timestamp float32 0 195 | frame_index int64 0 5.85k | episode_index int64 0 284 | index int64 0 254k | task_index int64 0 26 | observation.state listlengths 15 15 | action.left_ee listlengths 7 7 | action.right_ee listlengths 7 7 | action.gripper listlengths 2 2 | action.base_vel listlengths 3 3 | action.lift_cmd listlengths 1 1 | episode_uid stringclasses 285
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1.6 | 48 | 0 | 48 | 23 | [
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1.633333 | 49 | 0 | 49 | 23 | [
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1.733333 | 52 | 0 | 52 | 23 | [
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1.766667 | 53 | 0 | 53 | 23 | [
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1.8 | 54 | 0 | 54 | 23 | [
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1.833333 | 55 | 0 | 55 | 23 | [
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1.966667 | 59 | 0 | 59 | 23 | [
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2 | 60 | 0 | 60 | 23 | [
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2.166667 | 65 | 0 | 65 | 23 | [
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2.233333 | 67 | 0 | 67 | 23 | [
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2.266667 | 68 | 0 | 68 | 23 | [
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2.333333 | 70 | 0 | 70 | 23 | [
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2.366667 | 71 | 0 | 71 | 23 | [
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2.4 | 72 | 0 | 72 | 23 | [
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2.433333 | 73 | 0 | 73 | 23 | [
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2.466667 | 74 | 0 | 74 | 23 | [
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2.533333 | 76 | 0 | 76 | 23 | [
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2.833333 | 85 | 0 | 85 | 23 | [
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2.866667 | 86 | 0 | 86 | 23 | [
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2.9 | 87 | 0 | 87 | 23 | [
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2.933333 | 88 | 0 | 88 | 23 | [
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2.966667 | 89 | 0 | 89 | 23 | [
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3 | 90 | 0 | 90 | 23 | [
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3.033333 | 91 | 0 | 91 | 23 | [
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3.066667 | 92 | 0 | 92 | 23 | [
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3.1 | 93 | 0 | 93 | 23 | [
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3.133333 | 94 | 0 | 94 | 23 | [
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3.166667 | 95 | 0 | 95 | 23 | [
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3.2 | 96 | 0 | 96 | 23 | [
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3.233333 | 97 | 0 | 97 | 23 | [
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3.266667 | 98 | 0 | 98 | 23 | [
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ICL Demo Dataset
A small, recent collection of bimanual manipulation demonstrations on the YOR robot, in LeRobot v2.1 format. Recorded 3 and 6 August 2026.
285 episodes · 254,171 frames · 2.35 hours · 27 tasks · 3 camera views
This is a companion to adityx23/icl-dataset
— same robot, same schema, same task vocabulary, but a separate and much smaller
collection. Roughly ten demonstrations per task, several of them tasks that do not
appear in the larger dataset at all.
Outcomes
success |
episodes | frames |
|---|---|---|
success |
269 | 238,681 |
fail |
15 | 15,216 |
invalid |
1 | 274 |
Failures and unusable episodes sit in the same files as the successes, distinguished
only by the success field in meta/episodes.jsonl. A naive load returns all
285. To train on successes only:
import json
with open("meta/episodes.jsonl") as f:
episodes = [json.loads(l) for l in f if l.strip()]
train = [e["episode_index"] for e in episodes if e["success"] == "success"]
# -> 269 episode indices
At 94% success this set is cleaner than the larger dataset, but it is also small — most tasks have only ~11 episodes, so treat it as demonstration data or a fine-tuning / evaluation set rather than a training corpus on its own.
Tasks
| id | task (instruction) | episodes | minutes | success | fail | invalid |
|---|---|---|---|---|---|---|
| 3 | open the gatorade bottle | 23 | 10.8 | 15 | 8 | 0 |
| 2 | open the doctor pepper bottle | 15 | 9.2 | 12 | 3 | 0 |
| 16 | put the green pepper into the grocery bag | 12 | 3.3 | 11 | 1 | 0 |
| 5 | open the notebook and place the cube on it | 12 | 4.8 | 11 | 0 | 1 |
| 7 | pass the mustard to the plate | 12 | 4.0 | 11 | 1 | 0 |
| 17 | put the mustard into the box | 12 | 1.6 | 12 | 0 | 0 |
| 23 | stack the three cubes into a tower | 11 | 6.5 | 11 | 0 | 0 |
| 24 | stack the three cups into a tower | 11 | 12.5 | 11 | 0 | 0 |
| 13 | put the eggplant into the bag | 11 | 3.3 | 11 | 0 | 0 |
| 12 | put the circle on the peg | 11 | 1.8 | 11 | 0 | 0 |
| 21 | stack the colored octagons | 11 | 8.4 | 11 | 0 | 0 |
| 0 | hit the eggplant with the mallet | 11 | 3.0 | 11 | 0 | 0 |
| 1 | hit the yellow cube with the mallet using the left arm | 11 | 4.2 | 11 | 0 | 0 |
| 20 | sort the items into their containers | 11 | 19.6 | 11 | 0 | 0 |
| 4 | open the notebook | 11 | 2.9 | 11 | 0 | 0 |
| 6 | pass the gusset to the plate | 11 | 3.0 | 11 | 0 | 0 |
| 19 | sort the food items into the cups | 11 | 11.0 | 10 | 1 | 0 |
| 18 | put the square on the peg | 11 | 3.8 | 11 | 0 | 0 |
| 22 | stack the cubes and hit them with the mallet | 11 | 10.7 | 11 | 0 | 0 |
| 25 | uncap the black marker | 11 | 4.1 | 10 | 1 | 0 |
| 26 | uncap the red marker | 11 | 5.5 | 11 | 0 | 0 |
| 8 | pass the salt shaker from the left arm to the right arm | 6 | 2.1 | 6 | 0 | 0 |
| 9 | pass the salt shaker from the right arm to the left arm | 6 | 1.9 | 6 | 0 | 0 |
| 15 | put the eggplant into the box with the right arm | 6 | 1.0 | 6 | 0 | 0 |
| 11 | pick up the red chilli and place it on the plate with the right arm | 6 | 0.7 | 6 | 0 | 0 |
| 14 | put the eggplant into the box with the left arm | 5 | 0.9 | 5 | 0 | 0 |
| 10 | pick up the red chilli and place it on the plate with the left arm | 5 | 0.6 | 5 | 0 | 0 |
Task labels are natural-language instructions, one instruction per task and one
task_index per instruction, using the same vocabulary as adityx23/icl-dataset so
shared tasks mean the same thing in both.
