| --- |
| license: apache-2.0 |
| task_categories: |
| - robotics |
| tags: |
| - LeRobot |
| - manipulation |
| - pick-and-place |
| - cafe-serving |
| - omx |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # serving_a — Café Pick-and-Place (Long Episode) |
| |
| LeRobot **v3.0** dataset for OpenManipulator-X (OMX) cafe serving task. |
| This is the **Category A (Long Episode)** subset of the GR00T N1.7 fine-tuning dataset. |
| |
| A converted **v2.1** version (per-episode parquet/mp4 layout, GR00T-trainable) is produced from this dataset using `scripts/lerobot_conversion/convert_v3_to_v2.py`. |
| |
| --- |
| |
| ## Dataset summary |
| |
| | Item | Value | |
| | ------------------ | ---------------------------------------------- | |
| | Robot | OpenManipulator-X 4-DOF (`omx_follower`) | |
| | Codebase version | `v3.0` | |
| | Total episodes | 265 | |
| | Total frames | 144,788 | |
| | FPS | 30 | |
| | Cameras | `observation.images.top`, `observation.images.wrist` (640×480, 30 fps) | |
| | State / Action dim | 6 each (single_arm × 5, gripper × 1) | |
| | Action horizon | 16 (configured via `examples/OMX/omx_config.py`) | |
| | Tasks | 3 (see below) | |
|
|
| ## Tasks (`task_index`) |
| |
| | index | instruction | |
| | :---: | ------------------------------------------ | |
| | 0 | `pick up plate and place at target zone` | |
| | 1 | `pick up cup and place at target zone` | |
| | 2 | `return to home` | |
| |
| ### task distribution |
| |
| | task_index | frames | pct | |
| | ---------- | -----: | ---: | |
| | 0 (plate) | 49,698 | 34.3% | |
| | 1 (cup) | 66,874 | 46.2% | |
| | 2 (home) | 28,216 | 19.5% | |
|
|
| --- |
|
|
| ## Scenario composition (Category A — Long Episode) |
|
|
| Every episode starts at home pose, performs the task(s), and returns to home. |
| Each scenario was collected as a separate sub-dataset (`serving_a1`…`serving_a7`) and then merged. |
|
|
| | sub-id | scenario | env state | success | retry | total | |
| | :----: | ---------------------- | -------------------- | ------: | ----: | ----: | |
| | A-1 | one cup | cup=1 | 30 | 5 | **35** | |
| | A-2 | one plate | plate=1 | 30 | 5 | **35** | |
| | A-3 | two plates | plate=2 | 30 | 10 | **40** | |
| | A-4 | two cups | cup=2 | 30 | 10 | **40** | |
| | A-5 | one plate + one cup | plate=1, cup=1 | 38 | 12 | **50** | |
| | A-6 | one plate + two cups | plate=1, cup=2 | 35 | 10 | **45** | |
| | A-7 | empty env (stop) | empty (2 sub-cases) | 18 | 0 | **18** | |
| | | **Total** | | **211** | **52**| **265**| |
|
|
| * **success**: completed normally. |
| * **retry**: gripper miss → short back-off → retry → success, all within a single episode. |
| * **A-7 sub-cases**: 7 episodes with both workspaces empty; 11 episodes with pick workspace empty and place workspace already containing previously-served objects (forces VLM to learn "stop when nothing to pick" even with clutter in the place zone). |
|
|
| --- |
|
|
| ## Label boundary scheme |
|
|
| Multi-task episodes are segmented into per-action task ranges so the policy can learn the language–action grounding. |
|
|
| | sub-id | segment pattern | # boundaries | |
| | :----: | ------------------------------------------------------------ | :----------: | |
| | A-1 | `cup(1) → home(2)` | 1 | |
| | A-2 | `plate(0) → home(2)` | 1 | |
| | A-3 | `plate(0) → plate(0) → home(2)` (per-plate restart) | 2 | |
| | A-4 | `cup(1) → cup(1) → home(2)` (per-cup restart) | 2 | |
| | A-5 | `cup(1) → plate(0) → home(2)` | 2 | |
| | A-6 | `cup(1) → cup(1) → plate(0) → home(2)` | 3 | |
| | A-7 | `home(2)` only | 0 | |
|
|
| Boundaries were auto-detected from gripper signal events (`fully_close` → next `start_open`) and audited manually for edge cases. Episodes that lacked the expected number of events had their missing boundary estimated from the median percentile of complete episodes within the same scenario. |
|
|
| --- |
|
|
| ## Repository layout |
|
|
| ``` |
| serving_a/ |
| ├── data/chunk-000/file-000.parquet # all frames, concatenated |
| ├── meta/ |
| │ ├── info.json # codebase_version, features, totals |
| │ ├── tasks.parquet # task_index → instruction |
| │ └── episodes/chunk-000/file-000.parquet # per-episode metadata + stats |
| └── videos/ |
| ├── observation.images.top/chunk-000/file-000.mp4 |
| └── observation.images.wrist/chunk-000/file-000.mp4 |
| ``` |
|
|
| --- |
|
|
| ## Companion dataset |
|
|
| This is **Category A only**. The matching **Category B (atomic-focused demos)** dataset is available as: |
|
|
| > [`jae0311/serving_b`](https://huggingface.co/datasets/jae0311/serving_b) — 160 episodes, 75,089 frames |
|
|
| For GR00T N1.7 fine-tuning we use a 2-stage schedule: |
|
|
| | Stage | Data | max-steps | LR | Goal | |
| | :---: | --------------- | :-------: | :----: | ----------------------------------------- | |
| | 1 | `serving_b` (B) | 5,000 | 1e-4 | atomic pick-and-place reliability | |
| | 2 | A+B merged | 25,000 | 5e-5 | full long-episode performance from Stage 1 ckpt | |
|
|
| --- |
|
|
| ## Citation / acknowledgments |
|
|
| - Model: [GR00T N1.7](https://huggingface.co/nvidia/GR00T-N1.7-3B) (NVIDIA) |
| - Dataset format: [LeRobot](https://github.com/huggingface/lerobot) |
| - Robot: ROBOTIS OpenManipulator-X |
|
|
