Warp: Structured Output-Space Adaptation for Frozen Robot Policies
Warp: Structured Output-Space Adaptation for Frozen Robot Policies
This paper introduces Warp, a context-conditioned monotone bijective spline designed to adapt frozen robot policies through structured output-space transformations. The authors evaluate Warp across four ManiSkill tasks with controlled deployment shifts and on physical SO101 peg insertion experiments. Results show that Warp achieves the strongest recovery compared to matched evolution-strategy adapters and generic nonlinear controls in simulation, while reducing median successful cycle time by approximately 30% in physical trials under an interaction-limited RLPD/SAC pipeline. The study also notes that adaptation performance becomes task-dependent when using PPO, indicating that richer adapter structures do not universally improve adaptation across different optimizers.
The study evaluates Warp, a structured output-space adaptation method for frozen robot policies, demonstrating improved recovery on four simulated ManiSkill tasks and comparable success with reduced cycle time in physical SO101 peg insertion experiments.
Source: arXiv Robotics — research abstracts · Read original article ↗
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Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
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percent
≈30
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cle time by approximately 30%. These results identify structured output-space adaptation as a useful design space for adapting frozen robot policies.
Open source S5tasks
4
Reported trials
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hat enables nonlinear sample-dependent reshaping while preserving per-dimension ordering; Translation and Affine provide location-only and location--scale references. Across four ManiSkill tasks with controlled deployment shifts, Warp achieves the strongest recovery in a matched evolution-strategy (ES) adapter study, outperforming controls for spline parameterization, location--scale adaptation, and generic nonlinear
Open source S3
- paper: not_reported
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hat enables nonlinear sample-dependent reshaping while preserving per-dimension ordering; Translation and Affine provide location-only and location--scale references. Across four ManiSkill tasks with controlled deployment shifts, Warp achieves the strongest recovery in a matched evolution-strategy (ES) adapter study, outperforming controls for spline parameterization, location--scale adaptation, and generic nonlinear
Open source S3
capacity. Under PPO, the ordering becomes task dependent, showing that richer adapter structure does not automatically translate into better adaptation under a different optimizer. Finally, we test the practical benefit of this approach on physical SO101 peg insertion. Within an interaction-limited RLPD/SAC pipeline, Warp achieves comparable success to a strong stochastic residual while reducing median successful cy
Open source S4
cle time by approximately 30%. These results identify structured output-space adaptation as a useful design space for adapting frozen robot policies.
Open source S5
Source：arXiv Robotics — research abstracts · arxiv.org