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2,639 results for “Robotic”
Human Robotic Systems (HRS): Extreme Terrain Mobility Element
<p>During 2014, the <em>Extreme Terrain Mobility </em>project element is developing five technologies:</p><ul><li>Exoskeleton Development for ISS Evaluation</li><li>Extreme Terrain Mobility Testbed</li><li>Low Gravity Testbed using Tethered Stewart Platform</li><li>Prototype Crater Access Robot</li><li>Advanced Mobility Navigation Software</li></ul><p><strong>Exoskeleton Development for ISS Evaluation</strong></p><p>During FY12, HRS and GCD developed the X1 exoskeleton with the ultimate intent of augmenting crew endurance/strength in future missions.&nbsp; Offshoots of the technology involved lightweight exercise devices for ISS and strength measurement by using the torque sensing in the X1&rsquo;s joints.&nbsp; The objective for exoskeleton development in FY14 is to build prototype exoskeleton ankles and deliver them to the JSC space and life sciences organization for evaluation as exercise devices and to design a single-joint knee dynamometer, based on X1 technologies, capable of measuring crew strength.&nbsp;</p><p><strong>Extreme Terrain Mobility Testbed</strong></p><p>The objective of FY14 work is to present mature systems that are ready to be carried forward by a Science Mission Directorate Principal Investigator (PI) willing to propose a system with greater mobility than exists on current Mars rovers.&nbsp; HRS has recently identified a potential national need with the National Science Foundation (NSF) that requires no-emission vehicles, such as NASA rovers, on the Arctic, Antarctic, Alaska and polar coastal areas.&nbsp; We have an opportunity to deploy NASA Space Technologies to these areas. Minimal success requires disseminating results to potential SMD PIs and potential partners within the NSF polar program.&nbsp; Early in fiscal year 2014, the HRS extreme terrain mobility group will prepare an Analysis of Alternatives study of a 170 kg rover for the Advance Exploration System (AES) Resource Prospector (RP).</p><p><strong>Low Gravity Testbed using Tethered Stewart Platform</strong></p><p>This task creates a 6-DOF testbed for evaluating microgravity and low-gravity proximity and contact operations, e.g. in the vicinity of a Near Earth Asteroid (NEA). This is accomplished using an &quot;inverted Stewart platform&quot;, where the vehicle under test is suspended by six computer-controlled cable winches so that it can be maneuvered in all 6 Degrees-of-Freedom.</p><p><strong>Prototype Crater Access Robot</strong></p><p>This task will develop and demonstrate a &ldquo;mother-daughter&rdquo; approach to exploring craters using tethered robots.&nbsp; The small robots will be tethered to the larger robot with winches on both ends so that the &ldquo;mother&rdquo; can recover the &ldquo;daughter&rdquo; even in the event of failure of the small robot.&nbsp; In normal operation, the daughter robot will pay out the tether to move further away, and spool it back in to return.&nbsp; In FY13, this task demonstrated deployment of the daughter robot with an internal winch on a tether. The daughter robot is designed to move on steep slopes, up to vertical, to carry and point close-up instruments, and to collect samples.&nbsp; In FY14, this task will design and build a tether that provides power from the mother robot to the daughter robot and provides for communications between them.</p><p><strong>Advanced Mobility Navigation Software</strong></p><p>The Advanced Navigation Software task is developing approaches for dealing with the significant challenges of autonomous planetary surface navigation, including descent on rough and steep terrain, exploring lava tubes, navigating long distances without co
Human Robotic Systems (HRS): Robotic ISRU Acquisition Element
