Work

Interactive Robotic Moving Cable Segmentation by Motion Correlation

Year: 2025

Type: article

Abstract: Manipulating tangled hoses, cables, or ropes can be challenging for both robots and humans. Humans often approach these perceptually demanding tasks by pushing or pulling tangled cables and observing the resulting motions. We follow a similar idea to aid robotic cable manipulation. In this letter, we integrate visual and proprioceptive perception to segment a grasped cable by moving it even when the robot or the grasped cable sometimes perturb neighboring cables. We formulate the cable interactive segmentation problem in such a way that our methods do not require robot arm segmentation masks. Furthermore, a novel grasp sampling method can propose new cable grasp points given a partial cable segmentation to improve the segmentation via additional cable-robot interaction. We evaluate the proposedmotion correlation(MCor) method on data sequences recorded by our physical robotic setup and show that the method outperforms an earliermotion segmentation(MSeg) baseline.

Source: IEEE Robotics and Automation Letters

DOI: 10.1109/lra.2025.3574960

Authors: Ondřej Holešovský, Radoslav Škoviera, Václav Hlaváč

Institution: Czech Technical University in Prague

Language: English

Topic: Robot Manipulation and Learning

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,645

Funder: European Commission