Disentangling Dense Multi-Cable Knots
Abstract
Disentangling two or more cables often requires many steps to remove crossings between and within cables. We formalize the problem of disentangling multiple cables and present an algorithm, Iterative Reduction Of Non-planar Multiple cAble kNots (IRON-MAN), that outputs robot actions to remove crossings from multi-cable knotted structures. IRON-MAN uses a learned perception system inspired by prior work in single-cable untying to imitate a graph-based supervisor, and operates on RGB image inputs of the workspace. Given a sequence of images as input, the system can disentangle two-cable twists, three-cable braids, and knots of two or three cables, such as overhand, square, carrick bend, sheet bend, crown, and fisherman’s knots. IRON-MAN keeps track of task-relevant keypoints corresponding to cable endpoints and crossings and iteratively disentangles the cables by identifying and undoing crossings that are critical to knot structure. Using a da Vinci surgical robot, we experimentally evaluate the effectiveness of IRON-MAN on disentangling multi-cable knots of types that appear in the training data, as well as generalizing to novel classes of multi-cable knots. Results suggest that IRON-MAN is effective in disentangling knots involving up to three cables with 80.5% success and generalizing to knot types that are not present during training, with cables of identical or distinct colors. Supplementary material and videos can be found at https://tinyurl.com/multi-cable-disentangling.
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Connecting multiple ropes introduces more crossings and more endpoints, which amplifies the self-symmetry problem and makes it difficult to keep track of the status of every specific rope.
“Furthermore, connecting multiple ropes introduces more crossings while trying to tie/untie multiple ropes [241] than dealing with a single rope. It also presents more endpoints of ropes in the scene, which amplifies the self-symmetry problem and makes it difficult to keep track of the status of every specific rope.”
From Data-Driven Robotic Manipulation of Cloth-like Deformable Objects: The Present, Challenges and Future Prospects (2023) · cites this paper as [241]
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“Viswanath et al. (2021) [241] managed to untie multiple cables with their Iterative Reduction Of Non-planar Multiple cAble kNots (IRON-MAN) system that generates primitive actions to remove crossing on the cables.”
Background
- Authors
- Viswanath, V., Grannen, J., Sundaresan, P., Thananjeyan, B., Balakrishna, A., Novoseller, E., Ichnowski, J., Laskey, M., Gonzalez, J. E., & Goldberg, K.
- Affiliations
- University of California, Berkeley (US)
- Toyota Research Institute (US)
- ORCID
- Venue
- 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Publisher
- IEEE
- Published
- 2021-09-27
- Pages
- 3731-3738
- ISSN
- 2153-0858 (ISSN-L)
- OpenAlex
- W4205603020
- Cited by
- 21
- References
- 25
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 6 · 2023: 6 · 2022: 3
- FWCI
- 5.60
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
- Physical Sciences › Engineering › Biomedical Engineering › Soft Robotics and Applications
- Physical Sciences › Mathematics › Geometry and Topology › Geometric and Algebraic Topology
- Keywords
- Iron Man, da Vinci surgical robot
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