Datasets:
This dataset was created using LeRobot.
What this is
The robot-faithful repair of SN0429/so101_pick_cube_test_20260823_40ep.
Angles are exactly what the follower reported, with only the encoder wrap removed.
Use this one for ACT training and lerobot-replay. Its degree zero is LeRobot's own convention -
the pose held during calibration - which is what the real arm expects.
For 3D visualisation or Isaac Sim, use
..._40ep_urdf
instead: LeRobot's zero is about 97 degrees away from the SO-101 URDF's zero on elbow_flex, and the
sign is flipped, so rendering this copy against the URDF puts the arm in the wrong posture.
| Joint | Correction | Result |
|---|---|---|
elbow_flex |
unwrapped per episode, no offset | largest within-episode step 360 deg -> 6 deg |
| the other five | untouched | byte-identical to the original |
The original recording had two joints sitting on the STS3215 encoder's 0/4095 wrap point, because
the pose held during calibration was not the middle of their real travel. elbow_flex crossed it,
so the reading rolled 4095 -> 0 and the recorded angle jumped a full 360 degrees; wrist_roll
stopped 43 counts short of it and could not be commanded past it, leaving a ~16 degree gap between
commanded and measured position.
Unwrapping elbow_flex is common to both copies and is exact: a wrap is an artefact of the angle
representation, so making each episode continuous restores the trajectory (largest within-episode
step drops from 360 to 6 degrees).
wrist_roll is not recoverable in either copy. Where it was commanded past the boundary the arm
never went there, so no measurement of the intended pose exists. Do not train a policy on that
joint - those episodes need re-recording after recalibrating both arms.
Repaired with so101-unwrap-dataset; see SO101_ENCODER_WRAP.md in the LeRobot fork used here.
Dataset Structure
{
"codebase_version": "v3.0",
"fps": 30,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6
]
},
"observation.state": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos"
],
"shape": [
6
]
},
"observation.images.front": {
"dtype": "video",
"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"channels"
],
"info": {
"is_depth_map": false,
"video.height": 480,
"video.width": 640,
"video.codec": "av1",
"video.pix_fmt": "yuv420p",
"video.fps": 30,
"video.channels": 3,
"has_audio": false,
"video.g": 2,
"video.crf": 30,
"video.preset": 12,
"video.fast_decode": 0,
"video.video_backend": "pyav",
"video.extra_options": {}
}
},
"timestamp": {
"dtype": "float32",
"shape": [
1
],
"names": null
},
"frame_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"episode_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"task_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
}
},
"total_episodes": 40,
"total_frames": 35676,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
"robot_type": "so_follower",
"splits": {
"train": "0:40"
}
}
Citation
BibTeX:
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