US 12,406,348 B2
Neuromorphic foreign object detection
Justin R Urban, Tolland, CT (US); Kishore K. Reddy, Farmington, CT (US); Kin Gwn Lore, Belmont, MA (US); and Ganesh Sundaramoorthi, Duluth, GA (US)
Assigned to RTX CORPORATION, Farmington, CT (US)
Filed by RTX Corporation, Farmington, CT (US)
Filed on Jun. 16, 2023, as Appl. No. 18/336,605.
Prior Publication US 2024/0420302 A1, Dec. 19, 2024
Int. Cl. G06T 7/00 (2017.01); B64D 45/00 (2006.01); G06N 3/0455 (2023.01); H04N 7/18 (2006.01); H04N 23/54 (2023.01); H04N 25/47 (2023.01)
CPC G06T 7/0004 (2013.01) [B64D 45/00 (2013.01); G06N 3/0455 (2023.01); H04N 7/183 (2013.01); H04N 23/54 (2023.01); H04N 25/47 (2023.01); B64D 2045/009 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30108 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A neuromorphic foreign object debris (FOD) detection system comprising:
a FOD processing system including a FOD controller including a trained artificial intelligence machine learning (AIML) model representing an area of interest; and
a neuromorphic sensor in signal communication with the FOD processing system, the neuromorphic sensor having a field of view (FOV) containing the area of interest and configured to output pixel data in response to FOD appearing in the FOV,
wherein the FOD controller detects the FOD is present in the area of interest in response to receiving the pixel data, and generates an alert signal indicating the presence of the FOD.