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Datasets:
Joocjun
/
GR1-Tabletop-NextState-300x24

Tasks:
Robotics
Modalities:
Tabular
Video
Formats:
parquet
Size:
1M - 10M
Tags:
LeRobot
GR00T
GR1
robocasa
simulation
manipulation
Libraries:
Datasets
Dask
Polars
License:
Dataset card Data Studio Files
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  1. README.md +132 -0
  2. meta/episodes.jsonl +0 -0
  3. meta/info.json +269 -0
  4. meta/modality.json +121 -0
  5. meta/tasks.jsonl +186 -0
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README.md ADDED
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+ ---
2
+ license: apache-2.0
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+ task_categories:
4
+ - robotics
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+ tags:
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+ - LeRobot
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+ - GR00T
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+ - GR1
9
+ - robocasa
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+ - simulation
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+ - manipulation
12
+ size_categories:
13
+ - 10K<n<100K
14
+ ---
15
+
16
+ # GR1 Tabletop Merged LeRobot Datasets
17
+
18
+ Merged and subsampled versions of the GR1 tabletop manipulation datasets from the [NVIDIA PhysicalAI-Robotics-GR00T-X-Embodiment-Sim](https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim) collection, formatted in **LeRobot v2.0** format.
19
+
20
+ ## Dataset Variants
21
+
22
+ | Variant | Demos/Task | Tasks | Total Episodes | Total Frames | Approx Size |
23
+ |---------|-----------|-------|----------------|--------------|-------------|
24
+ | `1000x24/` | 1000 | 24 folders, 186 unique tasks | 24,000 | 6,020,058 | ~40 GB |
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+ | `300x24/` | 300 | 24 folders, 186 unique tasks | 7,200 | 1,803,236 | ~12 GB |
26
+ | `100x24/` | 100 | 24 folders, 185 unique tasks | 2,400 | 602,846 | ~4 GB |
27
+
28
+ ## Source Dataset
29
+
30
+ The original per-task datasets were downloaded from:
31
+ **[nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim](https://huggingface.co/datasets/nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim)**
32
+
33
+ To download the original dataset:
34
+ ```bash
35
+ # Install huggingface_hub
36
+ pip install huggingface_hub
37
+
38
+ # Download specific task datasets
39
+ from huggingface_hub import snapshot_download
40
+ snapshot_download(
41
+ repo_id="nvidia/PhysicalAI-Robotics-GR00T-X-Embodiment-Sim",
42
+ repo_type="dataset",
43
+ allow_patterns="gr1_unified.PnP*", # or specific task patterns
44
+ local_dir="./original_data"
45
+ )
46
+ ```
47
+
48
+ The 24 source task folders used (each with 1000 demos):
49
+ - 6 **PnP** tasks: Bottle→Cabinet, Can→Drawer, Cup→Drawer, Milk→Microwave, Potato→Microwave, Wine→Cabinet
50
+ - 18 **PosttrainPnPNovel** tasks: Various object transfers between surfaces (Cuttingboard→{Basket,Cardboardbox,Pan,Pot,Tieredbasket}, Placemat→{Basket,Bowl,Plate,Tieredshelf}, Plate→{Bowl,Cardboardbox,Pan,Plate}, Tray→{Cardboardbox,Plate,Pot,Tieredbasket,Tieredshelf})
51
+
52
+ ## Processing
53
+
54
+ Each merged dataset was created by:
55
+
56
+ 1. **Subsampling**: Randomly sampling N episodes (with seed=42) from each of the 24 task folders
57
+ 2. **Merging**: Combining all sampled episodes into a single dataset with:
58
+ - Re-indexed episode IDs (0 to total-1)
59
+ - Globally re-indexed task IDs across all source folders
60
+ - Updated parquet files with corrected `episode_index`, `task_index`, and `index` columns
61
+ - Consolidated `meta/` files (`info.json`, `episodes.jsonl`, `tasks.jsonl`, `modality.json`)
62
+
63
+ ### Note on task counts
64
+
65
+ The `100x24` variant has 185 unique tasks instead of 186. This is because some task folders contain multiple task variants (e.g., the `PosttrainPnPNovelFromTrayToTieredbasket` folder has 10 different object variants like eggplant, tomato, etc.). The "eggplant" variant only appears in 58 out of 1000 source episodes, so when randomly sampling only 100 episodes, none of the eggplant episodes were selected. This is expected behavior with random subsampling.
