System and method for machine-learning enabled micro-assembly control with the aid of a digital computer
US11893327B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 14, 2020 |
| Grant date | Feb 6, 2024 |
| Priority date | — |
| Expiry date | Jul 28, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2111/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
System and method that allow utilize machine learning algorithms to move a micro-object to a desired position are described. A sensor such as a high speed camera or capacitive sensing, tracks the locations of the objects. A dynamic potential energy landscape for manipulating objects is generated by controlling each of the electrodes in an array of electrodes. One or more computing devices are used to: estimate an initial position of a micro-object using the sensor; generate a continuous representation of a dynamic model for movement of the micro-object due to electrode potentials generated by at least some of the electrodes and use automatic differentiation and Gauss quadrature rules on the dynamic model to derive optimum potentials to be generated by the electrodes to move the micro-object to the desired position; and map the calculated optimized electrode potentials to the array to activate the electrodes.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.