# Robotics Datasets: AI Datasets
Source: https://savrn.com/datasets/tasks/robotics
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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SAVRN Model Hub · Datasets by Task

# Robotics Datasets

120 open-weight robotics datasets in the SAVRN Model Hub, with National Engineering Research Center for Big Data Software, IPEC at Shanghai AI Laboratory and Michal Podolinsky publishing the most.

120Datasets

83Publishers

8Licenses

## SAVRN's Take

Robotics data is the scarce input of physical AI, and this page shows who is filling the gap. NVIDIA's GR00T simulation trajectories lead in downloads, followed by Genrobot's collection of more than 13,000 hours of real two-handed manipulation, and a long list of classic datasets such as DROID, Language Table and KUKA converted to the LeRobot format.

Most of these sets are Apache 2.0 or CC-BY-4.0, which makes them usable for commercial training with attribution. The practical constraint is size: real-world robot data runs to hundreds of gigabytes or more, so plan storage and bandwidth before you plan training runs. Mixing public data with demonstrations from your own robot remains the most reliable recipe.

SAVRN Research, 2026-09-18

## Most Downloaded

| Dataset | Publisher | License | Monthly downloads |
| --- | --- | --- | --- |
| [PhysicalAI-Robotics-GR00T-X-Embodiment-Sim](https://savrn.com/datasets/physicalai-robotics-gr00t-x-embodiment-sim) | NVIDIA | cc-by-4.0 | 1.3M |
| [10Kh-RealOmin-OpenData](https://savrn.com/datasets/10kh-realomin-opendata) | Genrobot.ai | cc-by-sa-4.0 | 689.4k |
| [language_table_lerobot](https://savrn.com/datasets/language-table-lerobot) | IPEC at Shanghai AI Laboratory | apache-2.0 | 474.3k |
| [droid_lerobot](https://savrn.com/datasets/droid-lerobot) | IPEC at Shanghai AI Laboratory | apache-2.0 | 361.9k |
| [droid_1.0.1](https://savrn.com/datasets/droid-1-0-1) | Remi Cadene | apache-2.0 | 352.1k |
| [kuka_lerobot](https://savrn.com/datasets/kuka-lerobot) | IPEC at Shanghai AI Laboratory | apache-2.0 | 316.5k |
| [ABC-130k](https://savrn.com/datasets/abc-130k) | XDOF | apache-2.0 | 296.4k |
| [AgiBotWorld2026](https://savrn.com/datasets/agibotworld2026) | AgiBot World | cc-by-nc-sa-4.0 | 245.9k |
| [stereo-550](https://savrn.com/datasets/stereo-550) | FPV Labs | other | 242.8k |
| [ACE-Data-0](https://savrn.com/datasets/ace-data-0) | ACE Robotics | other | 242.5k |

## Licenses

| License | Datasets | Commercial use |
| --- | --- | --- |
| apache-2.0 | 68 | Yes |
| not stated | 13 | Not stated |
| other | 12 | Read the license |
| cc-by-4.0 | 10 | Yes |
| cc-by-nc-4.0 | 8 | Not without separate permission |
| mit | 3 | Yes |
| cc-by-sa-4.0 | 3 | Yes |
| unknown | 1 | Read the license |

## Who Publishes Them

| Publisher | Datasets |
| --- | --- |
| [National Engineering Research Center for Big Data Software](https://savrn.com/model-publishers/thulab) | 12 |
| [IPEC at Shanghai AI Laboratory](https://savrn.com/model-publishers/ipec-community) | 5 |
| [Michal Podolinsky](https://savrn.com/model-publishers/podolinsky) | 4 |
| [K](https://savrn.com/model-publishers/kob0105) | 4 |
| [Genrobot.ai](https://savrn.com/model-publishers/genrobot2025) | 3 |
| [Kun Zhao](https://savrn.com/model-publishers/fleaven) | 3 |

## All 120 Datasets, Page 1 of 2

Dataset · Robotics

### [PhysicalAI-Robotics-GR00T-X-Embodiment-Sim](https://savrn.com/datasets/physicalai-robotics-gr00t-x-embodiment-sim)

[NVIDIA](https://savrn.com/model-publishers/nvidia)

We provide a set of datasets used for post-training of GR00T N1. Each dataset is a collection of trajectories from different robot embodiments and tasks. Users can download a specific subset of data by specifying the dataset name. 1. Option 1: with huggingface-cli Replace gr1armsonly.CanSort/ with the dataset name you want to download. 2. Option 2: Github LFS Replace the "gr1armswaist.CupToDrawer" with the intended dataset folder

Publicly accessible cc-by-4.0

[View dataset](https://savrn.com/datasets/physicalai-robotics-gr00t-x-embodiment-sim)

Dataset · Robotics

### [10Kh-RealOmin-OpenData](https://savrn.com/datasets/10kh-realomin-opendata)

[Genrobot.ai](https://savrn.com/model-publishers/genrobot2025)

Boasting over 13,000 hours of cumulative data and 5 million+ clips, it ranks as the largest open-source embodied intelligence dataset in the industry. 1. 13,000+ hours of pure dual-hand data with frame-level alignment latency < 1ms 2. Full high-precision trajectory reconstruction, breaking the limit of superficial open source, fully ready-to-use 3. 3,000+ contributors and 10,000+ real household scenarios with exceptional diversity 4. Comprehensive manipulation skill coverage to empower general embodied intelligence training We are committed to delivering high-quality data that drives industry progress, lowering innovation barriers and accelerating the implementation of robotic…

Access requested at publisher cc-by-sa-4.0 n>1T

[View dataset](https://savrn.com/datasets/10kh-realomin-opendata)

Dataset · Robotics

### [language_table_lerobot](https://savrn.com/datasets/language-table-lerobot)

[IPEC at Shanghai AI Laboratory](https://savrn.com/model-publishers/ipec-community)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/language-table-lerobot)

Dataset · Robotics

### [droid_lerobot](https://savrn.com/datasets/droid-lerobot)

[IPEC at Shanghai AI Laboratory](https://savrn.com/model-publishers/ipec-community)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/droid-lerobot)

