--- 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
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arXiv Paper: 2511.16651 Project Homepage Code Repository
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.
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# 📢 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 🔥](#get-started-) - [Download the Dataset](#download-the-dataset) - [Dataset Structure](#dataset-structure) - [📅 TODO List ](#todo-list) - [License and Citation](#license-and-citation) # 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](https://github.com/huggingface/lerobot) (dataset v2.1). ### [meta/info.json](meta/info.json): ```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 - [x] [2025.11] Released: 632k simulation pretraining data (over 7433 hours). The directory is **sim**. - [x] [2026.01] Released: 589k 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](https://creativecommons.org/licenses/by-nc-sa/4.0/). Please consider citing our project if it helps your research. ```BibTeX @misc{contributors2025internroboticsrepo, title={InternData-A1}, author={InternData-A1 contributors}, howpublished={\url{https://github.com/InternRobotics/InternManip}}, year={2025} } ```