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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,688 datasets
NASA's MASTER instrument collected Level 1B and Level 2 data during 10 ER-2 aircraft flights from October 18 to November 13, 2024. The dataset includes georeferenced multispectral imagery across 50 bands and derived land surface temperature and emissivity products. It was produced by ORNL_CLOUD and distributed via NASA Earthdata.
A single orthophoto and Digital Surface Model (DSM) were captured on 10 February 2013 over biopiles and the nearby area at Casey Station, Antarctica. The data was created by Dr Arko Lucieer of TerraLuma and the University of Tasmania for the Australian Antarctic Division's Terrestrial and Nearshore Ecosystems research group. It was produced from UAV-based aerial photographs for a project on petroleum contaminant remediation.
Antarctic Specially Protected Area 135, Robinson Ridge, and Casey station were surveyed in January 2010 using a remote-controlled helicopter for aerial photography and differential GPS for terrain data. The dataset includes georeferenced photo mosaics, digital elevation models (DEMs), hillshades, and shapefiles outlining moss beds, streams, snowlines, and melt lake edges. Data collection was part of AAS Projects 1313 and 4036, led by Professor Sharon Robinson of the University of Wollongong.
An orthophoto and Digital Surface Model (DSM) of biopiles and the surrounding area at Casey Station, Antarctica, derived from UAV aerial photographs. The data was created by Dr Arko Lucieer of TerraLuma and the University of Tasmania for the Australian Antarctic Division's Terrestrial and Nearshore Ecosystems research group. The aerial photographs were captured on a single day, February 10, 2013.
An orthophoto and vector dataset documents a hydrocarbon remediation site at Casey Station, Antarctica, from February 10, 2013. The data includes a 1cm resolution orthophoto created from UAV imagery and two vector layers marking excavation and treatment barrier locations. It was produced by Dr. Arko Lucieer of TerraLuma and the University of Tasmania for the Australian Antarctic Division's Terrestrial and Nearshore Ecosystems research group.
Manual snow pit and ice core data, including temperature, density, salinity, and dO18, collected for a New Zealand Marsden Fund research grant. The dataset integrates measurements from snow water equivalent, differential GPS stations, automated weather stations, radiation sensors, UAV imagery, and SIMBA buoys. Data was gathered in McMurdo Sound between October and December 2022.
nuScenes Mini is a subset of the full nuScenes dataset for autonomous vehicle perception. It contains annotated sensor data from a vehicle equipped with cameras, LIDAR, and radar. The dataset was created by Motional (formerly nuTonomy) for research in autonomous driving.
NVIDIA provides a multimodal dataset for autonomous vehicle research, last updated on June 15, 2025. The dataset includes synthetic data, HD maps, and LiDAR point clouds. A download script is available for users with sufficient storage space.
A 2023 drone-based lidar survey of a mixed-conifer forest on Cle Elum Ridge, Washington, conducted on 6 March 2023 by the Natural Hazards Reconnaissance (RAPID) Facility. The dataset provides high-resolution point clouds at approximately 100 points per square meter, detailing vegetation structure and snow-on surface topography in areas with and without fuel-reduction treatments. It complements a 2021 survey to enable pre- and post-treatment comparisons of forest structure and snowpack.
Monthly mean profiles of aerosol optical properties are reported on a uniform spatial grid below 12km altitude. Data is derived from the CALIOP instrument on the CALIPSO satellite, a NASA and CNES partnership launched in 2006. The mission concluded in August 2023, with this specific product generated from version 5.00 Level 2 data.
Global stratospheric aerosol profiles derived from the CALIOP lidar instrument on the CALIPSO satellite. The dataset includes parameters like 532 nm total attenuated backscatter, particulate backscatter, extinction, and stratospheric aerosol optical depths on a uniform spatial grid. Data is produced by NASA and CNES from the CALIOP instrument, with the mission concluding in August 2023.
Monthly mean profiles of aerosol optical properties below 12 km altitude, generated from CALIOP lidar data. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission, a NASA and CNES partnership, collected this data from 2006 until its conclusion in 2023. This Level 3 product is derived from quality-screened, cloud-free columns of Version 5.00 CALIOP Level 2 data.
CALIPSO satellite data provides monthly mean vertical profiles of aerosol optical properties on a uniform spatial grid, derived from the CALIOP lidar instrument. This Level 3 product reports data below 12 km altitude, generated separately for day and night from version 5.00 Level 2 data. The mission was a NASA and CNES partnership, with science operations concluding in August 2023.
CALIPSO satellite data profiles the spatial distribution, optical properties, and composition of Polar Stratospheric Clouds (PSCs) on a uniform 5-km horizontal by 180-m vertical grid. The product includes CALIOP lidar measurements and incorporates Aura Microwave Limb Sounder data for HNO3, H2O, and derived meteorological parameters. NASA and the French Space Agency CNES collected this data from the satellite's launch in 2006 until the science mission concluded in August 2023.
Monthly mean vertical profiles of aerosol extinction coefficients and optical depth are derived from CALIOP lidar data for altitudes below 12 km. NASA and the French Space Agency CNES collected this data from the CALIPSO satellite, which operated from 2006 until its science mission concluded in August 2023. The product specifically averages data from atmospheric columns containing opaque clouds, providing a distinct cloudy-sky perspective.
A Kaggle-hosted dataset likely containing images or video frames of drones, birds, balloons, and kites. The dataset's purpose is inferred to be training and evaluating computer vision models for detecting and classifying these aerial objects. Specific details on volume, source, and creation date are unavailable.
A collection of guava plant images published on Kaggle. The dataset likely contains visual data for agricultural analysis, though specific details on volume, collection method, and time range are not provided. Its content and structure require verification after download.
A dataset hosted on Kaggle, likely containing video sequences captured from unmanned aerial vehicles. The specific number of sequences, subjects, and collection details are not provided in the metadata. The dataset's primary purpose appears to be for developing and benchmarking computer vision algorithms.
A Kaggle dataset titled 'wardronestypes'. The dataset likely contains information about categories or classifications of autonomous military systems, such as drones. The author, organization, and specific details are unknown.
NOAA_NCEI collected near-surface oceanographic and atmospheric data using three Saildrone autonomous surface vehicles in the eastern Bering Sea and northern Pacific Ocean from June to August 2020. The dataset includes measurements of water temperature, salinity, chlorophyll-a, dissolved oxygen, wind, air temperature, humidity, and air pressure. This experimental survey was conducted as an alternative to a canceled ship-based walleye pollock acoustic survey.