THULab/idm_openarm_merged_256_v2

idmopenarmmerged256v2 (TsFile)

Apache TsFile version of `glory-hyeok/idm-openarm-merged-256-v2`.

Overview

A LeRobot robot dataset recorded on a openarm_rh56f1 arm. Task(s): 0; 1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15. Each frame holds the commanded action and observed observation.state joint positions, plus camera views stored as videos in the original dataset.

• —Episodes: 1156
• —Frames: 492,920
• —Sampling rate: 20 fps
• —Tasks: 16 — "0; 1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15"

Schema (TsFile structure)

All episodes share one TsFile with episode_index and task_index as TAG columns; query a single episode with WHERE episode_index = N.

• —Time (INT64, milliseconds) — round(timestamp * 1000); the source timestamp column is dropped (it equals Time / 1000).
• —episode_index (TAG) — device dimension.
• —task_index (TAG) — device dimension.
• —episode_index (INT64) — measurement.
• —task_index (INT64) — measurement.
• —frame_index (INT64) — measurement.
• —sample_index (INT64) — measurement.
• —language_instruction (STRING) — measurement.
• —next_done (INT64) — measurement.
• —next_success (INT64) — measurement.
• —observation_state_0 (FLOAT) — measurement.
• —observation_state_1 (FLOAT) — measurement.
• —observation_state_2 (FLOAT) — measurement.
• —observation_state_3 (FLOAT) — measurement.
• —observation_state_4 (FLOAT) — measurement.
• —observation_state_5 (FLOAT) — measurement.
• —observation_state_6 (FLOAT) — measurement.
• —observation_state_7 (FLOAT) — measurement.
• —observation_state_8 (FLOAT) — measurement.
• —observation_state_9 (FLOAT) — measurement.
• —observation_state_10 (FLOAT) — measurement.
• —observation_state_11 (FLOAT) — measurement.
• —observation_state_12 (FLOAT) — measurement.
• —observation_state_13 (FLOAT) — measurement.
• —observation_state_14 (FLOAT) — measurement.
• —observation_state_15 (FLOAT) — measurement.
• —observation_state_16 (FLOAT) — measurement.
• —observation_state_17 (FLOAT) — measurement.
• —observation_state_18 (FLOAT) — measurement.
• —observation_state_19 (FLOAT) — measurement.
• —observation_state_20 (FLOAT) — measurement.
• —observation_state_21 (FLOAT) — measurement.
• —observation_state_22 (FLOAT) — measurement.
• —observation_state_23 (FLOAT) — measurement.
• —observation_state_24 (FLOAT) — measurement.
• —observation_state_25 (FLOAT) — measurement.
• —observation_state_26 (FLOAT) — measurement.
• —observation_state_27 (FLOAT) — measurement.
• —action_0 (FLOAT) — measurement.
• —action_1 (FLOAT) — measurement.
• —action_2 (FLOAT) — measurement.
• —action_3 (FLOAT) — measurement.
• —action_4 (FLOAT) — measurement.
• —action_5 (FLOAT) — measurement.
• —action_6 (FLOAT) — measurement.
• —action_7 (FLOAT) — measurement.
• —action_8 (FLOAT) — measurement.
• —action_9 (FLOAT) — measurement.
• —action_10 (FLOAT) — measurement.
• —action_11 (FLOAT) — measurement.
• —action_12 (FLOAT) — measurement.
• —action_13 (FLOAT) — measurement.
• —action_14 (FLOAT) — measurement.
• —action_15 (FLOAT) — measurement.
• —action_16 (FLOAT) — measurement.
• —action_17 (FLOAT) — measurement.
• —action_18 (FLOAT) — measurement.
• —action_19 (FLOAT) — measurement.
• —action_20 (FLOAT) — measurement.
• —action_21 (FLOAT) — measurement.
• —action_22 (FLOAT) — measurement.
• —action_23 (FLOAT) — measurement.
• —action_24 (FLOAT) — measurement.
• —action_25 (FLOAT) — measurement.
• —action_26 (FLOAT) — measurement.
• —action_27 (FLOAT) — measurement.
• —torque_0 (FLOAT) — measurement.
• —torque_1 (FLOAT) — measurement.
• —torque_2 (FLOAT) — measurement.
• —torque_3 (FLOAT) — measurement.
• —torque_4 (FLOAT) — measurement.
• —torque_5 (FLOAT) — measurement.
• —torque_6 (FLOAT) — measurement.
• —torque_7 (FLOAT) — measurement.
• —torque_8 (FLOAT) — measurement.
• —torque_9 (FLOAT) — measurement.
• —torque_10 (FLOAT) — measurement.
• —torque_11 (FLOAT) — measurement.
• —torque_12 (FLOAT) — measurement.
• —torque_13 (FLOAT) — measurement.

The vector columns are flattened per joint:

• —action_* — commanded joints: openarmheadpitchPos, openarmheadyawPos, openarmleftjoint1Pos, openarmleftjoint2Pos, openarmleftjoint3Pos, openarmleftjoint4Pos, openarmleftjoint5Pos, openarmleftjoint6Pos, openarmleftjoint7Pos, openarmrightjoint1Pos, openarmrightjoint2Pos, openarmrightjoint3Pos, openarmrightjoint4Pos, openarmrightjoint5Pos, openarmrightjoint6Pos, openarmrightjoint7Pos, lefthandthumb1jointPos, lefthandthumb2jointPos, lefthandindex1jointPos, lefthandmiddle1jointPos, lefthandring1jointPos, lefthandlittle1jointPos, righthandthumb1jointPos, righthandthumb2jointPos, righthandindex1jointPos, righthandmiddle1jointPos, righthandring1jointPos, righthandlittle1jointPos.
• —observation_state_* — observed joints: openarmheadpitchPos, openarmheadyawPos, openarmleftjoint1Pos, openarmleftjoint2Pos, openarmleftjoint3Pos, openarmleftjoint4Pos, openarmleftjoint5Pos, openarmleftjoint6Pos, openarmleftjoint7Pos, openarmrightjoint1Pos, openarmrightjoint2Pos, openarmrightjoint3Pos, openarmrightjoint4Pos, openarmrightjoint5Pos, openarmrightjoint6Pos, openarmrightjoint7Pos, lefthandthumb1jointPos, lefthandthumb2jointPos, lefthandindex1jointPos, lefthandmiddle1jointPos, lefthandring1jointPos, lefthandlittle1jointPos, righthandthumb1jointPos, righthandthumb2jointPos, righthandindex1jointPos, righthandmiddle1jointPos, righthandring1jointPos, righthandlittle1jointPos.

Usage

Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:

from pathlib import Path
from tsfile import TsFileReader

path = Path("data/idm_openarm_merged_256_v2.tsfile")
with TsFileReader(str(path)) as reader:
    schemas = reader.get_all_table_schemas()
    print("tables:", list(schemas))
    table_name = next(iter(schemas))
    table = schemas[table_name]
    columns = [column.get_column_name() for column in table.get_columns()]
    print("columns:", columns)
    field_names = [
        column.get_column_name()
        for column in table.get_columns()
        if column.get_column_name() not in {"Time", "time"}
    ]
    if field_names:
        with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
            batch = result.read_arrow_batch()
            if batch is not None:
                print(batch.to_pandas().head())

Source & license

• —Original dataset: https://huggingface.co/datasets/glory-hyeok/idm-openarm-merged-256-v2
• —Author / publisher: glory-hyeok
• —License: apache-2.0
• —Note: camera videos are NOT included; see the original dataset.