<p>During 2014, the <em>Robotic ISRU Resource Acquisition </em>project element will develop two technologies:</p><ul><li>Exploration Ground Data Systems (xGDS)</li><li>Sample Acquisition on Asteroids, Mars, Moons of Mars, and Lunar Cold Traps</li></ul><p>A primary technology of this element is development of HRS&rsquo;s Exploration Ground Data Systems (xGDS) software, a set of planning, monitoring, archiving, and search tools for dealing with data sent to or received from robotic spacecraft or crew systems.&nbsp; xGDS is being matured through technology development under HRS (with STMD funds) and field-tested with funds from the Human Exploration and Operations Mission Directorate (HEOMD) and Science Mission Directorate (SMD).&nbsp; The outcome of this development will be that the desired parts of the xGDS system (likely the traverse planner, real time plotting, and raster mapping tools) will be ready to be infused into the lunar Resource Prospector Mission (RPM).&nbsp; The scope of FY14 xGDS work includes maturing time delayed image and video processing and archiving tools and adding support for mobile devices.&nbsp; During 2014, xGDS will support the AES-funded Regolith and Environment Science and Oxygen and Lunar Volatile Extraction (RESOLVE) payload thermal vacuum chamber testing the SMD-funded Mojave Volatiles Prospector (MVP) project.&nbsp;</p><p>Another technology under this element will develop regolith sampling and excavation for reduced and low gravity environments.&nbsp; The objective for this work in FY14 is to acquire representative samples of target bodies in order to characterize the regolith for ISRU prospecting purposes which would also benefit science objectives and other relevant Strategic Knowledge Gaps (SKG&rsquo;s). The requirements of the Advanced Exploration Systems (AES) lunar Resource Prospector (RP) are focused on a lunar South pole mission near the impact site of the recent Lunar CRater Observation and Sensing Satellite (LCROSS) mission in order to obtain ground truth on the lunar surface.&nbsp; Orbital data from neutron spectrometers shows that most of the detected hydrogen on the moon is in these crater floor cold traps. The goal is to confirm the existence of volatiles such as water, hydrogen and helium in the regolith at the lunar poles.&nbsp; Other target bodies such as asteroids and Mars&rsquo; moons will also need prospecting and characterization. One of the primary potential uses of the returned asteroid in the Asteroid Initiative is for ISRU demonstrations in lunar orbit.&nbsp; Sampling devices will be needed to prospect the asteroid for useful resources, such as water on a carbonaceous condrite. The Mars&rsquo; moons and Mars itself are also of interest for ISRU purposes and can be sampled with robotic devices or by human crews to determine the ISRU value of their regolith.</p><p>Regolith excavation and sample acquisition in low gravity environments ( micro-G, 1/3 G, 1/6th G) is difficult due to the lack of reaction force from the weight of the excavation robot.&nbsp; On Earth, excavators are typically large and heavy to take advantage of this large reaction force to counter-act the digging forces. In space, new methods of digging and sampling must be found, due to their light weight in low gravity environments.&nbsp; Percussive excavation is one method for reducing digging forces, and in FY14, the HRS project will test interfaces for a large percussive excavation end effector: the Vibratory Implement for Percussive Excavation of Regolith (VIPER) which is designed to be mounted on the All-Terrain Hex-Limbed Extra-Terrestrial Explorer (ATHLETE) robot from JPL. The VIPER was designed and fabricated by HRS. A smaller percussive excavation implement called Badger, will be operated on the Centaur 2 mobility robot with a positioning mechanism. Firs
Human Robotic Systems (HRS): Controlling Robots over Time Delay Element
<p>This element involves the development of software that enables easier commanding of a wide range of NASA relevant robots through the Robot Application Programming Interface Delegate (RAPID) robot messaging system and infusing the developed software into flight projects.&nbsp; In June and July of 2013, RAPID was tested on ISS as the robot messaging software for the Technology Demonstration Mission (TDM) Human Exploration Telerobotics (HET) Surface Telerobotics experiment.