Set | ||||||||||
12 | Multi Vech Event | Upenn | 2018 | Veh | RA-L | Urban | O | O | O | O | O | O (stereo) | https://daniilidis-group.github.io/mvsec/ | Zhu, Alex Zihao, et al. "The Multi Vehicle Stereo Event Camera Dataset: An Event Camera Dataset for 3D Perception." IEEE Robotics and Automation Letters (2018). | |||||||||||
13 | VI Canoe | UIUC | 2018 | USV | IJRR | Terrain | O | O | O | O | https://databank.illinois.edu/datasets/IDB-9342111 | Miller, Martin, Soon-Jo Chung, and Seth Hutchinson. "The Visual–Inertial Canoe Dataset." The International Journal of Robotics Research 37.1 (2018): 13-20. | |||||||||||||
14 | RPG-event | ETH-RPG | 2017 | UAV / Hand | IJRR | Indoor | O | O | O | O | http://rpg.ifi.uzh.ch/davis_data.html | Mueggler, Elias, et al. "The event-camera dataset and simulator: Event-based data for pose estimation, visual odometry, and SLAM." The International Journal of Robotics Research 36.2 (2017): 142-149. | |||||||||||||
15 | Underwater Cave | UDG | 2017 | AUV | IJRR | Underwater | O | O | O | O | O | Profiling Sonar | http://cirs.udg.edu/caves-dataset/ | Mallios, Angelos, et al. "Underwater caves sonar data set." The International Journal of Robotics Research (2017): 0278364917732838. | |||||||||||
16 | Robot @ Home | MRPT | 2017 | Mob | IJRR | Indoor | O | O | O | O | O | Semantic Labels | http://mapir.isa.uma.es/mapirwebsite/index.php/mapir-downloads/203-robot-at-home-dataset | Ruiz-Sarmiento, J. R., Cipriano Galindo, and J. González-Jiménez. "Robot@ home, a robotic dataset for semantic mapping of home environments." The International Journal of Robotics Research 36.2 (2017): 131-141. | |||||||||||
17 | Zurich Urban MAV | ETH-RPG | 2017 | UAV | IJRR | Urban | O | O | O | O | Streetview images | http://rpg.ifi.uzh.ch/zurichmavdataset.html | The Zurich Urban Micro Aerial Vehicle Dataset | ||||||||||||
18 | Chilean Underground | Trimble | 2017 | Mob | IJRR | Terrain (Underground) | O | O | O | O | Encoder | http://dataset.amtc.cl/# | Leung, Keith, et al. "Chilean underground mine dataset." The International Journal of Robotics Research 36.1 (2017): 16-23. | ||||||||||||
19 | SceneNet RGB-D | Imperial | 2017 | Hand | ICCV | Indoor | O | O | O | https://robotvault.bitbucket.io/scenenet-rgbd.html | McCormac, John, et al. "Scenenet rgb-d: Can 5m synthetic images beat generic imagenet pre-training on indoor segmentation." The IEEE International Conference on Computer Vision (ICCV). Vol. 1. 2017. | ||||||||||||||
20 | Symphony Lake | Georgia Tech | 2017 | USV | IJRR | Terrain (Lake) | O | O | O | O | PTZ camera, Longterm | http://dream.georgiatech-metz.fr/?q=node/79 | Griffith, Shane, Georges Chahine, and Cédric Pradalier. "Symphony Lake Dataset." The International Journal of Robotics Research 36.11 (2017): 1151-1158. | ||||||||||||
21 | Agricultural robot | Bonn | 2017 | Mob | IJRR | Terrain | O | O | O | O | O | O | Multispectral camera | http://www.ipb.uni-bonn.de/data/sugarbeets2016/ | Chebrolu, Nived, et al. "Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields." The International Journal of Robotics Research 36.10 (2017): 1045-1052. | ||||||||||
22 | Beach Rover | TEC-MMA | 2017 | Mob | Terrain | O | O | O | O | O | O | O | Encoder | https://robotics.estec.esa.int/datasets/katwijk-beach-11-2015/ | Hewitt, Robert A., et al. "The Katwijk beach planetary rover dataset." The International Journal of Robotics Research (2017): 0278364917737153. | ||||||||||
23 | EuRoc | ETH-ASL | 2016 | UAV | IJRR | Indoor | O | O | O | O | O | http://projects.asl.ethz.ch/datasets/doku.php?id=kmavvisualinertialdatasets | M. Burri, J. Nikolic, P. Gohl, T. Schneider, J. Rehder, S. Omari, M. W. Achtelik, and R. Siegwart. The EuRoC Micro Aerial Vehicle Datasets. The International Journal of Robotics Research (IJRR), 2016. | ||||||||||||
