zjt24/aloha_dining_table

ALOHA Dining Table TsFile

This dataset is a TsFile conversion of the Hugging Face dataset htrbao/aloha-dining-table, which uses the LeRobot v2.1 format.

Modalities: Time-series. The original dataset also includes three video streams, observation.images.color.high, observation.images.color.wrist_right, and observation.images.color.wrist_left; those videos are not included in this repository and remain available in the source dataset.

Source Dataset

• Original dataset: htrbao/aloha-dining-table
• License: MIT
• Format: LeRobot v2.1
• Robot type: ALOHA
• Task: Spread the dining mat on the table, place the plate at the center of the mat, put the spoon to the left of the plate, and place the chopsticks to the right of the plate.
• Split: single train split (0:99)
• Scale: 99 episodes, 80,041 frames, 1 task, 1 data chunk
• Sampling rate: 15 fps
• Original video features:
• observation.images.color.high at 480x640x3
• observation.images.color.wrist_right at 480x640x3
• observation.images.color.wrist_left at 480x640x3

Converted Files

• TsFile: data/aloha_dining_table.tsfile
• Rows: 80,041
• Episodes: 99
• Tasks: 1 (task_index = 0)
• Table name: aloha_dining_table
• Time precision: milliseconds
• Metadata: meta/ is mirrored from the source dataset, with meta/info.json rewritten to describe the TsFile artifact and conversion mapping.

Schema

Column	Role	Type	Notes
Time	TIME	INT64	round(timestamp * 1000), in milliseconds; restarts per episode
episode_index	TAG	INT64	Source episode identifier
task_index	TAG	INT64	Source task identifier
frame_index	FIELD	INT64	Source frame index, preserved
sample_index	FIELD	INT64	Renamed from source index
action_0 ... action_13	FIELD	FLOAT	Flattened from action[14]
observation_state_0 ... observation_state_13	FIELD	FLOAT	Flattened from observation.state[14]
observation_velocity_0 ... observation_velocity_13	FIELD	FLOAT	Flattened from observation.velocity[14]
observation_effort_0 ... observation_effort_13	FIELD	FLOAT	Flattened from observation.effort[14]

The 14 action and observation state elements correspond to the ALOHA joint displacements named in the source metadata: left_waist, left_shoulder, left_elbow, left_forearm_roll, left_wrist_angle, left_wrist_rotate, left_gripper, right_waist, right_shoulder, right_elbow, right_forearm_roll, right_wrist_angle, right_wrist_rotate, and right_gripper.

episode_index and task_index are TAG columns, so they form the TsFile device dimension. To read one episode, filter by episode_index.

Conversion Notes

• The LeRobot frame Parquet files under data/chunk-000/ were merged into one TsFile for the train split.
• Vector columns were flattened by preserving the source column name, replacing . with _, and appending the element index.
• The source timestamp column is dropped because it is redundant with Time / 1000 seconds.
• The source index column is renamed to sample_index.
• Videos are not uploaded here. Use the original dataset videos: https://huggingface.co/datasets/htrbao/aloha-dining-table/tree/main/videos

Read Example

from tsfile import TsFileReader

path = "data/aloha_dining_table.tsfile"
table = "aloha_dining_table"

with TsFileReader(path) as reader:
    columns = [
        "episode_index",
        "task_index",
        "frame_index",
        "sample_index",
        "action_0",
        "observation_state_0",
    ]
    with reader.query_table(table, columns, batch_size=4096) as result:
        batch = result.read_arrow_batch()
        print(batch)