&nbsp; RAPID has also been made available to &mdash; and integrated with &mdash; the Robot Operating System (ROS), a popular software framework for developing state-of-the-art robots for ground and space. While ROS powers a number of new robots and components such as Robonaut 2&rsquo;s climbing legs and R5, the addition of RAPID allows these robots to interoperate in collaborative human-robot teams, safely and effectively over time-delayed communications links. The objective this year is to take this space-tested software and extend it to providing video streaming from remote robots and delivering this new capability to the Exploration Ground Data Systems (xGDS) area within HRS.&nbsp; xGDS will then deliver its software to Science Mission Directorate (SMD) funded field tests to improve the technology readiness moving leading (potentially) to being used for the Lunar Prospector Mission ground data systems.&nbsp; Success will involve delivering RAPID to xGDS and then xGDS supporting SMD field test.</p><p>The team is also developing algorithms for sensors capable of reconstructing remote worlds and efficiently shipping that remote environment back to earth using the RAPID robot messaging system.&nbsp; This type of system could eventually lead to scientists on earth gain new insights as they are able to step into the remote world.&nbsp; This sensor also has the ability to engage the public, bringing remote worlds back to earth.&nbsp; During FY13, this task used science operations personnel from current SMD projects to objectively measure improvement in remote science target selection and decision-making based. The team continues to work with SMD projects to ensure that the technologies being developed are directly responsive to SMD project personnel needs. The objective of this work in FY14 is to expand the range of science operations tasks addressed by the technology, and to perform laboratory demonstrations for JPL/SMD stakeholders of the immersive visualization of data from a sensor using an SMD representative environment.</p><p>During 2014, the &ldquo;Controlling<em> Robots Over Time Delay&rdquo;</em> project element will develop two technologies:</p><ul><li>Develop RAPID robot messaging for unified cross-center operations platform for TDM, xGDS, and CCSDS</li><li>Sensor Systems for the Construction of Immersive Virtual Environments</li></ul>
Sulfates, Clouds and Radiation Brazil (SCAR-B) AERONET (AErosol RObotic NETwork) Data
SCAR_B_AERONET data are Smoke, Clouds and Radiation Brazil (SCARB) Aerosol Robotic Network (AERONET) data for aerosol characterization.Smoke/Sulfates, Clouds and Radiation - Brazil (SCAR-B) data include physical and chemical components of the Earth's surface, the atmosphere and the radiation field collected in Brazil with an emphasis in biomass burning.The objectives for the SCAR mission are: to advance our knowledge of how the physical, chemical and radiative processes in our atmosphere are affected by sulfate aerosol and smoke from biomass burning; to improve our expertise at remotely sensing smoke, water vapor, clouds, vegetation and fires; and to assess the effects of deforestation and biomass burning on tropical landscapes.AERONET (AErosol RObotic NETwork) is an optical ground based aerosol monitoring network and data archive supported by NASA's Earth Observing System and expanded by federation with many non-NASA institutions. The network hardware consists of identical automatic sun-sky scanning spectral radiometers owned by national agencies and universities. Data from this collaboration provides globally distributed near real time observations of aerosol spectral optical depths, aerosol size distributions, and precipitable water in diverse aerosol regimes. The data undergo preliminary processing (real time data), reprocessing (final calibration ~6 mo. after data collection), quality assurance, archiving and distribution from NASA's Goddard Space Flight Center master archive and several identical data bases maintained globally. The data provide algorithm validation of satellite aerosol retrievals and as well as characterization of aerosol properties that are unavailable from satellite sensors.
Possible Genetic Basis for Failure of a Robotic-Assisted Laparoscopic Sacrocolpopexy
GEO Series GSE63236. Homo sapiens. 50 samples. Type: SNP genotyping by SNP array.
