libero_plus_object_noise_all_failures (TsFile)

Apache TsFile version of LSY-lab/libero_plus_object_noise_all_failures, a LIBERO-Plus robot manipulation dataset created with LeRobot.

Modalities: Time-series. The original dataset also contains robot camera videos; those videos are not included in this converted repository and remain available from the original Hugging Face dataset.

Overview

A LeRobot v3.0 Franka (panda) dataset recording multi-camera demonstrations for LIBERO object-manipulation tasks with injected visual noise. Each row is one frame of a robot episode, with the robot's end-effector, joint, gripper state and the commanded action recorded as fixed-size vectors.

• Scale: 96 episodes, 15,250 frames, 9 tasks, 1 data chunk.
• Sampling rate: 20 fps.
• Robot: franka (panda).
• Split: train (0:96).

Schema (TsFile structure)

• Time (INT64, milliseconds) — round(timestamp * 1000), restarting for each episode.
• episode_index, task_index (TAG, INT64) — episode and task device dimensions; query one episode with WHERE episode_index=0.
• frame_index, sample_index (FIELD, INT64) — frame position and source row index (source index renamed to sample_index).
• observation_state_0..7 (FIELD, FLOAT) — flattened observation.state (8 motors: x, y, z, axis_angle1..3, gripper, gripper).
• observation_states_ee_state_0..5 (FIELD, FLOAT) — flattened observation.states.ee_state (end-effector pose).
• observation_states_joint_state_0..6 (FIELD, FLOAT) — flattened observation.states.joint_state (7 joints).
• observation_states_gripper_state_0..1 (FIELD, FLOAT) — flattened observation.states.gripper_state.
• action_0..6 (FIELD, FLOAT) — flattened action (7 commanded motors).

The source timestamp column is represented by Time and not retained as a separate field. Vector columns are flattened to scalar FLOAT fields with their full source-column prefix and an element index. The camera video streams are not included; they remain available in the original videos directory.

Usage

Read data/libero_plus_object_noise_all_failures.tsfile with the Apache TsFile Java or Python SDK. All episodes share one table; use the TAG columns to select an episode or task.

Source & license

• Original dataset: https://huggingface.co/datasets/LSY-lab/libero_plus_object_noise_all_failures
• Author / publisher: LSY-lab
• Paper: not declared by the original dataset
• License: Apache License 2.0