Digital Twin Driven Textile Classification and Foreign Object Recognition in Automated Sorting Systems
The increasing demand for sustainable textile recycling requires robust automation solutions capable of handling deformable garments and detecting foreign objects in cluttered environments. This work presents a digital twin driven robotic sorting system that integrates grasp prediction, multi modal perception, and semantic reasoning for real world textile classification. A dual arm robotic cell equipped with RGBD sensing, capacitive tactile feedback, and collision-aware motion planning autonomously separates garments from an unsorted basket, transfers them to an inspection zone, and classifies them using state of the art Visual Language Models (VLMs). We benchmark nine VLM s from five mod...
| Authors | Serkan Ergun, Tobias Mitterer, Hubert Zangl |
|---|---|
| Primary category | cs.CV |
| Published | 5 March 2026 |
| Last updated at source | 12 June 2026 |
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