Abstract
Ropes, cables, and other deformable linear objects appear in tasks from untangling to cable routing and suturing, yet controlling their shape remains a challenge in robot manipulation. We study model-based shape control in a general setting: the object lies unfixated on a support surface and two arms may grasp and move it anywhere along its length. Because each arm chooses a grasp point, direction, and magnitude, the joint action space is combinatorially large, and the dynamics model's per-prediction cost bounds how much of it a planner can search. We present ForwardDLO, a recurrent latent dynamics model for this unfixated bimanual setting that predicts per-segment displacements grounded in the observed rope state at every step. Our model reaches accuracy comparable to more expensive baselines while containing no explicit segment-to-segment operations, which makes batched evaluation of candidate actions cheap. On open-loop prediction of real rope motion it reaches the lowest error of the learned models we evaluate, 13% below the strongest baseline. Within a fixed time budget it scores 8 to 22 times more candidate actions than models of comparable accuracy while matching them in real-world shape matching; and on a simulated routing task at a 30Hz control rate, this throughput converts into 98% task success versus at most 30% for the baselines at their own budgets. We release the model, code, and a dataset of 2.42 million simulated and 14,107 real rope transitions at https://anonymous.4open.science/r/ForwardDLO/
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Publication details
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- Open access
- Green open access
Cite this article
APA 7
Missal, T., Guler, B., Domingues, L., Manschitz, S., Peters, J., & Costa, P. D. P. (2026). ForwardDLO: Model-Based Bimanual Shape Matching of Unconstrained Deformable Linear Objects. https://omanscience.com/en/articles/forwarddlo-model-based-bimanual-shape-matching-of-unconstrained-deformable-linear-objects
MLA 9
Missal, Tim, et al. "ForwardDLO: Model-Based Bimanual Shape Matching of Unconstrained Deformable Linear Objects." https://omanscience.com/en/articles/forwarddlo-model-based-bimanual-shape-matching-of-unconstrained-deformable-linear-objects.
Chicago (author–date)
Missal, Tim, Berk Guler, Lucas Domingues, Simon Manschitz, Jan Peters, and Paula Dornhofer Paro Costa. 2026. "ForwardDLO: Model-Based Bimanual Shape Matching of Unconstrained Deformable Linear Objects." https://omanscience.com/en/articles/forwarddlo-model-based-bimanual-shape-matching-of-unconstrained-deformable-linear-objects.
Harvard
Missal, T., Guler, B., Domingues, L., Manschitz, S., Peters, J. and Costa, P. D. P. (2026) 'ForwardDLO: Model-Based Bimanual Shape Matching of Unconstrained Deformable Linear Objects', Available at: https://omanscience.com/en/articles/forwarddlo-model-based-bimanual-shape-matching-of-unconstrained-deformable-linear-objects.
Vancouver
Missal T, Guler B, Domingues L, Manschitz S, Peters J, Costa PDP. ForwardDLO: Model-Based Bimanual Shape Matching of Unconstrained Deformable Linear Objects. https://omanscience.com/en/articles/forwarddlo-model-based-bimanual-shape-matching-of-unconstrained-deformable-linear-objects
IEEE
T. Missal, B. Guler, L. Domingues, S. Manschitz, J. Peters, and P. D. P. Costa, "ForwardDLO: Model-Based Bimanual Shape Matching of Unconstrained Deformable Linear Objects," https://omanscience.com/en/articles/forwarddlo-model-based-bimanual-shape-matching-of-unconstrained-deformable-linear-objects.