Autonomously Untangling Long Cables

Kaushik Shivakumar,
Vainavi Viswanath,
Justin Kerr,
Brijen Thananjeyan,
Ellen Novoseller,
Jeffrey Ichnowski,
Ken Goldberg,
Joseph Gonzalez,
Michael Laskey,
Alejandro Escontrela (UC Berkeley)
Paper Website
Paper #034
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Cables are ubiquitous in many settings, but often become tangled. Cables are prone to self-occlusions and knots making them difficult to perceive and manipulate. This challenge is exacerbated as cable length increases: long cables require slack management and new primitives to facilitate observability and reachability. In this paper, we focus on autonomously untangling cables of lengths up to 2.7 meters using a bilateral robot. We develop new motion primitives to efficiently untangle and manage the slack of long cables, as well as specialized grippers for this task. We then propose Sliding and Grasping for Tangle Manipulation (SGTM), an algorithm that composes these primitives to untangle cables from starting configurations consisting of knots and several self-crossings. We demonstrate that SGTM successfully untangles cables with a success rate of 67% on isolated overhand and figure 8 knots and 50% on more complex configurations. Supplementary material, visualizations, and videos can be found at

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