66
+
67
+ ## Dataset Structure (LeRobot v2.0)
68
+
69
+ ```
70
+ <variant>/
71
+ ├── data/
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+ │ └── chunk-000/
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+ │ ├── episode_000000.parquet
74
+ │ ├── episode_000001.parquet
75
+ │ └── ...
76
+ ├── videos/
77
+ │ └── chunk-000/
78
+ │ └── observation.images.ego_view/
79
+ │ ├── episode_000000.mp4
80
+ │ ├── episode_000001.mp4
81
+ │ └── ...
82
+ └── meta/
83
+ ├── info.json
84
+ ├── episodes.jsonl
85
+ ├── tasks.jsonl
86
+ ├── modality.json
87
+ ├── stats.json
88
+ └── relative_stats.json
89
+ ```
90
+
91
+ ### Features
92
+
93
+ | Feature | Type | Shape |
94
+ |---------|------|-------|
95
+ | `observation.images.ego_view` | video (h264) | [256, 256, 3] @ 20fps |
96
+ | `observation.state` | float64 | [44] |
97
+ | `action` | float64 | [44] |
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+ | `timestamp` | float64 | [1] |
99
+ | `next.reward` | float64 | [1] |
100
+ | `next.done` | bool | [1] |
101
+ | `task_index` | int64 | [1] |
102
+ | `episode_index` | int64 | [1] |
103
+ | `annotation.human.coarse_action` | int64 | [1] |
104
+
105
+ Robot: **GR1ArmsAndWaistFourierHands** (44-DOF: arms, hands, legs, neck, waist)
106
+
107
+ ## Usage
108
+
109
+ ```python
110
+ # Download a specific variant
111
+ from huggingface_hub import snapshot_download
112
+
113
+ snapshot_download(
114
+ repo_id="Joocjun/GR1-Tabletop-Merged-LeRobot",
115
+ repo_type="dataset",
116
+ allow_patterns="100x24/**", # or "300x24/**" or "1000x24/**"
117
+ local_dir="./gr1_merged"
118
+ )
119
+ ```
120
+
121
+ ## License
122
+
123
+ Apache 2.0 (following the original NVIDIA dataset license)
124
+
125
+
126
+ ## Modification: Next-State Hand Actions
127
+
128
+ Hand action channels (left_hand indices 7-12, right_hand indices 29-34) have been replaced with next-state values:
129
+ - `action[t][7:13] = observation.state[t+1][7:13]`
130
+ - `action[t][29:35] = observation.state[t+1][29:35]`
131
+ - Last timestep repeats current state.
132
+ - `stats.json` removed so training auto-regenerates normalization stats.
meta/episodes.jsonl ADDED
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meta/info.json ADDED
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1
+ {
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+ "codebase_version": "v2.0",
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+ "robot_type": "GR1ArmsAndWaistFourierHands",
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+ "total_episodes": 7200,
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+ "total_frames": 1803236,
6
+ "total_tasks": 186,
7
+ "total_videos": 7200,
8
+ "total_chunks": 8,
9
+ "chunks_size": 1000,
10
+ "fps": 20.0,
11
+ "splits": {
12
+ "train": "0:7200"
13
+ },
14
+ "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
15
+ "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
16
+ "features": {
17
+ "observation.images.ego_view": {
18
+ "dtype": "video",
19
+ "shape": [
20
+ 256,
21
+ 256,
22
+ 3
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+ ],
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+ "names": [
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+ "height",
26
+ "width",
27
+ "channel"
28
+ ],
29
+ "video_info": {
30
+ "video.fps": 20.0,
31
+ "video.codec": "h264",
32
+ "video.pix_fmt": "yuv420p",
33
+ "video.is_depth_map": false,
34
+ "has_audio": false
35
+ }
36
+ },
37
+ "observation.state": {
38
+ "dtype": "float32",
39
+ "shape": [
40
+ 44
41
+ ],
42
+ "names": [
43
+ "l_shoulder_pitch",
44
+ "l_shoulder_roll",
45
+ "l_shoulder_yaw",
46
+ "l_elbow_pitch",
47
+ "l_wrist_yaw",
48
+ "l_wrist_roll",
49
+ "l_wrist_pitch",
50
+ "L_pinky_proximal_joint",
51
+ "L_ring_proximal_joint",
52
+ "L_middle_proximal_joint",
53
+ "L_index_proximal_joint",
54
+ "L_thumb_proximal_pitch_joint",
55
+ "L_thumb_proximal_yaw_joint",
56
+ "l_leg_hip_roll",
57
+ "l_leg_hip_yaw",
58
+ "l_leg_hip_pitch",
59
+ "l_leg_knee_pitch",
60
+ "l_leg_ankle_pitch",
61
+ "l_leg_ankle_roll",
62
+ "head_yaw",
63
+ "head_roll",
64
+ "head_pitch",
65
+ "r_shoulder_pitch",
66
+ "r_shoulder_roll",
67
+ "r_shoulder_yaw",
68
+ "r_elbow_pitch",
69
+ "r_wrist_yaw",
70
+ "r_wrist_roll",
71
+ "r_wrist_pitch",
72
+ "R_pinky_proximal_joint",
73
+ "R_ring_proximal_joint",
74
+ "R_middle_proximal_joint",
75
+ "R_index_proximal_joint",
76
+ "R_thumb_proximal_pitch_joint",
77
+ "R_thumb_proximal_yaw_joint",
78
+ "r_leg_hip_roll",
79
+ "r_leg_hip_yaw",
80
+ "r_leg_hip_pitch",
81
+ "r_leg_knee_pitch",
82
+ "r_leg_ankle_pitch",
83
+ "r_leg_ankle_roll",
84
+ "torso_waist_yaw",
85
+ "torso_waist_pitch",
86
+ "torso_waist_roll"
87
+ ]
88
+ },
89
+ "action": {
90
+ "dtype": "float32",
91
+ "shape": [
92
+ 44
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+ ],
