pointblind2dc (TsFile)

Apache TsFile version of paszea/pointblind2dc.

Overview

A LeRobot robot-manipulation dataset collected on a lekiwi robot. Each episode records the robot reaching to fetch an object: the commanded action, the measured arm state, and a 2D target point in the environment, sampled frame by frame.

• Robot: lekiwi (6-DoF arm: shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper).
• Task: "Fetch an object." (1 task).
• Scale: 70 episodes, 137,862 frames, single train split.
• Sampling rate: 30 fps.
• Videos: none — this dataset has no camera streams.

Schema (TsFile structure)

• Time (INT64, milliseconds) — round(timestamp * 1000), restarts per episode.
• episode_index (TAG) — episode device dimension; query one episode with WHERE episode_index=0.
• task_index (TAG) — task device dimension (single task here).
• frame_index (FIELD, INT64) — original per-episode frame counter.
• sample_index (FIELD, INT64) — source index column, renamed.
• action_0..action_5 (FIELD, FLOAT) — commanded action per joint (shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper).
• observation_state_0..observation_state_5 (FIELD, FLOAT) — measured arm state, same joint order as the action.
• observation_environment_state_0..1 (FIELD, FLOAT) — the (x0, y0) target point in the environment.

Vector columns are flattened by preserving the source name (. → _) and appending the element index. The source timestamp column is dropped because it equals Time ÷ 1000 seconds.

Usage

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

Source & license

• Original dataset: https://huggingface.co/datasets/paszea/pointblind2dc
• Author / publisher: paszea
• Created with: LeRobot
• License: apache-2.0