libero_10_no_noops_first9

This dataset was converted from godnpeter/libero_10_no_noops_first9 to Apache TsFile format.

Dataset Description

The original dataset is a LeRobot-format robot dataset recorded with a Franka robot for nine LIBERO manipulation tasks.

• Modalities: Time-series. The original dataset also includes video streams.
• Robot type: franka
• Codebase version: LeRobot v2.1
• Recording frequency: 20 Hz
• Split: train (0:338)
• Scale: 338 episodes, 90,603 frames, 9 tasks, and 676 source videos
• Source data path: data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet
• Source video path: videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4

Tasks:

• task_index=0: put the white mug on the left plate and put the yellow and white mug on the right plate
• task_index=1: put the white mug on the plate and put the chocolate pudding to the right of the plate
• task_index=2: put the yellow and white mug in the microwave and close it
• task_index=3: put both the alphabet soup and the cream cheese box in the basket
• task_index=4: put both the alphabet soup and the tomato sauce in the basket
• task_index=5: put both moka pots on the stove
• task_index=6: put both the cream cheese box and the butter in the basket
• task_index=7: put the black bowl in the bottom drawer of the cabinet and close it
• task_index=8: pick up the book and place it in the back compartment of the caddy

Source Dataset

• Original dataset: godnpeter/libero_10_no_noops_first9
• Authors: godnpeter
• License: apache-2.0

TsFile Conversion

The numeric robot state/action/time/task data was converted into one TsFile:

data/libero_10_no_noops_first9.tsfile

Conversion details:

• All 338 source episodes are stored in one TsFile table named libero_10_no_noops_first9.
• episode_index and task_index are TsFile TAG columns. Query a single episode with WHERE episode_index=N.
• Time = round(timestamp * 1000) in milliseconds. The source timestamp column is not retained because it equals Time / 1000 seconds.
• frame_index is kept. Source index is renamed to sample_index.
• Vector columns are flattened by preserving the source column name, replacing . with _, and appending the element index.
• Values from flattened vector columns are stored as single-precision FLOAT.
• The converted TsFile contains 90,603 rows and 20 columns including Time, TAG columns, and FIELD measurements.

Flattened vector features:

• observation.state[8] -> observation_state_0..observation_state_7
• action[7] -> action_0..action_6

Schema roles:

• TIME: Time in milliseconds.
• TAG: episode_index, task_index.
• FIELD: frame_index, sample_index, and the flattened robot observation/action measurements.

Dropped or omitted source fields:

• timestamp is dropped because it is represented by Time.
• observation.images.wrist_image and observation.images.image are video features and are not converted into TsFile columns.
• MP4 videos are not included in this repository. They remain in the original dataset under videos/.

The mirrored meta/info.json records the original video path and includes a tsfile_conversion section describing the converted schema, row count, TAG columns, dropped timestamp column, omitted video features, and time mapping.

Read Example

from tsfile import TsFileReader

path = "data/libero_10_no_noops_first9.tsfile"
reader = TsFileReader(path)
table = reader.get_all_table_schemas()["libero_10_no_noops_first9"]
columns = [c.get_column_name() for c in table.get_columns()]
print(columns[:10])