We present SCOPE, a fast and efficient framework for modeling and manipulating deformable linear objects (DLOs). Unlike conventional energy-based approaches, SCOPE leverages convex approximations to significantly reduce computational cost while maintaining smooth and physically plausible deformations. This trade-off between speed and accuracy makes the method particularly suitable for applications requiring real-time or near-real-time response. The effectiveness of the proposed framework is demonstrated through comprehensive simulation experiments, highlighting its ability to generate smooth shape trajectories under geometric and length constraints.
@article{arxiv.2601.19742,
title = {SCOPE: Smooth Convex Optimization for Planned Evolution of Deformable Linear Objects},
author = {Ali Jnadi and Hadi Salloum and Yaroslav Kholodov and Alexander Gasnikov and Karam Almaghout},
journal= {arXiv preprint arXiv:2601.19742},
year = {2026}
}
Comments
Proceedings of Machine Learning Research tbd:1_13, 2025 International Conference on Computational Optimization