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README.md

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+---
+license: apache-2.0
+task_categories:
+- robotics
+tags:
+- LeRobot
+- robotics
+- manipulation
+- sim
+- pick-and-place
+- pi0.5
+- libero
+- behavior-1k
+- omnigibson
+- franka
+size_categories:
+- 1K<n<10K
+pretty_name: SENTINEL sim pnp multitask, cuRobo-prior shortcut, n10
+---
+
+# sim-pnp-multitask-prior-n10-libero
+
+A 1,694-episode LeRobot v2.1 dataset of 13 single-object **pick-and-place** tasks in OmniGibson / BEHAVIOR-1K, collected automatically using a **cuRobo motion-planning shortcut** seeded from a real teleop grasp prior. Same 3-camera LIBERO schema we use for π0.5 sim SFT.
+
+This is the auto-collected sibling of [`IDEAS-Lab-Northwestern/sentinel-pnp-multitask`](https://huggingface.co/datasets/IDEAS-Lab-Northwestern/sentinel-pnp-multitask) (human teleop) — same task family, methodologically distinct (scripted phase-A grasp + closed-loop place).
+
+## Quick facts
+
+| | |
+|---|---|
+| Codebase version | LeRobot v2.1 |
+| Robot | Franka Panda (longfinger) |
+| Total episodes | 1,694 |
+| Total frames | 2,505,357 |
+| FPS | 30 |
+| Tasks | 13 (single-object pnp, "middle of the table" → "green goal") |
+| Cameras | 3 × 256×256 H.264 (`image_left`, `image_right`, `wrist_image`) |
+| State | 8D (EEF xyz + axis-angle rxyz + gripper L/R) |
+| Actions | 7D EEF-delta (`dpos_xyz`, `drot_xyz`) + gripper |
+| Chunks | 2 (chunk-000: eps 0–999, chunk-001: eps 1000–1693) |
+| Size on disk | ~7.7 GB |
+
+## Collection methodology
+
+Collected on a **vast.ai dual-RTX 4090** instance over ~18.5 h per GPU (~37 GPU-hours total), driven by the `phase_a_grasp_from_dataset` shortcut in [SENTINEL-Lite](https://github.com/666harrypeng/SENTINEL-Lite):
+
+1. **Phase A — grasp**: an example successful grasp is read out of a small **real-teleop LeRobot prior dataset** for each (task, seed) cell. **cuRobo** plans and executes the approach + close in OmniGibson.
+2. **Phase B — place**: closed-loop OSC EEF-delta controller (`action_normalize=False`, assisted grasping) drives the object to the green goal region.
+3. Per (task, seed) cell the pipeline keeps running until **10 successful episodes** are recorded (the "n10" in the dataset name). Cells with persistent failures are skipped.
+4. The two GPUs ran disjoint (task, seed) shards; their outputs were merged afterwards (episode indices and the global `index` column reindexed, `chunks_size=1000` re-shuffled).
+
+Driver logs and the merge script are preserved alongside the source captures on the collection box; the per-shard targets were 99 (task, seed) units done + 15 skipped per GPU (114 planned).
+
+## Tasks
+
+| `task_index` | Prompt |
+|---:|---|
+| 0 | pick up the teacup in the middle of the table and place it at the green goal |
+| 1 | pick up the mug in the middle of the table and place it at the green goal |
+| 2 | pick up the coffee cup in the middle of the table and place it at the green goal |
+| 3 | pick up the goblet in the middle of the table and place it at the green goal |
+| 4 | pick up the bowl in the middle of the table and place it at the green goal |
+| 5 | pick up the cocktail glass in the middle of the table and place it at the green goal |
+| 6 | pick up the chalice in the middle of the table and place it at the green goal |
+| 7 | pick up the decanter in the middle of the table and place it at the green goal |
+| 8 | pick up the saucepan in the middle of the table and place it at the green goal |
+| 9 | pick up the water glass in the middle of the table and place it at the green goal |
+| 10 | pick up the gravy boat in the middle of the table and place it at the green goal |
+| 11 | pick up the beaker in the middle of the table and place it at the green goal |
+| 12 | pick up the beer glass in the middle of the table and place it at the green goal |
+
+## File layout (LeRobot v2.1)
+
+```
+data/chunk-000/episode_000000.parquet … episode_000999.parquet
+data/chunk-001/episode_001000.parquet … episode_001693.parquet
+videos/chunk-{000,001}/{image_left,image_right,wrist_image}/episode_NNNNNN.mp4
+meta/info.json
+meta/tasks.jsonl
+meta/episodes.jsonl
+meta/episodes_stats.jsonl
+```
+
+## Loading
+
+```python
+from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
+ds = LeRobotDataset("IDEAS-Lab-Northwestern/sim-pnp-multitask-prior-n10-libero")
+print(len(ds), ds.features)
+sample = ds[0]  # frame 0 of episode 0
+```
+
+## Schema details
+
+```
+state  : float32 [8]  = (eef_x, eef_y, eef_z, axisangle_x, axisangle_y, axisangle_z, gripper_l, gripper_r)
+actions: float32 [7]  = (dpos_x, dpos_y, dpos_z, drot_x, drot_y, drot_z, gripper)
+image_left   : video 256×256×3 RGB, h264, 30fps
+image_right  : video 256×256×3 RGB, h264, 30fps
+wrist_image  : video 256×256×3 RGB, h264, 30fps
+```
+
+## Intended use
+
+LoRA fine-tuning of vision-language-action policies (π0.5, OpenVLA-style) on diverse single-object pnp prompts where the grasp prior is **scripted by cuRobo MP** rather than learned from a small set of human teleops. Pairs well with the human-teleop counterpart for ablations on data-collection methodology.
+
+## Sister datasets (same org)
+
+- [`sentinel-pnp-multitask`](https://huggingface.co/datasets/IDEAS-Lab-Northwestern/sentinel-pnp-multitask) — human teleop counterpart
+- [`sim-stack-flat-30-libero`](https://huggingface.co/datasets/IDEAS-Lab-Northwestern/sim-stack-flat-30-libero), [`sim-stack-same-30-libero`](https://huggingface.co/datasets/IDEAS-Lab-Northwestern/sim-stack-same-30-libero) — same schema, stack family
+- [`sim-dusty-transfer-30-libero`](https://huggingface.co/datasets/IDEAS-Lab-Northwestern/sim-dusty-transfer-30-libero), [`sim-lid-transport-food-30-libero`](https://huggingface.co/datasets/IDEAS-Lab-Northwestern/sim-lid-transport-food-30-libero) — same schema, other task families
+
+## License
+
+Apache-2.0. The underlying BEHAVIOR-1K assets are subject to their own [terms of use](https://behavior.stanford.edu/).

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