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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,664 datasets
NVIDIA's PhysicalAI Autonomous Vehicles NCore dataset consists of approximately 1,100 multi-sensor driving clips extracted from a larger 1,700-hour collection. This subset, updated in March 2026, provides high-fidelity data specifically formatted for the NCore standard with verified calibration and labeling.
ACT Government Open Data provides canopy cover footprints for the Australian Capital Territory. The polygons are derived from a 2020 LiDAR Canopy Height Model, estimating high vegetation above 3 meters at a 1-meter resolution. The dataset is maintained by the Office of Nature Conservation.
Juan Camilo León Pamplona's dataset systematizes literature on technology and warfare, focusing on drones and Lethal Autonomous Weapon Systems (LAWS) in the Colombian context post-2016 Peace Agreement. The 1.2 MB XLSX file contains a conceptual framework distinguishing UAV/UAS, automation versus autonomy, and controversies over responsibility, proportionality, and distinction in International Humanitarian Law. It serves to map the field, categorize findings, and build an analytical agenda for war and post-conflict studies.
NASA's AEOLUS-CALVAL-DAWN_DC8_1 dataset contains wind profile data collected using the Doppler Aerosol WiNd (DAWN) lidar instrument on a DC-8 aircraft. The data was gathered during a 2019 airborne campaign comprising five flights and 46 flight hours over the Eastern Pacific and Southwest U.S. The campaign aimed to validate the European Space Agency's Aeolus satellite mission and demonstrate the integration of wind, water vapor, and aerosol observations.
Summer 2019 remotely sensed data collected by the High-Spectral Resolution Lidar (HSRL) onboard the NASA DC-8 aircraft during the FIREX-AQ campaign. The campaign was a NOAA/NASA interagency study of North American fires, with the DC-8 completing 23 science flights from Boise, Idaho and Salina, Kansas. The overarching goal was to provide detailed measurements of trace gas and aerosol emissions from wildfires and prescribed fires to understand chemical transformation and air quality impacts.
North American wildfire plumes were remotely sensed by the Cloud Physics Lidar onboard a NASA ER-2 aircraft during the summer 2019 FIREX-AQ campaign. The data collection is complete and was part of a NOAA/NASA interagency study to understand fire emissions' impact on tropospheric chemistry and air quality. The ER-2 payload included eight satellite analog instruments providing fire temperature, plume heights, and vegetation/soil albedo information.
The Agricultural Experimental Station of the University of California, Riverside, is the collection site for this dataset. It provides LiDAR point cloud data and ground-truth trajectories to facilitate the evaluation of odometry algorithms in agricultural environments. The dataset consists of 18 sequences collected over two winter seasons, covering 7.5 km over 3 hours and constituting 150 GB of data.
Lidar Atmospheric Sensing Experiment (LASE) data collected during the Convection And Moisture Experiment (CAMEX-3) campaign from 6 August to 23 September, 1998. The campaign, based at Patrick Air Force Base, Florida, studied Hurricanes Bonnie, Danielle, Earl, and Georges. The dataset was produced by NASA to characterize hurricane environments for model input and to fill gaps in sonde data.
September 9 to September 20, 1994 vertical profile data collected by the Lidar In-Space Technology Experiment aboard the STS-64 mission. The dataset contains lidar measurements of clouds, aerosols, atmospheric temperature, density, and surface properties across three wavelengths. It was processed by NASA and includes geolocated profiles interpolated to a common altitude grid.
From August 2023 to July 2024, the National Oceanic and Atmospheric Administration (NOAA) contracted NV5 to collect topobathymetric lidar data for river sections in Missouri, Arkansas, and Oklahoma. The final data, covering approximately 745 square statute miles, were processed into Cloud Optimized GeoTIFF format Digital Elevation Models (DEMs) with 1-meter pixel resolution. The data represent both terrestrial and underwater elevations, transformed to geoidal height (Geoid18).
NASA's UAVSAR platform collected this PolSAR scene data, which includes Stokes parameters for polarimetric analysis. The dataset is published on datagov and was last updated on 2026-03-12. It contains files in PNG, BIN, ISO, and HTML formats.
A complete airborne LiDAR survey of the Northern Ireland coastline was commissioned in 2021. The survey captured the intertidal area and extended approximately 200 meters landward of the high-water mark. This dataset is the Digital Terrain Model derived from that LiDAR data, provided by OpenDataNI.
A complete airborne LiDAR survey of the Northern Ireland coastline was commissioned in 2021 as part of the NI 3D Coastal Survey. The survey captured the intertidal area and extended approximately 200 meters landward of the high-water mark. This dataset is the Digital Surface Model derived from that LiDAR data, provided by OpenDataNI.
Northern Ireland's coastline was surveyed in 2021 via airborne LiDAR as part of the NI 3D Coastal Survey. The resulting Digital Terrain Model covers the intertidal zone and extends approximately 200 meters landward of the high-water mark. The dataset is provided by OpenDataNI under the OGL-UK-3.0 license.
A Digital Surface Model derived from a complete airborne LiDAR survey of the Northern Ireland coastline conducted in 2021. The survey captured the intertidal area and extended approximately 200 meters landward of the high-water mark. The dataset is provided by OpenDataNI under the OGL-UK-3.0 license.
Lidar measurements provide vertical profiles of upper tropospheric and stratospheric aerosols collected at NASA Langley Research Center in Hampton, Virginia. The dataset contains annual granules with four key parameters: stratospheric integrated backscatter, altitude levels, scattering ratio, and aerosol backscattering coefficient. Data collection began in May 1974 using a ground-based 48-inch ruby laser system with 150-meter vertical resolution.
Psi0 Apple-to-Plate VR Teleoperation Dataset provides 79 human-demonstrated loco-manipulation trajectories for fine-tuning the Psi0 Vision-Language-Action model. The data was collected using a Unitree G1 29-DOF humanoid robot within the Isaac Lab simulation environment. It was published by cloudwalk-research and last updated on April 13, 2026.
AutomatumData provides high-precision movement data of traffic participants extracted from drone recordings. The dataset is suited for the simulation, validation, and development of automated driving algorithms and for traffic analysis. It was last updated on 2026-04-13.
SoftArmControl is a collection of CSV files containing experimental data for a soft robotic arm. The data includes pose information (yaw and pitch angles) while varying motor positions, and is organized into three datasets for model identification, pose-reaching control, and trajectory-following control. The dataset was created by Carlos Relaño and includes associated Matlab and C++ code for reproducing results from a related paper.
Cloud Lidar System (CLS) data collected by a NASA ER-2 aircraft during the Atlantic Stratocumulus Transition Experiment (ASTEX) in June 1992. The dataset records cloud altitudes, layer boundaries, and geophysical location information to study the transition from stratocumulus to trade cumulus clouds. It was produced by the National Aeronautics and Space Administration as part of the First ISCCP Regional Experiments (FIRE) to improve cloud parameterizations in climate models.