Coordinated movement of a swarm of nonholonomic wheeled robots modeled as virtual visco-elastic body - raw experiment data
<p>Raw experiment data from verification of 2 control algorithms on 5 nonholonomic mobile robots using OptiTrack motion capture system : virtual spring damper mesh control (algorithm A1) with and without obsticles and swarm selforganization using worm creep algorithm (algorithm A4). Conducted experiment allowed for adjustment of the control parameters (describend in Data.m files) to achieve better performance of the swarm movement.</p> <p>Abbreviations: d1, d2 - are desired interrobot distances, NO- no obsticles, Wo - with obsticles, Sor - self-organization</p> <p> </p>
Coordinated movement of a swarm of nonholonomic wheeled robots modeled as virtual visco-elastic body - videos from experiments
<p>Videos from experiments associated with raw experiment data for project titled: "Coordinated movement of a swarm of nonholonomic wheeled robots modeled as virtual visco-elastic body"</p>
Research on visualization and error compensation of demolition robot attachment changing
<p>visualization and error compensation of demolition robot attachment changing</p>
"Learning Grasping and Walking Motion Generation for Humanoid Robots" video material
<p>"Learning Grasping and Walking Motion Generation for Humanoid Robots" video material</p>
Loader robot dataset (2024-04-18)
<p>The dataset contains images captured by three RealSense cameras mounted on the back of the loader robot and one Zedx mounted on the front of it. The following topics have been recorded on the bag files:</p> <ul> <li>/loader/ugv0/back_lslidar_packet</li> <li>/loader/ugv0/camera_bc/color/camera_info </li> <li>/loader/ugv0/camera_bc/color/image_raw/compressed</li> <li>/loader/ugv0/camera_bl/color/camera_info</li> <li>/loader/ugv0/camera_bl/color/image_raw/compressed</li> <li>/loader/ugv0/camera_br/color/camera_info </li> <li>/loader/ugv0/camera_br/color/image_raw/compressed </li> <li>/loader/ugv0/gps/fix </li> <li>/loader/ugv0/gps/time </li> <li>/loader/ugv0/gps/vel </li> <li>/loader/ugv0/imu_rion </li> <li>/loader/ugv0/lio_sam/mapping/path </li> <li>/loader/ugv0/zed_node/left/camera_info</li> <li>/loader/ugv0/zed_node/left/image_rect_color </li> <li>/loader/ugv0/zed_node/right/camera_info</li> <li>/loader/ugv0/zed_node/right/image_rect_color</li> <li>/tf</li> <li>/tf_static</li> </ul>
Wir sind die Roboter / We Are the Robots
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1677408732.9317.jpg">https://4dcity.org/imgupload/1677408732.9317.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/52406240411_5c032f04af_m.jpg">https://live.staticflickr.com/65535/52406240411_5c032f04af_m.jpg</a>
Raw Acoustic data samples from hydrophone SLim Towed Array towed by marine robot acquired during STO-CMRE sea trials
<p>Sample raw acoustic datasets acquired from hydrophone array SLiTA (SLim Towed Array, specific for AUV applications) towed by marine autonomous vehicles (e.g, Autonomous Underwater Vehicles, AUVs) [*] during three STO-CMRE sea trials:</p> <ul> <li>PORTOPALO (2013), at Portopalo di Capo Passero, Sicily, Italy, on 18-19 February 2013</li> <li>COLLAB13, at Palmaria Island, La Spezia, Italy, on 30 June - 7 July 2013</li> <li>COLLAB14, at Massa, Italy, on 29-31 October 2014</li> </ul> <p>Access to this dataset is restricted to NATO and H2020 INFORE consortium. This data set is provided to INFORE consortium partners for the purposes of executing tasks under the INFORE Grant Agreement and may not be used for other purposes or further distributed.</p> <p>The creation of derived products, as well the use in scientific publications must be pre-approved by NATO STO CMRE and acknowledged.