easyminnn/titw-lerobot

Touch in the Wild (LeRobot v2.0)

3,699 portable visuo-tactile gripper episodes (12 tasks, lab and in-the-wild) with a 12×64 taxel array, converted to LeRobot v2.0.

Part of a set of tactile manipulation datasets converted to a single common LeRobot v2.0 layout so they can be mixed in one training run.

At a glance

Episodes	3,699
Frames	1,418,122 (20 fps)
Tasks	12, namespaced by collection group (four_tasks/…, indoor_data/…, in_the_wild_data/…, pretrain_data/…)
Video	ego_view (observation.images.main) — 224×224
Tactile	array — observation.tactile_array, shape [12, 64]
Action	7-D per-step EE delta + gripper (FreeTacMan layout)
Tactile type	array, needs a taxel encoder

Notes

• Source runs at 59.94 fps; this conversion applies stride 3 to reach 20 fps, matching the touch_in_the_wild task config (dataset_frequeny 59.94, obs_down_sample_steps 3).
• The pretrain_data group is action-free — it carries video and tactile only and is intended for representation pretraining. Filter by task prefix if you need action labels.

Format

GR00T-flavoured LeRobot v2.0: per-episode Parquet under data/chunk-{:03d}/ and per-episode MP4 under videos/chunk-{:03d}/{video_key}/, with meta/info.json, meta/episodes.jsonl, meta/tasks.jsonl and meta/modality.json.

from datasets import load_dataset          # metadata / parquet only
# or read directly:
import pyarrow.parquet as pq, json
info = json.load(open("meta/info.json"))
tbl  = pq.read_table("data/chunk-000/episode_000000.parquet")

meta/modality.json names the tactile stream and the state/action slot layout, so the dataset can be loaded by an Isaac-GR00T style loader without extra configuration.

Provenance & license

This is a format conversion of binghaohuang-robot/touch_in_the_wild-dataset (https://huggingface.co/datasets/binghaohuang-robot/touch_in_the_wild-dataset), released under the MIT license. All sensor data originates from the authors of that dataset; please cite their work. No frames were dropped or re-timed beyond what is listed under Conversion above.