24 | TUM-MONO | TUM | 2016 | Hand | Arxiv | Indoor, Urban | O | Photometric Calibration | https://vision.in.tum.de/data/datasets/mono-dataset | Engel, Jakob, Vladyslav Usenko, and Daniel Cremers. "A photometrically calibrated benchmark for monocular visual odometry." arXiv preprint arXiv:1607.02555 (2016). | |||||||||||||||
25 | Cityscape | Daimler AG | 2016 | Veh | CVPR | Urban | O | O | O | O | https://www.cityscapes-dataset.com/ | M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele. The Cityscapes Dataset for Semantic Urban Scene Understanding. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 | |||||||||||||
26 | Solar-UAV | ETHZ | 2016 | UAV | CVPR | Terrain | O | O | O | O | O | http://projects.asl.ethz.ch/datasets/doku.php?id=fsr2015 | P. Oettershagen, T. Stastny, T. Mantel, A. Melzer, K. Rudin, P. Gohl, G. Agamennoni, K. Alexis, and R. Siegwart. Long-Endurance Sensing and Mapping Using a Hand-Launchable Solar-Powered UAV. In Proceedings of International Conference on Field and Service Robotics (FSR), pages 441–454. Springer, 2016 | ||||||||||||
27 | CoRBS | DFKI | 2016 | Hand | WACV | Indoor | O | O | O | http://corbs.dfki.uni-kl.de/?pagerd_tumlltzzf42zsv6de7b9 | O. Wasenmuller, M. Meyer, and D. Stricker. CoRBS: Comprehensive RGB-D benchmark for SLAM using Kinect v2. In IEEE Winter Conference on Applications of Computer Vision (WACV), pages 1–7. IEEE, 2016 | ||||||||||||||
28 | Oxford-robotcar | Oxford | 2016 | Veh | IJRR | Urban | O | O | O | O | O | O | http://robotcar-dataset.robots.ox.ac.uk | Maddern, Will, et al. "1 year, 1000 km: The Oxford RobotCar dataset." The International Journal of Robotics Research (2016): 0278364916679498. | |||||||||||
29 | NCLT | UMich | 2016 | Mob | IJRR | Urban | O | O | O | O | O | FOG | http://robots.engin.umich.edu/nclt/ | Carlevaris-Bianco, Nicholas, Arash K. Ushani, and Ryan M. Eustice. "University of Michigan North Campus long-term vision and lidar dataset." The International Journal of Robotics Research 35.9 (2016): 1023-1035 | |||||||||||
30 | MPO-Japan | Kyushu U | 2016 | Veh | IROS | Urban, Terrain | O | O | O | O | O | FARO 3D | http://robotics.ait.kyushu-u.ac.jp/kurazume_lab/research-e.php?content=db | Jung, Hojung, et al. "Multi-modal panoramic 3D outdoor datasets for place categorization." Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on. IEEE, 2016. | |||||||||||
31 | CCSAD | CIMAT | 2015 | Veh | CAIP | Urban | O | O | O | http://aplicaciones.cimat.mx/Personal/jbhayet/ccsad-dataset | R. Guzman, J. B. Hayet, and R. Klette. Towards Ubiquitous Autonomous Driving: The CCSAD Dataset. In Conference on Computer Analysis of Images and Patterns (CAIP), pages 582–593. Springer, 2015. | ||||||||||||||
32 | TUM-Omni | TUM | 2015 | Hand | IROS | Indoor, Urban | O | O | https://vision.in.tum.de/data/datasets/omni-lsdslam | Caruso, David, Jakob Engel, and Daniel Cremers. "Large-scale direct slam for omnidirectional cameras." Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on. IEEE, 2015. | |||||||||||||||
33 | Augmented ICL-NUIM | Redwood | 2015 | Hand | CVPR | Indoor | O | O | O | http://redwood-data.org/indoor/index.html | Choi, Sungjoon, Qian-Yi Zhou, and Vladlen Koltun. "Robust reconstruction of indoor scenes." Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on. IEEE, 2015. | ||||||||||||||
34 | Cambridge Landmark | Cambridge | 2015 | Hand | ICCV | Urban | O | O | O | http://mi.eng.cam.ac.uk/projects/relocalisation/ | A. Kendall, M. Grimes, and R. Cipolla, “Posenet: A convolutional network for real-time 6-dof camera relocalization,” in ICCV, 2015. | ||||||||||||||
35 | ICL-NUIM | Imperial | 2014 | Hand | ICRA | Indoor | O | O | O | https://www.doc.ic.ac.uk/~ahanda/VaFRIC/iclnuim.html | A. Handa, T. Whelan, J. McDonald, and A. J. Davison. A Benchmark for RGB-D Visual Odometry, 3D Reconstruction and SLAM. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 1524–1531. IEEE, 2014 | ||||||||||||||
