mlsanityData to 14 Oct 2026

KnotDLO: Toward Interpretable Knot Tying

arXiv 2506.22176 ↗First posted 27 Jun 2025cs.RO cs.CVcited by 0

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Abstract (arXiv)

This work presents KnotDLO, a method for one-handed Deformable Linear Object (DLO) knot tying that is robust to occlusion, repeatable for varying rope initial configurations, interpretable for generating motion policies, and requires no human demonstrations or training. Grasp and target waypoints for future DLO states are planned from the current DLO shape. Grasp poses are computed from indexing the tracked piecewise linear curve representing the DLO state based on the current curve shape and are piecewise continuous. KnotDLO computes intermediate waypoints from the geometry of the current DLO state and the desired next state. The system decouples visual reasoning from control. In 16 trials of knot tying, KnotDLO achieves a 50% success rate in tying an overhand knot from previously unseen configurations.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 36 references that are in the map. First posted on arXiv 27 Jun 2025.

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14 of 36 references.

References · 14

  1. 2018Open3D: A Modern Library for 3D Data Processingcited by 721
  2. 2018Zero-Shot Visual Imitationcited by 117
  3. 2017Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulationcited by 90
  4. 2020Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networkscited by 78
  5. 2020Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Datacited by 51
  6. 2019Self-Supervised Learning of State Estimation for Manipulating Deformable Linear Objectscited by 45
  7. 2020Tracking Partially-Occluded Deformable Objects while Enforcing Geometric Constraintscited by 12
  8. 2021Trajectory Optimization for Manipulation of Deformable Objects: Assembly of Belt Drive Unitscited by 11
  9. 2021Disentangling Dense Multi-Cable Knotscited by 7
  10. 2020Learning Topological Motion Primitives for Knot Planningcited by 6
  11. 2022Global Model Learning for Large Deformation Control of Elastic Deformable Linear Objects: An Efficient and Adaptive Approachcited by 6
  12. 2021Shape Control of Deformable Linear Objects with Offline and Online Learning of Local Linear Deformation Modelscited by 4
2 more
  1. 2023MultiDLO: Simultaneous Shape Tracking of Multiple Deformable Linear Objects with Global-Local Topology Preservationcited by 3
  2. 2022The Robustness of Tether Friction in Non-idealized Terrainscited by 1

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  1. 2025UniStateDLO: Unified Generative State Estimation and Tracking of Deformable Linear Objects Under Occlusion for Constrained Manipulation
  2. 2024Learning for Deformable Linear Object Insertion Leveraging Flexibility Estimation from Visual Cues
  3. 2026Point It, Strike It: Direction-Conditioned Dynamic Manipulation of Deformable Linear Objects ↗
  4. 2026TWISTED-RL: Hierarchical Skilled Agents for Knot-Tying without Human Demonstrations
  5. 2026RopeDreamer: A Kinematic Recurrent State Space Model for Dynamics of Flexible Deformable Linear Objects ↗
  6. 2026DexKnot: Generalizable Visuomotor Policy Learning for Dexterous Bag-Knotting Manipulation
  7. 2025Knot So Simple: A Minimalistic Environment for Spatial Reasoning
  8. 2026WireCraft: A Simulation Benchmark for Industrial DLO Manipulation