AI RESEARCH
Wiggle and Go! System Identification for Zero-Shot Dynamic Rope Manipulation
arXiv CS.AI
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ArXi:2604.22102v1 Announce Type: cross Many robotic tasks are unforgiving; a single mistake in a dynamic throw can lead to unacceptable delays or unrecoverable failure. To mitigate this, we present a novel approach that leverages learned simulation priors to inform goal-conditioned dynamic manipulation of ropes for efficient and accurate task execution. Related methods for dynamic rope manipulation either require large real-world datasets to estimate rope behavior or the use of iterative improvements on attempts at the task for goal completion. We.