Dataset · Robotics

### [droid_1.0.1](https://savrn.com/datasets/droid-1-0-1)

[Remi Cadene](https://savrn.com/model-publishers/cadene)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/droid-1-0-1)

Dataset · Robotics

### [kuka_lerobot](https://savrn.com/datasets/kuka-lerobot)

[IPEC at Shanghai AI Laboratory](https://savrn.com/model-publishers/ipec-community)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/kuka-lerobot)

Dataset · Robotics

### [AgiBotWorld2026](https://savrn.com/datasets/agibotworld2026)

[AgiBot World](https://savrn.com/model-publishers/agibot-world)

Real-World Embodied Intelligence Dataset As robotics research advances into real-world scenarios, the demand for authentic, high-quality data has become increasingly urgent. Following AGIBOT WORLD's "ImageNet moment," we now release the AGIBOT WORLD 2026 dataset. Built upon massive real-world scenes, it systematically spans pivotal research directions in embodied intelligence, designed to power the next generation of embodied agents. The AGIBOT WORLD 2026 dataset is collected from 100% real-world environments, covering commercial spaces, home, and other general-purpose scenarios. Collected on the AGIBOT G2 robot platform through a free-form collection mode, the dataset provides developers…

Publicly accessible cc-by-nc-sa-4.0 1K<n<10K

[View dataset](https://savrn.com/datasets/agibotworld2026)

Dataset · Robotics

### [stereo-550](https://savrn.com/datasets/stereo-550)

[FPV Labs](https://savrn.com/model-publishers/fpvlabs)

A first-person calibrated stereo RGB video dataset capturing everyday human manipulation across objects, materials, tools, and multi-step activities. Every session is recorded as a synchronized left/right camera pair with per-session stereo calibration, giving the visual geometry of hands, object interaction, state change, and task progression, signals directly relevant to embodied perception, video-language learning, and human-to-robot representation research. The dataset's strongest differentiator is dense, free-form action captioning at scale. Every recording is segmented into second-scale spans, each carrying a descriptive natural-language caption (e.g. "place small metal cup on kitchen…

Access requested at publisher other 1K<n<10K

[View dataset](https://savrn.com/datasets/stereo-550)

Dataset · Robotics

### [bridge_orig_lerobot](https://savrn.com/datasets/bridge-orig-lerobot)

[IPEC at Shanghai AI Laboratory](https://savrn.com/model-publishers/ipec-community)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/bridge-orig-lerobot)

Dataset · Robotics

### [fractal20220817_data_lerobot](https://savrn.com/datasets/fractal20220817-data-lerobot)

[IPEC at Shanghai AI Laboratory](https://savrn.com/model-publishers/ipec-community)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/fractal20220817-data-lerobot)

Dataset · Robotics

### [droid](https://savrn.com/datasets/droid)

[Remi Cadene](https://savrn.com/model-publishers/cadene)

This dataset was created using LeRobot. One of the biggest open-source dataset for robotics with 27.044,326 frames, 92,223 episodes, 31,308 unique task description in natural language. Ported from Tensorflow Dataset format (2TB) to LeRobotDataset format (400GB) with the help from IPEC-COMMUNITY.

Publicly accessible apache-2.0 10M<n<100M

[View dataset](https://savrn.com/datasets/droid)

Dataset · Robotics

### [2025-challenge-demos](https://savrn.com/datasets/2025-challenge-demos)

[BEHAVIOR-1K](https://savrn.com/model-publishers/behavior-1k)

This dataset was created using LeRobot.

Publicly accessible mit

[View dataset](https://savrn.com/datasets/2025-challenge-demos)

Dataset · Robotics

### [Retargeted_AMASS_for_bxi_elf2](https://savrn.com/datasets/retargeted-amass-for-bxi-elf2)

[Kun Zhao](https://savrn.com/model-publishers/fleaven)

This project aims to retarget motion data from the AMASS dataset to various robot models and open-source the retargeted data to facilitate research and applications in robotics and human-robot interaction. AMASS (Archive of Motion Capture as Surface Shapes) is a high-quality human motion capture dataset, and the SMPL-X model is a powerful tool for generating realistic human motion data. By adapting the motion data from AMASS to different robot models, we hope to provide a more diverse and accessible motion dataset for robot training and human-robot interaction. This open-source project includes the following: 1. Retargeted Motions: Motion files retargeted from AMASS to various robot models.…

Publicly accessible cc-by-4.0 10K<n<100K

[View dataset](https://savrn.com/datasets/retargeted-amass-for-bxi-elf2)

Dataset · Robotics

### [Retargeted_AMASS_for_FourierN1](https://savrn.com/datasets/retargeted-amass-for-fouriern1)

[Kun Zhao](https://savrn.com/model-publishers/fleaven)

This project aims to retarget motion data from the AMASS dataset to various robot models and open-source the retargeted data to facilitate research and applications in robotics and human-robot interaction. AMASS (Archive of Motion Capture as Surface Shapes) is a high-quality human motion capture dataset, and the SMPL-X model is a powerful tool for generating realistic human motion data. By adapting the motion data from AMASS to different robot models, we hope to provide a more diverse and accessible motion dataset for robot training and human-robot interaction. This open-source project includes the following: 1. Retargeted Motions: Motion files retargeted from AMASS to various robot models.…

Publicly accessible cc-by-4.0 10K<n<100K

[View dataset](https://savrn.com/datasets/retargeted-amass-for-fouriern1)

Dataset · Robotics

### [Retargeted_AMASS_for_robotics](https://savrn.com/datasets/retargeted-amass-for-robotics)

[Kun Zhao](https://savrn.com/model-publishers/fleaven)

