Dataset Viewer
Auto-converted to Parquet Duplicate
Search is not available for this dataset
video
video
1.03
28.4
label
class label
2 classes
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
0observation.images.base
End of preview. Expand in Data Studio

FARM UF850 — Bottle Pick-and-Place with a UFactory UF850

LeRobot-format dataset of teleoperated single-arm manipulation collected on a UFactory UF850 (6-DoF arm with parallel gripper) using a Meta Quest as the teleop controller. 200 episodes across 2 natural-language tasks: moving a bottle between a desk and a box.

Collected with the FARM edge agent (repository) as a CS153 final project. Intended for a full fine-tune of π0.5.

Quick stats

Episodes 200
Total frames 59,183
Duration 32.9 min
Episode length (median) 9.3 s (279 frames); range 31–851
FPS 30
Robot UFactory UF850, 6-DoF + parallel gripper (7-D state/action)
Cameras 2 × Intel RealSense D435 (base + wrist), 640×480, h264
Unique tasks 2
Format LeRobot v2.0

Tasks

count task
101 Picking up the bottle and placing it on the box
99 Picking up the bottle off of the box and putting it on the desk

State / action space

7-dim float32 in both observation.state and action:

idx name unit observed range
0 joint1 rad [-1.017, 1.237]
1 joint2 rad [-1.508, 0.361]
2 joint3 rad [-2.417, -0.060]
3 joint4 rad [-3.083, 2.689]
4 joint5 rad [ 0.051, 2.019]
5 joint6 rad [-2.275, 1.767]
6 gripper 0 (open) → 1 (closed) [0.000, 1.000]

action[t] is the next-step absolute state (observation.state[t+1]); the final frame repeats its own state. Downstream training (openpi) converts the 6 joint dims to deltas and keeps the gripper absolute.

Cameras

  • observation.images.base — fixed base view, 640×480 RGB, h264
  • observation.images.wrist — wrist-mounted view, 640×480 RGB, h264

Layout

meta/{info.json, episodes.jsonl, tasks.jsonl, stats.json}
data/chunk-000/episode_NNNNNN.parquet
videos/chunk-000/observation.images.{base,wrist}/episode_NNNNNN.mp4
Downloads last month
30