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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,670 datasets
745 square statute miles of topobathymetric lidar data covering river sections in Missouri, Arkansas, and Oklahoma, collected from August 2023 to July 2024 by NV5 under contract for NOAA. The dataset includes point cloud data in LAS format with classifications for ground, water surface, bathymetric bottom, submerged aquatic vegetation, and other features according to ASPRS standards. Horizontal datum is NAD83 (2011) UTM 15, and vertical datum is GRS80 ellipsoid heights.
March 2026 publication from the Communications Security Establishment Canada details cyber threats to drone operations. The guide explores risks like data breaches, unauthorized access, and operational disruptions. It is provided as an HTML document under an open government license.
CALIPSO satellite data provides vertical feature masks for clouds and aerosols at a 5 km resolution. The dataset is produced by NASA and the French CNES from the CALIOP lidar instrument, launched in 2006 as part of the A-Train satellite constellation. It was last updated in March 2026.
CALIPSO satellite data provides vertical feature masks for clouds and aerosols at a 5 km resolution. The mission, a joint NASA and CNES project launched on April 28, 2006, studies their impact on Earth's radiation budget and climate. It operates within the international 'A-Train' satellite constellation for coincident Earth observations.
CALIPSO satellite data provides global observations of cloud and aerosol layers to study Earth's radiation budget and climate. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission is a joint project between NASA and the French space agency CNES, launched in 2006. These Level 2 data products contain 1 km resolution cloud layer information.
CALIPSO satellite data provides observations of cloud and aerosol layers to study their impact on Earth's radiation budget and climate. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission is a joint project between NASA and the French space agency CNES, launched on April 28, 2006. It flies as part of the international 'A-Train' satellite constellation for coincident Earth observations.
CALIPSO satellite data collected from its 2006 launch onward, providing observations of atmospheric aerosol layers. The dataset is produced by NASA and the French agency CNES, using the CALIOP lidar instrument. It consists of 5 km resolution aerosol layer data from the satellite flying in the international A-Train constellation.
CALIPSO satellite data collected from its launch on April 28, 2006, as part of the international A-Train constellation. The dataset consists of half-orbit emissivity and cloud particle data from the Imaging Infrared Radiometer (IIR), co-located with lidar tracks. It is a joint mission between NASA and the French space agency CNES.
M3ED is the first multi-sensor event camera dataset focused on high-speed dynamic motions in robotics. It provides synchronized data from a car, legged robot, and UAV operating in challenging conditions like off-road trails and dense forests. The dataset includes high-resolution stereo event cameras, grayscale and RGB cameras, an IMU, a 64-beam LiDAR, and RTK localization, contributed by the Daniilidis Group and KumarRobotics.
Kaggle hosts a dataset related to self-driving cars. The dataset likely contains information pertinent to autonomous vehicle technology. Metadata is minimal; actual content requires verification after download.
Kaggle hosts this dataset titled 'Tarikh Islam Dataset'. The dataset likely contains textual records related to Islamic history. Metadata is minimal; specifics about its size, origin, and content require verification after download.
A dataset from the 100-Car Naturalistic Driving Study funded by the AAA Foundation for Traffic Safety. The data were collected by the Virginia Tech Transportation Institute under sponsorship from NHTSA, VDOT, and Virginia Tech. The primary aim was to understand the relationship between potentially unsafe driving behaviors and crashes, near-crashes, and incidents.
A collection of publicly available large-scale LiDAR datasets archived uniformly for easy access. Initial efforts focus on Europe, with plans to expand to the USA and other regions for global coverage. Every dataset includes files in the original data format and translated to the COPC format, with an overview file for faster browsing.
A 1997 USAF study compared the speed and accuracy with which seven groups of military and civilian pilots learned to fly the RQ-1A Predator UAV. Participants completed multimedia tutorials and then flew a high-fidelity simulator, performing basic maneuvers, landings, and 30 reconnaissance scenarios while detailed performance measures were automatically recorded. The dataset was authored by Brian T. Schreiber and originates from the Air Force Research Laboratory.
A dataset titled 'drone_blackwater yollo model' published on Kaggle. The title suggests it may contain imagery or data related to drone operations, possibly for training a computer vision model. The dataset's author, organization, size, and specific contents are unknown.
Data recorded in and around Karlsruhe, Germany, using a vehicle equipped with multiple cameras, a Velodyne HDL 64 laser scanner, and a GPS/IMU unit. It provides benchmarks for computer vision and machine learning research, including stereo, optical flow, and object detection. The dataset was created by the Max Planck Campus Tübingen.
Topobathy lidar data covering approximately 225 square miles along Tampa Bay shores. The data were collected by Dewberry using a CZMIL Nova system between January 26 and February 27, 2021. It includes 52 tiles of 5000 m x 5000 m DEMs with points classified as ground, water surface, bathymetric bottom, and submerged objects.
Lidar point cloud data collected by NOAA's National Geodetic Survey using a Riegl VQ880G system. The data includes classifications for ground, water surface, submerged objects, and aquatic vegetation according to ASPRS standards. It may also contain lidar intensity values and encoded RGB image values.
Florida Keys Outer Reef Block 01 topobathy lidar data collected by the NOAA National Geodetic Survey between July and November 2016. The data are in LAS 1.2 format with points classified as unclassified, noise, bathymetric, and submerged object. The dataset likely includes lidar intensity values and encoded RGB image values.
2018 lidar data collected by NOAA's National Geodetic Survey using a Riegl VQ880G system. The data likely contains point clouds classified according to ASPRS standards, including ground, water surface, and submerged objects. Data may also include lidar intensity values and encoded RGB image values.