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Datasets:
basematrix
/
ego-desktop-demo

Tasks:
Robotics
Modalities:
Tabular
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Formats:
parquet
Size:
1K - 10K
Tags:
lerobot
embodied-ai
ego-centric
hand-tracking
manipulation
binocular
Libraries:
Datasets
pandas
Polars
License:
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  1. README.md +147 -0
  2. data/chunk-000/file-000.parquet +3 -0
  3. meta/episodes/chunk-000/file-000.parquet +3 -0
  4. meta/info.json +256 -0
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  6. meta/tasks.parquet +3 -0
  7. videos/observation.images.ego_left/chunk-000/file-000.mp4 +3 -0
  8. videos/observation.images.ego_right/chunk-000/file-000.mp4 +3 -0
  9. videos/observation.images.exo_iphone/chunk-000/file-000.mp4 +3 -0
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1
+ ---
2
+ license: cc-by-nc-4.0
3
+ task_categories:
4
+ - robotics
5
+ tags:
6
+ - lerobot
7
+ - embodied-ai
8
+ - ego-centric
9
+ - hand-tracking
10
+ - manipulation
11
+ - binocular
12
+ - multi-view
13
+ - retargeting
14
+ configs:
15
+ - config_name: default
16
+ data_files:
17
+ - split: train
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+ path: data/chunk-*/file-*.parquet
19
+ ---
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+
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+ # BaseMatrix EGO Desktop Demo
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+
23
+ Human hand manipulation demonstrations captured with binocular egocentric cameras + exocentric view, processed through a 6-stage pipeline into structured observations for robot learning.
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+
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+ **This is a preview dataset.** Full-scale datasets with hundreds of episodes are available upon request — contact info@basematrix.ai.
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+
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+ ## Quick Start
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+
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+ ```python
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+ from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
31
+
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+ dataset = LeRobotDataset("basematrix/ego-desktop-demo")
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+ print(dataset)
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+ print(dataset[0].keys())
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+ ```
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+
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+ ## Dataset Summary
38
+
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+ | Property | Value |
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+ |----------|-------|
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+ | Format | LeRobot v3.0 |
42
+ | Episodes | 1 |
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+ | Frames | 2,114 |
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+ | Duration | ~70 seconds |
45
+ | FPS | 30 |
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+ | Scene | Desktop object manipulation |
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+ | Capture device | Orbbec EGO binocular (stereo fisheye, 1600x1300) + iPhone EXO (1920x1080) |
48
+ | Time sync | Hardware PTS (< 40 us L-R stereo) + audio beep sync (< 3.3 ms EXO) |
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+
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+ ## Features (24 channels)
51
+
52
+ ### Observation — Vision (3 video streams)
53
+
54
+ | Feature | Shape | Description |
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+ |---------|-------|-------------|
56
+ | `observation.images.ego_left` | (3, 1300, 1600) | Left stereo fisheye, 30fps H.264 |
57
+ | `observation.images.ego_right` | (3, 1300, 1600) | Right stereo fisheye, 30fps H.264 |
58
+ | `observation.images.exo_iphone` | (3, 1080, 1920) | Exocentric iPhone view, 30fps |
59
+
60
+ ### Observation — State (11 channels)
61
+
62
+ | Feature | Shape | Description |
63
+ |---------|-------|-------------|
64
+ | `observation.state.camera_pose` | (7,) | ORB-SLAM3 stereo-inertial 6DoF: tx, ty, tz, qx, qy, qz, qw |
65
+ | `observation.state.left_wrist` | (3,) | Left wrist 3D position in world frame (meters) |
66
+ | `observation.state.right_wrist` | (3,) | Right wrist 3D position in world frame (meters) |
67
+ | `observation.state.left_keypoints_3d` | (63,) | Left hand 21 joints x 3 coords (MANO topology, world frame) |