36 | MRPT-Malaga | MRPT | 2014 | Veh | AR | Urban | O | O | O | O | O | https://www.mrpt.org/robotics_datasets | J.L. Blanco-Claraco, F.A. Moreno-Dueñas, J. Gonzalez-Jimenez. “The Málaga Urban Dataset: High-rate Stereo and Lidars in a realistic urban scenario“, The International Journal of Robotics Research (IJRR), Feb 2014, vol. 33, no. 2, 207-214. (Bibtex) DOI: 10.1177/0278364913507326 (OnlineFirst; Draft PDF | ||||||||||||
37 | KITTI | KIT | 2013 | Veh | IJRR | Urban | O | O | O | O | O | O | O | O | http://www.cvlibs.net/datasets/kitti/index.php | A. Geiger, P. Lenz, C. Stiller, and R. Urtasun. Vision Meets Robotics: The KITTI Dataset. The International Journal of Robotics Research (IJRR), 32(11):1231–1237, 2013 | |||||||||
38 | Canadian Planetary | UToronto | 2013 | Mob | IJRR | Terrain | O | O | O | O | O | O | http://asrl.utias.utoronto.ca/datasets/3dmap/#Datasets | Tong, C., Gingras, D., Larose, K., Barfoot, T. D., and Dupuis, E. “The Canadian Planetary Emulation Terrain 3D Mapping Dataset.” International Journal of Robotics Research, 2013 | |||||||||||
39 | Microsoft 7 scenes | Microsoft | 2013 | Hand | CVPR | Indoor | O | O | O | https://www.doc.ic.ac.uk/~ahanda/VaFRIC/iclnuim.html | J. Shotton, B. Glocker, C. Zach, S. Izadi, A. Criminisi, and A. Fitzgibbon, “Scene coordinate regression forests for camera relocalization in rgb-d images,” in CVPR, June 2013. | ||||||||||||||
40 | SeqSLAM | QUT | 2012 | Veh | ICRA | Urban | O | O | https://wiki.qut.edu.au/display/cyphy/Open+datasets+and+software | M. J. Milford and G. F. Wyeth. SeqSLAM: Visual route-based navigation for sunny summer days and stormy winter nights. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 1643–1649. IEEE, 2012 | |||||||||||||||
41 | ETH-challenging | ETH-ASL | 2012 | Hand | IJRR | Urban, Terrain | O | O | O | O | O | http://projects.asl.ethz.ch/datasets/doku.php?id=laserregistration:laserregistration | F. Pomerleau, M. Liu, F. Colas, and R. Siegwart. Challenging data sets for point cloud registration algorithms. The International Journal of Robotics Research (IJRR), 31(14):1705–1711, 2012 | ||||||||||||
42 | TUM-RGBD | TUM | 2012 | Hand / Mob | IROS | Indoor | O | O | O | https://vision.in.tum.de/data/datasets/rgbd-dataset | J. Sturm, N. Engelhard, F. Endres, W. Burgard, and D. Cremers. A Benchmark for the Evaluation of RGB-D SLAM Systems. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 573–580. IEEE, 2012 | ||||||||||||||
43 | ASRL-Kagara-airborn | UToronto | 2012 | UAV | FSR | Terrain | O | O | O | http://asrl.utias.utoronto.ca/~mdw/kagarudataset.html | M. Warren, D. McKinnon, H. He, A. Glover, M. Shiel, and B. Upcroft. Large Scale Monocular Vision-only Mapping from a Fixed-Wing sUAS. In Proceedings of International Conference on Field and Service Robotics (FSR), pages 495–509. Springer, 2012 | ||||||||||||||
44 | Devon Island Rover | UToronto | 2012 | Mob | IJRR | Terrain | O | O | O | Sunsensor, Inclinometer | http://asrl.utias.utoronto.ca/datasets/devon-island-rover-navigation/ | Furgale, P. T., Carle, P., Enright, J., and Barfoot, T. D. “The Devon Island Rover Navigation Dataset.” International Journal of Robotics Research, 31(6):707–713, 2012 | |||||||||||||
45 | ACFR Marine | ACFR | 2012 | AUV | Underwater | O | O | O | O | O | http://marine.acfr.usyd.edu.au/datasets/ | ACFR dataset | |||||||||||||
46 | UTIAS Multi-Robot | UT-IAS | 2011 | Mob | IJRR | Urban | O | O | http://asrl.utias.utoronto.ca/datasets/mrclam/ | K. Y. K. Leung, Y. Halpern, T. D. Barfoot, and H. H. T. Liu. The UTIAS multi-robot cooperative localization and mapping dataset. The International Journal of Robotics Research (IJRR), 30(8):969–974, 2011 | |||||||||||||||
47 | Ford Campus | UMich | 2011 | Veh | IJRR | Urban | O | O | O | O | O | O | O | http://robots.engin.umich.edu/SoftwareData/Ford | G. Pandey, J. R. McBride, and R. M. Eustice. Ford Campus vision and LIDAR data set. The International Journal of Robotics Research (IJRR), 30(13):1543–1552, 2011 | ||||||||||
