Datasets:

DynamicIntelligence
/

humanoid-robots-training-dataset

license: cc-by-nc-4.0
task_categories:
  - robotics
tags:
  - lerobot
  - hand-pose
  - rgb-d
  - humanoid
  - manipulation
  - 6dof
  - mediapipe
  - egocentric
  - motion-semantics
size_categories:
  - 10K<n<100K
language:
  - en
pretty_name: Dynamic Intelligence - Egocentric Human Motion Annotation Dataset

Dynamic Intelligence - Egocentric Human Motion Annotation Dataset

RGB-D hand manipulation dataset captured with iPhone 13 TrueDepth sensor for humanoid robot training. Includes 6-DoF hand pose trajectories, synchronized video, and semantic motion annotations.

Dataset Overview

Metric	Value
Episodes	147
Total Frames	~72,000
FPS	30
Tasks	12 manipulation tasks
Total Duration	~40 minutes
Avg Episode Length	~16.3 seconds

Task Distribution

Task	Description	Episodes	Count
1	Fold the t-shirt on the bed.	0–7	8
2	Pick up the two items on the floor and put them on the bed.	8–17	10
3	Fold the jeans on the bed.	18–27	10
4	Fold the underwear on the table.	28–37	10
5	Put the pillow in its correct place.	38–47	10
6	Place the tableware on the kitchen counter.	48–57	10
7	Get out of the room and close the door behind you.	58–66	9
8	Put the sandals in the right place.	67–76	10
9	Put the cleaning cloth in the laundry basket.	77–86	10
10	Screw the cap back on the bottle.	87–96	10
11	Tuck the chairs into the table.	97–127	31
12	Put the dishes in the sink.	128–146	19

Repository Structure

humanoid-robots-training-dataset/
│
├── data/
│   ├── chunk-000/                    # Parquet files (episodes 0-99)
│   │   ├── episode_000000.parquet
│   │   └── ...
│   └── chunk-001/                    # Parquet files (episodes 100-146)
│       ├── episode_000100.parquet
│       └── ...
│
├── videos/
│   ├── chunk-000/rgb/                # MP4 videos (episodes 0-99)
│   │   ├── episode_000000.mp4
│   │   └── ...
│   └── chunk-001/rgb/                # MP4 videos (episodes 100-146)
│       ├── episode_000100.mp4
│       └── ...
│
├── meta/                             # Metadata & Annotations
│   ├── info.json                     # Dataset configuration (LeRobot format)
│   ├── stats.json                    # Feature min/max/mean/std statistics
│   ├── events.json                   # Disturbance & recovery annotations
│   └── annotations_motion_v1_frames.json  # Motion semantic annotations
│
└── README.md

Data Schema

Parquet Columns (per frame)

Column	Type	Description
`episode_index`	int64	Episode number (0–146)
`frame_index`	int64	Frame within episode
`timestamp`	float64	Time in seconds
`language_instruction`	string	Task description
`observation.camera_pose`	float[6]	Camera 6-DoF (x, y, z, roll, pitch, yaw)
`observation.left_hand`	float[9]	Left hand keypoints (wrist + thumb + index)
`observation.right_hand`	float[9]	Right hand keypoints (wrist + index + middle)
`action.camera_delta`	float[6]	Camera delta 6-DoF
`action.left_hand_delta`	float[9]	Left hand delta keypoints
`action.right_hand_delta`	float[9]	Right hand delta keypoints
`rgb`	video	Synchronized RGB video frame

6-DoF Format

Coordinate System:

Origin: Camera (iPhone TrueDepth)
X: Right (positive)
Y: Down (positive)
Z: Forward (positive, into scene)

Motion Semantics Annotations

File: meta/annotations_motion_v1_frames.json

Coarse temporal segmentation with motion intent, phase, and error labels.

Motion Types

Events Metadata

File: meta/events.json

Disturbances and recovery actions for select episodes.

Disturbance Types

Type	Description
`OCCLUSION`	Hand temporarily blocked from camera
`TARGET_MOVED`	Object shifted unexpectedly
`SLIP`	Object slipped during grasp
`COLLISION`	Unintended contact
`DEPTH_DROPOUT`	Depth sensor lost valid readings

Recovery Actions

Action	Description
`REGRASP`	Release and re-acquire object
`REACH_ADJUST`	Modify approach trajectory
`ABORT`	Stop current action
`REPLAN`	Compute new action sequence

Usage

With LeRobot

from lerobot.common.datasets.lerobot_dataset import LeRobotDataset

dataset = LeRobotDataset("DynamicIntelligence/humanoid-robots-training-dataset")

episode = dataset[0]
state = episode["observation.camera_pose"]    # [6] camera 6-DoF
rgb = episode["observation.images.rgb"]       # Video frame
task = episode["language_instruction"]        # "Fold the t-shirt on the bed."

Direct Parquet Access

import pandas as pd
from huggingface_hub import hf_hub_download

path = hf_hub_download(
    repo_id="DynamicIntelligence/humanoid-robots-training-dataset",
    filename="data/chunk-000/episode_000000.parquet",
    repo_type="dataset"
)
df = pd.read_parquet(path)
print(df["language_instruction"].iloc[0])  # "Fold the t-shirt on the bed."
print(f"Frames: {len(df)}")

Citation

If you use this dataset in your research, please cite:

@dataset{dynamic_intelligence_2025,
  author = {Dynamic Intelligence},
  title = {Egocentric Human Motion Annotation Dataset},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/DynamicIntelligence/humanoid-robots-training-dataset}
}

Contact

Email: shayan@dynamicintelligence.company Organization: Dynamic Intelligence

Hand Landmark Reference

Each hand has tracked joints. The observation.left_hand and observation.right_hand contain 3D keypoints for key finger joints.

Visualizer

Explore the dataset interactively: DI Hand Pose Sample Dataset Viewer