Egocentric hand-manipulation dataset in LeRobot v3.0 format, produced by the RoboX export pipeline from real on-device hand-tracking recordings. It is structured for native loading, visualization, and training with LeRobot-compatible tooling (LeRobot).

What this is

This release packages 28 egocentric human demonstrations, spanning 15 tasks across four activity groups (object transfer, organization, assembly, and kitchen activities), as a standard LeRobotDataset v3.0. It opens in the LeRobot visualizer, carries natural language task descriptions, and exposes documented state and action channels with per-frame provenance and imputation masks.

Compared with the earlier format-demo release, the action channel is now a proper per-frame delta action (14 dimensions), the wrist rotation delta is a true relative rotation vector, quaternion orientation is unit-norm and hemisphere-continuous, and the export ships recommended normalization, feature semantics, and a passing structural and numerical validation report. It is ready for experimentation and policy training within the LeRobot ecosystem.

Read before training: this is human hand motion

The observation.state and action channels are derived from tracked human hand motion, not from commands issued to a physical robot. They describe where a human hand was and how it moved between frames.

No robot retargeting is applied. target_embodiment is null and no robot telemetry is present. Using this to train a policy for deployment on a specific arm (for example SO-ARM101) requires a retargeting and validation step that this dataset does not provide.
Scale is small. 28 episodes and 7,730 frames. This suits prototyping, imitation-learning experiments, and cross-embodiment research, not a production policy on its own.
FPS is declared, not independently verified. The stated rate is 30 fps.
State comes from MediaPipe hand tracking with roughly 3.7 percent of frames imputed. Per-frame imputation flags are in meta/robox_frame_masks.parquet.

Visualize this dataset

Online (LeRobot visualizer):

Open episode 0 in the LeRobot visualizer

Browse other episodes by changing the trailing episode_0 to any index from 0 to 27.

Locally (with LeRobot installed):

python -m lerobot.scripts.visualize_dataset \
  --repo-id RoboXTechnologies/lerobot-dataset \
  --episode-index 0

A tabular preview of the per-frame parquet data also appears through the Hugging Face Dataset Viewer on the dataset page.

Dataset summary

Episodes: 28
Frames: 7730
Tasks: 15
Declared FPS: 30
Robot type label: robox_ego_hand (a human hand source, not a physical robot)
Codebase version: v3.0
State dim: 15
Action dim: 14 (per-frame delta of state)

State and action

observation.state has 15 dimensions describing absolute hand pose. action has 14 dimensions describing the per-channel delta to the next frame, where the wrist rotation delta is a 3-D relative rotation vector rotvec(q[t+1] . inverse(q[t])) rather than a quaternion subtraction. See meta/robox_feature_semantics.json and meta/robox_training_hints.json for units and recommended normalization.

observation.state (dim 15)

Index	Name	Unit	Meaning
0	`wrist_x`	meters	Wrist position in the egocentric camera frame
1	`wrist_y`	meters	Wrist position in the egocentric camera frame
2	`wrist_z`	meters	Wrist position in the egocentric camera frame
3	`wrist_qx`	unit quaternion	Wrist orientation, unit-norm, hemisphere-continuous
4	`wrist_qy`	unit quaternion	Wrist orientation, unit-norm, hemisphere-continuous
5	`wrist_qz`	unit quaternion	Wrist orientation, unit-norm, hemisphere-continuous
6	`wrist_qw`	unit quaternion	Wrist orientation, unit-norm, hemisphere-continuous
7	`finger_curl_thumb`	normalized 0..1	Finger curl (0 extended, 1 fully curled)
8	`finger_curl_index`	normalized 0..1	Finger curl (0 extended, 1 fully curled)
9	`finger_curl_middle`	normalized 0..1	Finger curl (0 extended, 1 fully curled)
10	`finger_curl_ring`	normalized 0..1	Finger curl (0 extended, 1 fully curled)
11	`finger_curl_pinky`	normalized 0..1	Finger curl (0 extended, 1 fully curled)
12	`pinch_thumb_index`	meters	Fingertip pinch distance
13	`pinch_thumb_middle`	meters	Fingertip pinch distance
14	`pinch_thumb_ring`	meters	Fingertip pinch distance

action (dim 14): d_wrist_x, d_wrist_y, d_wrist_z, d_wrist_rotvec_x, d_wrist_rotvec_y, d_wrist_rotvec_z, d_finger_curl_thumb, d_finger_curl_index, d_finger_curl_middle, d_finger_curl_ring, d_finger_curl_pinky, d_pinch_thumb_index, d_pinch_thumb_middle, d_pinch_thumb_ring.

Recommended normalization (from meta/robox_training_hints.json): MEAN_STD for both observation.state and action, excluding the quaternion indices [3, 4, 5, 6] from state mean/std and treating them with IDENTITY quaternion mode.

Features

Key	dtype	shape
`observation.images.front`	video	[480, 640, 3]
`observation.state`	float32	[15]
`action`	float32	[14]
`timestamp`	float32	[1]
`frame_index`	int64	[1]
`episode_index`	int64	[1]
`index`	int64	[1]
`task_index`	int64	[1]

Validation

meta/robox_validation.json reports the structural and numerical checks for this release:

Quaternion channels unit-norm (non-unit ratio 0.0).
Frozen (repeated) action frames 3.6 percent, within the 10 percent limit.
Imputed frames 3.67 percent, within the 40 percent limit.
Rotation spikes 0 (max rotation-vector magnitude 0.994 rad, below the 1.0 rad threshold).

Structure

meta/info.json                    # schema, fps, feature spec (canonical)
meta/tasks.parquet                # task_index to natural language task
meta/episodes/*.parquet           # per episode index, length, video timestamps
meta/stats.json                   # per feature statistics
meta/robox_export.json            # licence, provenance, action semantics (RoboX sidecar)
meta/robox_feature_semantics.json # per channel names, units, missing-data policy
meta/robox_training_hints.json    # recommended normalization and action semantics
meta/robox_frame_masks.parquet    # per frame imputation flags
meta/robox_provenance.parquet     # per episode source provenance
meta/robox_validation.json        # structural and numerical validation report
data/chunk-000/*.parquet          # per frame state, action, timestamp
videos/observation.images.front/chunk-000/*.mp4  # RGB, one shard per chunk

Episodes are packed into shared chunk shards (one .mp4 and one .parquet per chunk). Per-episode boundaries are addressed by the row ranges and video timestamps in meta/episodes.

Licence and provenance

Licence: robox-commercial-nonexclusive-v1
Commercial use: allowed
Exclusivity: non-exclusive
Export id: robox-p1-20260702
Source recordings: 4 (IDs listed in meta/robox_export.json)

Full licensing, buyer, and source-recording provenance are in meta/robox_export.json. This dataset is distributed under its stated commercial terms, not an open-source licence, despite the Hub license: other tag.

Created with

This dataset was created using LeRobot and the RoboX LeRobot v3 export worker.

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Total file size:

53.6 MB