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Robotics & Autonomous Systems

Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation

1,663 datasets

TRACE-P: DC-8 Aircraft Lidar and In-Situ Atmospheric Data

The western Pacific region during March-April 2001 is the focus of this dataset from NASA's Transport and Chemical Evolution over the Pacific (TRACE-P) campaign. It combines Differential Absorption Lidar (DIAL) remote sensing and in-situ instrument data from the DC-8 aircraft to measure trace gases, aerosols, ozone, and meteorological parameters. The dataset is part of the NASA Global Tropospheric Experiment (GTE) and represents a completed, multi-instrument atmospheric survey.

TabularTime SeriesGeospatialATMOSPHERIC CHEMISTRYPacific RegionTrace GasesCloud DataAEROSOLSNasa GteTrace PAircraft In SituLidar Remote Sensing+1

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Robotics & Autonomous Systems

ISC2010: Victoria River Condition Metrics from Remote Sensing, 2010-2013

Victoria, Australia's river condition was assessed using the Index of Stream Condition (ISC) between 2010 and 2013. The Department of Environment and Primary Industries (DEPI) developed this dataset using remote sensing data, specifically 15cm aerial photography and multi-pulse LiDAR, to map Physical Form and Riparian Vegetation metrics. The full package includes all spatial vector features and aspatial statistical summary tables derived from this mapping project.

TabularGeospatialPoint CloudGeospatial MetricsRiver ConditionEnvironmental AssessmentFinance+1

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Robotics & Autonomous Systems

World Bank Gender Statistics for Iran, Latest Sex-Disaggregated Data

Gender statistics from the World Bank covering the Islamic Republic of Iran. The data includes sex-disaggregated indicators across demography, education, health, economic opportunities, public life, and agency. It was last updated on 2026-04-28 and is licensed under CC-BY-4.0.

TabularAudioCSVDevelopment IndicatorsWorld BankHealthcareFinanceDemographyEconomic OpportunityGender Equality+1

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Robotics & Autonomous Systems

CRSLP: Cooperative Roadside LiDAR Placement Benchmark with 900+ Plans

CRSLP is a benchmark dataset for evaluating cooperative roadside LiDAR placement strategies. It covers 13 sites, over 100 traffic scenarios, and more than 900 placement plans with corresponding long IoU sequences. The dataset, created by Yang Ma and last updated in 2026, includes over 3600 frames of point cloud data per test configuration, totaling 1.6 GB.

TabularPoint CloudZIPRoadside SensorsAutonomous VehiclesTraffic ScenariosBenchmarkSensor PlacementLidar Placement+1

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Robotics & Autonomous Systems

AfriSAR Forest Canopy Structure from UAVSAR PolInSAR and TomoSAR

NASA's AfriSAR dataset provides forest vertical structure and uncertainty products for Gabonese forests, derived from multi-baseline Polarimetric Interferometric SAR and Polarimetric Coherence Tomographic SAR techniques. Data were collected during multiple UAVSAR flights in February-March 2016 as part of a joint NASA/ESA campaign. Supplementary products include radar backscatter, coherence, and viewing and terrain geometry data.

GeospatialMultimodalZIPGabonSynthetic Aperture RadarForest Canopy StructureBenchmarkBiomass EstimationSynthetic+1

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Robotics & Autonomous Systems

CALIPSO Lidar: Vertical Feature Mask and Atmospheric Profiles

Data collection began on April 28, 2006, and is ongoing, with multiple product versions covering different periods. This dataset comprises multiple lidar data products from the CALIPSO satellite mission, a joint NASA and CNES project, designed to study the impact of clouds and aerosols on Earth's climate. The data includes vertical feature masks, aerosol and cloud layer profiles, and derived monthly gridded products, with measurements from the CALIOP, IIR, and WFC instruments.

