#### NOTE
This is a **Hugging Face dataset**. For large datasets, ensure `huggingface_hub>=1.1.3` to avoid rate limits. Learn more in the Hugging Face integration docs.
# LeRobot Community Dataset v3 — Cross-Embodiment Starter
A curated cross-embodiment starter subset drawn from [lerobot/community_dataset_v3](https://huggingface.co/datasets/lerobot/community_dataset_v3): **497 episodes across 50 unique robot embodiments**, with up to 10 episodes from each embodiment.
## Usage
### Load in FiftyOne
```python
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
dataset = fouh.load_from_hub("Voxel51/community_v3_10per_embodiment")
print(dataset)
# Filter by embodiment
so100_view = dataset.match(fo.ViewField("robot_type") == "so100")
```
### Browse by robot type
```python
session = fo.launch_app(dataset)
# In App: filter sidebar by robot_type field to explore embodiments
```
## Overview
| Metric | Value |
|-----------------------|--------------------------------------------------------|
| **Total Episodes** | 497 |
| **Robot Embodiments** | 50 |
| **FPS values** | 10, 15, 20, 25, 30, 50 |
| **Duration range** | 0.02 – 148.6 seconds |
| **Source dataset** | lerobot/community_dataset_v3 (v3.0) |
| **Format** | FiftyOne dataset (multimodal, LeRobotEpisodeReference) |
## Robot Types Covered (50 embodiments)
| Robot Type | Episodes | Source Dataset |
|-------------------------|------------|------------------------------------------------------------------|
| Unitree_G1_Dex3 | 10 | kuehnrobin/g1_stack_cube_left |
| Unitree_G1_Gripper | 10 | unitreerobotics/G1_MountCameraRedGripper_Dataset |
| Unitree_G1_Inspire | 10 | eastflag/g1_can_twohand |
| Unitree_G1_inspire | 7 | ccccccww/test1 (only 7 available total) |
| Unitree_Z1_Dual | 10 | unitreerobotics/Z1_DualArmStackBox_Dataset |
| Unitree_Z1_Single | 10 | unitreerobotics/Z1_StackBox_Dataset |
| agilex | 10 | Pi-robot/place_white_bottle |
| aiworker | 10 | noisyduck/ffw_bg2_rev4_ai_worker_demo_250714_2 |
| aloha | 10 | HuaihaiLyu/test_shorts |
| aloha_solo | 10 | AshtinDonuts/aloha_test6 |
| arx5 | 10 | villekuosmanen/pick_coffee_capsule_under_dome |
| arx5_bimanual | 10 | villekuosmanen/move_glass_cups |
| bi_so100_follower | 10 | LeRobot-worldwide-hackathon/46-3580-bi_so100_pour_water_real |
| bi_xarm6_follower | 10 | kumarhans/ethernetGrab8 |
| ffw | 10 | lcwoo/ffw_test |
| g1 | 10 | hainh22/pick_cube_train |
| koch | 10 | Dongkkka/blue_pen_pick_and_place |
| koch_follower | 10 | aidinism/arm-record-14 |
| mcx | 10 | relaxedandcalm/ds_move_the_motor |
| moss | 10 | Beegbrain/moss_stack_cubes |
| multi_robot | 10 | arclabmit/lx7r_knockover_test_dataset |
| mycobot320 | 10 | GreenIsGood/pick_scan_and_place_warehouse_boxes_05_06_01_smthng |
| panda_follower | 10 | konstantinZ/pickup-single-cotton-V2 |
| piper | 10 | hangwu/piper_joint_ep_20250421_realsense |
| piper_follower | 10 | CnLori/so101_piper |
| rx200 | 10 | underctrl/toy_pickup_and_place |
| sam_bimanual | 10 | girardijp/sam_fold_cloth_single |
| sam_two | 10 | 1g0rrr/demo2_upart_peeloff |
| so100 | 10 | Gano007/so100_lolo |
| so100-blue | 10 | Chojins/chess_game_001_blue_stereo_flip |
| so100-red | 10 | Chojins/chess_game_001_red_stereo |
| so100MovellaDot | 10 | sergiov2000/so100_movella_pick_ball_C3 (5) + D3 (5) |
| so100_bimanual | 10 | Claessens14/playing_with_fold_april21_ego_single_fold_v1 |
| so100_follower | 10 | triton7777/cube_to_bowl_so100 |
| so100_follower_bimanual | 10 | LeRobot-worldwide-hackathon/160-LegoBot-lego_pixelart_stage_2_v2 |
| so100_with_koch | 10 | rgarreta/so100_dataset1 |
| so101 | 10 | hawnsoung/so101_test_coff_5 |
| so101_follower | 10 | MostafaOthman/pickplace_sweetsjp_smallcandy |
| stretch | 10 | Suzumiya894/stretch_test |
| stretch3 | 10 | Suzumiya894/stretch_smolvla_dataset |
| trossen_ai_mobile | 10 | mrrl-emcnei/trossen_dataset0 |
| trossen_ai_solo | 10 | minjunkevink/trossen_objects_pick_place |
| trossen_ai_stationary | 10 | ANRedlich/trossen_ai_stationary_test_08 |
| unknown | 10 | easonjcc/rm_test_02 |
| ur5e_gello | 10 | Arururu12/UR5e_Gello_Cube_bin_v2 |
| widowx | 10 | jesbu1/usc_widowx_combined_play_data |