</p> <p>These data are available to partners of NATO Nations after the execution of the project on the basis of existing NATO policies and rules for data release, other memorandum of understanding and agreements, and on the basis of CMRE terms and conditions for data reuse.</p> <p>Acoustic raw data from SliTa array header specification is described in the Table below,</p> <table> <thead> <tr> <th> <p><strong>Field Name</strong></p> </th> <th> <p><strong>Data Type</strong></p> </th> <th> <p><strong>Description</strong></p> </th> </tr> </thead> <tbody> <tr> <td> <p>headersize</p> </td> <td> <p>int</p> </td> <td> <p>Size of header in bytes</p> </td> </tr> <tr> <td> <p>dataFormat</p> </td> <td> <p>int</p> </td> <td> <p>0 means 2’s complement; 1 means Offset Binary</p> </td> </tr> <tr> <td> <p>fs</p> </td> <td> <p>float</p> </td> <td> <p>Sampling Frequency [Hz]</p> </td> </tr> <tr> <td> <p>inputRange</p> </td> <td> <p>int</p> </td> <td> <p>Flag to determine the max voltage.<br> {3=10V, 2=5V, else 2.5V}</p> </td> </tr> <tr> <td> <p>gainHydPreamp</p> </td> <td> <p>float</p> </td> <td> <p>Preamplifier fain</p> </td> </tr> <tr> <td> <p>gainA2dAmp</p> </td> <td> <p>float</p> </td> <td> <p>A/D gain</p> </td> </tr> <tr> <td> <p>dataWidth</p> </td> <td> <p>int</p> </td> <td> <p>Flag to determine the number of bit per sample<br> {3=24bit, 2=20bit, 1=18bit, else 15bit}</p> </td> </tr> <tr> <td> <p>acqLength</p> </td> <td> <p>float</p> </td> <td> <p>Size (in seconds) on each block of data returned by A/D</p> </td> </tr> <tr> <td> <p>octave</p> </td> <td> <p>int</p> </td> <td> <p>Determine the array spacing:<br> {1=0.21m, 2=0.42, 3=0.84, 4=1.05m}</p> </td> </tr> <tr> <td> <p>pc_day</p> </td> <td> <p>int</p> </td> <td> <p>Day from PC time</p> </td> </tr> <tr> <td> <p>pc_month</p> </td> <td> <p>int</p> </td> <td> <p>Month from PC time</p> </td> </tr> <tr> <td> <p>pc_year</p> </td> <td> <p>int</p> </td> <td> <p>Year from PC time</p> </td> </tr> <tr> <td> <p>pc_hr</p> </td> <td> <p>int</p> </td> <td> <p>Hour from PC time</p> </td> </tr> <tr> <td> <p>pc_min</p> </td> <td> <p>int</p> </td> <td> <p>Minute from PC time</p> </td> </tr> <tr> <td> <p>pc_sec</p> </td> <td> <p>int</p> </td> <td> <p>Seconds from PC time</p> </td> </tr> <tr> <td> <p>gps_month</p> </td> <td> <p>int</p> </td> <td> <p>Month from GPS</p> </td> </tr> <tr> <td> <p>gps_day</p> </td> <td> <p>int</p> </td> <td> <p>Day from GPS</p> </td> </tr> <tr> <td> <p>gps_year</p> </td> <td> <p>int</p> </td> <td> <p>Year from GPS</p> </td> </tr> <tr> <td> <p>oex_hr</p> </td> <td> <p>int</p> </td> <td> <p>Hour from Frontseat PC</p> </td> </tr> <tr> <td> <p>oex_min</p> </td> <td> <p>int</p> </td> <td> <p>Minute from Frontseat PC</p> </td> </tr> <tr> <td> <p>oex_sec</p> </td> <td> <p>double</p> </td> <td> <p>Seconds from Frontseat PC</p> </td> </tr> <tr> <td> <p>lat_deg</p> </td> <td> <p>int</p> </td> <td> <p>Latitude [degrees]</p> </td> </tr> <tr> <td> <p>lat_min</p> </td> <td> <p>double</p> </td> <td> <p>Latitude [minutes]</p> </td> </tr> <tr> <td> <p>lon_deg</p> </td> <td> <p>int</p> </td> <td> <p>Longitude [degrees]</p> </td> </tr> <tr> <td> <p>lon_min</p> </td> <td> <p>double</p> </td> <td> <p>Longitude [minutes]</p> </td> </tr> <tr> <td> <p>heading</p> </td> <td> <p>float</p> </td> <td> <p>Size of header in bytes</p> </td> </tr> <tr> <td> <p>cog</p> </td> <td> <p>float</p> </td> <td> <p>0 means 2’s complement; 1 means Offset Binary</p> </td> </tr> <tr> <td> <p>depth</p> </td> <td> <p>float</p> </td> <td> <p>Sampling Frequency [Hz]</p> </td> </tr> <tr> <td> <p>altitude</p> </td> <td> <p>double</p> </td> <td> <p>Flag to determine the max voltage.