DeformSmith: Physics Harness-Guided Hierarchical Generation of Deformable Assets for Robot Manipulation
DeformSmith generates physically credible deformable assets for robot manipulation from text or a single image using hierarchical agentic construction and physics-guided testing.
DeformSmith progressively builds, tests, and refines geometry, physical models, material behavior, and robot interaction through a shared physics-grounded harness until assets are ready for simulation. Robot manipulation feedback and replayable interaction data close the generation loop. It outperforms PhysGen3D, PhysGM, and PhysX-Omni on visual quality and physical plausibility while supporting data synthesis for deformable-object manipulation.
- Generates interactive deformable assets from text or single image
- Shared physics harness iteratively builds, tests, and refines assets
- Outperforms PhysGen3D, PhysGM, and PhysX-Omni baselines
From the original article
1 min read at huggingface.co
Creating deformable assets for robot manipulation requires jointly specifying their geometry, appearance, and physical properties. This is especially challenging for deformable objects, since text and images provide limited evidence about how they deform and respond to contact, yet these responses directly affect their suitability for interaction.
By Can Li, Jie Gu, Zishun Deng · huggingface.co
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