| xarm | 10 | Anas0711/orange_bobo_pose_action_state_june3_1130am |
| xarm6 | 10 | kumarhans/glue_stick |
| xarm_end_effector | 10 | lukicdarkoo/pick_plazma |
| xarm_lite6 | 10 | ReubenLim/xarm_lite6_gripper_cube_in_box |
## Dataset Structure
Each sample in this FiftyOne dataset is one episode, with:
| Field | Type | Description |
|----------------------------|-------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `robot_type` | string | Embodiment identifier (50 unique values) |
| `task` | string | Task description |
| `tasks` | list[string] | All task descriptions for episode |
| `episode_index` | int | Episode index within the source dataset |
| `length` | int | Number of frames |
| `duration` | float | Duration in seconds |
| `fps` | float | Recording frame rate |
| `media_reference` | LeRobotEpisodeReference | Reference to video clips |
| `dataset_name` | string | Source contributor dataset (`/`) |
| `qwen3vl_embedding` | vector (2048) | Qwen3-VL-Embedding-2B video embedding (via [qwen3vl_embeddings](https://github.com/harpreetsahota204/qwen3vl_embeddings)): up to 32 evenly spaced frames from the episode’s time window, last-token pooled and L2-normalised, in the same space as text embeddings from the same model |
| `qwen3vl_embedding_camera` | string | Camera stream used for `qwen3vl_embedding` |
| `uniqueness` | float | FiftyOne Brain uniqueness, computed from `qwen3vl_embedding` |
| `representativeness` | float | FiftyOne Brain representativeness, computed from `qwen3vl_embedding` |
`qwen3vl_embedding` is a video embedding: each vector is computed from a clip spanning the episode, never from a single frame. The brain runs `qwen3vl_embedding_sim` (similarity index) and `qwen3vl_embedding_umap` (2D UMAP) are both built on it, and the similarity index accepts text queries as well as episodes. For text queries, register the model source first:
```python
import fiftyone.zoo as foz
foz.register_zoo_model_source(
"https://github.com/harpreetsahota204/qwen3vl_embeddings",
overwrite=True,
)
view = dataset.sort_by_similarity(
"folding a cloth", k=10, brain_key="qwen3vl_embedding_sim"
)
```
## Parsing Decisions
- **Episode selection**: shard-0 episodes (first N from `data/chunk-000/file-000.parquet` and corresponding video `chunk-000/file-000.mp4`) for each source dataset. This gives the cheapest complete subset without splitting episodes across shards.
- **Cap**: 10 episodes per embodiment, or all available if fewer than 10 exist.
- **`Unitree_G1_inspire`**: Kept separate from `Unitree_G1_Inspire`; only 7 episodes existed in total across all contributing datasets — all 7 are included.
- **`so100MovellaDot`**: No single source dataset had ≥10 episodes (max 5 per dataset). Combined 5 episodes from `sergiov2000/so100_movella_pick_ball_C3` and 5 from `so100_movella_pick_ball_D3` to reach 10.
- **Schema heterogeneity**: The 50 embodiments use different camera setups, action dimensions, and FPS values. This FiftyOne dataset stores each sample document-style with only common fields (`robot_type`, `task`, `duration`, `fps`, `length`, `episode_index`). Camera-specific features are accessible via `media_reference` pointing to the source video clips.
- **No v2.x conversion**: All 51 source sub-datasets were already at codebase_version v3.0 — no conversion needed.
- **No media re-encoding**: Source video files are referenced as-is. Codecs may vary by embodiment (H.264, H.265, etc.).
- **`episode_index` values**: Preserved from source datasets. Two `so100MovellaDot` sources both have indices 0–4; this is intentional — the `media_reference` key distinguishes them.
## Source
All data originates from [lerobot/community_dataset_v3](https://huggingface.co/datasets/lerobot/community_dataset_v3), a crowdsourced collection from 235 community contributors worldwide. Please acknowledge the original contributors when using this dataset.
## License
Apache 2.0 (same as source dataset). Individual datasets may have additional attribution requirements — see [lerobot/community_dataset_v3](https://huggingface.co/datasets/lerobot/community_dataset_v3) for contributor details.