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Benchmarks / Research
parcelstow · coenwerem
ParcelStow evaluates imitation-learned robot-policy robustness under execution-timing variation in Isaac Lab.
Overview
ParcelStow evaluates imitation-learned robot-policy robustness under execution-timing variation in Isaac Lab.
Publisher summary: “Isaac Lab robot learning benchmark for assessing imitation-learned policy robustness under execution-timing variation”
Use its repository to inspect the implementation, documentation and supported workflows. This directory record identifies the maintainer, code license and related resources; it does not claim that the project has been installed or tested on your robot.
Project information
- Maintainer
- coenwerem
- Primary language
- Python
- Repository code license
- Apache-2.0
- Model-weight license
- Not recorded
- Dataset license
- Not recorded
- Hardware design license
- Not recorded
- Maintenance
- Not archived in the last recorded metadata
- Last observed repository push
- 2026-10-06
Code licenses do not automatically cover model weights, datasets or hardware designs. Unrecorded license details require confirmation with the publisher.
Documentation sections
- ParcelStow
- Does Imitation Learning Preserve Robustness Under Execution-Timing Variation?
- Expert–ACT Comparison
- Execution Timing and Task Success
- Nominal and Scaled-Speed Task Success
- Get the Code
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