This project aims to retarget motion data from the AMASS dataset to various robot models and open-source the retargeted data to facilitate research and applications in robotics and human-robot interaction. AMASS (Archive of Motion Capture as Surface Shapes) is a high-quality human motion capture dataset, and the SMPL-X model is a powerful tool for generating realistic human motion data. By adapting the motion data from AMASS to different robot models, we hope to provide a more diverse and accessible motion dataset for robot training and human-robot interaction. This open-source project includes the following: 1. Retargeted Motions: Motion files retargeted from AMASS to various robot models.…

Publicly accessible cc-by-4.0 10K<n<100K

[View dataset](https://savrn.com/datasets/retargeted-amass-for-robotics)

Dataset · Robotics

### [Hy-Embodied-0.5-VLA-Data](https://savrn.com/datasets/hy-embodied-0-5-vla-data)

[Tencent](https://savrn.com/model-publishers/tencent)

We introduce Hy-Embodied-0.5-VLA (Hy-VLA) — an end-to-end Vision-Language-Action system that spans the full robot learning stack: data collection, model design, pre-training, supervised fine-tuning, RL post-training, and real-world deployment. Built on the Hy-Embodied-0.5 MoT backbone, Hy-VLA integrates a flow-matching action expert, a compact memory encoder for multi-frame history, and a delta-chunk action representation decoupled from embodiment-specific kinematics. Powered by 10,000+ hours of high-fidelity UMI demonstrations collected via a custom fingertip interface with optical motion-capture, Hy-VLA achieves state-of-the-art results on the RoboTwin 2.0 benchmark (90.9% / 90.1% on…

Publicly accessible cc-by-4.0 1M<n<10M

[View dataset](https://savrn.com/datasets/hy-embodied-0-5-vla-data)

Dataset · Robotics

### [FDM-gcodes](https://savrn.com/datasets/fdm-gcodes)

[Kieran O'Connor](https://savrn.com/model-publishers/kpoc)

A massive, highly-diverse dataset of Fused Deposition Modeling (FDM) G-codes generated directly from Printables. This dataset is specifically designed for training machine learning models on raw 3D printing manufacturing instructions (G-code). It can be used for tasks like G-code generation, print failure prediction, semantic analysis of toolpaths, and printer-agnostic slice classification. To ensure a highly robust and diverse set of training data, every original 3D model from the source dataset has been iteratively sliced into multiple variants (default: 10 per model) using PrusaSlicer. The pipeline supports and natively slices.stl,.obj,.3mf,.step, and.amf files. For each variant, a…

Publicly accessible other n>1T

[View dataset](https://savrn.com/datasets/fdm-gcodes)

Dataset · Robotics

### [pico-robotics-basic](https://savrn.com/datasets/pico-robotics-basic)

[Jiu](https://savrn.com/model-publishers/skycn110)

First-person stereo video, depth and head pose of real shelf-work and facility tasks, captured on a Pico VR headset. By OpenElephant Intelligence (公象智能), Beijing. This is the free, open entry point to a much larger commercial collection (10,000+ hours). It is meant for evaluating the data quality and format before requesting the Advanced Edition or a commercial license. Real store shelving with beverage coolers, snack gondolas and hanging snack racks. Most tasks are "error correction": the shelf starts out mis-stocked and the operator finds and fixes the misplaced items. A large indoor sports hall with fitness equipment, mats and event cabling. spatialcalibration.json gives, for the left…

Access requested at publisher cc-by-nc-4.0 1K<n<10K

[View dataset](https://savrn.com/datasets/pico-robotics-basic)

Dataset · Robotics

### [pico-robotics-advanced](https://savrn.com/datasets/pico-robotics-advanced)

[Jiu](https://savrn.com/model-publishers/skycn110)

First-person stereo video, depth, head pose, pose-aligned point clouds and time-stamped action captions of real shelf-work and facility tasks, captured on a Pico VR headset. By OpenElephant Intelligence (公象智能), Beijing. The Advanced Edition adds 3D geometry and language to the Basic Edition: every episode comes with world-aligned point clouds, a ready-to-view MCAP recording, and a sequence of time-stamped captions describing what the operator is doing. It is a sample of a 10,000+ hour commercial collection. Gated. Requests are reviewed manually, usually within 3 business days. Real store shelving with beverage coolers, snack gondolas and hanging snack racks. Most tasks are "error…

Access requested at publisher cc-by-nc-4.0 1K<n<10K

[View dataset](https://savrn.com/datasets/pico-robotics-advanced)

Dataset · Robotics

### [ABC-130k](https://savrn.com/datasets/abc-130k)

[XDOF](https://savrn.com/model-publishers/xdof)

ABC-130k is the largest open-source robot teleoperation dataset. It contains bimanual manipulation trajectories collected on two-arm YAM stations. Episodes are distributed as MCAP files, with subtask annotations kept as separate artifacts so they can be revised or extended independently of the underlying episode data. For details on the accompanying paper, see abc.bot. Please see the GitHub repo here for code to train and deploy with this dataset. Each episode is a directory containing one or two MCAP files that share a single absolute time base. An episode.mcap file will always be present, and for annotated episodes there will be an additional annotation.mcap. Full channel-level…

Access requested at publisher apache-2.0 n>1T

[View dataset](https://savrn.com/datasets/abc-130k)

Dataset · Robotics

### [ACE-Data-0](https://savrn.com/datasets/ace-data-0)

[ACE Robotics](https://savrn.com/model-publishers/acerobotics)

▶ Demo video Learning to act in the physical world requires more than observing what an action looks like: models must capture how first-person perception, whole-body motion, dexterous manipulation, object state, sound, and touch evolve together as humans pursue goals over time. Existing datasets fragment this experience across viewpoints, modalities, or spatial scales. ACE-Data-0 records all of it in one pass, on one clock, in one world frame. Participants receive goal-level instructions ("prepare a cup of tea and serve it at the table") rather than step-by-step scripts, so planning, hesitation, and improvisation enter the data by themselves. Human states, object states, and contact are…

Publicly accessible other 10K<n<100K

[View dataset](https://savrn.com/datasets/ace-data-0)

