license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- robotics
- isaac-sim
- assembly
- manipulation
- imitation-learning
- contact-rich
configs:
- config_name: default
data_files: data/*/*.parquet
AssembleBench
Multi-task contact-rich assembly demonstrations for imitation learning / VLA fine-tuning, and the training set behind the AssembleBench benchmark: 14 tasks on the NIST ATB-1 taskboard (insert round and square pegs, mesh gears, thread nuts) on the DROID robot platform.
Read the writeup: Benchmarking Robot Models on Contact-Rich Assembly.
This dataset was created using LeRobot.
Summary
| Episodes | 1355 |
| Frames | 444651 |
| FPS | 15 |
| Tasks | 14 (pegs, gears, nuts; no M20) |
| Action | DROID 8-D joint position (7 arm + binary gripper) |
| Cameras | observation.images.front, observation.images.wrist at 180x320 |
| Proprio | observation.state (8), joint_vel (7), eef_pos (3), eef_quat (4) |
Tasks (episode counts)
Language-conditioned pick / insert / mesh / thread:
| family | task | n |
|---|---|---|
| peg_round | 4 / 8 / 12 / 16 mm | 96 / 99 / 100 / 100 |
| peg_square | 4 / 8 / 12 / 16 mm | 98 / 98 / 99 / 100 |
| gear_mesh | small / medium / large | 92 / 97 / 92 |
| nut_thread | M8 / M12 / M16 | 90 / 95 / 99 |
M20 removed: embedding analysis (PCA / t-SNE) showed M20 as a separate mode that split the nut cluster; it is not included.
How it was built
Built from a cleaned and topped-up revision of
lukasskellijs/assembly_bench_2,
with a second QC pass for duplicates, idle chunks, length outliers, and within-family
Mahalanobis outliers. Pipeline:
- Start from the cleaned v2 revision (911 eps: dups + long outliers already removed from the original 1500).
- Drop all M20 nut episodes.
- Append scripted-expert top-up HDF5 demos that refill the gaps left by the clean pass (success-filtered Isaac Lab recordings).
- QC blocklist (45 trajectories by MD5 of full
action || state):- exact-duplicate extras (none remained after clean + ingest dedup)
- idle runs >= 15 frames (action-chunk size used in training)
- per-task length >3 sigma and clear within-family 20-PC Mahalanobis outliers (retry / thrash / bad seat)
- Final exact-duplicate scan must be zero or the build aborts.
Quality over quantity: mild multivariate peg shape outliers that look like valid successes were kept.
Schema
DROID joint-position contract:
| key | shape | notes |
|---|---|---|
action |
(8,) | absolute joint targets + gripper |
observation.state |
(8,) | joint pos (7) + gripper |
observation.joint_vel |
(7,) | rad/s |
observation.eef_pos |
(3,) | base-frame XYZ (m) |
observation.eef_quat |
(4,) | world WXYZ |
observation.images.front |
video HxWx3 | 180x320 |
observation.images.wrist |
video HxWx3 | 180x320 |
Load
from lerobot.datasets.lerobot_dataset import LeRobotDataset
ds = LeRobotDataset("hud-evals/AssembleBench")
print(ds.num_episodes, ds.num_frames)
print(ds[0]["observation.images.wrist"].shape)
Intended use
- Supervised fine-tuning of VLA / diffusion / ACT policies with action chunk size 15
- Multi-task assembly benchmarking (peg / gear / nut families)
Not a teleop human dataset. Demonstrations are from a privileged scripted expert in Isaac Sim / Isaac Lab; visuals and proprio match the policy observation contract.
Reference checkpoints
pi0.5 finetunes trained on this dataset:
| Checkpoint | What it is |
|---|---|
pi05-AssembleBench-12k |
behavior-cloning baseline, all 14 tasks |
pi05-AssembleBench-cgdagger-r3 |
BC + 3 rounds of code-gated DAgger, the final checkpoint |
Lineage
- Simulator: NVIDIA Isaac Sim 6 / Isaac Lab Arena
- Format: LeRobot v3.0