THULab/self_repair_gripper

self-repair-gripper (TsFile)

Apache TsFile version of YOLO2431/self-repair-gripper.

Overview

This dataset is a LeRobot v2.1 bimanual dataset of a self-repair gripper task, recorded with a YAM bimanual arm.

• Robot: Yam bimanual (yam_bimanual)
• Scale: 130 episodes, 267,566 frames, 30 fps
• Split: train
• Cameras (not uploaded): head, left_wrist, right_wrist, plus three depth streams (observation.depth_ffv1.*)

Schema (TsFile structure)

The TsFile table is named self_repair_gripper.

Role	Columns
Time	Time, INT64 milliseconds
TAG	episode_index, task_index
FIELD	frame_index, sample_index
FIELD	observation_state_0 … observation_state_31
FIELD	action_0 … action_31

Vector columns are flattened into scalar FLOAT measurements (single precision). The source index column is retained as sample_index.

Conversion notes

• Time = round(timestamp * 1000) with millisecond precision; time restarts inside each episode, while episode_index and task_index identify the TsFile device.
• The original timestamp field is omitted because it is exactly represented by Time / 1000.
• Camera video streams are NOT included in this repository; they remain in the source videos tree.
• meta/ is mirrored from the source. Aside from the redundant timestamp column and the excluded videos, no source rows or numeric fields are dropped.

Read example

from tsfile import TsFileReader

with TsFileReader("data/self_repair_gripper.tsfile") as reader:
    print(reader.get_all_table_schemas()["self_repair_gripper"])

Source & license

• Original dataset: https://huggingface.co/datasets/YOLO2431/self-repair-gripper
• Author: YOLO2431
• License: apache-2.0