ImageTime SeriesGeospatialPoint CloudCloud EmissivityAerosol ProfilesLidar BackscatterClimate ResearchCloud AerosolSatellite ImagerySatellite Remote SensingCloud Aerosol ScienceEarth ObservationLidar Aerosol ProfilesLidar ValidationCloud Properties+1

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Robotics & Autonomous Systems

GEDIMetrics: QGIS Plugin for GEDI Spaceborne LiDAR Data Integration

GEDIMetrics is a QGIS plugin for accessing and integrating multi-product GEDI spaceborne LiDAR data. The dataset includes version 1.0.2 of the plugin, test inputs, study areas, and exported outputs from an evaluation workflow. It was authored by Alexander Cotrina-Sanchez and last updated on May 21, 2026.

GeospatialPoint CloudZIPParquetTextForestryBenchmarkGeospatial AnalysisQgis Plugin+1

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Robotics & Autonomous Systems

SnowEx23 BCEF: Terrestrial Lidar Digital Terrain Models

Digital Terrain Models derived from terrestrial lidar scans collected during the SnowEx 2023 campaign at the Bonanza Creek Experimental Forest near Fairbanks, Alaska. Data were captured in October 2022 (snow-off) and March 2023 (snow-on) and are provided as GeoTIFF files, each corresponding to a unique survey site. The dataset is part of a larger collection, with unprocessed point cloud data available separately.

ImageGeospatialPoint CloudAlaskaDigital Terrain ModelSnowexSnow CoverComputer Vision+1

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Robotics & Autonomous Systems

NEL-MSCPSO: Benchmark and UAV Path Planning Data

Dafei Wu published source code and raw experimental data for the NEL-MSCPSO algorithm on figshare in 2026. The 150.8 MB repository includes results from CEC2022 benchmark tests and multi-amphibious UAV path planning experiments. Materials such as convergence curves, displacement-time trajectories, and optimization results are provided to reproduce the paper's findings.

TabularBenchmarkPath PlanningUavAlgorithm CodeSwarm Optimization+1

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Robotics & Autonomous Systems

LiDAR-Derived Forest Biomass and Canopy Metrics for Sonoma County 2013

Forest biomass, canopy height, and tree cover estimates at 30-meter resolution for Sonoma County, California, USA, for the nominal year 2013. The dataset was produced by NASA using LiDAR data, field plot measurements, and random forest modeling. It includes estimates of above-ground biomass uncertainty alongside the primary metrics.

GeospatialPoint CloudZIPCanopy HeightForest InventoryTree CoverAbove Ground BiomassSynthetic+1

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Robotics & Autonomous Systems

Network Parameter Configurations for a YOLOv11-Based UAV PV Detection Model

A set of network parameter configurations for a lightweight YOLOv11-based detection model designed for unmanned aerial vehicle (UAV) rooftop photovoltaic (PV) inspection. The dataset likely contains parameters describing the model architecture, such as layer configurations and module specifications. It was authored by Jiajun Zhu and last updated on May 6, 2026.

TabularExcelYoloBenchmarkComputer VisionUavModel parametersPhotovoltaic Detection+1

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Robotics & Autonomous Systems

ASO OLYMPEX: Snow Depth and Terrain from Airborne LiDAR

NASA's GPM Ground Validation Airborne Snow Observatory (ASO) OLYMPEX dataset provides 3-meter resolution geospatial data on snow depth, bare earth surface, and land cover classification for the Olympic Mountains. It was collected during the OLYMPEX field campaign using a Riegl Q1560 LiDAR and an ITRES CASI-1500 imaging spectrometer on flights in February and March 2016, with a baseline no-snow measurement from September 2014. The data are delivered in GeoTIFF format and support research on snowpack, hydrology, and terrain modeling.

ImageGeospatialPoint CloudCryospheric IndicatorsLand Surface ClassificationComputer VisionSnow Depth+1

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Robotics & Autonomous Systems

GOES-R PLT Cloud Physics Lidar Atmospheric Profile Data

NASA's GOES-R PLT Cloud Physics Lidar dataset contains multi-wavelength lidar measurements of cirrus clouds and aerosols collected from the ER-2 high-altitude aircraft. The data, gathered from April 13 to May 14, 2017, was used for post-launch validation of the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper instruments. It includes parameters like backscatter coefficient, depolarization ratio, layer heights, and ice water content.

