#deformable-objects News & Analysis

3 articles tagged with #deformable-objects. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AIBullisharXiv – CS AI · Jun 17/10

🧠

DeMaVLA: A Vision-Language-Action Foundation Model for Generalizable Deformable Manipulation

Researchers introduce DeMaVLA, a Vision-Language-Action foundation model designed to enable robots to generalize deformable-object manipulation across diverse household tasks without requiring category-specific training. The model combines a VLM backbone with an efficient action expert using flow matching and is trained on 5,000 hours of real-world demonstrations plus corrective learning from robot failures, achieving strong performance on folding benchmarks.

AINeutralarXiv – CS AI · Jun 46/10

🧠

Instant-Fold: In-Context Imitation Learning for Deformable Object Manipulation

Instant-Fold is an in-context imitation learning framework that enables robots to manipulate deformable objects like cloth by learning from single human demonstrations. The system uses deformation-aware visual representations and flow-matching transformers to generalize across diverse folding modes and transfers directly to real-world tasks without additional training.

AINeutralarXiv – CS AI · May 126/10

🧠

PhysHanDI: Physics-Based Reconstruction of Hand-Deformable Object Interactions

PhysHanDI introduces a physics-based framework for reconstructing 3D hand-object interactions involving deformable materials like cloth and soft objects. By simulating physically plausible object deformations driven by hand movements and using inverse physics to refine hand reconstruction, the method achieves superior performance in reconstruction and prediction tasks compared to existing approaches.