Datasets:

Voxel51
/

xense-strap-tape-120ep

import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub

dataset = load_from_hub("Voxel51/xense-strap-tape-120ep")

session = fo.launch_app(dataset)

Download a snapshot and load it locally

import fiftyone as fo
from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="Voxel51/xense-strap-tape-120ep",
    repo_type="dataset",
    local_dir="xense-strap-tape-120ep",
)

dataset = fo.Dataset.from_dir(
    dataset_dir="xense-strap-tape-120ep",
    dataset_type=fo.types.LeRobotDataset,
    name="xense_strap_tape",
)

session = fo.launch_app(dataset)

Dataset Details

Dataset Description

120 teleoperated episodes (191,261 frames, 30 fps) on robot type bi_flexiv_rizon4_rt. The task is "Grab the tape and strap the tape." Each episode has three RGB camera streams, four tactile video streams (left and right sensor on each side), and 20-D TCP state and action. The source is a LeRobot v3.0 repo recorded with the Xense LeRobot fork.

Shared by: Xense on Hugging Face
Language(s): en
License: apache-2.0

Dataset Sources

Repository: https://huggingface.co/datasets/Xense/strap-tape-taccap-0929 (code: https://github.com/Vertax42/lerobot-xense)

Dataset Structure

Topology. media_type: multimodal, 120 samples, one per episode, 30 fps, 1,016-2,856 frames (33.9-95.2 s), 191,261 frames total. Samples hold a media_reference to the per-frame parquet data and 7 video streams.

Field	FiftyOne type	Description
`media_reference`	`LeRobotEpisodeReference`	Pointers into `data/` parquet and the 7 video streams
`episode_index`	`IntField`	Episode index (0-119)
`task`	`StringField`	The single task instruction
`tasks`	`ListField(StringField)`	All task strings of the episode
`length`	`IntField`	Frames in the episode
`duration`	`FloatField`	Episode duration in seconds
`robot_type`	`StringField`	`bi_flexiv_rizon4_rt`
`fps`	`FloatField`	30

Data behind media_reference (per-frame, from meta/info.json):

Feature	Shape	Description
`observation.state`	(20,)	Bimanual TCP: `left_tcp.{x,y,z,r1..r6}`, `right_tcp.{x,y,z,r1..r6}`, `left_gripper.pos`, `right_gripper.pos`
`action`	(20,)	Same 20 names and layout as `observation.state`
`observation.images.head`, `left_wrist`, `right_wrist`	480x640x3	RGB cameras (H.264 yuv420p)
`observation.images.left_tactile_left`, `left_tactile_right`, `right_tactile_left`, `right_tactile_right`	400x700x3	Four tactile video streams (H.264 yuv420p)

Label types and why. The importer produces episode-level samples with a media_reference; numeric streams (state, action) are read through the viewer and are not stored as FiftyOne label fields. The source has a single task, so task is constant. No custom fields were added, so the FiftyOne dataset matches what the LeRobot export contains.

dataset.info. lerobot entry with format, format_major, episode_count, imported_episode_count, skipped_episodes (empty).

Parsing decisions.

All episodes imported from the full repo (0.84 GB). No source file was modified, and no transcoding or metadata repair was needed.
All 7 video streams were imported; no modality was excluded. All streams are standard H.264 yuv420p.
The source does not state the tactile sensor model or the physical meaning of the tactile images.

Dataset Creation

Source Data

Data Collection and Processing

The source card states only that it was created using LeRobot. The citation names the Xense LeRobot fork, LeRobot-Xense: LeRobot with Xense Tactile Robotics Support.

Annotations

Annotation process

A single task string is stored in meta/tasks.parquet.

Citation

BibTeX:

@misc{vertax2026lerobotxense,
    author = {vertax42 and Xense Robotics Team},
    title = {LeRobot-Xense: LeRobot with Xense Tactile Robotics Support},
    howpublished = {\url{https://github.com/Vertax42/lerobot-xense}},
    year = {2026}
}

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