Dataset · Robotics

### [HiFi-UMI-2K](https://savrn.com/datasets/hifi-umi-2k)

[Simple World Lab](https://savrn.com/model-publishers/simple-world-lab)

src="https://cloud.simpleai.tech/simpleworldlab/media/posters/data-canvas.jpg" alt="A mosaic of diverse HiFi-UMI demonstrations" width="960" HiFi-UMI is a portable, high-fidelity bimanual capture system for collecting robot-free manipulation demonstrations. HiFi-UMI-2K is the large-scale dataset produced by this system and is designed to provide action-grounded supervision for manipulation policy pre-training and post-training without requiring a robot during data collection. The release contains a curated 2,000-hour subset of a source corpus exceeding 20,000 hours and 4.32 million episodes across more than 480 scenes. Each episode includes synchronized multi-view video, calibrated bimanual…

Publicly accessible cc-by-4.0

[View dataset](https://savrn.com/datasets/hifi-umi-2k)

Dataset · Robotics

### [Gen-HumanEgo](https://savrn.com/datasets/gen-humanego)

[Genrobot.ai](https://savrn.com/model-publishers/genrobot2025)

1,800+ hours of egocentric human demonstrations with synchronized, structured supervision for embodied AI and robot learning. Gen-HumanEgo contains real-world first-person demonstrations collected across diverse tasks, people, environments, and ways of performing activities using a unified six-camera DAS-Ego setup. GenRobot's Data Foundation Model (DFM) processes the recordings to provide complementary training signals for human motion, spatial understanding, and task understanding. - 3D hand reconstruction: 3D hand keypoints, MANO parameters, and full hand geometry. For a detailed introduction to the dataset, see our Gen-HumanEgo Technical Blog The task-organized directory tree follows the…

Publicly accessible cc-by-sa-4.0 n>1T

[View dataset](https://savrn.com/datasets/gen-humanego)

Dataset · Robotics

### [OmniEgo](https://savrn.com/datasets/omniego)

[Delta Intelligence](https://savrn.com/model-publishers/delta-intelligence)

The D1 dataset is exported from the D1 headset multi-camera human motion capture system developed by Delta Intelligence. Each recorded episode contains synchronized multi-view video streams and whole-body skeleton and headset pose data. The dataset supports research and development in: - Human detection, keypoint detection, and pose estimation - Egocentric visual observation and synchronization checking - Imitation learning, behavior cloning, and embodied intelligence model training - Visual-inertial odometry and SLAM-related observation analysis Unlike purely third-person datasets, D1 combines egocentric RGB and fisheye views with global whole-body skeleton and headset pose states, making…

Publicly accessible other

[View dataset](https://savrn.com/datasets/omniego)

Dataset · Robotics

### [benchmark-datasets](https://savrn.com/datasets/benchmark-datasets)

[Latency Sensitive Bench](https://savrn.com/model-publishers/latency-sensitive-bench)

Accepted zero-latency teacher rollouts for the supported benchmark tasks. - humanoidbenchbalancesimple: 90 training and 10 validation episodes. The observation.image values are PNG bytes declared as the Hugging Face Image feature, so the Dataset Viewer renders them instead of showing their encoded representation. Canonical LeRobot MP4 files remain under each split's videos/ directory. - mikasainterceptgrabfast: fixed 250/25 StarVLA split. Every Viewer row includes its corresponding observation.images.top and observation.images.wrist frame. The canonical LeRobot data remains under the task path with its RGB observations stored in MP4 files.…

Publicly accessible other

[View dataset](https://savrn.com/datasets/benchmark-datasets)

Dataset · Robotics

### [GiT_hdf5](https://savrn.com/datasets/git-hdf5)

[XGQ](https://savrn.com/model-publishers/xgq12345)

[ GitHub ] [ arXiv ] [ HuggingFace ] [ ModelScope ] Grounded in Time is a benchmark and dataset for temporal grounding under perceptual ambiguity in robotic manipulation. Its tasks are deliberately built so that the object a command refers to cannot be identified from the current frame alone. Each scene contains several perceptually near-identical objects, and what separates them is not appearance but the temporal structure of the episode — which test tube was contaminated first, which container was filled last, which part was handed over just now. A model that grounds the instruction on the present frame alone will pick the wrong object; resolving the reference requires tracking and…

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/git-hdf5)

Dataset · Robotics

### [OmniDex](https://savrn.com/datasets/omnidex)

[Aceroboticsdex](https://savrn.com/model-publishers/willfny)

OmniDex: Scaling Dexterous Hand Grasping to Diverse Cluttered Scenes. Upload in progress. This public repository is receiving the full STD data and its object/support assets. Files become available progressively. The release is complete only when std/1.0.0/release.json reports uploadedverifiedpublic. File counts and total sizes are being measured; this page does not claim a complete release yet. Large components are packaged into numbered archives, generally around 5 GiB of source files per shard. Observations use.tar; other components use.tar.zst. A scene or an object directory is kept within one archive. Each archive has a per-file size and SHA256 sidecar. Original annotation values and…

Publicly accessible other

[View dataset](https://savrn.com/datasets/omnidex)

Dataset · Robotics

### [VR-egodex-depth-cache-full](https://savrn.com/datasets/vr-egodex-depth-cache-full)

[VR-VLA](https://savrn.com/model-publishers/vr-vla)

Per-frame metric scene depth (Depth-Anything-V2 Metric Indoor Large, 20 m ceiling) for the episodes inpainted in VR-VLA/VR-egodex-inpaint-cache-full. Depth is the second input Eq. 4 compositing needs beside the inpainted plate; together they let scripts/egodex/buildtask.py retarget an episode onto all 16 embodiments. Archive names are IDENTICAL to the inpaint repo, one tar per /: Episode numbers match the source dataset's episode%06d.mp4. is part of the key: most task names exist in both train/ and test/ with overlapping episode numbers. Archives are uncompressed tar (PNG payload). train/addremovelidv2.1.tar (308 GB, 1,158 episodes) exceeds the Hub's 50 GB file limit and is stored as…

Publicly accessible other

[View dataset](https://savrn.com/datasets/vr-egodex-depth-cache-full)

