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README.md

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+---
+license: cc-by-4.0
+task_categories:
+- robotics
+tags:
+- LeRobot
+- robotics
+- bimanual
+- teleoperation
+- manipulation
+- dexterous-hand
+- guardrails
+pretty_name: GLIDE Data
+size_categories:
+- 100K<n<1M
+configs:
+- config_name: lift_plate_mixed
+  data_files: lift_plate_mixed/data/*/*.parquet
+- config_name: lift_plate_success
+  data_files: lift_plate_success/data/*/*.parquet
+- config_name: stand_marker_mixed
+  data_files: stand_marker_mixed/data/*/*.parquet
+- config_name: stand_marker_success
+  data_files: stand_marker_success/data/*/*.parquet
+- config_name: pour_wine_mixed
+  data_files: pour_wine_mixed/data/*/*.parquet
+- config_name: pour_wine_success
+  data_files: pour_wine_success/data/*/*.parquet
+---
+
+<h1 align="center" style="font-size: 2em; font-weight: 600; line-height: 1.25; color: #1f2328; margin: 0.67em 0 16px; padding-bottom: 0.3em; border-bottom: 1px solid #d1d9e0;"><img src="img/icon.png" width="24" alt="GLIDE icon" style="display: inline-block; vertical-align: middle; width: 0.8em; margin: 0; border: none;"> GLIDE:<br/>
+Learning Beyond What Humans Can Demonstrate</h1>
+
+<p align="center" style="margin: 0 0 16px;">
+    <a href="https://yuchen-song.github.io/" style="color: #0969da; text-decoration: none;"><strong style="color: #0969da;">Yuchen Song</strong></a>
+    ,
+    <a href="https://adityamittal03.github.io/" style="color: #0969da; text-decoration: none;"><strong style="color: #0969da;">Aditya Mittal</strong></a>
+    ,
+    <a href="https://unnat.github.io/" style="color: #0969da; text-decoration: none;"><strong style="color: #0969da;">Unnat Jain</strong></a>
+</p>
+
+<p align="center" style="margin: 0 0 16px;">
+    <img src="img/ucirvine-blue.png" height="20" alt="UC Irvine" style="display: inline-block; height: 20px; width: auto; margin: 0; border: none;">
+</p>
+
+<p align="center" style="margin: 0 0 16px;">
+    <a href="https://arxiv.org/abs/2609.24996"><img src="https://img.shields.io/badge/arXiv-2609.24996-maroon.svg" alt="Paper"></a>
+    <a href="https://guardrail-policy.github.io/"><img src="https://img.shields.io/badge/Website-github.io-green" alt="Website"></a>
+    <a href="https://github.com/Yuchen-Song/glide_code"><img src="https://img.shields.io/badge/Code-GitHub-blue.svg" alt="Code"></a>
+    <a href="https://creativecommons.org/licenses/by/4.0/"><img src="https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg" alt="License: CC BY 4.0"></a>
+</p>
+
+<p align="center" style="margin: 0 0 16px;">
+  <img src="img/teaser.png" width="90%" alt="GLIDE overview" style="display: inline-block; width: 90%; margin: 0; border: none;"/>
+</p>
+
+**TL;DR:** GLIDE uses closed-loop, self-refined guardrails to make infeasible
+robot manipulation tasks demonstrable, learnable, and the trained policies more
+reliable to deploy.
+
+This repository hosts the real-robot demonstration datasets used to train the
+GLIDE π₀.₅ policies. The robot runtime used to collect the data and evaluate
+policies is in [glide_code](https://github.com/Yuchen-Song/glide_code).
+
+## Tasks
+
+- **🍅 Tomato plate transfer** (`lift_plate_*`): use both grippers to grasp a
+  plate of tomatoes and carry it from the tabletop to an elevated surface
+  without tilting the plate or spilling.
+- **🖍️ Marker handover & stand** (`stand_marker_*`): grasp a marker with one
+  gripper, transfer it to the other gripper, place it upright on the table, and
+  withdraw without knocking it over.
+- **🍷 Wine serving** (`pour_wine_*`): use a left parallel-jaw gripper to hold a
+  bottle and a right 15-DoF CRAFT hand to hold a glass while pouring wine from
+  the bottle into the glass.
+
+## Subsets
+
+Each task has two subsets, each a self-contained LeRobot dataset:
+
+- **`*_mixed`**: every recorded demonstration, successful and failed
+  (mixed quality).
+- **`*_success`**: only the successful episodes from the matching `*_mixed`
+  subset.
