Fisher-Preserving Guidance: Training-Free Manifold Constraints for Safe Diffusion Control
Diffusion models are effective for waypoint prediction in visual navigation, but standard sampling and test time guidance can produce unreliable or inefficient trajectories when updates drift off the training manifold. We propose Fisher Preserving Guidance with Outer Product Span Projection, a training-free inference method that avoids large Fisher drift associated with off-distribution actions while optimizing a task objective. Our method computes the Fisher-preserving update via a low-rank Jacobian factorization, requiring only a single backward pass per step and enabling real-time use. We further introduce Truncated Fisher Denoising Sensitivity as an uncertainty signal and use it for r...
| Authors | Hao Ren, Zetong Bi, Yiming Zeng et al. |
|---|---|
| Primary category | cs.RO |
| Published | 28 May 2026 |
| Last updated at source | 28 May 2026 |
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