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10 episodes Β· 30 fps Β· 2 cameras Β· 640Γ—480 h264

up-down_20261024_112623

Carry a part WITH pin (GOOD) from the inspection camera to the green box.

Part of a quality-control pipeline built at the Robotekin LeRobot Hackathon 2026: an SO-101 arm picks a metal part, a vision model checks whether it has a pin, and a sorting policy drops it in the green box (with pin) or the white box (without pin). This dataset belongs to Stage 3 β€” Sorting, GOOD branch.

Naming note: good / bad describe the part, not the quality of the demonstration. GOOD = part with a pin β†’ green box. BAD = part without a pin (defective) β†’ white box. up-down-bad_* datasets are successful demonstrations of carrying a defective part to the white box. No failed or negative demonstrations were intentionally recorded. Other informal names: so101-pick-cube_* contains the metal bracket, not a cube, and up-down_* is the GOOD-box sorting task (except the 23 October sessions, see below).

What this dataset contains

Starts with the part held in front of the inspection camera (the end of a pick episode). The arm carries it to the green box and releases it. The task string says "good box": GOOD means the part has a pin.

Stored task "Carry the bracket from the camera to the good box and release it"
Episodes 10 (1,757 frames, 58.6 s in total)
Recorded 2026-10-24 11:26
Frame rate 30 fps
Cameras observation.images.front, observation.images.wrist (640x480 RGB)
State / action observation.state / action, 6 values each
Object locations 1 (numbering of meta/recording_notes.json)

How it was used

  • GOOD-branch source for MikelRubi/act-up-down-good. Versions v2–v5 were trained on up-down-green-all, a local combination of the GOOD-box sessions (213 episodes); its exact list of source sessions was not recorded.

Pipeline

tray  ──► act-pick ──► part held up to the camera ──► pin-classifier ──┬─ pin    (GOOD) ──► act-up-down-good ──► green box
                                                                      └─ no pin (BAD)  ──► act-up-down-bad  ──► white box

Related models: MikelRubi/act-pick β†’ MikelRubi/pin-classifier β†’ MikelRubi/act-up-down-good | MikelRubi/act-up-down-bad. Project page: MikelRubi/robotekin-so101-pin-sorting. On the robot the stages are chained by the team's demo app (30_full_demo_app.py); during recording the operator chose the box after looking at the part. The box for each result is set by the operator's order; the usual order is shown above.

This session is also part of the combined dataset MikelRubi/robotekin-so101-green-box, which joins all the sessions of this task.

Recording setup

  • Robot: SO-101 follower arm (LeRobot so_follower, 6 joints including the gripper), teleoperated with an SO-101 leader arm (leader/follower). The policies never see the leader; action is the leader position sent to the follower.
  • Cameras: two USB RGB cameras, front (fixed overhead camera looking down at the tray) and wrist (mounted on the gripper).
  • Joints (state and action, same order): shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper. Arm joints in degrees, gripper 0–100 (LeRobot SO-101 calibration).
  • Format: LeRobot dataset v3.0, H.264 video. Recorded on 23–24 October 2026 at the Robotekin LeRobot Hackathon (Robotory, Vitoria-Gasteiz).

Known limitations

  • A single short recording session in one room and lighting setup. No success labels are stored: every saved episode is treated as a successful demonstration.
  • Camera models and their exact mounting positions are not documented in the dataset.

Acknowledgements

Recorded by Iker Azurmendi, Mikel Zulueta, Ander Autillo and Diego Suarez during the Robotekin LeRobot Hackathon 2026 (23–25 October 2026, Vitoria-Gasteiz). Thanks to Bravo Robots and to Robotekin for the hackathon, to Hugging Face for LeRobot, and to everyone who took part in it.

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