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:
Nov. 17, 2020

Filed:

Dec. 27, 2017
Applicant:

Deepmap Inc., Palo Alto, CA (US);

Inventor:

Lin Yang, San Carlos, CA (US);

Assignee:

DEEPMAP INC., Palo Alto, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01C 21/32 (2006.01); G01S 17/89 (2020.01); G01C 11/12 (2006.01); G06T 7/73 (2017.01); G06T 7/68 (2017.01); G06K 9/00 (2006.01); G06T 7/55 (2017.01); G06T 17/05 (2011.01); G01C 11/30 (2006.01); G06T 7/246 (2017.01); G06K 9/46 (2006.01); G01C 11/06 (2006.01); G01C 21/36 (2006.01); G06T 7/11 (2017.01); G05D 1/00 (2006.01); G05D 1/02 (2020.01); G06T 7/70 (2017.01); G06T 7/593 (2017.01); G06K 9/62 (2006.01); B60W 40/06 (2012.01); G01S 19/42 (2010.01); G08G 1/00 (2006.01); G06T 17/20 (2006.01); G01C 21/00 (2006.01); G01S 19/47 (2010.01); G01S 19/46 (2010.01);
U.S. Cl.
CPC ...
G01C 11/12 (2013.01); B60W 40/06 (2013.01); G01C 11/06 (2013.01); G01C 11/30 (2013.01); G01C 21/005 (2013.01); G01C 21/32 (2013.01); G01C 21/3602 (2013.01); G01C 21/3635 (2013.01); G01C 21/3694 (2013.01); G01S 19/42 (2013.01); G05D 1/0088 (2013.01); G05D 1/0246 (2013.01); G06K 9/00791 (2013.01); G06K 9/00798 (2013.01); G06K 9/00805 (2013.01); G06K 9/4671 (2013.01); G06K 9/6212 (2013.01); G06T 7/11 (2017.01); G06T 7/246 (2017.01); G06T 7/248 (2017.01); G06T 7/55 (2017.01); G06T 7/593 (2017.01); G06T 7/68 (2017.01); G06T 7/70 (2017.01); G06T 7/73 (2017.01); G06T 7/74 (2017.01); G06T 17/05 (2013.01); G06T 17/20 (2013.01); G08G 1/20 (2013.01); B60W 2552/00 (2020.02); G01S 17/89 (2013.01); G01S 19/46 (2013.01); G01S 19/47 (2013.01); G05D 2201/0213 (2013.01); G06T 2200/04 (2013.01); G06T 2207/10021 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20048 (2013.01); G06T 2207/30252 (2013.01); G06T 2207/30256 (2013.01); G06T 2210/56 (2013.01); G06T 2215/12 (2013.01);
Abstract

A vehicle computing system performs enhances relatively sparse data collected by a LiDAR sensor by increasing the density of points in certain portions of the scan. For instance, the system generates 3D triangles based on a point cloud collected by the LiDAR sensor and filters the 3D triangles to identify a subset of 3D triangles that are proximate to the ground. The system interpolates points within the subset of 3D triangles to identify additional points on the ground. As another example, the system uses data collected by the LiDAR sensor to identify vertical structures and interpolate additional points on those vertical structures. The enhanced data can be used for a variety of applications related to autonomous vehicle navigation and HD map generation, such as detecting lane markings on the road in front of the vehicle or determining a change in the vehicle's position and orientation.


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