<br> {3=10V, 2=5V, else 2.5V}</p> </td> </tr> <tr> <td> <p>sog(dm/s)</p> </td> <td> <p>int</p> </td> <td> <p>Preamplifier fain</p> </td> </tr> <tr> <td> <p>sow(dm/s)</p> </td> <td> <p>int</p> </td> <td> <p>A/D gain</p> </td> </tr> <tr> <td> <p>track_stat</p> </td> <td> <p>int</p> </td> <td> <p>Flag to determine the number of bit per sample<br> {3=24bit, 2=20bit, 1=18bit, else 15bit}</p> </td> </tr> <tr> <td> <p>fix_type</p> </td> <td> <p>int</p> </td> <td> <p>Size (in seconds) on each block of data returned by A/D</p> </td> </tr> <tr> <td> <p>pps_output</p> </td> <td> <p>int</p> </td> <td> <p>Determine the array spacing:<br> {1=0.21m, 2=0.42, 3=0.84, 4=1.05m}</p> </td> </tr> </tbody> </table> <p>[*] Alain Maguer, Rodney Dymond, Piero Guerrini, Luigi Troiano, Vittorio Grandi, Alberto Figoli, Claudio Olivero, Alessandro Sapienza, Stefano Fioravanti, John Potter Receiving and transmitting acoustic systems for AUV/gliders. Proceedings of the 3rd International Conference and Exhibition on Underwater Acoustic Measurements: Technologies and Results, 21-26 June, 2009, Nafplion, Greece. <a href="https://openlibrary.cmre.nato.int/bitstream/handle/20.500.12489/651/NURC-PR-2009-004.pdf">https://openlibrary.cmre.nato.int/bitstream/handle/20.500.12489/651/NURC-PR-2009-004.pdf</a></p>
Automatic Centralized Control of UnderactuatedLarge-scale Mutli-robot Systems using a Generalized Coordinate Transformation
<p>Controlling large-scale particle or robot systems is challenging because of their high dimensionality. We use a centralized stochastic approach that allows for optimal control at the cost of a central element instead of a decentralized approach. Previous works are often restricted to the assumption of fully actuated robots. Here we propose an approach for underactuated robots that allows for energy-efficient control of the robot system. We consider a simple task of gathering the robots (minimizing positional variance) and steering them towards a goal point within a bounded area without obstacles. We make two main contributions. First, we present a generalized coordinate transformation for underactuated robots, whose physical properties should be considered. We choose Euler-Lagrange systems that describe a large class of robot systems. Second, we propose an optimal control mechanism with the prime objective of energy efficiency. We show the feasibility of our approach in numerical simulations and robot simulations.</p> <p> </p> <p> </p> <p> </p>
Heavy-Duty Electrically Actuated Quadruped Robot Exp. data
<p>数据解释格式可以参考 \url{https://github.com/mit-biomimetics/Cheetah-Software}</p>
The Effect of Preemptive Pregabalin on Postoperative Pain and Respiratory Dynamics in Robotic Prostatectomy Operation.
ClinicalTrials.gov study NCT06170359. IPD Sharing: NO. Countries: 0. Publications: 0.
Effect of Minimally Invasive Surgical Assisted by Robots on Intraventricular Hemorrhage
ClinicalTrials.gov study NCT06486480. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Evaluation of Low Flow and Normal Flow Anesthesia Management in Robotic Assisted Laparoscopic Surgeries
ClinicalTrials.gov study NCT06430593. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Efficacy of Robot-Assisted Rehabilitation of Hand Paralysis After Stroke
ClinicalTrials.gov study NCT02711787. IPD Sharing: NO. Countries: 0. Publications: 0.
The Accuracy of Static Navigation Systems and Robotic System in Partially Edentulous in Posterior Area
ClinicalTrials.gov study NCT06173921. IPD Sharing: NO. Countries: 0. Publications: 0.
ROBYN Study - Robotic Assisted Surgery in Gynecological Indications Compared to Conventional Laparoscopy
ClinicalTrials.gov study NCT05496244. IPD Sharing: Not stated. Countries: 0. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.