idm_openarm_merged_256_v2 (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: openarm_head_pitch_Pos, openarm_head_yaw_Pos, openarm_left_joint1_Pos, openarm_left_joint2_Pos, openarm_left_joint3_Pos, openarm_left_joint4_Pos, openarm_left_joint5_Pos, openarm_left_joint6_Pos, openarm_left_joint7_Pos, openarm_right_joint1_Pos, openarm_right_joint2_Pos, openarm_right_joint3_Pos, openarm_right_joint4_Pos, openarm_right_joint5_Pos, openarm_right_joint6_Pos, openarm_right_joint7_Pos, left_hand_thumb_1_joint_Pos, left_hand_thumb_2_joint_Pos, left_hand_index_1_joint_Pos, left_hand_middle_1_joint_Pos, left_hand_ring_1_joint_Pos, left_hand_little_1_joint_Pos, right_hand_thumb_1_joint_Pos, right_hand_thumb_2_joint_Pos, right_hand_index_1_joint_Pos, right_hand_middle_1_joint_Pos, right_hand_ring_1_joint_Pos, right_hand_little_1_joint_Pos.
• observation_state_* — observed joints: openarm_head_pitch_Pos, openarm_head_yaw_Pos, openarm_left_joint1_Pos, openarm_left_joint2_Pos, openarm_left_joint3_Pos, openarm_left_joint4_Pos, openarm_left_joint5_Pos, openarm_left_joint6_Pos, openarm_left_joint7_Pos, openarm_right_joint1_Pos, openarm_right_joint2_Pos, openarm_right_joint3_Pos, openarm_right_joint4_Pos, openarm_right_joint5_Pos, openarm_right_joint6_Pos, openarm_right_joint7_Pos, left_hand_thumb_1_joint_Pos, left_hand_thumb_2_joint_Pos, left_hand_index_1_joint_Pos, left_hand_middle_1_joint_Pos, left_hand_ring_1_joint_Pos, left_hand_little_1_joint_Pos, right_hand_thumb_1_joint_Pos, right_hand_thumb_2_joint_Pos, right_hand_index_1_joint_Pos, right_hand_middle_1_joint_Pos, right_hand_ring_1_joint_Pos, right_hand_little_1_joint_Pos.

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.