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codebase_version
string
robot_type
string
total_episodes
int64
total_frames
int64
total_tasks
int64
chunks_size
int64
data_files_size_in_mb
int64
video_files_size_in_mb
int64
fps
int64
splits
dict
data_path
string
features
dict
video_path_original
string
tsfile_conversion
dict
v3.0
panda
5,000
575,101
128
1,000
100
500
10
{ "train": "0:5000" }
data/vlabench_primitive_ft_lerobot_video.tsfile
{ "Time": { "dtype": "int64", "shape": [ 1 ], "tsfile_role": "TIME", "unit": "ms" }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "tsfile_role": "TAG" }, "task_index": { "dtype": "int64", "shape": [ 1 ], "tsfile_role": "TAG" }, ...
videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4
{ "source_dataset": "VLABench/vlabench_primitive_ft_lerobot_video", "source_data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet", "converted_data_path": "data/vlabench_primitive_ft_lerobot_video.tsfile", "table_name": "vlabench_primitive_ft_lerobot_video", "granularity": "merged", "time_...

VLABench Primitive Tasks — LeRobot v3.0 (TsFile)

Apache TsFile version of VLABench/vlabench_primitive_ft_lerobot_video.

Overview

This dataset is organized in the LeRobot v3.0 format and is used for integrating VLABench into the LeRobot framework officially. Compared with the v2.0 and the RLDS versions, this release stores the visual observations in a video-compressed format rather than as individual image files, giving better storage efficiency and data-loading performance.

It contains demonstrations for 10 primitive manipulation tasks on a Franka Panda arm, collected across 128 concrete language-instructed task variants (e.g. "Pick up the mahjong of 1 pin", "Insert the rose into the vase"). Models trained on this data can be evaluated on multiple generalization tracks in VLABench.

The 10 primitive task categories are: add_condiment, insert_flower, select_book, select_chemistry_tube, select_drink, select_fruit, select_mahjong, select_painting, select_poker, select_toy.

  • Robot: Franka Panda, 7-DoF.
  • Episodes: 5,000 (episode_index 0–4999).
  • Frames: 575,101 time-series rows.
  • Tasks: 128 language-instructed variants (task_index 0–127); the full task_index → instruction mapping is in meta/tasks.parquet.
  • Sampling rate: 10 fps (from meta/info.json).

Baseline models: pi05-primitive-10task, pi0-fast-primitive-10task, pi0-primitive-10task.

Schema (TsFile structure)

All 5,000 episodes are stored in a single TsFile table; episode_index and task_index are TAG columns (the TsFile device dimension), so one episode is selected with WHERE episode_index=0.

  • Time (INT64, milliseconds) — round(timestamp * 1000); restarts at 0 for each episode, stepping by 100 ms (10 fps).
  • episode_index (TAG) — source episode id, 0–4999.
  • task_index (TAG) — source task id, 0–127; resolve to the instruction text via meta/tasks.parquet.
  • frame_index (FIELD, INT64) — frame number within the episode.
  • sample_index (FIELD, INT64) — the source global index column, renamed.
  • state_0 … state_6 (FIELD, FLOAT) — robot proprioceptive state, flattened from the 7-element state vector.
  • actions_0 … actions_6 (FIELD, FLOAT) — action command, flattened from the 7-element actions vector.

The source timestamp column is dropped because it equals Time / 1000 seconds. No other columns or rows are dropped.

Videos

The three camera video streams of the original dataset (image, second_image, wrist_image) are NOT included in this repository. They are large and non–time-series; obtain them from the original dataset: https://huggingface.co/datasets/VLABench/vlabench_primitive_ft_lerobot_video (the videos/ directory).

Usage

Read the .tsfile file with the Apache TsFile Java or Python SDK.

Source & license

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