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+Learning Beyond What Humans Can Demonstrate + +

+ Yuchen Song + , + Aditya Mittal + , + Unnat Jain +

+ +

+ UC Irvine +

+ +

+ Paper + Website + Code + License: CC BY 4.0 +

+ +

+ GLIDE overview +

+ +**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`: + +``` +/ +├── 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} +} +``` diff --git a/img/icon.png b/img/icon.png new file mode 100644 index 0000000000000000000000000000000000000000..8bc15eee3191a5bb6903bd87c8e7637612f7695f --- /dev/null +++ b/img/icon.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0c4b702ee92d93d5fba885a86c1218591a85126577b2dc543864847810960d40 +size 634108 diff --git a/img/teaser.png 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