US 12,310,274 B1
Precision agriculture using pose georeferenced analytics
Andrew Muehlfeld, St. Paul, MN (US); Henry Nelson, St. Paul, MN (US); Ryan Nelson, St. Paul, MN (US); Eric Taipale, St. Paul, MN (US); and Nicholas Witthoeft, St. Paul, MN (US)
Assigned to SENTERA, INC., St. Paul, MN (US)
Filed by Sentera, Inc., St. Paul, MN (US)
Filed on Apr. 7, 2022, as Appl. No. 17/715,440.
Int. Cl. A01B 79/00 (2006.01); A01B 79/02 (2006.01); B64U 10/13 (2023.01); G06T 3/02 (2024.01); G06T 3/4038 (2024.01); G06V 10/75 (2022.01); G06V 20/10 (2022.01); G06V 20/17 (2022.01); B64U 101/30 (2023.01)
CPC A01B 79/005 (2013.01) [A01B 79/02 (2013.01); B64U 10/13 (2023.01); G06T 3/02 (2024.01); G06T 3/4038 (2013.01); G06V 10/751 (2022.01); G06V 20/17 (2022.01); G06V 20/188 (2022.01); B64U 2101/30 (2023.01); B64U 2201/10 (2023.01)] 24 Claims
OG exemplary drawing
 
1. A precision agriculture method, comprising:
receiving a plurality of drone images of an agricultural field that are captured by an imaging system of an unmanned aerial vehicle (UAV), the imaging system includes at least one camera that includes poses comprising internal parameters and external parameters;
analyzing each one of the drone images using at least one computer processor, wherein the analyzing includes for each one of the drone images:
identifying at least one weed in the drone image and determining a pixel-space location of the at least one weed in the drone image; and
applying a transform to the pixel-space location to determine the world-space location of the at least one weed in the drone image using transform parameters that are determined by using the poses, including the internal parameters and the external parameters, of the at least one camera, wherein the internal parameters include one or more of: a pixel-space location of an optical center of the camera; a physical dimension of the camera; a pixel-space dimension of the camera; a focal length of a lens of the camera; and coefficients of a distortion model which describe distortion of the lens;
and saving the world-space locations for all of the weeds from all of the drone images in data storage; and
producing a spot spray weed prescription for the agricultural field using the world-space locations of the weeds.