Datasets:
metadata
pretty_name: InternData-A1
size_categories:
- n>1T
task_categories:
- other
- robotics
language:
- en
tags:
- Embodied-AI
- Robotic manipulation
extra_gated_prompt: >-
### InternData-A1 COMMUNITY LICENSE AGREEMENT
InternData-A1 Release Date: July 26, 2025. All the data and code within this
repo are under [CC BY-NC-SA
4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).
extra_gated_fields:
First Name: text
Last Name: text
Email: text
Country: country
Affiliation: text
Phone: text
Job title:
type: select
options:
- Student
- Research Graduate
- AI researcher
- AI developer/engineer
- Reporter
- Other
Research interest: text
geo: ip_location
By clicking Submit below I accept the terms of the license and acknowledge that the information I provide will be collected stored processed and shared in accordance with the InternData Privacy Policy: checkbox
extra_gated_description: >-
The information you provide will be collected, stored, processed and shared in
accordance with the InternData Privacy Policy.
extra_gated_button_content: Submit
InternData-A1
InternData-A1 is a hybrid synthetic-real manipulation dataset containing over 630k trajectories and 7,433 hours across 4 embodiments, 18 skills, 70 tasks, and 227 scenes, covering rigid, articulated, deformable, and fluid-object manipulation.
📢 News
- Supplementary information: We have supplemented the updated dataset with camera intrinsics, extrinsics, end-effector poses, and TCP poses. For lerobot v2.1, the directory is sim_updated. For lerobot v3.0, the directory is sim_updated_lerobotv30.
🔑 Key Features
- Heterogeneous multi-robot platforms: ARX Lift-2, AgileX Split Aloha, A2D, Franka
- Hybrid synthetic-real manipulation demonstrations with task-level digital twins, containing four task categories:
- Articulation tasks
- Basic tasks
- Long-horizon tasks
- Pick and place tasks
- Diverse scenarios include:
- Moving Object Manipulation in Conveyor Belt Scenarios
- Rigid, articulated, deformable, and fluid-object manipulation
- Multi-robot / multi-arm collaboration
- Human-robot interaction
📋 Table of Contents
Get started 🔥
Download the Dataset
To download the full dataset, you can use the following code. If you encounter any issues, please refer to the official Hugging Face documentation.
# Make sure you have git-lfs installed (https://git-lfs.com)
git lfs install
# When prompted for a password, use an access token with write permissions.
# Generate one from your settings: https://huggingface.co/settings/tokens
git clone https://huggingface.co/datasets/InternRobotics/InternData-A1
# If you want to clone without large files - just their pointers
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/InternRobotics/InternData-A1
Dataset Structure
Folder hierarchy
data
├── sim
│ ├── articulation_tasks
│ │ └── ...
│ ├── basic_tasks
│ │ └── ...
│ ├── long_horizon_tasks # category
│ │ ├── franka # robot
│ │ │ └── ...
│ │ ├── lift2
│ │ │ ├── sort_the_rubbish # task
│ │ │ │ ├── data
│ │ │ │ │ ├── chunk-000
│ │ │ │ │ │ ├── episode_000000.parquet
│ │ │ │ │ │ ├── episode_000001.parquet
│ │ │ │ │ │ ├── episode_000002.parquet
│ │ │ │ │ │ ├── ...
│ │ │ │ │ ├── chunk-001
│ │ │ │ │ │ ├── ...
│ │ │ │ │ ├── ...
│ │ │ │ ├── meta
│ │ │ │ │ ├── episodes.jsonl
│ │ │ │ │ ├── episodes_stats.jsonl
│ │ │ │ │ ├── info.json
│ │ │ │ │ ├── modality.json
│ │ │ │ │ ├── stats.json
│ │ │ │ │ ├── tasks.jsonl
│ │ │ │ ├── videos
│ │ │ │ │ ├── chunk-000
│ │ │ │ │ │ ├── images.rgb.head
│ │ │ │ │ │ │ ├── episode_000000.mp4
│ │ │ │ │ │ │ ├── episode_000001.mp4
│ │ │ │ │ │ │ ├── ...
│ │ │ │ │ │ ├── ...
│ │ │ │ │ ├── chunk-001
│ │ │ │ │ │ ├── ...
│ │ │ │ │ ├── ...
│ │ │ ├──...
│ │ ├── split_aloha
│ │ │ └── ...
│ │ ├── ...
│ ├── pick_and_place_tasks
│ │ └── ...
│ ├── ...
├── real
│ ├── ...
This subdataset(such as sort_the_rubbish) was created using LeRobot (dataset v2.1).
