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:
Feb. 03, 2015

Filed:

Mar. 13, 2013
Applicant:

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

Inventors:

Byron McCall Stanley, Cambridge, MA (US);

Matthew Tyler Cornick, Woburn, MA (US);

Charles Michael Coldwell, Belmont, MA (US);

Jeffrey Charles Koechling, Wayland, MA (US);

Beijia Zhang, Cambridge, MA (US);

Assignee:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01S 13/88 (2006.01); G05D 1/02 (2006.01); G01S 13/87 (2006.01); G01S 13/06 (2006.01);
U.S. Cl.
CPC ...
G05D 1/0257 (2013.01); G01S 13/87 (2013.01); G01S 13/06 (2013.01); G05D 1/0268 (2013.01);
Abstract

Described are a method and a system for localization of a vehicle. The method includes the acquisition of SPR images of a subsurface region along a vehicle track. Acquired SPR images are compared to SPR images previously acquired for a subsurface region that at least partially overlaps the subsurface region along the vehicle track. In some embodiments, the comparison includes an image correlation procedure. Location data for the vehicle are determined based in part on location data for the SPR images previously acquired for the second subsurface region. Location data can be used to guide the vehicle along a desired path. The relatively static nature of features in the subsurface region provides the method with advantages over other sensor-based navigation systems that may be adversely affected by weather conditions, dynamic features and time-varying illumination. The method can be used in a variety of applications, including self-driving automobiles and autonomous platforms.


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