--- title: TacVerse-Opendata canonical_url: "https://www.modelscope.cn/datasets/XenseRobotics/TacVerse-Opendata" md_url: "https://www.modelscope.cn/datasets/XenseRobotics/TacVerse-Opendata.md" repository: XenseRobotics/TacVerse-Opendata chinese_name: TacVerse-Opendata last_updated: 2026-09-18 license: cc-by-sa-4.0 downloads: 62754 stars: 0 --- # TacVerse-Opendata > TacVerse-Opendata - XenseRobotics 在 ModelScope 开源的数据集。Bimanual visuo-tactile manipulation datasets in LeRobot v3.0 format, collected with XTac-UMI-G1 grippers and Xense Neutron tactile sensors. XenseRobotics/TacVerse-Opendata 是 ModelScope 魔搭社区上的数据集，采用 cc-by-sa-4.0 许可。 - **Repository**: XenseRobotics/TacVerse-Opendata - **License**: cc-by-sa-4.0 - **Downloads**: 62754 - **Stars**: 0 - **Last updated**: 2026-09-18 Source: https://www.modelscope.cn/datasets/XenseRobotics/TacVerse-Opendata ---

Language: English (current) · 中文

Xense Robotics

Representative frames from TacVerse's bimanual demonstrations.

TacVerse collection and processing pipeline

Collected with XTac-UMI-G1 grippers, released as LeRobot datasets.

# TacVerse Open Data Collection of **122** LeRobot v3.0 task datasets — **17,690** episodes, **370.2 hours**, **40.0M** frames, ~145 GB. Each subfolder is a standalone LeRobot dataset (`meta/info.json`, `data/`, `videos/`). Collection timestamps have been removed from titles and metadata. Every frame carries **six synchronized video streams** — two wrist cameras and four **Xense Neutron** visuotactile channels (two per gripper) — at 30 fps, alongside per-hand 6-DoF pose and continuous jaw aperture. ```python from modelscope import snapshot_download from lerobot.datasets.lerobot_dataset import LeRobotDataset root = snapshot_download(repo_id="XenseRobotics/TacVerse-Opendata", repo_type="dataset") ds = LeRobotDataset("taccap-g1-wipe-mirror", root=f"{root}/taccap-g1-wipe-mirror") ``` ## At a glance | | This collection | Planned total | |---|---|---| | Task datasets | **122** | 350+ | | Scene families | **3** | 3 | | Episodes | **17,690** | ~480,000 | | Hours | **370.2** | **10,000+** | | Frames | **39,977,972** | ~1.1B | | Frame rate | 30 fps | 30 fps | | Visual streams | 2 wrist (640×480) | — | | Tactile streams | 4 (700×400) | — | | Robot type | `bi_taccap_gripper` | — | | Format | LeRobot v3.0 | LeRobot v3.0 | | Total size | ~145 GB | ~13 TB | | Size per hour | 0.39 GB | — | **This collection** is measured from this repository. **Planned total** is the TacVerse programme's target — this release is one openly published slice of it; see the [landing page](https://huggingface.co/datasets/TacVerse/TacVerse) for programme-wide figures. Planned episodes, frames and size are all extrapolated from this repository's own density (48 episodes and 0.39 GB per hour); the planned size follows the programme's own 1.3 GB per hour, not this repository's re-encoded density. ## Scenes The collection spans three scene families.