Dataset · Robotics

### [DiverseUMI-sample100](https://savrn.com/datasets/diverseumi-sample100)

[Pantheon Industries](https://savrn.com/model-publishers/pantheon-inc)

Pantheon DiverseUMI (100h Sample) contains 99.6 hours of bimanual tabletop manipulation, recorded with two handheld UMI grippers and a fisheye camera above the table (a 360-degree dual-fisheye camera in some recordings). It has 12,219 episodes from 1,134 recordings. Each episode is one task, such as stacking two blocks or passing a ball between the grippers. Every episode has three synchronized videos (the top camera and both wrist cameras), wrist pose arrays and per-step actions with validity masks, and dense model-generated labels of what the operator does. Operators worked freely with everyday objects. Tasks in one recording can overlap in time, so 156 pairs of episodes share some…

Access requested at publisher other 10K<n<100K

[View dataset](https://savrn.com/datasets/diverseumi-sample100)

Dataset · Robotics

### [LIBERO-Pro2.0-Eval](https://savrn.com/datasets/libero-pro2-0-eval)

[Zhou Xueyang](https://savrn.com/model-publishers/zhouxueyang)

LIBERO-Pro2.0: A Benchmark for Evaluating the Robustness of Embodied Foundation Models This repository provides the evaluation resources for LIBERO-Pro2.0, a robustness benchmark for embodied foundation models. It evaluates generalization under static distribution shifts and adaptation to interventions during task execution, covering 22 static and 20 runtime perturbation types across six domains. The release includes BDDL tasks, initial states, simulator assets, evaluation service/client code and resumable batch runners. GitHub maintains the source; LIBERO-Pro2.0-Train provides HDF5 demonstrations, training metadata and trajectory source indices. Training trajectories are not required to…

Publicly accessible

[View dataset](https://savrn.com/datasets/libero-pro2-0-eval)

Dataset · Robotics

### [sunvage-vertens3d-simhome](https://savrn.com/datasets/sunvage-vertens3d-simhome)

[Sunvage Lab](https://savrn.com/model-publishers/sunvage-lab)

English | 中文 Physically-annotated indoor scene USD assets derived from 14,169 real interior design schemes on the sunvage floorplan platform — every furniture instance carries collision shapes, mass, friction and restitution, and opens directly in USD physics simulators. sunvage-vertens3d-simhome is a collection of physically-annotated indoor scene USD assets derived from real interior design schemes in the sunvage (三维家) floorplan library. It provides both whole-home multi-space scenes and individual single-space scenes. Every physical instance carries collision shapes and mass properties, and the scenes can be loaded directly into USD physics simulators such as Isaac Sim / Isaac Lab for…

Access requested at publisher other 1K<n<10K

[View dataset](https://savrn.com/datasets/sunvage-vertens3d-simhome)

Dataset · Robotics

### [DiverseUMI-sample25](https://savrn.com/datasets/diverseumi-sample25)

[Pantheon Industries](https://savrn.com/model-publishers/pantheon-inc)

Pantheon DiverseUMI (25h Sample) contains 25.0 hours of bimanual tabletop manipulation, recorded with two handheld UMI grippers and a fisheye camera above the table (a 360-degree dual-fisheye camera in some recordings). It has 4,587 episodes from 293 recordings. Each episode is one task, such as stacking two blocks or passing a ball between the grippers. Every episode has three synchronized videos (the top camera and both wrist cameras), wrist pose arrays and per-step actions with validity masks, and dense model-generated labels of what the operator does. Operators worked freely with everyday objects. Tasks in one recording can overlap in time, so 73 pairs of episodes share some frames. Of…

Access requested at publisher other 1K<n<10K

[View dataset](https://savrn.com/datasets/diverseumi-sample25)

Dataset · Robotics

### [telearms-yam-cube-v4](https://savrn.com/datasets/telearms-yam-cube-v4)

[MuchenLiu](https://savrn.com/model-publishers/mliu48)

Teleoperated bimanual manipulation demonstrations collected in MuJoCo with a BimanualYAM robot, packaged in LeRobot v3.0 format for pi0.5 training. Three RGB views per frame — camerafront, cameraleft, cameraright (224x224, H.264). Robot state and action are both 14-dimensional: 6 arm joints plus 1 gripper per arm. A 128-dimensional non-robot state carries object/scene information for diagnostics. Actions are stored as absolute joint targets. The training recipe converts the 12 arm dimensions to deltas relative to the current action-chunk anchor while the 2 gripper dimensions stay absolute. The normalization statistics in meta/stats.json are computed in that 50-step relative space — do not…

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/telearms-yam-cube-v4)

Dataset · Robotics

### [DexCanvas](https://savrn.com/datasets/dexcanvas)

[DexGEM Lab](https://savrn.com/model-publishers/dex-gem)

DexCanvas: Bridging Human Demonstrations and Robot Learning for Dexterous Manipulation DexCanvas is a dataset of 111,857 complete right-hand trajectories and 55,442,683 frames of rigid hand–object interaction. Every Parquet row is one trajectory with a shared time axis for hand kinematics, object pose, and per-frame contacts. For each trajectory, the repository also provides the complete dual-camera JPEG stream of the corresponding capture and shape-specific kinematic assets for replay. Camera images are associated at the complete Raw trajectory level. The release does not claim that trajectory frame i corresponds to image i. - 111,857 trajectories; 55,442,683 frames; 96,484,004 contact…

Access requested at publisher odbl 100K<n<1M

[View dataset](https://savrn.com/datasets/dexcanvas)

Dataset · Robotics

### [ego-stereo-cn-v1](https://savrn.com/datasets/ego-stereo-cn-v1)

[Tate Zhou](https://savrn.com/model-publishers/tatezhou)

