CoolFace
Datasetpublic

IDEAS-Lab-Northwestern/datagen-dusty-v1-joint-5cam

datagen-dusty-v1-joint-5cam Auto-generated SFT dataset for the dusty_transfer family (wipe a dusty container clean with a sponge, then transfer a target object into it) — cuRobo-planned, physics- & LTL-safety-checked demos, converted to LeRobot v2.1. Creator: yypeng666 (IDEAS-Lab-Northwestern) Source bench: IDEAS-Lab-Northwestern/ManiGuard-Bench — all 26 dusty_transfer base tasks. Per task: 40 success + LTL-safe trajectories -> 1040 episodes. Contents… See the full description on the dataset page: https://huggingface.co/datasets/IDEAS-Lab-Northwestern/datagen-dusty-v1-joint-5cam.

sourceHugging Facecc-by-nc-4.0updated 1mo agoView on Hugging Face
0likes868downloads
Dataset Card

datagen-dusty-v1-joint-5cam

Auto-generated SFT dataset for the dusty_transfer family (wipe a dusty container clean with a sponge, then transfer a target object into it) — cuRobo-planned, physics- & LTL-safety-checked demos, converted to LeRobot v2.1.

  • —Creator: yypeng666 (IDEAS-Lab-Northwestern)
  • —Source bench: IDEAS-Lab-Northwestern/ManiGuard-Bench — all 26 dusty_transfer base tasks.
  • —Per task: 40 success + LTL-safe trajectories -> 1040 episodes.

Contents

Episodes1040 (26 base tasks x 40)
Frames1879498
Unique language tasks21
Robot / controlFrankaPanda / absolute joint
FPS / resolution / format30 / 256x256 / LeRobot v2.1

Task

Wipe a dusty container (e.g. stockpot) clean with a sponge, then transfer a target object (e.g. potato) from a tray into the cleaned container. Per-episode prompt (meta/tasks.jsonl) from the base task diagnostics. Demo must reach the goal AND stay LTL-safe; failed/unsafe attempts dropped.

Schema

state(8)=[arm_q(7),gripper(1)]; actions(8)=[arm_q[t+1](7),gripper_cmd(1)] next-achieved (default SFT target); actions_commanded(8)=[curobo_target_q(7),gripper_cmd(1)] (cuRobo command, extra). Absolute joint (delta at train time). Cameras (all 5 kept, pick subset at train time): image_opposite,image_left,image_right,image_left_shoulder (third-person) + wrist_image.

Notes

  • —Camera subset + arm-joint delta are TRAIN-time choices; all 5 streams + absolute joints ship here.
  • —MimicGen sim-state replay dump is NOT included (kept in the raw archive; not needed for SFT).

License

Released under CC BY-NC 4.0 (see `LICENSE`). The generated artifacts — joint state/action trajectories, rendered demonstration videos, and language prompts — are © 2026 IDEAS Lab, Northwestern University.

The underlying scene and object assets shown in the rendered videos come from BEHAVIOR-1K and remain subject to its license; this dataset does not redistribute them as assets.

Paper & Citation

Part of ManiGuard: paper (arXiv:2608.17386) · code · docs

bibtex
@misc{peng2026maniguard,
  title         = {{MANIGUARD}: A Benchmark and Data Suite for Specification-Grounded
                   Safety Evaluation and Improvement of Robotic Manipulation},
  author        = {Peng, Yiyan and Wang, Philip and Zhan, Simon Sinong and Lyu, Yiqi
                   and Ni, Zhenyang and Yan, Jixin and Wong, Fiorelli and Jiao, Ruochen
                   and Yin, Hang and Cao, Xinyu and Shao, Huajie and Li, Manling
                   and Zhang, Ruohan and Zhu, Qi},
  year          = {2026},
  eprint        = {2608.17386},
  archivePrefix = {arXiv},
  primaryClass  = {cs.RO},
  url           = {https://arxiv.org/abs/2608.17386},
}