aleleanza/diffusion-policy-vac-pipe
Robotics • Updated
Search is not available for this dataset
timestamp float64 0 22.1 | frame_index int64 0 1.11k | episode_index int64 0 201 | task_index int64 0 0 | observation.state listlengths 12 12 | observation.wrench listlengths 6 6 | observation.admittance_params listlengths 4 4 | observation.stiffness_cmd float64 3.56 2k | observation.zeta float64 0.8 2.5 | observation.target_pose listlengths 6 6 | action.user_cmd listlengths 6 6 | action.vel_cmd listlengths 6 6 | action.absolute listlengths 12 12 | action.delta listlengths 12 12 | next.done bool 2
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End of preview. Expand in Data Studio
VAC — Pipe Insertion (dual-camera)
Kinesthetic teleoperation dataset for a contact-rich pipe-insertion task under a Variable Admittance Controller (VAC), recorded on a Doosan M0609 arm with an Inspire RH56 hand and a Bota wrist force/torque sensor. Stored in LeRobot v2 format (Parquet + MP4).
- Task:
pipe_fixing— grasp a pipe and insert/fix it, with compliance modulated online by the operator (variable stiffness + damping). - Episodes: 202 · Frames: 145,712 · Rate: 50 Hz
- Robot:
doosan_m0609_inspire_rh56 - Cameras (2):
observation.images.camera— RealSense D405 (wrist-side / primary view), 640×480observation.images.orbbec— Orbbec Femto Bolt (third-person / secondary view), 640×480
Recorded oversampled at 50 Hz on purpose — downsample offline to your control rate rather than re-recording slower.
Why this dataset
Most manipulation datasets log only kinematics + vision. This one also logs the
full admittance state and the operator's online stiffness/damping commands, so you
can learn policies that output compliance (predict K, ζ) instead of only motion.
The synchronized Bota wrench stream makes it suitable for force-conditioned imitation
learning on a genuinely contact-rich task.
Feature schema (per timestep)
| Key | Dim | Meaning |
|---|---|---|
observation.state |
12 | TCP pos_{x,y,z} + rotvec_{x,y,z} + 6 Inspire hand joints |
observation.wrench |
6 | Bota FT in base frame: Fx,Fy,Fz (N), Tx,Ty,Tz (Nm) |
observation.admittance_params |
4 | K_trans (N/m), K_rot (Nm/rad), B_trans, B_rot |
observation.stiffness_cmd |
1 | Commanded translational stiffness K_trans_cmd (N/m) |
observation.zeta |
1 | Commanded damping ratio ζ (default 1.2) |
observation.target_pose |
— | Admittance target pose |
observation.images.camera |
640×480 | RealSense D405 (wrist) RGB |
observation.images.orbbec |
640×480 | Orbbec Femto Bolt RGB |
action.user_cmd |
6 | Operator delta command d{x,y,z,rx,ry,rz} (pre-admittance) |
action.vel_cmd |
6 | Cartesian velocity vx,vy,vz (mm/s), wx,wy,wz (deg/s) (post-admittance) |
action.absolute |
12 | Absolute TCP + hand target |
action.delta |
— | Delta TCP target |
next.done |
1 | Episode termination flag |
Hand state spans dims 6–11 of observation.state (hand_thumb_rot, hand_thumb_bend,
hand_index, hand_middle, hand_ring, hand_little). The Inspire hand is operated
as a binary open/grasp gripper in the downstream policies.
pre vs post: action.user_cmd is the operator's intent before the admittance
filter; action.vel_cmd is the Cartesian velocity the controller actually executed
after the admittance dynamics. Policies can imitate either side of the controller.
Layout (LeRobot v2)
dataset_pipe_02_06/
├── meta/
│ ├── info.json # fps, dims, feature names, n_episodes, n_frames_total
│ ├── episodes.jsonl # one entry per episode (index, length, task)
│ └── tasks.jsonl # task index → "pipe_fixing"
├── data/chunk-000/episode_NNNNNN.parquet
└── videos/chunk-000/
├── observation.images.camera/episode_NNNNNN.mp4
└── observation.images.orbbec/episode_NNNNNN.mp4
Usage
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
ds = LeRobotDataset("aleleanza/vac-pipe-dual-cam")
print(ds.num_episodes, ds.num_frames, ds.fps)
sample = ds[0]
# sample["observation.images.camera"], sample["observation.wrench"],
# sample["action.vel_cmd"], ...
Train D405-only (use observation.images.camera) or dual-camera (add
observation.images.orbbec). The companion Diffusion Policy models use the D405 stream
resized to 84×84 as front_rgb.
Hardware setup
- Arm: Doosan M0609 (6-DoF collaborative)
- Hand: Inspire RH56 (operated as binary open/grasp)
- F/T: Bota Systems wrist sensor (
/bota_ft_sensor/wrench), tared per trial - Control: Variable Admittance Controller — operator modulates stiffness
Kand damping ζ online; admittance integrates the external wrench into a compliant motion. - Recording: kinesthetic teleop via the project's
lerobot_recorder.
Related
- Models:
aleleanza/diffusion-policy-vac-pipe— 6-variant input/output Diffusion Policy ablation trained on this dataset. - Collection: VAC — Pipe Insertion.
Citation
If you use this dataset, please credit the VAC project (Doosan M0609 variable-admittance manipulation). Recorded at SUPSI.
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