Two human egocentric stereo episodes recorded on real job sites in Hangzhou, China, released as a public, verifiable sample of a production egocentric data-collection pipeline. This is a sample, not a benchmark. It exists so that anyone evaluating egocentric data vendors can inspect real output — actual frame timing, actual synchronisation, actual annotation depth — instead of reading a capability deck. Independently validated. The dataset passes The same two episodes previously passed an external buyer's incoming data QC (August 2026). Total: 4,914 frames / 163.47 s, two synchronised streams per episode. Two numbers worth pausing on, because they are where most egocentric data fails: - p99…

Publicly accessible cc-by-nc-4.0 n<1K

[View dataset](https://savrn.com/datasets/ego-stereo-cn-v1)

Dataset · Robotics

### [SAGE-data](https://savrn.com/datasets/sage-data)

[Letian Cheng](https://savrn.com/model-publishers/cltray)

Manipulation datasets for SAGE: Subgoal-Conditioned Action Generation for Latent World Model Planning. Sizes are archive sizes in decimal GB. Training and validation archives are under training/; evaluation archives are under evaluation/. Evaluation archives contain the inputs required by the released query manifests, not a complete training dataset. Simulator assets and model weights are installed separately. Download only the evaluation data you need, for example LIBERO Scene2: To download Scene2 training and validation instead, use allowpatterns=["training/liberoscene2"]. Replace liberoscene2 with liberocaddy or robotwina2b for the other environments. Omitting allowpatterns downloads all…

Publicly accessible

[View dataset](https://savrn.com/datasets/sage-data)

Dataset · Robotics

### [kuka-centrifuge-expert-review_20260917_174048](https://savrn.com/datasets/kuka-centrifuge-expert-review-20260917-174048)

[Andrea Rosasco](https://savrn.com/model-publishers/ar0s)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/kuka-centrifuge-expert-review-20260917-174048)

Dataset · Robotics

### [rollout_gripper_open_80k_20260928_172345_20260928_172409](https://savrn.com/datasets/rollout-gripper-open-80k-20260928-172345-20260928-172409)

[Wen Xiya](https://savrn.com/model-publishers/hailey-5-2026)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/rollout-gripper-open-80k-20260928-172345-20260928-172409)

Dataset · Robotics

### [tracker-pov](https://savrn.com/datasets/tracker-pov)

[Eidon AI](https://savrn.com/model-publishers/eidon-ai)

1,274 hours of egocentric video paired with 7-point IMU arm tracking, recorded during ordinary household work. Contributors wore a head-mounted camera and a seven-sensor IMU harness while doing real chores in their own homes: laundry, cleaning, dishes, cooking. Each recording pairs first-person video with 24 Hz orientation data for both hands, both forearms, both upper arms, and the chest. This is a complete, final release. Eidon AI (Solidic Labs Inc) has wound down; the dataset is published under CC-BY-4.0 so it outlives the company. The release is split across two repos and a bucket. The data/NNN/ split exists only to keep directories manageable; the grouping carries no meaning. Both are…

Publicly accessible cc-by-4.0 10K<n<100K

[View dataset](https://savrn.com/datasets/tracker-pov)

Dataset · Robotics

### [nick-sep14](https://savrn.com/datasets/nick-sep14)

[Nathaniel Nifong](https://savrn.com/model-publishers/naavox)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/nick-sep14)

Dataset · Robotics

### [EgoDex-Retarget-16robot](https://savrn.com/datasets/egodex-retarget-16robot)

[VR-VLA](https://savrn.com/model-publishers/vr-vla)

EgoDex egocentric human demonstrations retargeted onto 16 robot embodiments. For every episode, the human wrist and hand motion is solved into a joint trajectory for each robot, and the robot is rendered and composited into the original scene, over hand-erased frames and per-frame metric depth. Each (robot, task) pair is one LeRobot v3.0 dataset. VR-VLA/VR-egodex-inpaint-cache-full (hand-erased frames), VR-VLA/VR-egodex-depth-cache-full (depth), bi199797/VR-egodex-apple-lerobot (source episodes). Upload in progress; the table is the first upload (2026-10-02). More datasets are added as their builds finish. 206 tasks (113 train, 93 test), 30 fps. The 14 single-arm robots are used as a pair…

Publicly accessible other

[View dataset](https://savrn.com/datasets/egodex-retarget-16robot)

Dataset · Robotics

### [gr00t-libero-x-features-v3](https://savrn.com/datasets/gr00t-libero-x-features-v3)

[Michal Podolinsky](https://savrn.com/model-publishers/podolinsky)

Aligned rollouts of a LIBERO-X fine-tune of GR00T-N1.7 on the LIBERO-X simulator, with K = 10 action chunks sampled at every policy inference. Sample 0 is the chunk the robot executes; the other 9 are drawn from the same observation and never executed. This is what sampling-based failure detectors such as STAC need, alongside the per-token backbone features used by representation probes (e.g. SAFE). 218 tasks (72 / 73 / 73 for LEVEL1 / LEVEL2 / LEVEL3) × 10 initial states = 2,180 episodes, all with features and all 10 samples. This is the K=10 companion to same checkpoint, same 218 tasks, same initial states and seed (identical rolloutids), but a separate run with a different execution…

Access requested at publisher 1K<n<10K

[View dataset](https://savrn.com/datasets/gr00t-libero-x-features-v3)

Dataset · Robotics

### [pi0.5-libero-10-features-v3](https://savrn.com/datasets/pi0-5-libero-10-features-v3)

[Michal Podolinsky](https://savrn.com/model-publishers/podolinsky)

Aligned rollouts of the stock openpi pi05libero policy on LIBERO libero10, in two matched scene variants (normal and the LIBERO-Occ occluded suite), with K = 10 action chunks sampled at every policy inference. Sample 0 is the chunk the robot executes; the other 9 are drawn from the same observation (a fresh flow-matching noise key per call) and never executed. This is what sampling-based failure detectors such as STAC need, alongside the per-token prefix features used by representation probes (e.g. SAFE). 10 tasks × 2 variants × 25 initial states = 500 episodes, all with features and all 10 samples. This is a separate run of the same 500 initial states (seed 7) as which has one chunk per…

Access requested at publisher n<1K

[View dataset](https://savrn.com/datasets/pi0-5-libero-10-features-v3)

