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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,692 datasets
Volume 1 of the Texas Coastal Hazards Atlas contains geospatial data for hurricane preparedness and coastal management along the state's southeast coast. The dataset, authored by James Gibeaut and hosted by the Texas Data Repository, includes sections on bay erosion, hurricane surge modeling, shoreline projections, and environmental sensitivity. It was last updated on October 15, 2025.
October 1986 data from the NASA ER-2 Cloud Lidar System during the First ISCCP Regional Experiment (FIRE) Cirrus campaign. It contains calculated cloud top height and ground height measurements. The data was collected by NASA's Langley Research Center Atmospheric Science Data Center (LARC_ASDC).
Ground-penetrating radar, helicopter EM bird surveys, and in-situ measurements characterize snow layers, ice thickness, and surface roughness near Ross Island. Data collection focused on validating satellite radar measurements across the McMurdo Ice Shelf and Sound. The work was conducted by SCIOPS from 2009 to 2012, with a significant update in 2011 for sea ice studies.
Lidar measurements from a High Spectral Resolution Lidar instrument deployed at Eureka, Nunavut, Canada. The dataset includes fields for aerosol backscatter and circular depolarization ratio, is updated daily, and represents an ongoing collection. The instrument was deployed by Ed Eloranta at the University of Wisconsin.
Four intensive field campaigns between 1986 and 1992 collected coordinated airborne, satellite, and surface observations to study cirrus and marine stratocumulus cloud systems. The Cloud Lidar System aboard the NASA ER-2 airplane recorded cloud altitudes, layer boundaries, and geophysical location. Data was produced by the LARC_ASDC organization.
Four intensive field observation periods collected lidar data on cirrus and marine stratocumulus clouds between 1986 and 1992. The dataset contains raw lidar return signals from coordinated satellite, airborne, and surface observations, processed by the University of Utah and archived by NASA's LARC ASDC. The primary goal was to improve cloud and radiation parameterizations used in general circulation models.
University of Utah lidar data from the First ISCCP Regional Experiment (FIRE) Cirrus Phase II field campaign. The dataset contains raw, background-subtracted lidar return signals for studying cirrus cloud properties and life cycles. Observations were conducted during an intensive field period from November 13 to December 7, 1991.
NASA ER-2 aircraft lidar data from the 1992 ASTEX campaign measured cloud altitudes and layer structure over the eastern North Atlantic Ocean. The Cloud Lidar System instrument recorded geophysical location, time, and heights for up to five cloud layers across four spectral channels. This dataset was collected by NASA's LARC_ASDC organization during the intensive field observation period from June 1 to June 28, 1992.
November 13 to December 7, 1991 data from the Second FIRE Cirrus intensive field observation in Coffeyville, Kansas. The dataset contains images of cirrus clouds captured by a High Spectral Resolution Lidar, showing backscatter and depolarization ratio. It was collected by the LARC_ASDC organization to study cloud properties and interactions for improving climate models.
U2UData-2 is a large-scale simulation dataset for swarm UAV autonomous flight, specifically designed for Long-Horizon tasks. It was created by author fengtt42 and last updated on the Hugging Face platform in September 2025. The dataset addresses limitations in existing methods by modeling complex dependencies and dynamic goal shifts required for real-world deployment.
6,700 samples collected over 67 distinct terrains for robotic manipulation of granular materials. The dataset, created by pthangeda, includes terrain metadata, RGB images, and 16-bit depth images of terrains before scooping. It was last updated on October 4, 2024.
U2UData-2 is a large-scale dataset for swarm Unmanned Aerial Vehicle autonomous flight focused on Long-Horizon tasks. It was created by author fengtt42 to address limitations in existing methods that fail in real-world deployment for complex, non-sequential missions. The dataset was last updated in September 2025.
2,115 drone images of illegal waste dumpsites collected as part of the Raven Scan project. Images have a resolution of 1280 x 1280 pixels and are captured from a nadir perspective. The dataset is hosted by INS-IntelligentNetworkSolutions and was last updated on December 5, 2024.
SnowEx23 Bonanza Creek Experimental Forest Terrestrial Lidar Scans Raw V001 contains unprocessed point cloud data from terrestrial lidar scans collected during the SnowEx 2023 campaign. NSIDC_CPRD collected the data in October 2022 (snow-off) and March 2023 (snow-on) near Fairbanks, Alaska. Digital terrain models derived from this raw data are available as a separate dataset.
Snow water equivalent and snow density raster data derived from lidar and ground-penetrating radar measurements. The data was collected during the NASA SnowEx 2020 field campaign in Grand Mesa, Colorado. It is provided by NSIDC_CPRD.
CALIPSO satellite data provides the distribution of blowing snow properties over Antarctica using back-scatter retrievals. This Level 2 product was created by NASA and the French CNES from the CALIOP instrument. Data collection for this version is complete, with the satellite launched in 2006 and last updated in 2020.
A 126-file raster dataset provides a discretized map of likely flood extent for the Austin-Round Rock Combined Statistical Area. The files were generated using the Height Above Natural Drainage (HAND) method on 1-meter resolution LIDAR data, processed with open-source TauDEM and Python GIS tools. Author Daniel Hardesty Lewis published the dataset via the Texas Data Repository on March 18,ๆไปฌๅ็ฐ 2024.
A multimodal question-answering dataset derived from the nuScenes-QA dataset for autonomous driving scenarios. It contains 2,229 training and 659 validation samples for day scenes, and 659 training and 659 validation samples for night scenes. The dataset was created by KevinNotSmile for evaluation in a research paper and was last updated on January 19, 2024.
PHUMA is a physically-grounded humanoid locomotion dataset created by DAVIAN-Robotics. It leverages large-scale human motion data, processed through physics-constrained retargeting to overcome physical artifacts. The dataset was last updated in November 2025.
Oxford city centre was traversed by an autonomous Nissan LEAF vehicle between May 2014 and December 2015. The dataset contains nearly 20 million images from six cameras, along with LIDAR, GPS, and INS data, totaling over 1,000 km of recorded traffic data. It was collected by the OPR-Project and hosted on Hugging Face.