# Detection and Physical Interaction with Deformable Linear Objects

arXiv: https://arxiv.org/abs/2205.08041 · HTML: https://mlsanity.com/paper/2205.08041/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 39 references that are in the map.
- First posted on arXiv 17 May 2022.

## Builds on (most cited first, 7 of 7)

- [Deep Distance Transform for Tubular Structure Segmentation in CT Scans](https://mlsanity.com/paper/1912.03383/) (2019)
- [Self-Supervised Learning of State Estimation for Manipulating Deformable Linear Objects](https://mlsanity.com/paper/1911.06283/) (2019)
- [Tracking Partially-Occluded Deformable Objects while Enforcing Geometric Constraints](https://mlsanity.com/paper/2011.00627/) (2020)
- [Deformable One-Dimensional Object Detection for Routing and Manipulation](https://mlsanity.com/paper/2201.06775/) (2022)
- [Real-Time Ellipse Detection for Robotics Applications](https://mlsanity.com/paper/2102.12670/) (2021)
- [Efficient Spatial Representation and Routing of Deformable One-Dimensional Objects for Manipulation](https://mlsanity.com/paper/2202.06172/) (2022)
- [Omnifont Persian OCR System Using Primitives](https://mlsanity.com/paper/2202.06371/) (2022)

## Built on by (most cited first, 2 of 2)

- [ISCUTE: Instance Segmentation of Cables Using Text Embedding](https://mlsanity.com/paper/2402.11996/) (2024)
- [CloudTracks: A Dataset for Localizing Ship Tracks in Satellite Images of Clouds](https://mlsanity.com/paper/2401.14486/) (2024)

## Abstract (arXiv)

Deformable linear objects (e.g., cables, ropes, and threads) commonly appear in our everyday lives. However, perception of these objects and the study of physical interaction with them is still a growing area. There have already been successful methods to model and track deformable linear objects. However, the number of methods that can automatically extract the initial conditions in non-trivial situations for these methods has been limited, and they have been introduced to the community only recently. On the other hand, while physical interaction with these objects has been done with ground manipulators, there have not been any studies on physical interaction and manipulation of the deformable linear object with aerial robots. This workshop describes our recent work on detecting deformable linear objects, which uses the segmentation output of the existing methods to provide the initialization required by the tracking methods automatically. It works with crossings and can fill the gaps and occlusions in the segmentation and output the model desirable for physical interaction and simulation. Then we present our work on using the method for tasks such as routing and manipulation with the ground and aerial robots. We discuss our feasibility analysis on extending the physical interaction with these objects to aerial manipulation applications.