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- Original source card
- license: cc-by-4.0
task_categories:
- robotics
- video-classification
tags:
- robotics
- manipulation
- sim-to-real
- cosmos-transfer
- isaac-sim
- gr1-humanoid
- pick-and-place
pretty_name: GR1 Manipulation - Isaac Sim Rendered (RGB/Depth/Seg)
size_categories:
- 10K<n<100K
- Dataset Description
- Dataset Structure
- Tasks
- Recording Settings
- Source Data
- Intended Use
- License
gr1-isaacsim
Mirror of the exact bmcore v24 holdout subset. Source: khang123452/GR1-Manipulation-IsaacSim-Rendered.
All 44 task-relative paths match public RGB episodes. Exclude depth and segmentation; uploader basename collisions require preserved unique filenames.
Contains 44 video files. Benchmark label: real (classical rendering). This mirror repackages the media; it does not grant additional rights.
Source revision reviewed: 77a04466eb4cadc3061056c68f8f33e842df7a81.
Original source card
license: cc-by-4.0 task_categories: - robotics - video-classification tags: - robotics - manipulation - sim-to-real - cosmos-transfer - isaac-sim - gr1-humanoid - pick-and-place pretty_name: GR1 Manipulation - Isaac Sim Rendered (RGB/Depth/Seg) size_categories: - 10K<n<100K
GR1 Manipulation β Isaac Sim Rendered Dataset
Dataset Description
Multi-modal rendered dataset of NVIDIA GR1 humanoid robot performing tabletop manipulation tasks in Isaac Sim. Each episode is rendered as 3 synchronized MP4 videos:
- RGB β ray-traced color video
- Depth β normalized depth map (grayscale, 0β10m range)
- Segmentation β semantic segmentation with per-object class coloring
This dataset is designed as input for NVIDIA Cosmos Transfer 2.5 to generate photorealistic sim-to-real augmented training data for robot learning.
Dataset Structure
{task_name}/
episode_NNNN_rgb.mp4 # 1280x720, 20fps, RayTracedLighting
episode_NNNN_depth.mp4 # 1280x720, 20fps, normalized depth
episode_NNNN_seg.mp4 # 1280x720, 20fps, semantic segmentation
Tasks
| # | Task Name | Episodes | Frames/Episode |
|---|---|---|---|
| 1 | PnPBottleToCabinetClose |
458 | ~120β400 |
| 2 | PnPCanToDrawerClose |
2 | ~120β400 |
| 3 | PnPCupToDrawerClose |
2 | ~120β400 |
| 4 | PnPMilkToMicrowaveClose |
2 | ~120β400 |
| 5 | PnPPotatoToMicrowaveClose |
2 | ~120β400 |
| 6 | PnPWineToCabinetClose |
2 | ~120β400 |
| 7 | PosttrainPnPNovelFromCuttingboardToBasketSplitA |
2 | ~120β400 |
| 8 | PosttrainPnPNovelFromCuttingboardToCardboardboxSplitA |
2 | ~120β400 |
| 9 | PosttrainPnPNovelFromCuttingboardToPanSplitA |
2 | ~120β400 |
| 10 | PosttrainPnPNovelFromCuttingboardToPotSplitA |
2 | ~120β400 |
| 11 | PosttrainPnPNovelFromCuttingboardToTieredbasketSplitA |
2 | ~120β400 |
| 12 | PosttrainPnPNovelFromPlacematToBasketSplitA |
2 | ~120β400 |
| 13 | PosttrainPnPNovelFromPlacematToBowlSplitA |
1 | ~120β400 |
| 14 | PosttrainPnPNovelFromPlacematToPlateSplitA |
2 | ~120β400 |
| 15 | PosttrainPnPNovelFromPlacematToTieredshelfSplitA |
2 | ~120β400 |
| 16 | PosttrainPnPNovelFromPlateToBowlSplitA |
2 | ~120β400 |
| 17 | PosttrainPnPNovelFromPlateToCardboardboxSplitA |
1 | ~120β400 |
| 18 | PosttrainPnPNovelFromPlateToPanSplitA |
2 | ~120β400 |
| 19 | PosttrainPnPNovelFromPlateToPlateSplitA |
1 | ~120β400 |
| 20 | PosttrainPnPNovelFromTrayToCardboardboxSplitA |
2 | ~120β400 |
| 21 | PosttrainPnPNovelFromTrayToPlateSplitA |
2 | ~120β400 |
| 22 | PosttrainPnPNovelFromTrayToPotSplitA |
2 | ~120β400 |
| 23 | PosttrainPnPNovelFromTrayToTieredbasketSplitA |
1 | ~120β400 |
| 24 | PosttrainPnPNovelFromTrayToTieredshelfSplitA |
2 | ~120β400 |
Recording Settings
| Setting | Value |
|---|---|
| Camera | egoview (1st-person, attached to robot0_head_pitch) |
| FOV | 90Β° vertical |
| Resolution | 1280Γ720 |
| FPS | 20 |
| Renderer | Isaac Sim RayTracedLighting, SPP=32 |
| Lighting | Dome light, intensity=1500 |
| USD Export | robosuite exporter, geomgroup=[0,1,0,0,0,0] (visual meshes only) |
Source Data
- Robot: NVIDIA GR1 humanoid (from gr00trobosuite)
- Tasks: RoboCasa GR1 tabletop pick-and-place tasks
- Simulation: MuJoCo β USD β Isaac Sim Replicator pipeline
- Original trajectories: 1000 episodes per task in HDF5 format
Intended Use
Input for Cosmos Transfer 2.5 world generation model to produce photorealistic augmented manipulation videos for robot policy training (sim-to-real transfer).
License
CC-BY-4.0
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