Time SeriesGeospatialTextCirrus CloudsBenchmarkLidar Cloud PhysicsGeostationary Satellite ValidationAtmospheric AerosolsAirborne Remote Sensing+1

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Robotics & Autonomous Systems

CMS: High-Resolution Tree Canopy Cover for Northeast USA

State-level data for Pennsylvania (2008), Delaware (2014), and Maryland (2013) provides 1-meter resolution tree canopy cover for the Northeast USA. The data were created using a rules-based expert system that integrated leaf-on LiDAR and imagery, exploiting spectral, height, and spatial information. Additional states are planned to be added as processing is completed.

GeospatialPoint CloudZIPForestryNortheast UsaGeospatial AnalysisTree Canopy Cover+1

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Robotics & Autonomous Systems

Forest Biomass Estimates from LiDAR and PALSAR in Brazil

2012 estimates of forest aboveground biomass for the Paragominas municipality in Para, Brazil. The dataset was produced by NASA using gradient boosting machine models to assimilate ground inventory plot data with LiDAR and PALSAR remote sensing metrics. It provides spatially explicit predictions of biomass and uncertainty for three focal study areas and the entire municipality.

GeospatialPoint Cloud🇧🇷 BrazilZIPCarbon StockForest BiomassPalsar+1

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Robotics & Autonomous Systems

Corruption Perceptions Index: Country Scores and Rankings

Transparency International's Corruption Perceptions Index scores countries from 0 (highly corrupt) to 100 (very clean). The dataset includes scores and rankings based on assessments by experts and business executives. It was last updated on 2026-05-21.

TabularCSVGovernanceGovernance And Civil SocietyIndicatorsCountry RankingsDevelopmentSocioeconomicsSocioeconomic IndicatorsCorruption PerceptionsPoverty+1

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Robotics & Autonomous Systems

GCPEx Lidar Quicklooks for Aerosol and Water Vapor Profiles

Two lidar systems, the Semi Autonomous Tropospheric Aerosol Lidar and the Tropospheric Water Vapor Lidar, collected imagery during the GPM Cold-season Precipitation Experiment from January to March 2012 in Canada. This dataset provides quicklook imagery to address shortcomings in GPM snowfall retrieval algorithms by capturing microphysical properties and remote sensing observations of precipitating snow. The system operated semi-autonomously, shutting down automatically during rain events.

ImageGeospatialSnowfall ValidationAtmospheric ScienceWater Vapor ProfilesLidar MeasurementsAerosol BackscatterSynthetic+1

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Robotics & Autonomous Systems

Multi-strategy Sea Horse Optimization Algorithm for UAV Path Planning

A modified Sea Horse Optimization algorithm (moSHO) designed for threat-aware unmanned aerial vehicle path planning. The dataset likely contains results from evaluating moSHO on 23 benchmark functions and UAV path planning experiments. Amir Seyyedabbasi authored this dataset, which was last updated on May 11, 2026.

TabularCSVAutonomous NavigationMetaheuristicsBenchmarkOptimization AlgorithmsBenchmark FunctionsUav Path Planning+1

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Robotics & Autonomous Systems

Multi-strategy Sea Horse Optimization Algorithm for UAV Path Planning

A 5.7 KB CSV file presents a modified Sea Horse Optimization algorithm (moSHO) for threat-aware unmanned aerial vehicle path planning. The dataset, authored by Amir Seyyedabbasi and last updated in May 2026, describes an algorithm that integrates three cooperative strategies to improve exploration and avoid local optima. It includes evaluation results from 23 benchmark functions and experiments on a UAV path planning model under threat environments.

TabularCSVAutonomous NavigationMetaheuristicsBenchmarkOptimization AlgorithmsUav Path Planning+1

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Robotics & Autonomous Systems

Airborne Lidar Point Clouds for Quebec Terrain Modeling

Lidar data provides 3D point clouds with X, Y, Z coordinates representing precise surface reflections from airborne laser surveys. These datasets result from intergovernmental collaborations with Quebec ministries, federal, and municipal sectors, enabling detailed terrain and surface models. Data availability is indicated on a download map, with coverage expanding as new surveys are completed.

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