Dataset · Robotics

### [test](https://savrn.com/datasets/test-2)

[Mklovin](https://savrn.com/model-publishers/mklovin)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/test-2)

Dataset · Robotics

### [groot-libero-10-features-v3](https://savrn.com/datasets/groot-libero-10-features-v3)

[Michal Podolinsky](https://savrn.com/model-publishers/podolinsky)

Aligned rollouts of the stock NVIDIA GR00T-N1.7-LIBERO (libero10 checkpoint) policy on LIBERO libero10, in two matched scene variants (normal and the LIBERO-Occ occluded suite), with K = 10 action chunks sampled at every policy inference. Sample 0 is the chunk the robot executes; the other 9 are drawn from the same observation and never executed. This is what sampling-based failure detectors such as STAC need, alongside the per-token backbone features used by representation probes (e.g. SAFE). 10 tasks × 2 variants × 25 initial states = 500 episodes, all with features and all 10 samples. This is a separate run of the same 500 initial states (seed 7) as which has one chunk per inference plus…

Access requested at publisher n<1K

[View dataset](https://savrn.com/datasets/groot-libero-10-features-v3)

Dataset · Robotics

### [gr00t-N1.7-libero-x-features](https://savrn.com/datasets/gr00t-n1-7-libero-x-features)

[Michal Podolinsky](https://savrn.com/model-publishers/podolinsky)

Aligned rollouts of a LIBERO-X fine-tune of GR00T-N1.7 on the LIBERO-X simulator, over the exact 90 tasks that checkpoint was fine-tuned on (30 tasks × 3 difficulty levels, LEVEL1–LEVEL3). Train and eval task sets are identical by design, so this is an in-distribution dataset for the checkpoint. 90 tasks × 20 rollouts = 1,800 episodes (600 per level). Every GR00T inference, executed action, and video frame in an episode is joinable by array row. This is the LIBERO-X counterpart of — same layer-16 backbone feature schema, same alignment contract — but on a fine-tuned checkpoint and a harder, distribution-shifted benchmark. The two differ in a few protocol details (no settle steps, native…

Access requested at publisher 1K<n<10K

[View dataset](https://savrn.com/datasets/gr00t-n1-7-libero-x-features)

Dataset · Robotics

### [RoboTwin2.0-RGB-D](https://savrn.com/datasets/robotwin2-0-rgb-d)

[Hongxiao Yu](https://savrn.com/model-publishers/hongxiaoy)

An RGBD robotic manipulation dataset regenerated from RoboTwin 2.0, augmented with depth camera data for training imitation learning policies such as PI-0. Uses the LargeD435 camera configuration (640×480 resolution), matching the raw shape in configs/data/robotwin.yaml. Both versions cover all 50 manipulation tasks in RoboTwin 2.0, with depth: true and LargeD435 cameras (640×480). Each camera provides both RGB and depth (uint16, millimeters) data. Raw collected data is stored as HDF5 files. Each episode contains: - jointaction/ — left/right arm joint positions + gripper state - observation/ /rgb — RGB images (JPEG encoded) - observation/ /depth — depth maps (float32, millimeters)…

Publicly accessible mit

[View dataset](https://savrn.com/datasets/robotwin2-0-rgb-d)

Dataset · Robotics

### [record-test_20261018_163809](https://savrn.com/datasets/record-test-20261018-163809)

[Ss](https://savrn.com/model-publishers/mohsenkhajoee)

This dataset was created using LeRobot. Dataset Structure "codebaseversion": "v3.0", "fps": 30, "features": { "action": { "dtype": "float32", "names": [ "shoulderpan.pos", "shoulderlift.pos", "elbowflex.pos", "wristflex.pos", "wristroll.pos", "gripper.pos" "shape": [ 6

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/record-test-20261018-163809)

Dataset · Robotics

### [SlugTrails](https://savrn.com/datasets/slugtrails)

[Yunqian Cheng](https://savrn.com/model-publishers/head-inthe-cloud)

SlugTrails is an egocentric floor-plan localization benchmark for large indoor buildings. This Hugging Face package (slugtrails-1.0) is the canonical public data blob: anonymized RGB, Project Aria MPS trajectories, floor-plan–aligned ground truth, CAD-derived maps, and official evaluation / finetune splits. manifests/ holds our official splits for the paper protocol (SHA-256 digests in RELEASE.json). You may define your own sampling if you prefer; numbers comparable to the paper should use these manifests. - 3 campus buildings / 6 floors — floor-plan outline 22 089 m², circulation space 5317 m² (same figures as the paper) - 6 Aria sessions (~30 Hz RGB); trajectory length ≈ 1.80 km (≈…

Publicly accessible cc-by-4.0 10GB<n<100GB

[View dataset](https://savrn.com/datasets/slugtrails)

Dataset · Robotics

### [kitting_connector](https://savrn.com/datasets/kitting-connector)

[Jimmy Ho](https://savrn.com/model-publishers/syqnal)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/kitting-connector)

Dataset · Robotics

### [0603_pi0_onlyright](https://savrn.com/datasets/0603-pi0-onlyright)

[National Engineering Research Center for Big Data Software](https://savrn.com/model-publishers/thulab)

Apache TsFile version of weiye11/0603pi0onlyright. A right-arm-only teleoperation dataset recorded on an SO-100 robot and packaged in the LeRobot v2.1 layout. Each row is one control step: a 6-dimensional right-arm joint/gripper state and the 6-dimensional commanded action. The source dataset card does not name the manipulation task; the metadata records a single task (taskindex = 0). - Time (INT64, milliseconds) — round(timestamp 1000); restarts at 0 for each episode. - episodeindex (TAG) — episode / device dimension. - taskindex (TAG) — task dimension (constant 0 here). - frameindex (FIELD, INT64) — source frame counter; sampleindex (FIELD, INT64) — source index column (renamed).…

Publicly accessible apache-2.0 1K<n<10K

[View dataset](https://savrn.com/datasets/0603-pi0-onlyright)

