TSL: Tracking Deformable Linear Objects for Bimanual Shoe Lacing
Haining Luo, Yiannis Demiris
- Year
- 2025
- Citations
- 3
Abstract
Robot manipulation of Deformable Linear Objects (DLOs) in tasks such as Shoe Lacing (SL) is challenging due to the objects' high dimensionality. One of the key components to successful manipulation is accurate state estimation. Existing methods focus on the DLO itself without considering the interaction with the scene objects. The estimated DLO relation with the scene objects is an important factor in task planning. In SL, the shoelace and shoe relation decides whether the shoelace should be inserted, and the target eyelet for insertion. In this work, we propose an algorithm, Tracking for Shoe Lacing (TSL), which combines probabilistic registration with physical simulation, to preserve the topological relations between the shoelace and the shoe. Leveraging the physical simulation, it also identifies system anomalies during the tracking process. We propose two evaluation metrics: Sequential H-Signature, which qualitatively describes the shoelace-shoe relation to assess algorithm performance, and Dynamic Time Warping (DTW) distance, which quantitatively evaluates tracking errors against the groundtruth. The result shows that TSL achieves tracking error on a par with the state-of-the-art algorithm, and it is the only method that correctly estimates the shoelace-shoe relations across all experimental conditions.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002