Data-driven physics-based models with implicit actuations
US12223577B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Jan 25, 2023 |
| Grant date | Feb 11, 2025 |
| Priority date | — |
| Expiry date | Aug 11, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2219/2021
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
One embodiment of the present invention sets forth a technique for generating actuation values based on a target shape such that the actuation values cause a simulator to output a simulated soft body that matches the target shape. The technique includes inputting a latent code that represents a target shape and a point on a geometric mesh into a first machine learning model. The technique further includes generating, via execution of the first machine learning model, one or more simulator control values that specify a deformation of the geometric mesh, where each of the simulator control values is based on the latent code and corresponds to the input point, and generating, via execution of the simulator, a simulated soft body based on the one or more simulator control values and the geometric mesh. The technique further includes causing the simulated soft body to be outputted to a computing device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.