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tags:
- robotics
- lerobot
- video
configs:
- config_name: videos
default: true
drop_labels: true
data_files:
- split: train
path:
- wipe_table/record_*/videos/**/*.mp4
- checkout/record_*/videos/**/*.mp4
- close_curtain/record_*/videos/**/*.mp4
- cloth_basket/record_*/videos/**/*.mp4
- fruit_basket/record_*/videos/**/*.mp4
- make_bed/record_*/videos/**/*.mp4
- pillow/record_*/videos/**/*.mp4
- push_cart/record_*/videos/**/*.mp4
Selfcollected Dataset
English · 中文
Real-robot data collected with SONIC for WB-WAM task post-training. LeRobot v3.0, 20 Hz, RGB 360 × 270. The release contains 1,011 episodes, 242,668 frames, 8 tasks, and 12 independent recordings (3.370 hours).
Each <task>/record_XXXX/ is an independent LeRobot dataset. Recordings of the same task remain separate:
<task>/record_XXXX/
data/chunk-000/file-000.parquet
videos/<camera>/chunk-000/file-000.mp4
meta/info.json
meta/stats.json
meta/tasks.parquet
meta/episodes/chunk-000/file-000.parquet
The Dataset Viewer plays the MP4 files. The corresponding Parquet state/action rows and metadata are available under each recording in Files and versions.
| Field | Meaning |
|---|---|
observation.state |
float32[110]: body state[9], G1 joint angles[29], G1 joint velocities[29], left/right Wuji hands[40], root[3] |
action |
float32[136]: next SONIC token[64], left/right Wuji hands[40], G1 joints[29], root[3] |
state_mask_110, action_mask_136 |
bool[110/136]; True means invalid. Both hands have supervision. |
timestamp, frame_index, episode_index, index, task_index |
Time and row/episode/task indices. |
next.done |
Last frame of an episode. |
The action contains absolute next-frame joint targets (+50 ms), not joint increments. Root[3] denotes roll, pitch, and body-frame z angular velocity, not XYZ position. The original train/validation labels are retained in episode metadata. See each record's meta/info.json for exact slices and camera keys.
Download the unpacked files directly:
hf download WB-WAM/Self-Collected --repo-type dataset --local-dir ./data/real_archive
To load one recording with LeRobot 0.4.4, use its local record directory as root:
from lerobot.datasets.lerobot_dataset import LeRobotDataset
dataset = LeRobotDataset("WB-WAM/Self-Collected", root="./data/real_archive/<task>/record_XXXX")
sample = dataset[0]
Training code and instructions: WB-WAM Official.
