US 12,436,112 B2
Multispectral nondestructive characterization of edible objects
Garrett Allan Stevenson, Livermore, CA (US)
Assigned to LAWRENCE LIVERMORE NATIONAL SECURITY, LLC, Livermore, CA (US)
Filed by Lawrence Livermore National Security, LLC, Livermore, CA (US)
Filed on Feb. 28, 2023, as Appl. No. 18/115,735.
Prior Publication US 2024/0288382 A1, Aug. 29, 2024
Int. Cl. G01N 22/02 (2006.01); G01N 33/02 (2006.01); G06T 7/00 (2017.01)
CPC G01N 22/02 (2013.01) [G01N 33/02 (2013.01); G06T 7/0004 (2013.01); G06T 2207/10012 (2013.01); G06T 2207/10048 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30128 (2013.01)] 37 Claims
OG exemplary drawing
 
1. A system comprising:
a plurality of sensors, including:
a radar system, configured to acquire data concurrently about an object that includes an inedible exterior portion and a potentially edible interior portion, the radar system being configured to transmit a radar beam from the radar system to irradiate the object, and to detect a return signal of the radar beam; and
an optical sensor configured to acquire optical data of the object; and
a computer system coupled to the plurality of sensors and configured to use the optical data to localize the object relative to an aperture of the radar system and to calculate a trajectory of the object in relation to the aperture of the radar system and form a radar image of the interior portion of the object based on the return signal, and to characterize the object based on the acquired data, wherein characterizing the object includes applying a machine learning algorithm to the radar image to characterize the object.