timestamp float64 0 36.2 | frame_index int64 0 1.8k | episode_index int64 0 155 | observation.state listlengths 48 48 | action listlengths 16 16 | task large_stringclasses 1
value | next.done bool 2
classes | success bool 1
class |
|---|---|---|---|---|---|---|---|
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End of preview. Expand in Data Studio
OpenArm — place cube in flask (202 episodes)
Teleoperated demonstrations on a single-arm (right follower) OpenArm. Task: pick a grey cylinder from an L-bracket and place it at a flask.
| session | episodes | ticks |
|---|---|---|
session3 |
100 | 68,808 |
session4 |
49 | 32,216 |
session5 |
53 | 28,107 |
| total | 202 | 129,131 |
Layout
session3/
data/episode_000078.parquet state + actions, 50 Hz
frames/episode_000078.tar -> episode_000078/{cam_high,cam_right_wrist,cam_side}/%06d.png
meta/episodes.jsonl
Frames are shipped as one uncompressed tar per episode rather than loose PNGs. The raw set is 386,861 files, and per-file overhead made uploading it impractical; the tars carry byte-identical PNGs.
tar -xf session3/frames/episode_000078.tar -C frames/
Format notes
- Images are 480×640 RGB PNG, three cameras:
cam_high(chest),cam_right_wrist,cam_side. actionis 16-wide, but dimensions 0–7 are all zero — the left arm was not driven. The live joints areaction[8:16], so the gripper is index 15.observation.stateis 48-wide: 16 joints × (position, velocity, effort).- State is logged at 50 Hz, cameras at 30 fps. Frame index for a state row is
round(rel_time * 30), clamped to that camera's frame count. - Per-camera frame counts differ slightly within an episode. Where a camera ran short, the last frame is duplicated to fill; where it ran long, the extras are dropped. 532 duplicated frames across the pool.
- Only episodes marked successful during collection are included.
Code that reads this data: https://github.com/OALcementys/OpenArmDev
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