# In-Hand Following of Deformable Linear Objects Using Dexterous Fingers with Tactile Sensing

arXiv: https://arxiv.org/abs/2403.12676 · HTML: https://mlsanity.com/paper/2403.12676/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Mar 2024.

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

- [CaRoBio: 3D Cable Routing with a Bio-inspired Gripper Fingernail](https://mlsanity.com/paper/2508.09558/) (2025)
- [ViTac-Tracing: Visual-Tactile Imitation Learning of Deformable Object Tracing](https://mlsanity.com/paper/2603.18784/) (2026)

## Abstract (arXiv)

Most research on deformable linear object (DLO) manipulation assumes rigid grasping. However, beyond rigid grasping and re-grasping, in-hand following is also an essential skill that humans use to dexterously manipulate DLOs, which requires continuously changing the grasp point by in-hand sliding while holding the DLO to prevent it from falling. Achieving such a skill is very challenging for robots without using specially designed but not versatile end-effectors. Previous works have attempted using generic parallel grippers, but their robustness is unsatisfactory owing to the conflict between following and holding, which is hard to balance with a one-degree-of-freedom gripper. In this work, inspired by how humans use fingers to follow DLOs, we explore the usage of a generic dexterous hand with tactile sensing to imitate human skills and achieve robust in-hand DLO following. To enable the hardware system to function in the real world, we develop a framework that includes Cartesian-space arm-hand control, tactile-based in-hand 3-D DLO pose estimation, and task-specific motion design. Experimental results demonstrate the significant superiority of our method over using parallel grippers, as well as its great robustness, generalizability, and efficiency.