arXiv · 2604.22102
Wiggle and Go! System Identification for Zero-Shot Dynamic Rope Manipulation
Abstract
Many robotic tasks are unforgiving; a single mistake in a dynamic throw can lead to unacceptable delays or unrecoverable failure. We introduce Wiggle and Go!, a two-stage framework for zero-shot rope manipulation: a brief, safe wiggle action is observed to predict descriptive rope parameters, which then conditions a trajectory optimizer for zero-shot goal-conditioned execution. Unlike prior dynamic rope manipulation methods that require large real-world datasets or iterative real-world refinement, our identification module is task-agnostic, supporting diverse manipulation policies without retraining. We achieve a 3.55\,cm average accuracy on 3D target striking in real using rope system parameters in comparison to 15.29\,cm for uninformed baselines, and over 50\% success on multi-objective lobbing and draping tasks. Predicted parameters transfer to unseen motions with 0.95 Pearson correlation between simulated and real rope dynamics, indicating that the identification module generalizes across the task corpus. Project website: https://wiggleandgo.github.io/
Explore related subjects
Keep this discovery
Arthur Jakobsson, Abhinav Mahajan, Karthik Pullalarevu, Krishna Suresh, Yunchao Yao, Yuemin Mao, Bardienus Duisterhof, Shahram Najam Syed, Jeffrey Ichnowski. 2026-04-23. Wiggle and Go! System Identification for Zero-Shot Dynamic Rope Manipulation. https://arxiv.org/abs/2604.22102
Cite the original work for its findings. Save a collection to share your selection of sources.