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NDPP-Grasp: Non-Differentiable Physical Plausibility Constraints Guide Task-Oriented Dexterous Grasp Generation

NDPP-Grasp proposes injecting physical plausibility constraints directly into the denoising process of a task-aligned grasp diffusion model, so that guidance can be applied throughout generation even when the constraints are non-differentiable. Existing diffusion methods first train a grasp diffusion model for task alignment and then apply physical plausibility correction after generation, leaving the generation trajectory itself unguided by physical constraints. The work was accepted to NeurIPS 2026.

Part of the event: Dexterous Grasping Framework via Denoising with Non-Differentiable Physical Constraint Injection

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