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license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- manipulation
- pick-and-place
- cafe-serving
- omx
size_categories:
- 100K<n<1M
---
# serving_ab — Café Pick-and-Place (Long Episode + Atomic Demos)
LeRobot **v3.0** dataset for OpenManipulator-X (OMX) café serving task.
This is the **merged dataset combining Category A (Long Episode) and Category B (Atomic Demos)** used for the full GR00T N1.7 fine-tuning schedule.
---
## Dataset summary
| Item | Value |
| ------------------ | ---------------------------------------------- |
| Robot | OpenManipulator-X 4-DOF (`omx_follower`) |
| Codebase version | `v3.0` |
| Total episodes | 425 (A: 265, B: 160) |
| Total frames | 219,877 |
| Total duration | ~2h 2m @ 30 fps |
| 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) | 74,679 | 34.0% |
| 1 (cup) | 96,803 | 44.0% |
| 2 (home) | 48,395 | 22.0% |
---
## Composition
### Category A — Long Episode (265 episodes, eps 0~264)
Multi-step pick-and-place scenarios starting and ending at home pose.
| sub-id | scenario | env state | total |
| :----: | -------------------- | -------------------- | ----: |
| A-1 | one cup | cup=1 | 35 |
| A-2 | one plate | plate=1 | 35 |
| A-3 | two plates | plate=2 | 40 |
| A-4 | two cups | cup=2 | 40 |
| A-5 | one cup + one plate | plate=1, cup=1 | 50 |
| A-6 | two cups + one plate | plate=1, cup=2 | 45 |
| A-7 | empty (stop) | empty / leftovers | 20 |
### Category B — Atomic Demos (160 episodes, eps 265~424)
Skill-focused demonstrations to strengthen foundational grip reliability and multi-object handling.
| sub-id | skill | total |
| :----: | -------------------------------- | ----: |
| B-1 | plate single pick-and-place | 50 |
| B-2 | cup single pick-and-place | 50 |
| B-3 | sequential two plates | 20 |
| B-4 | sequential 2~3 cups | 20 |
| B-5 | retry recovery | 20 |
Pick locations follow a **3×4 grid (12 positions, 7.5 cm spacing)** spanning the OMX reachable workspace; each cell is visited 4~5 times in B-1/B-2 and 3 times in A-1/A-2 for position diversity.
---
## Label boundary scheme
Multi-task episodes are segmented into per-action task ranges. Boundaries were auto-detected from gripper state events (`fully_close` → next `start_open`); missing boundaries in incomplete episodes were estimated from the median position percentile of complete episodes in the same scenario.
| sub-id | segment pattern |
| :----: | -------------------------------------------------------------- |
| A-1 | `cup(1) → home(2)` |
| A-2 | `plate(0) → home(2)` |
| A-3 | `plate(0) → plate(0) → home(2)` (per-plate segment restart) |
| A-4 | `cup(1) → cup(1) → home(2)` (per-cup segment restart) |
| A-5 | `cup(1) → plate(0) → home(2)` |
| A-6 | `cup(1) → cup(1) → plate(0) → home(2)` |
| A-7 | `home(2)` only |
| B-1 | `plate(0) → home(2)` |
| B-2 | `cup(1) → home(2)` |
| B-3 | `plate(0) → plate(0) → home(2)` |
| B-4 | `cup(1) → cup(1) → home(2)` (or 3 cups) |
| B-5 | `<obj> → <obj> → home(2)` (retry segments same task_index) |
---
## Repository layout
```
serving_ab/
├── data/chunk-000/file-000.parquet # all 219,877 frames concatenated
├── meta/
│ ├── info.json # codebase_version=v3.0, totals
│ ├── tasks.parquet # task_index → instruction
│ ├── tasks.jsonl # mirror of tasks.parquet
│ ├── modality.json # GR00T modality mapping (state/action/video/annotation)
│ ├── stats.json # aggregate stats (mean/std/min/max/q01/q99)
│ └── episodes/chunk-000/file-000.parquet # per-episode metadata + stats (107 cols)
└── videos/
├── observation.images.top/chunk-000/file-000.mp4 # ~924 MB
└── observation.images.wrist/chunk-000/file-000.mp4 # ~1.59 GB
```
---
## Companion datasets
| Repo | Format | Episodes | Notes |
| ------------------------------------------------------------------- | ------ | -------: | --------------------------- |
| [`jae0311/serving_a`](https://huggingface.co/datasets/jae0311/serving_a) | v3.0 | 265 | Category A only (long episodes) |
| [`jae0311/serving_b`](https://huggingface.co/datasets/jae0311/serving_b) | v2.1 | 160 | Category B only (atomic demos) |
---
## Recommended training schedule (GR00T N1.7)
| Stage | Data | max-steps | LR | Goal |
| :---: | -------------- | :-------: | :----: | ------------------------------------------------- |
| 1 | `serving_b` | 5,000 | 1e-4 | atomic pick-and-place reliability (90%+) |
| 2 | `serving_ab` | 25,000 | 5e-5 | long-episode performance from Stage 1 checkpoint |
- effective batch size: 32 (per_device_batch=8 × grad_accum=4)
- action horizon: 16
- color jitter: brightness 0.2, contrast 0.2, saturation 0.4, hue 0.08
---
## 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
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