Search is not available for this dataset
action list | observation.state list | timestamp float32 0 30.7 ⌀ | frame_index int64 0 921 ⌀ | episode_index int64 0 49 ⌀ | index int64 0 38.3k ⌀ | task_index int64 0 0 ⌀ |
|---|---|---|---|---|---|---|
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End of preview. Expand in Data Studio
xlerobot-coffee-real-2cam
All real-world data for the X-Lerobot Coffee Automata project in one repo: the four manipulation tasks plus the navigation task of the coffee-service chain. Its counterpart repo holds the other domain — the two share this layout, these task slugs, and the feature schema.
- Domain: 🌍 real-world
- Environments: 📍 Room 128 (
env-room-128) - Format: LeRobot
v3.0— each task folder is a complete dataset root (meta/ data/ videos/) - Project hub (requirements, conventions, models):
IntelligentDecisionLab/xlerobot-coffee-automata
Tasks in this repo
| Folder | Task | Kind | Description | Environment | Episodes | Frames | FPS | Robot |
|---|---|---|---|---|---|---|---|---|
room-128/t1_place_cup |
t1 | manipulation | Place the cup on the machine platform | Room 128 (room-128) |
20 | 7,583 | 30 | xlerobot |
room-128/t1_place_cup_redcup_success0 |
t1 | manipulation | Place the cup on the machine platform — redcup_success0 variant |
Room 128 (room-128) |
1 | 911 | 30 | xlerobot |
room-128/t1_place_cup_redcup_success1 |
t1 | manipulation | Place the cup on the machine platform — redcup_success1 variant |
Room 128 (room-128) |
50 | 35,289 | 30 | xlerobot |
room-128/t3_cup_to_tray_redcup_success0 |
t3 | manipulation | Move the filled cup from the machine to the tray — redcup_success0 variant |
Room 128 (room-128) |
50 | 38,271 | 30 | xlerobot |
room-128/t5_tray_to_table_redcup_success0 |
t5 | manipulation | Move the filled cup from the tray to the user's table — redcup_success0 variant |
Room 128 (room-128) |
28 | 20,717 | 30 | xlerobot |
room-128/t5_tray_to_table_redcup_success1 |
t5 | manipulation | Move the filled cup from the tray to the user's table — redcup_success1 variant |
Room 128 (room-128) |
13 | 8,810 | 30 | xlerobot |
room-128/t5_tray_to_table_redcup_success2 |
t5 | manipulation | Move the filled cup from the tray to the user's table — redcup_success2 variant |
Room 128 (room-128) |
11 | 8,231 | 30 | xlerobot |
Not yet uploaded: t2_push_button (t2), t4_navigate (t4).
Environment matters. Recordings come from more than one physical space, and the background,
lighting and machine placement differ between them — so a policy trained on one is not automatically
valid in another. Each task folder records where it was captured (environments.json at the repo root
is the machine-readable source); always state the environment when you report a result, and treat a
cross-environment evaluation as a generalization test, not a like-for-like one.
Load one task
Download only the folder you need, then point LeRobotDataset at it:
from huggingface_hub import snapshot_download
from lerobot.datasets.lerobot_dataset import LeRobotDataset
repo = "IntelligentDecisionLab/xlerobot-coffee-real-2cam"
root = snapshot_download(repo, repo_type="dataset", allow_patterns="t1_place_cup/*")
ds = LeRobotDataset(repo, root=f"{root}/t1_place_cup")
allow_patterns matters — without it you pull every task in the repo.
Per-frame features
| Feature | dtype | shape | Meaning |
|---|---|---|---|
action |
float32 | [17] |
Commanded targets — 17-D on XLeRobot (left/right arm ×6, head ×2, base x/y/theta vel); 6-D on SO-101 (shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper). |
observation.state |
float32 | [71] |
RAW telemetry — on XLeRobot, 17 motors × {pos, current_raw, load_raw, vel_hw} + base x/y/theta vel = 71-D, or 84-D when the GY-91 IMU is enabled (13 extra channels; imu.mag_* carries no signal, an MPU6500 has no magnetometer). 117-D on SO-101/sim, which additionally bakes in the EKF breakdown (estimated/tau_ext, model/tau_*, tcp/wrench/, hpi/gripper/). |
observation.images.head |
video | [480, 640, 3] |
Head / overview camera (RGB). |
observation.images.right_wrist |
video | [480, 640, 3] |
RIGHT-arm wrist camera (RGB, Innomaker U20CAM, MJPG 640×480@30). Added 2026-08-07: a close view for aiming the button press in t2, and a second viewpoint on the cup during the left-arm tasks. |
observation.images.head_depth |
image | [480, 640, 1] |
Overview depth (int16, 1-channel). Not used by ACT; dropped when building training variants. |
Notes
observation.hpiis the physics-informed external-torque signal (EKF from motor load, no F/T sensor). Force-aware (A1) models consume it; vanilla models ignore it.- Depth (
*_depth, int16, 1-ch) is not ingested by ACT — drop it when building training variants (coffee_build_variants.py --drop_features observation.images.<key>_depth). - Task strings: frames should embed the recording condition (e.g.
"Place the cup on the coffee machine platform size:M start:left") so cells stay separable after merges. Older recordings use a baretask1label.
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