The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 17, 2019

Filed:

May. 05, 2016
Applicant:

Massachusetts Institute of Technology, Cambridge, MA (US);

Inventors:

Jifei Ou, Somerville, MA (US);

Gershon Dublon, Cambridge, MA (US);

Chin-Yi Cheng, Cambridge, MA (US);

Liang Zhou, Riverside, CA (US);

Hiroshi Ishii, Cambridge, MA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B29C 64/386 (2017.01); B33Y 10/00 (2015.01); B33Y 50/02 (2015.01); G06F 3/0488 (2013.01); B29C 64/129 (2017.01); B33Y 30/00 (2015.01); B33Y 80/00 (2015.01);
U.S. Cl.
CPC ...
G06F 3/04883 (2013.01); B29C 64/129 (2017.08); B29C 64/386 (2017.08); B33Y 10/00 (2014.12); B33Y 30/00 (2014.12); B33Y 50/02 (2014.12); B33Y 80/00 (2014.12);
Abstract

A computer produces a digital model that efficiently describes a dense array of many micro-pillars. The digital model achieves this efficiency by describing an entire micro-pillar with only a few parameters. For example, an entire micro-pillar may be described by two of more of the following parameters: height, base thickness, profile and tilt. The computer outputs instructions to fabricate the micro-pillar array, in accordance with the digital model. A 3D printer fabricates the micro-pillar array, based on the instructions. Applying vibration to a directional array of micro-pillars may cause the array of micro-pillars to actuate motion of a passive object that is touching the array. Also, a sensor may measure sounds caused by swipes against a micro-pillar array, and output signals indicative of the measurements. A computer performs a machine learning algorithm that takes the measurements as an input, and classifies the swipes.


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