Dataset · Robotics

### [2026-10-14_twist_02-lerobot-with-rinse](https://savrn.com/datasets/2026-10-14-twist-02-lerobot-with-rinse)

[Yongliang Lyu](https://savrn.com/model-publishers/lyl472324464)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/2026-10-14-twist-02-lerobot-with-rinse)

Dataset · Robotics

### [23Sep_STEA_pick_Cortex_filtered](https://savrn.com/datasets/23sep-stea-pick-cortex-filtered)

[Alphabot2](https://savrn.com/model-publishers/alphabot2)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/23sep-stea-pick-cortex-filtered)

Dataset · Robotics

### [4_20260930_113445](https://savrn.com/datasets/4-20260930-113445)

[Zihang Ma](https://savrn.com/model-publishers/mzh008)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/4-20260930-113445)

Dataset · Robotics

### [act_recollect_gripper_open_bottom_right_20260928_123339_20260928_123349](https://savrn.com/datasets/act-recollect-gripper-open-bottom-right-20260928-123339-20260928-123349)

[Wen Xiya](https://savrn.com/model-publishers/hailey-5-2026)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/act-recollect-gripper-open-bottom-right-20260928-123339-20260928-123349)

Dataset · Robotics

### [augs_hiliter_01](https://savrn.com/datasets/augs-hiliter-01)

[National Engineering Research Center for Big Data Software](https://savrn.com/model-publishers/thulab)

Apache TsFile version of nitsuga-hug/augs-hiliter01. A SO follower (SO-101/SO-100) dataset for the "pnphiliter" pick-and-place task, collected with augmented human-in-the-loop data. Each frame records the 6-D joint state and the 6-D commanded action. Task (taskindex 0): "pnphiliter". - Time (INT64, milliseconds) - per-episode sample time, round(timestamp 1000) in milliseconds (the source timestamp column equals Time / 1000 seconds and is therefore not stored separately). - episodeindex, taskindex (TAG) - device dimensions identifying one demonstration episode and one task; query a single episode with WHERE episodeindex=0. - action0..5, observationstate0..5 (FIELD) - FLOAT 6-D SO-follower…

Publicly accessible apache-2.0 10K<n<100K

[View dataset](https://savrn.com/datasets/augs-hiliter-01)

Dataset · Robotics

### [axiboai_piper_umi_ee_pick_place](https://savrn.com/datasets/axiboai-piper-umi-ee-pick-place)

[National Engineering Research Center for Big Data Software](https://savrn.com/model-publishers/thulab)

Apache TsFile version of axiboai/piper-umi-ee-pick-place. This is a pick-and-place demonstration dataset recorded on an AgileX Piper arm with a single 6-DoF end-effector (pipersingleeef6d) and packaged in the LeRobot v2.1 layout. Each row is one control step: a 10-dimensional end-effector state (position x, y, z, rotation as 6-D rot6d, and gripper) together with the 10-dimensional commanded action. The metadata records a single task (taskindex = 0). - Time (INT64, milliseconds) — round(timestamp 1000); restarts at 0 for each episode. - episodeindex (TAG) — episode / device dimension. - taskindex (TAG) — task dimension (constant 0 here). - frameindex (FIELD, INT64) — source frame counter…

Publicly accessible apache-2.0 10K<n<100K

[View dataset](https://savrn.com/datasets/axiboai-piper-umi-ee-pick-place)

Dataset · Robotics

### [barcode_neck16_30hz](https://savrn.com/datasets/barcode-neck16-30hz)

[Minsoo](https://savrn.com/model-publishers/mimiminsoo)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/barcode-neck16-30hz)

Dataset · Robotics

### [C3_screwdriver_trio_20260918_150329](https://savrn.com/datasets/c3-screwdriver-trio-20260918-150329)

[Jan Philipp](https://savrn.com/model-publishers/janphilipp)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/c3-screwdriver-trio-20260918-150329)

Dataset · Robotics

### [cafe_001](https://savrn.com/datasets/cafe-001)

[National Engineering Research Center for Big Data Software](https://savrn.com/model-publishers/thulab)

Apache TsFile version of kjydb/cafe001. A teleoperation dataset recorded on a PS-A-03 500 arm and packaged in the LeRobot v2.1 layout. Each row is one control step: a 13-dimensional Cartesian state (position x, y, z, orientation rx, ry, rz, linear velocities x.vel, y.vel, z.vel, angular velocities pitch.vel, roll.vel, yaw.vel, and gripper.status) and the matching 13-dimensional commanded action. The metadata records a single task (taskindex = 0). - Time (INT64, milliseconds) — round(timestamp 1000); restarts at 0 for each episode. - episodeindex (TAG) — episode / device dimension. - taskindex (TAG) — task dimension (constant 0 here). - frameindex (FIELD, INT64) — source frame counter…

Publicly accessible apache-2.0 10K<n<100K

[View dataset](https://savrn.com/datasets/cafe-001)

## Other Tasks

- [Text Generation](https://savrn.com/datasets/tasks/text-generation) 140
- [Other](https://savrn.com/datasets/tasks/other) 50
- [Text Classification](https://savrn.com/datasets/tasks/text-classification) 50
- [Text Retrieval](https://savrn.com/datasets/tasks/text-retrieval) 44
- [Question Answering](https://savrn.com/datasets/tasks/question-answering) 39
- [Speech Recognition](https://savrn.com/datasets/tasks/speech-recognition) 34
- [Image to Text](https://savrn.com/datasets/tasks/image-to-text) 29
- [Time Series Forecasting](https://savrn.com/datasets/tasks/time-series-forecasting) 23
- [Tabular Classification](https://savrn.com/datasets/tasks/tabular-classification) 22
- [Image Classification](https://savrn.com/datasets/tasks/image-classification) 18
- [Object Detection](https://savrn.com/datasets/tasks/object-detection) 16
- [Visual Question Answering](https://savrn.com/datasets/tasks/visual-question-answering) 16

[See all](https://savrn.com/datasets/tasks)