ViaCatalyst/abc130k-screwdriver-mcap-lerobot-v3

ABC-130k MCAP → validated LeRobot v3 telemetry

Before → after: raw MCAP telemetry becomes a documented LeRobot v3.0 episode with preserved state/action mappings, provenance, and reader validation. Convert your MCAP free →

Community conversion produced by ViaCatalyst BYOD. This repository is not an official upstream release and is not affiliated with ABC-130k or Voxel51.

This is a provenance-complete conversion of one pinned MCAP episode from Voxel51's Apache-2.0 repackaging of ABC-130k. It is a reproducible reference for MCAP numeric-topic selection and LeRobot v3 compatibility.

At a glance

Property	Value
Input format	MCAP
LeRobot format	v3.0
Robot	ABC-130k bimanual teleoperation
Task	Put the screwdriver in the bin
Episodes / frames	1 / 136
Duration / FPS	6.8 seconds / 20
State / action dimensions	26 / 12
Selected state topic	/left-arm-state.plot
Selected action topic	/left-arm-action.plot
Official LeRobot reader	Passed with LeRobot 0.6.0

Feature mapping and action preservation

LeRobot feature	Source
observation.state	Numeric fields from /left-arm-state.plot: end-effector pose, joint position, torque, and velocity
action	Numeric fields from /left-arm-action.plot: end-effector pose and joint position
Episode and frame indices	Single source-log episode and message ordering
timestamp	Output frame_index / 20 seconds; source pairing evidence is retained in validation-report.json

Action messages are copied directly from the selected source topic. The conversion does not replay a policy, regenerate commands, interpolate actions, or relabel the episode. The source MCAP includes camera data, but the current MCAP adapter intentionally converts only the documented numeric telemetry topics; no visual modality is claimed by this release.

Intended use

• Validating MCAP numeric-topic selection and LeRobot v3 readers
• Reproducible testing of ROS-adjacent telemetry conversion workflows
• Small offline imitation-learning or educational experiments after reviewing validation evidence

Validation evidence

All seven critical checks passed, including schema/counts, timeline, finite feature values, LeRobot v3 metadata, provenance, and the official LeRobot reader smoke test. The readiness score is 84/100 — Review recommended. The report retains two medium-confidence robust-outlier signals (37.5% for state and action) for user review; they are not proof of corruption.

Read the complete evidence in validation-report.json.

Source, integrity, and license

• Source: Voxel51/ABC-130k, an Apache-2.0 modified subset of ABC-130k
• Pinned revision: 9659e8ce4b39580f48369cc31bc2e47a217c40e7
• Source file: data/val/put_the_screwdriver_in_the_bin/episode_02eb2789-4234-4d4c-984e-08872ed00c1d/episode.fo.mcap
• Source SHA-256: f605f24fc0c3edee1549dd47a8934b48d68a700ee61fc93093e7815e0b058069
• Adapter: mcap 1.0.0; converter revision 4230bc4b56abe85116b202398b1a625a81c1c55c

Audit artifacts: provenance.json, bundle-manifest.json, bundle-manifest.external.json, and UPSTREAM_LICENSE.md.

The source card declares Apache-2.0. This conversion retains the license, upstream attribution, and citation; it does not transfer ownership or replace source terms.

Limitations

• This is one MCAP episode, not the full ABC-130k corpus.
• It contains numeric telemetry only; it is not the source's full camera-plus-telemetry multimodal representation.
• State/action streams are paired by message index; review synchronization evidence before control training.
• Validation does not measure downstream policy quality or task success.

Load with LeRobot

from lerobot.datasets.lerobot_dataset import LeRobotDataset

dataset = LeRobotDataset("ViaCatalyst/abc130k-screwdriver-mcap-lerobot-v3")
print(dataset.meta.total_episodes, dataset.meta.total_frames)

Conversion tooling

Converted and validated with the ViaCatalyst BYOD Processing Platform, a free workflow for converting robotics data to LeRobot format. For high-volume datasets, contact ViaCatalyst support through the platform.

Citation

@misc{abc2026,
  title={Scalable Behavior Cloning with Open Data, Training, and Evaluation},
  author={Allshire, Arthur and Singh, Himanshu Gaurav and Singh, Ritvik and others},
  year={2026},
  eprint={2606.27375},
  archivePrefix={arXiv},
  primaryClass={cs.RO},
  doi={10.48550/arXiv.2606.27375}
}