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This dataset was created using LeRobot.
Dataset Description
Bimanual DK1 teleop recording (cable tie, 2026-06-12). Pre-roll losslessly trimmed (forced IDR at episode start) so each episode video aligns exactly with the recorded data (from_timestamp=0).
- Robot: TRLC DK1 bimanual (
bi_dk1_follower) — 2× 6-DOF arms with grippers - Task: Take a green cable tie from the red box, thread the tail through the head to close it, then place it in the transparent bin on the left.
- Episodes: 98
- Total frames: 244,146 (67.8 min @ 60 fps)
- Avg episode length: 41.5s
- License: apache-2.0
Cameras
| Camera | Resolution | Codec | FPS |
|---|---|---|---|
observation.images.head |
640x360 | hevc | 60 |
observation.images.left_wrist |
640x360 | hevc | 60 |
observation.images.right_wrist |
640x360 | hevc | 60 |
Observation Space
observation.state: float32[40] — left_joint_1.pos, left_joint_2.pos, left_joint_3.pos, left_joint_4.pos, left_joint_5.pos, left_joint_6.pos... (joint positions, velocities, torques for both arms + grippers)observation.images.*: 3 camera streams
Action Space
action: float32[14] — left_joint_1.pos, left_joint_2.pos, left_joint_3.pos, left_joint_4.pos, left_joint_5.pos, left_joint_6.pos... (joint position targets for both arms + grippers)
Loading the Dataset
from lerobot.datasets.lerobot_dataset import LeRobotDataset
dataset = LeRobotDataset("andreaskoepf/dk1_cable_tie_2026-06-12")
# Access a frame
frame = dataset[0]
print(frame["observation.state"].shape) # torch.Size([40])
print(frame["action"].shape) # torch.Size([14])
print(frame["observation.images.head"].shape) # torch.Size([3, 720, 1280])
Dataset Structure
{
"codebase_version": "v3.0",
"robot_type": "bi_dk1_follower",
"total_episodes": 98,
"total_frames": 244146,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 28,
"video_files_size_in_mb": 6920,
"fps": 60,
"splits": {
"train": "0:98"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
"features": {
"action": {
"dtype": "float32",
"names": [
"left_joint_1.pos",
"left_joint_2.pos",
"left_joint_3.pos",
"left_joint_4.pos",
"left_joint_5.pos",
"left_joint_6.pos",
"left_gripper.pos",
"right_joint_1.pos",
"right_joint_2.pos",
"right_joint_3.pos",
"right_joint_4.pos",
"right_joint_5.pos",
"right_joint_6.pos",
"right_gripper.pos"
],
"shape": [
14
]
},
"observation.state": {
"dtype": "float32",
"names": [
"left_joint_1.pos",
"left_joint_2.pos",
"left_joint_3.pos",
"left_joint_4.pos",
"left_joint_5.pos",
"left_joint_6.pos",
"left_gripper.pos",
"right_joint_1.pos",
"right_joint_2.pos",
"right_joint_3.pos",
"right_joint_4.pos",
"right_joint_5.pos",
"right_joint_6.pos",
"right_gripper.pos",
"left_joint_1.vel",
"left_joint_2.vel",
"left_joint_3.vel",
"left_joint_4.vel",
"left_joint_5.vel",
"left_joint_6.vel",
"right_joint_1.vel",
"right_joint_2.vel",
"right_joint_3.vel",
"right_joint_4.vel",
"right_joint_5.vel",
"right_joint_6.vel",
"left_joint_1.torque",
"left_joint_2.torque",
"left_joint_3.torque",
"left_joint_4.torque",
"left_joint_5.torque",
"left_joint_6.torque",
"left_gripper.torque",
"right_joint_1.torque",
"right_joint_2.torque",
"right_joint_3.torque",
"right_joint_4.torque",
"right_joint_5.torque",
"right_joint_6.torque",
"right_gripper.torque"
],
"shape": [
40
]
},
"observation.images.head": {
"dtype": "video",
"shape": [
360,
640,
3
],
"names": [
"height",
"width",
"channels"
],
"info": {
"video.height": 360,
"video.width": 640,
"video.codec": "hevc",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 60,
"video.channels": 3,
"has_audio": false
}
},
"observation.images.left_wrist": {
"dtype": "video",
"shape": [
360,
640,
3
],
"names": [
"height",
"width",
"channels"
],
"info": {
"video.height": 360,
"video.width": 640,
"video.codec": "hevc",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 60,
"video.channels": 3,
"has_audio": false
}
},
"observation.images.right_wrist": {
"dtype": "video",
"shape": [
360,
640,
3
],
"names": [
"height",
"width",
"channels"
],
"info": {
"video.height": 360,
"video.width": 640,
"video.codec": "hevc",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 60,
"video.channels": 3,
"has_audio": false
}
},
"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
}
}
}
Citation
BibTeX:
@misc{andreaskoepf_dk1_cable_tie_2026_06_12,
title = {Take a green cable tie from the red box, thread the tail through the head to close it, then place it in the transparent bin on the left.},
author = {The Robot Learning Company},
year = {2026},
publisher = {HuggingFace},
url = {https://huggingface.co/datasets/andreaskoepf/dk1_cable_tie_2026-06-12}
}
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