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "piper",
"total_episodes": 1544,
"total_frames": 1477285,
"total_tasks": 1,
"total_videos": 4632,
"total_chunks": 2,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:1544"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
"features": {
"images.rgb.head": {
"dtype": "video",
"shape": [
360,
640,
3
],
"names": [
"height",
"width",
"channel"
],
"info": {
"video.height": 360,
"video.width": 640,
"video.codec": "av1",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 30,
"video.channels": 3,
"has_audio": false
}
},
"images.rgb.hand_left": {
"dtype": "video",
"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"channel"
],
"info": {
"video.height": 480,
"video.width": 640,
"video.codec": "av1",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 30,
"video.channels": 3,
"has_audio": false
}
},
"images.rgb.hand_right": {
"dtype": "video",
"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"channel"
],
"info": {
"video.height": 480,
"video.width": 640,
"video.codec": "av1",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 30,
"video.channels": 3,
"has_audio": false
}
},
"head_camera_intrinsics": {
"dtype": "float32",
"shape": [
4
],
"names": [
"fx",
"fy",
"cx",
"cy"
]
},
"hand_left_camera_intrinsics": {
"dtype": "float32",
"shape": [
4
],
"names": [
"fx",
"fy",
"cx",
"cy"
]
},
"hand_right_camera_intrinsics": {
"dtype": "float32",
"shape": [
4
],
"names": [
"fx",
"fy",
"cx",
"cy"
]
},
"head_camera_to_robot_extrinsics": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"hand_left_camera_to_robot_extrinsics": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"hand_right_camera_to_robot_extrinsics": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"states.left_joint.position": {
"dtype": "float32",
"shape": [
6
],
"names": [
"left_joint_0",
"left_joint_1",
"left_joint_2",
"left_joint_3",
"left_joint_4",
"left_joint_5"
]
},
"states.left_gripper.position": {
"dtype": "float32",
"shape": [
1
],
"names": [
"left_gripper_0"
]
},
"states.left_ee_to_left_armbase_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"states.left_ee_to_robot_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"states.left_tcp_to_left_armbase_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"states.left_tcp_to_robot_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"states.right_joint.position": {
"dtype": "float32",
"shape": [
6
],
"names": [
"right_joint_0",
"right_joint_1",
"right_joint_2",
"right_joint_3",
"right_joint_4",
"right_joint_5"
]
},
"states.right_gripper.position": {
"dtype": "float32",
"shape": [
1
],
"names": [
"right_gripper_0"
]
},
"states.right_ee_to_right_armbase_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"states.right_ee_to_robot_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"states.right_tcp_to_right_armbase_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"states.right_tcp_to_robot_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"states.robot_to_env_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"actions.left_joint.position": {
"dtype": "float32",
"shape": [
6
],
"names": [
"left_joint_0",
"left_joint_1",
"left_joint_2",
"left_joint_3",
"left_joint_4",
"left_joint_5"
]
},
"actions.left_gripper.position": {
"dtype": "float32",
"shape": [
1
],
"names": [
"left_gripper_0"
]
},
"actions.left_ee_to_left_armbase_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"actions.left_ee_to_robot_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"actions.left_tcp_to_left_armbase_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"actions.left_tcp_to_robot_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"actions.right_joint.position": {
"dtype": "float32",
"shape": [
6
],
"names": [
"right_joint_0",
"right_joint_1",
"right_joint_2",
"right_joint_3",
"right_joint_4",
"right_joint_5"
]
},
"actions.right_gripper.position": {
"dtype": "float32",
"shape": [
1
],
"names": [
"right_gripper_0"
]
},
"actions.right_ee_to_right_armbase_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"actions.right_ee_to_robot_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"actions.right_tcp_to_right_armbase_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"actions.right_tcp_to_robot_pose": {
"dtype": "float32",
"shape": [
7
],
"names": [
"position.x",
"position.y",
"position.z",
"quaternion.w",
"quaternion.x",
"quaternion.y",
"quaternion.z"
]
},
"master_actions.left_joint.position": {
"dtype": "float32",
"shape": [
6
],
"names": [
"left_joint_0",
"left_joint_1",
"left_joint_2",
"left_joint_3",
"left_joint_4",
"left_joint_5"
]
},
"master_actions.left_gripper.position": {
"dtype": "float32",
"shape": [
1
],
"names": [
"left_gripper_0"
]
},
"master_actions.left_gripper.openness": {
"dtype": "float32",
"shape": [
1
],
"names": [
"left_gripper_0"
]
},
"master_actions.right_joint.position": {
"dtype": "float32",
"shape": [
6
],
"names": [
"right_joint_0",
"right_joint_1",
"right_joint_2",
"right_joint_3",
"right_joint_4",
"right_joint_5"
]
},
"master_actions.right_gripper.position": {
"dtype": "float32",
"shape": [
1
],
"names": [
"right_gripper_0"
]
},
"master_actions.right_gripper.openness": {
"dtype": "float32",
"shape": [
1
],
"names": [
"right_gripper_0"
]
},
"timestamp": {
"dtype": "float32",
"shape": [
1
],
"names": null
},
"frame_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"episode_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"task_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
}
}
}
key format in features
Select appropriate keys for features based on characteristics such as ontology, single-arm or bimanual-arm, etc.
|-- images
|-- rgb
|-- head
|-- hand_left
|-- hand_right
|-- states
|-- left_joint
|-- position
|-- right_joint
|-- position
|-- left_gripper
|-- position
|-- right_gripper
|-- position
|-- actions
|-- left_joint
|-- position
|-- right_joint
|-- position
|-- left_gripper
|-- position
|-- right_gripper
|-- position
📅 TODO List
- [2025.11] Released: 632k simulation pretraining data (over 7433 hours). The directory is sim.
- [2026.01] Released: 550k simulation pretraining data with full annotations of camera intrinsics, extrinsics, ee pose and tcp pose. For lerobot v2.1, the directory is sim_updated. For lerobot v3.0, the directory is sim_updated_lerobotv30.
- To be released: real-world post-training data.
License and Citation
All the data and code within this repo are under CC BY-NC-SA 4.0. Please consider citing our project if it helps your research.
@misc{contributors2025internroboticsrepo,
title={InternData-A1},
author={InternData-A1 contributors},
howpublished={\url{https://github.com/InternRobotics/InternManip}}, year={2025}
}