Evidence item
The abstract reports convergence within 3 cm, collision-free paths for the navigation-function field, and lower collision-free rates for image-only supervision. DATASET_RESULT
Source: SE(3) Neural Potential Fields for 6-DoF Trajectory Planning Directly from Images Without Explicit 3D Reconstruction · locator {} · excerpt hash sha256:dd5a21f0ad3d3039ed4450231fee726a2639f3f752d3dc2e904d9b31b1203b9d
Exact excerpt
We present an SE(3) neural potential field learned from posed RGB images and supervised with a navigation function, the geodesic distance to the grasp through free space recovered from those same images during training, which removes both failures. On two tabletop scenes, from obstacle-blocked starts executed on a UR10, the field converges within 3 cm of the grasp from every start and every path it executes is collision-free against the ground-truth geometry, against 25% and 0% under image supervision alone; mean clearance rises from under a centimeter to 8.6-8.8 cm and arm-link contacts fall from 20.6-50.4% to 2.7-5.5% of executed configurations.
Linked claims
| Claim | Direction | Relevance | Steps | Counted |
|---|---|---|---|---|
| 00a3f605 | SUPPORT | DIRECT | 0 | yes |
Audits
None.