48 | San francisco | Stanford | 2011 | Veh | CVPR | Urban | O | O | O | O | O | O | O | DMI | https://sites.google.com/site/chenmodavid/datasets | Chen, David M., et al. "City-scale landmark identification on mobile devices." Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on. IEEE, 2011. | |||||||||
49 | Annotated-laser | NTU | 2011 | Veh | IJRR | Urban | O | O | O | O | http://any.csie.ntu.edu.tw/data | S. W. Yang, C. C. Wang, and C. Thorpe. The annotated laser data set for navigation in urban areas. The International Journal of Robotics Research (IJRR), 30(9):1095–1099, 2011 | |||||||||||||
50 | MIT-DARPA-Urban | MIT | 2010 | Veh | IJRR | Urban | O | O | O | O | O | O | O | http://grandchallenge.mit.edu/wiki/index.php?title=PublicData | A. S. Huang, M. Antone, E. Olson, L. Fletcher, D. Moore, S. Teller, and J. J. Leonard. A High-rate, Heterogeneous Data Set From The DARPA Urban Challenge. The International Journal of Robotics Research (IJRR), 29(13):1595–1601, 2010 | ||||||||||
51 | St Lucia Stereo | UToronto | 2010 | Veh | ACRA | Urban | O | O | O | http://asrl.utias.utoronto.ca/~mdw/uqstluciadataset.html | M. Warren, D. McKinnon, H. He, and B. Upcroft. Unaided Stereo Vision based Pose Estimation. In G. Wyeth and B. Upcroft, editors, Australasian Conference on Robotics and Automation (ACRA), Brisbane, 2010. Australian Robotics and Automation Association. | ||||||||||||||
52 | St Lucia Multiple Times | QUT | 2010 | Veh | ICRA | Urban | O | O | https://wiki.qut.edu.au/display/cyphy/St+Lucia+Multiple+Times+of+Day | A. J. Glover, W. P. Maddern, M. J. Milford, and G. F. Wyeth. FAB-MAP + RatSLAM: appearance-based SLAM for multiple times of day. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 3507–3512. IEEE, 2010 | |||||||||||||||
53 | Marulan | ACFR | 2010 | Mob | IJRR | Terrain | O | O | O | O | O | O | Infrared | http://sdi.acfr.usyd.edu.au/ | Peynot, Thierry, Steve Scheding, and Sami Terho. "The marulan data sets: Multi-sensor perception in a natural environment with challenging conditions." The International Journal of Robotics Research 29.13 (2010): 1602-1607. | ||||||||||
54 | COLD | KTH | 2009 | Hand | IJRR | Indoor | O | O | O | O | https://www.pronobis.pro/#data | A. Pronobis and B. Caputo. COLD: The CoSy Localization Database. The International Journal of Robotics Research (IJRR), 28(5):588–594, 2009. | |||||||||||||
55 | NewCollege | Oxford-Robot | 2009 | Mob | IJRR | Urban | O | O | O | O | http://www.robots.ox.ac.uk/NewCollegeData/ | M. Smith, I. Baldwin, W. Churchill, R. Paul, and P. Newman. The New College Vision and Laser Data Set. The International Journal of Robotics Research (IJRR), 28(5):595–599, 2009. | |||||||||||||
56 | Rawseeds-indoor | Milano | 2009 | Mob | IROSW | Indoor | O | O | O | O | O | O | O | O | http://www.rawseeds.org/home/category/benchmarking-toolkit/datasets/ | Bonarini, A, Burgard, W, Fontana, G. (2006) Rawseeds: Robotics advancement through web-publishing of sensorial and elaborated extensive data sets. In: Proceedings of IROS workshop on benchmarks in robotics research, Beijing, China, 2006. USA: IEEE. | |||||||||
57 | Rawseeds-outdoor | Milano | 2009 | Mob | IROSW | Urban | O | O | O | O | O | O | O | O | O | http://www.rawseeds.org/home/category/benchmarking-toolkit/datasets/ | Bonarini, A, Burgard, W, Fontana, G. (2006) Rawseeds: Robotics advancement through web-publishing of sensorial and elaborated extensive data sets. In: Proceedings of IROS workshop on benchmarks in robotics research, Beijing, China, 2006. USA: IEEE. | ||||||||
58 | FABMAP | Oxford-Robot | 2008 | Veh | IJRR | Urban | O | O | http://www.robots.ox.ac.uk/~mobile/IJRR_2008_Dataset/ | Cummins, Mark, and Paul Newman. "FAB-MAP: Probabilistic localization and mapping in the space of appearance." The International Journal of Robotics Research 27.6 (2008): 647-665. | |||||||||||||||
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