Neural networks to generate robotic task demonstrations
US12415270B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 15, 2022 |
| Grant date | Sep 16, 2025 |
| Priority date | — |
| Expiry date | May 25, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05B2219/39298
- WIPO fieldHandling
- WIPO sectorMechanical engineering
Abstract
A technique for training a neural network, including generating a plurality of input vectors based on a first plurality of task demonstrations associated with a first robot performing a first task in a simulated environment, wherein each input vector included in the plurality of input vectors specifies a sequence of poses of an end-effector of the first robot, and training the neural network to generate a plurality of output vectors based on the plurality of input vectors. Another technique for generating a task demonstration, including generating a simulated environment that includes a robot and at least one object, causing the robot to at least partially perform a task associated with the at least one object within the simulated environment based on a first output vector generated by a trained neural network, and recording demonstration data of the robot at least partially performing the task within the simulated environment.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.