68
+ | `observation.state.right_keypoints_3d` | (63,) | Right hand 21 joints x 3 coords (MANO topology, world frame) |
69
+ | `observation.state.left_contact` | (1,) | Left hand contact state (0/1) |
70
+ | `observation.state.right_contact` | (1,) | Right hand contact state (0/1) |
71
+ | `observation.state.left_force` | (3,) | Reserved — force/torque (zeros, sensor not connected) |
72
+ | `observation.state.right_force` | (3,) | Reserved — force/torque (zeros, sensor not connected) |
73
+ | `observation.state.left_tactile` | (48,) | Reserved — tactile array (zeros, sensor not connected) |
74
+ | `observation.state.right_tactile` | (48,) | Reserved — tactile array (zeros, sensor not connected) |
75
+ | `observation.state.gripper_force` | (2,) | Reserved — gripper force (zeros, sensor not connected) |
76
+
77
+ ### Action (4 channels)
78
+
79
+ | Feature | Shape | Description |
80
+ |---------|-------|-------------|
81
+ | `action.left_wrist_delta` | (3,) | Left wrist displacement (dx, dy, dz in meters) |
82
+ | `action.right_wrist_delta` | (3,) | Right wrist displacement (dx, dy, dz in meters) |
83
+ | `action.left_grasp` | (1,) | Left hand grasp signal (0 = open, 1 = grasping) |
84
+ | `action.right_grasp` | (1,) | Right hand grasp signal (0 = open, 1 = grasping) |
85
+
86
+ ## Processing Pipeline
87
+
88
+ Each recording goes through 6 automated stages:
89
+
90
+ | Stage | Tool | Output |
91
+ |-------|------|--------|
92
+ | L0 | Audio beep detection (1kHz) | Multi-camera time alignment |
93
+ | L1 | Nearest-neighbor PTS matching | Stereo frame pairs + EXO sync |
94
+ | L2 | ORB-SLAM3 (stereo-inertial) | 6DoF camera trajectory |
95
+ | L3 | Hands23 + WiLoR + HaWoR | Contact detection, 3D hand skeleton, world-frame wrist trajectory |
96
+ | L4 | GPT-4.1 Vision | Semantic annotation (objects, phases, sub-activities) |
97
+ | L5 | Cross-layer verification (24 checks) | Quality score + dataset card |
98
+ | L6 | LeRobot v3.0 packaging | This dataset |
99
+
100
+ ### Hand Tracking Stack
101
+
102
+ Three complementary models provide different levels of hand understanding:
103
+
104
+ - **Hands23 (HOI-DETR)**: Hand-object interaction detection — bounding boxes, contact state, grasp classification
105
+ - **WiLoR-mini**: Single-frame 3D hand pose — 21 MANO keypoints per hand
106
+ - **HaWoR**: Temporal hand-in-world reconstruction — globally consistent wrist trajectories in ORB-SLAM3's world coordinate frame
107
+
108
+ ## Retargeting
109
+
110
+ This dataset provides **human-frame observations** (hand skeleton + wrist trajectory). To use with a specific robot embodiment:
111
+
112
+ - **For parallel-jaw grippers** (Franka, ALOHA, UR5): Map `left/right_wrist` + `left/right_grasp` to end-effector pose + gripper open/close via inverse kinematics
113
+ - **For dexterous hands** (LEAP, Allegro, Shadow): Map `left/right_keypoints_3d` (21 MANO joints) to robot finger joint angles via fingertip-position optimization
114
+
115
+ The `action.{left,right}_wrist_delta` features can serve as a starting point for action-space definition, though most VLA pipelines will want to define actions in robot joint space after retargeting.
116
+
117
+ ## Coordinate System
118
+
119
+ - **World frame**: ORB-SLAM3 stereo-inertial SLAM coordinate system. Origin at first tracked frame. Right-handed, Y-up.
120
+ - **Hand keypoints**: Relative to wrist (wrist = origin), following MANO joint topology (0=wrist, 1-4=thumb, 5-8=index, 9-12=middle, 13-16=ring, 17-20=pinky).
121
+ - **Camera pose**: Position (tx, ty, tz) in meters + orientation as unit quaternion (qx, qy, qz, qw).
122
+
123
+ ## Capture Hardware
124
+
125
+ - **Head-mounted**: Orbbec Femto Mega (EGO configuration) — 140g, dual global-shutter fisheye, 1000Hz IMU, 120mm stereo baseline, H.264 encoding
126
+ - **Exocentric**: iPhone — standard wide lens, 1080p 30fps, audio beep sync
127
+
128
+ ## Citation
129
+
130
+ ```bibtex
131
+ @misc{basematrix2026ego,
132
+ title={BaseMatrix EGO Desktop Demo: Binocular Egocentric Hand Manipulation Dataset},
133
+ author={BaseMatrix},
134
+ year={2026},
135
+ url={https://huggingface.co/datasets/basematrix/ego-desktop-demo}
136
+ }
137
+ ```
138
+
139
+ ## License
140
+
141
+ CC BY-NC 4.0 — free for research and evaluation. Contact info@basematrix.ai for commercial licensing.
142
+
143
+ ## Contact
144
+
145
+ - Website: [basematrix.ai](https://basematrix.ai)
146
+ - Email: info@basematrix.ai
147
+ - Pipeline demo: [basematrix.ai/pipeline-showcase](https://basematrix.ai/pipeline-showcase/)
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