Datasets:

THULab
/

246-Golf

A LeRobot teleoperation dataset recorded on an SO-101 arm performing a single manipulation task: "Pick up the golf ball and place it on the gray mark at the back." Each episode captures the synchronized robot proprioception (joint states) and the commanded action at 30 Hz while the operator demonstrates the pick-and-place motion. The dataset was contributed as part of the LeRobot Worldwide Hackathon.

Robot: SO-101 (6-DOF: shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper).
Scale: 30 episodes / 26,134 frames / 1 task.
Sampling rate: 30 fps.
LeRobot codebase version: v2.1.

Schema (TsFile structure)

Time (INT64, milliseconds) — per-frame timestamp, round(timestamp * 1000), restarts at 0 for each episode (≈33 ms between frames at 30 fps).
episode_index (TAG) — episode identifier (the device dimension). Query a single episode with WHERE episode_index=0.
task_index (TAG) — task identifier; this dataset has a single task (0).
frame_index (FIELD, INT64) — frame counter within the episode.
sample_index (FIELD, INT64) — the source index global row counter, renamed.
observation_state_0 … observation_state_5 (FIELD, FLOAT) — measured joint positions of the 6 arm joints (shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper).
action_0 … action_5 (FIELD, FLOAT) — commanded target for the same 6 joints.

The 6-element observation.state and action vectors are flattened to one FLOAT field per joint, in the source joint order. The source timestamp column is dropped because it equals Time / 1000 seconds.

Camera video streams (observation.images.phone, observation.images.usbcam) are not included in this repository; see the original dataset's videos/ directory for them: LeRobot-worldwide-hackathon/246-Golf.

Usage

Read the .tsfile files with the Apache TsFile Java or Python SDK.

Source & license

Original dataset: https://huggingface.co/datasets/LeRobot-worldwide-hackathon/246-Golf
Author / publisher: LeRobot-worldwide-hackathon
Paper: none
License: not declared by the original dataset; please defer to the original.

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