US Patent Application 18218940. AMPLITUDE AND BIPHASE CONTROL OF MEMS SCANNING DEVICE simplified abstract

AMPLITUDE AND BIPHASE CONTROL OF MEMS SCANNING DEVICE

Organization Name

MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor(s)

Michael Edward Samples of Redmond WA (US)

Mikhail Smirnov of Bellevue WA (US)

Jozef Barnabas Houben of Seattle WA (US)

Damon Marlow Domjan of Seattle WA (US)

Joshua Owen Miller of Woodinville WA (US)

AMPLITUDE AND BIPHASE CONTROL OF MEMS SCANNING DEVICE - A simplified explanation of the abstract

This abstract first appeared for US patent application 18218940 titled 'AMPLITUDE AND BIPHASE CONTROL OF MEMS SCANNING DEVICE

Simplified Explanation

The patent application describes a MEMS scanning device that uses laser projectors and scanning mirrors to generate a raster scan on a display. The device also includes a thermometer to detect the current temperature and a display observing camera to capture images of the display.

• The device uses laser projectors and scanning mirrors to create a raster scan on a display.
• A thermometer is used to detect the current temperature.
• A display observing camera captures images of the display.
• The captured images are used to extract features.
• The extracted features are compared with ideal features to identify any discrepancies.
• If the identified discrepancy is above a certain threshold, temperature models are updated accordingly.
• The temperature models are custom-built using machine learning algorithms.
• This innovation allows for more accurate temperature modeling and adjustment in the MEMS scanning device.

Original Abstract Submitted

A MEMS scanning device (“Device”) includes at least (1) laser projector(s) controlled by a laser drive to project a laser beam, (2) MEMS scanning mirror(s) controlled by a MEMS drive to scan the laser beam to generate a raster scan, (3) a display configured to receive the raster scan, (4) a thermometer configured to detect a current temperature, (5) a display observing camera configured to capture an image of a predetermined area of the display, and (6) a computer-readable media that stores temperature model(s), each of which is custom-built using machine learning. The device uses the display observing camera to capture image(s) of predetermined pattern(s), which are then used to extract feature(s). The extracted feature(s) are compared with ideal feature(s) to identify a discrepancy. When the identified discrepancy is greater than a threshold, the temperature model(s) are updated accordingly.