Scene families and representative objects

| Scene | Datasets | Episodes | Hours | |---|---|---|---| | **Office** | 44 | 3,028 | 55.5 | | **Home** | 70 | 13,124 | 286.9 | | **Workbench** | 8 | 1,538 | 27.7 | | **Total** | **122** | **17,690** | **370.2** | ### Task families | Scene | Task family | Datasets | Episodes | Hours | Largest tasks | |---|---|---|---|---|---| | **Office** | Desk tidying | 5 | 138 | 2.7 | `arrange-desk-items`, `remove-item-from-display-cover`, `put-item-in-display-cover` | | | Document handling | 3 | 51 | 1.5 | `flip-bound-document`, `pull-single-sheet`, `organize-folders` | | | Stationery | 2 | 31 | 1.5 | `paper-punching`, `arrange-pens-sticky-notes` | | | Print area | 3 | 231 | 9.3 | `organize-printing-paper-stack`, `organize-printing-papers-stack`, `remove-and-place-paper` | | | Meeting room | 4 | 65 | 2.6 | `organize-meeting-table-items`, `prepare-whiteboard-marker`, `align-remote-and-laser-pointer` | | | Pantry | 7 | 194 | 3.9 | `tear-open-the-coffee-bag`, `scoop-coffee-granules`, `grasp-the-water-cup-and-twist-off-the-cup-lid` | | | Cable management | 12 | 1,824 | 28.7 | `plug-the-charger-into-the-power-strip`, `connect-the-charger-to-the-type-c-data-cable`, `locate-cover-grip-clip-into-slot` | | | Connectors and ports | 8 | 494 | 5.2 | `unplug-usb-cable-from-port`, `insert-usb-connector-into-port`, `put-earphone-into-case` | | **Home** | Kitchen and dining | 15 | 1,256 | 39.3 | `place-food-with-tongs`, `rotate-seasoning-bottle-to-target`, `place-egg-into-egg-tray` | | | Drinks and food service | 6 | 329 | 8.5 | `place-paper-cup`, `pick-up-bread-slices`, `assemble-and-place-cup` | | | Food packaging | 10 | 925 | 13.1 | `open-resealable-bag`, `arrange-food-packaging-bags`, `pick-up-marshmallows` | | | Household items | 13 | 2,778 | 51.9 | `arrange-tabletop-items`, `press-remote-buttons`, `place-chess-pieces` | | | Cabinets and storage | 6 | 3,267 | 66.2 | `operate-shoe-box`, `snap-plastic-buckle`, `insert-hook-assembly` | | | Cleaning | 4 | 1,131 | 16.8 | `wipe-mirror`, `clean-desk`, `mask-extraction-and-stacking` | | | Clothing and textiles | 5 | 2,389 | 54.6 | `fold-garment`, `open-folded-towel`, `fold-towel` | | | Personal care | 7 | 996 | 34.5 | `arrange-skincare-products`, `cosmetics-are-scanned-and-boxed`, `press-pump-bottle` | | | Medical and lab | 4 | 53 | 2.0 | `liquid-medicine-bottles-cartoning`, `arrange-medicine-boxes`, `identify-and-place-reagent-bottle` | | **Workbench** | Precision assembly | 3 | 1,061 | 19.2 | `place-washer-onto-stud`, `insert-divider`, `insert-jst-connector` | | | Inspection and sorting | 5 | 477 | 8.6 | `compare-elastomer-hardness`, `sort-resistors`, `sort-screws-nuts-washers-into-bins` | ## Sensor key map

Sensor key map — each image stream keyed to its physical mount

Tactile keys map to fingertip sensors; wrist keys to gripper cameras.

This collection carries the two wrist and four tactile keys only; it has no head streams. ## Provenance These datasets were assembled from the TacVerse capture programme and re-exported for this release. They do not carry `meta/sessions.json`, so the per-day capture sessions behind each task are not recoverable from the files themselves. End-effector poses were recomputed where the capture stack had not yet applied the measured tracker→TCP mount transform (added upstream on 2026-08-01). Only the 9 pose dimensions per arm were touched — jaw aperture, wrist video and tactile video are the captured values throughout. ## License - **License:** cc-by-sa-4.0 - **Homepage:** [TacVerse/TacVerse](https://huggingface.co/datasets/TacVerse/TacVerse) ## Citation **BibTeX:** ```bibtex @misc{tacverse2026, title = {TacVerse: A Large-Scale Bimanual Visuo-Tactile Manipulation Dataset}, author = {Xense Robotics}, year = {2026}, howpublished = {\url{https://huggingface.co/datasets/TacVerse/TacVerse}}, note = {Collected with the XTac-UMI-G1 handheld gripper and Xense Neutron visuotactile sensors} } ```