metadata
license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- so100
- push
- cup
- tsfile
- format:tsfile
- time-series
modality:
- timeseries
configs:
- config_name: default
data_files:
- split: train
path: data/push_cup_target.tsfile
push_cup_target (TsFile)
Apache TsFile version of lirislab/push_cup_target.
Overview
This dataset is a LeRobot v2.1 dataset of an SO-100 arm pushing a cup toward a target.
- Robot: SO-100 (so100)
- Scale: 30 episodes, 8,528 frames, 30 fps
- Split: train
- Cameras (not uploaded):
realsense_topandrealsense_side
Schema (TsFile structure)
The TsFile table is named push_cup_target.
| Role | Columns |
|---|---|
| Time | Time, INT64 milliseconds |
| TAG | episode_index, task_index |
| FIELD | frame_index, sample_index |
| FIELD | action_0 … action_5 |
| FIELD | observation_state_0 … observation_state_5 |
Vector columns are flattened into scalar FLOAT measurements (single precision). The source index column is retained as sample_index.
Conversion notes
Time = round(timestamp * 1000)with millisecond precision; time restarts inside each episode, whileepisode_indexandtask_indexidentify the TsFile device.- The original
timestampfield is omitted because it is exactly represented byTime / 1000. - Camera video streams are NOT included in this repository; they remain in the source videos tree.
meta/is mirrored from the source. Aside from the redundanttimestampcolumn and the excluded videos, no source rows or numeric fields are dropped.
Read example
from tsfile import TsFileReader
with TsFileReader("data/push_cup_target.tsfile") as reader:
print(reader.get_all_table_schemas()["push_cup_target"])
Source & license
- Original dataset: https://huggingface.co/datasets/lirislab/push_cup_target
- Author: lirislab
- License: apache-2.0