+
+| Subset | Robot | Episodes | Frames | FPS | Duration | Size |
+| --- | --- | ---: | ---: | ---: | ---: | ---: |
+| `lift_plate_mixed` | `yam_dual_arm` | 30 | 13,170 | 30 | 7.3 min | 144 MB |
+| `lift_plate_success` | `yam_dual_arm` | 19 | 8,508 | 30 | 4.7 min | 94 MB |
+| `stand_marker_mixed` | `yam_dual_arm` | 30 | 12,769 | 30 | 7.1 min | 128 MB |
+| `stand_marker_success` | `yam_dual_arm` | 22 | 9,216 | 30 | 5.1 min | 93 MB |
+| `pour_wine_mixed` | `yam_dual_arm_craft_hand` | 60 | 162,158 | 45 | 60.1 min | 2.3 GB |
+| `pour_wine_success` | `yam_dual_arm_craft_hand` | 30 | 83,240 | 45 | 30.8 min | 1.2 GB |
+
+Language instructions (one per task):
+
+| Task | Instruction |
+| --- | --- |
+| 🍅 Tomato plate transfer | "Use both arms to pick up the plate and put it onto the box" |
+| 🖍️ Marker handover & stand | "Pick up the marker with one gripper, transfer it to the other gripper, and lift it upright on the table." |
+| 🍷 Wine serving | "Use left gripper to pick up the wine bottle, right hand to pick up the wine cup, and pour wine from bottle to the cup." |
+
+## Data Format
+
+All subsets use the [LeRobot](https://github.com/huggingface/lerobot) dataset
+format, `codebase_version: v2.1`:
+
+```
+<subset>/
+├── meta/
+│   ├── info.json              # schema, fps, feature names
+│   ├── tasks.jsonl            # language instruction
+│   ├── episodes.jsonl         # per-episode length and task
+│   └── episodes_stats.jsonl   # per-episode feature statistics
+├── data/chunk-000/episode_XXXXXX.parquet
+└── videos/chunk-000/observation.images.{head,left_wrist,right_wrist}/episode_XXXXXX.mp4
+```
+
+Every subset records three RGB cameras (`head`, `left_wrist`, `right_wrist`) at
+640×480 as H.264 MP4, along with the robot state, the executed action, and the
+raw teleoperation signals.
+
+### Two-gripper tasks (`lift_plate_*`, `stand_marker_*`)
+
+Two YAM arms, each with a parallel-jaw gripper, teleoperated with Quest
+controllers.
+
+| Feature | Shape | Description |
+| --- | --- | --- |
+| `observation.state` | 14 | `left_joint_0..5`, `left_gripper`, `right_joint_0..5`, `right_gripper` |
+| `action` | 14 | Commanded joints and grippers, same order as the state |
+| `teleoperation.matrices.{head,left_controller,right_controller}` | 4×4 | Quest head and controller poses |
+| `teleoperation.buttons` | 8 | Trigger, squeeze, A/B buttons for each controller |
+
+### CRAFT-hand task (`pour_wine_*`)
+
+A left YAM arm with a parallel-jaw gripper and a right YAM arm with a 15-DoF
+CRAFT hand, teleoperated with Quest hand tracking.
+
+| Feature | Shape | Description |
+| --- | --- | --- |
+| `observation.state` | 28 | `left_joint_0..5`, `left_gripper`, `right_joint_0..5`, `craft_motor_0..14_raw` |
+| `action` | 28 | Commanded joints, gripper, and CRAFT motors, same order as the state |
+| `teleoperation.matrices.{head,left_hand,right_hand}` | 4×4 | Quest head and wrist poses |
+| `teleoperation.landmark_matrices.{left_hand,right_hand}` | 25×4×4 | Quest hand-landmark poses |
+| `teleoperation.hand_states` | 12 | Pinch, squeeze, and tap flags and values per hand |
+| `teleoperation.tracking` | 9 | Tracking validity, event counts, and packet ages for head and hands |
+
+All subsets also include the standard LeRobot index columns: `timestamp`,
+`frame_index`, `episode_index`, `index`, and `task_index`.
+
+## Usage
+
+Download a single subset:
+
+```bash
+hf download yuchensong/glide_data \
+  --repo-type dataset \
+  --include "stand_marker_success/*" \
+  --local-dir ./glide_data
+```
+
+Load it with a LeRobot release that reads the v2.1 format, such as the version
+pinned by [OpenPI](https://github.com/Physical-Intelligence/openpi):
+
+```python
+from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
+
+dataset = LeRobotDataset(
+    repo_id="yuchensong/glide_data",
+    root="./glide_data/stand_marker_success",
+)
+frame = dataset[0]
+print(frame["observation.state"].shape, frame["action"].shape)
+```
+
+Or read the tabular data directly:
+
+```python
+import pandas as pd
+
+df = pd.read_parquet(
+    "./glide_data/stand_marker_success/data/chunk-000/episode_000000.parquet"
+)
+```
+
+To train π₀.₅ policies, follow OpenPI's instructions for computing
+normalization statistics and fine-tuning on a local LeRobot dataset.
+
+## License
+
+This dataset is released under the
+[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)
+license.
+
+## Citation
+
+```bibtex
+@article{song2026glide,
+  title={Learning Beyond What Humans Can Demonstrate},
+  author={Song, Yuchen and Mittal, Aditya and Jain, Unnat},
+  journal={arXiv preprint arXiv:2609.24996},
+  year={2026}
+}
+```

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