94
+ "names": [
95
+ "l_shoulder_pitch",
96
+ "l_shoulder_roll",
97
+ "l_shoulder_yaw",
98
+ "l_elbow_pitch",
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+ "l_wrist_yaw",
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+ "l_wrist_roll",
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+ "l_wrist_pitch",
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+ "L_pinky_proximal_joint",
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+ "L_ring_proximal_joint",
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+ "L_middle_proximal_joint",
105
+ "L_index_proximal_joint",
106
+ "L_thumb_proximal_pitch_joint",
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+ "L_thumb_proximal_yaw_joint",
108
+ "l_leg_hip_roll",
109
+ "l_leg_hip_yaw",
110
+ "l_leg_hip_pitch",
111
+ "l_leg_knee_pitch",
112
+ "l_leg_ankle_pitch",
113
+ "l_leg_ankle_roll",
114
+ "head_yaw",
115
+ "head_roll",
116
+ "head_pitch",
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+ "r_shoulder_pitch",
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+ "r_shoulder_roll",
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+ "r_shoulder_yaw",
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+ "r_elbow_pitch",
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+ "r_wrist_yaw",
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+ "r_wrist_roll",
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+ "r_wrist_pitch",
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+ "R_pinky_proximal_joint",
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+ "R_ring_proximal_joint",
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+ "R_middle_proximal_joint",
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+ "R_index_proximal_joint",
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+ "R_thumb_proximal_pitch_joint",
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+ "R_thumb_proximal_yaw_joint",
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+ "r_leg_hip_roll",
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+ "r_leg_hip_yaw",
132
+ "r_leg_hip_pitch",
133
+ "r_leg_knee_pitch",
134
+ "r_leg_ankle_pitch",
135
+ "r_leg_ankle_roll",
136
+ "torso_waist_yaw",
137
+ "torso_waist_pitch",
138
+ "torso_waist_roll"
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+ ]
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+ },
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+ "timestamp": {
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+ "dtype": "float64",
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+ "shape": [
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+ ]
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+ },
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+ "next.reward": {
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+ }
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+ }
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+ }
meta/modality.json ADDED
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1
+ {
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+ "state": {
3
+ "left_arm": {
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+ "original_key": "observation.state",
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+ "start": 0,
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+ "end": 7
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+ },
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+ "left_hand": {
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+ "original_key": "observation.state",
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+ "start": 7,
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+ "end": 13
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+ },
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+ "left_leg": {
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+ "original_key": "observation.state",
15
+ "start": 13,
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+ "end": 19
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+ },
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+ "neck": {
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+ "original_key": "observation.state",
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+ "start": 19,
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+ "end": 22
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+ },
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+ "right_arm": {
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+ "end": 29
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+ "right_hand": {
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+ "end": 35
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meta/tasks.jsonl ADDED
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