Three of the source runs alternated arm or hand-off direction episode-by-episode. Those were verified from gripper timing and split into per-episode tasks rather than being labelled with a single instruction for the run — so, for example, the salt shaker run contributes six left-to-right episodes and six right-to-left.
Structure
meta/
info.json LeRobot v2.1 header
episodes.jsonl one row per episode: index, task, length, outcome, provenance
episodes_stats.jsonl per-episode feature statistics
tasks.jsonl 27 task instructions, indexed
data/chunk-XXX/episode_NNNNNN.parquet
videos/chunk-XXX/observation.images.<cam>/episode_NNNNNN.mp4 h264, 640x480, 30 fps
Cameras are zed (scene), fish0 (left gripper), fish1 (right gripper).
Per-frame features
| feature | shape | description |
|---|---|---|
observation.state |
[15] |
measured proprioception: lj0..lj6, rj0..rj6, lift |
action.left_ee |
[7] |
commanded left end-effector pose, [qw,qx,qy,qz,x,y,z] |
action.right_ee |
[7] |
commanded right end-effector pose |
action.gripper |
[2] |
commanded [left, right], 0.0 = closed, 1.0 = open |
action.base_vel |
[3] |
commanded base velocity [vx, vy, omega] |
action.lift_cmd |
[1] |
commanded lift, -1 / 0 / 1 |
3 × observation.images.* |
480x640x3 |
h264 video |
Plus timestamp, frame_index, episode_index, index, task_index.
observation.state is measured; everything under action.* is the operator's
commanded target, so gripper state lives in the action space.
Stable episode identity
episode_index is required by LeRobot to run contiguously from 0, so it necessarily
changes whenever episodes are added, dropped or reordered — it has shifted meaning in
this dataset's history, silently invalidating cached copies.
Every episode therefore also carries episode_uid, which does not change across
rebuilds:
"episode_uid": "clean_the_plate_20260730_182850:000069"
└─ collection run ──────────────┘ └ index within that run
It appears in two places: as a field on every record in meta/episodes.jsonl, and as
an episode_uid string column in every parquet (constant within a file), so it travels
with the frames themselves and is visible in the dataset viewer. That column is an
addition to the standard LeRobot v2.1 schema; it is declared in meta/info.json under
features, and loaders that select columns explicitly are unaffected.
Use episode_uid as the join key for anything you want to survive a dataset update —
annotations, evaluation results, hand-picked subsets. Use episode_index only to
locate the parquet and video files in this revision.
The uid is derived from source_dataset and source_episode, so it can be regenerated
at any time rather than being an opaque stored value. It changes only if a source
collection run is itself renamed or restructured.
Trimmed subsets (subset)
Every episode carries a subset string field in meta/episodes.jsonl and a matching
column in every parquet. In this dataset it is empty on all 285 episodes — nothing here
is trimmed. It exists so this dataset's schema stays byte-identical to
adityx23/icl-dataset, where the
same column marks a 100-episode selection of an over-sampled task.
Provenance
Merged from 24 collection runs. Every episode records where it came from:
{"episode_index": 0, "tasks": ["stack the three cubes into a tower"], "length": 1062,
"success": "success",
"source_dataset": "3_cube_tower_stack_20260803_114230", "source_episode": 0}
Episodes that were themselves folded in from a second run of the same task carry an
additional source_run / source_episode pair from that merge.
Known limitations
- Small. ~11 episodes per task; two tasks have more only because duplicate runs of the same task were merged.
- Labels are the operator's, recorded at collection time and not independently
audited. An automated screen for the failure mode that plagued the larger dataset
(episodes marked success where the robot never moved) flagged one episode here,
put the mustard into the box— the object is already in the box at frame 1. - One episode carries
merged_from_unknown, meaning no outcome was recorded at collection and it was folded intoinvalid. - No train/validation split is defined.
- Camera extrinsics/intrinsics are not published; the two gripper fisheyes are identical models distinguished only by which USB port they occupy.
License
Not specified. No licence has been chosen for this data, so downstream use is legally ambiguous. Check with the authors before using it.
Revision history
2026-08-07 — episode_uid and subset added. Two string columns were added to
meta/episodes.jsonl and to every parquet, and declared in meta/info.json under
features (14 features -> 16), matching the schema of
adityx23/icl-dataset.
episode_uid gives each episode an identity that survives rebuilds; subset is empty
throughout this dataset. Both are additions to the standard LeRobot v2.1 schema. No
episode index, task index or video changed.
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