US 11,991,946 B2
Adaptively adjusting parameters of equipment operating in unpredictable terrain
Sergey Yaroshenko, Newark, CA (US); Gabriella Levine, San Francisco, CA (US); Elliott Grant, Woodside, CA (US); Daniel Ribeiro Silva, San Jose, CA (US); Linda Kanu, Pleasanton, CA (US); and Francis Ebong, San Francisco, CA (US)
Assigned to MINERAL EARTH SCIENCES LLC, Mountain View, CA (US)
Filed by Mineral Earth Sciences LLC, Mountain View, CA (US)
Filed on Sep. 27, 2021, as Appl. No. 17/485,928.
Prior Publication US 2023/0102576 A1, Mar. 30, 2023
Int. Cl. A01B 79/00 (2006.01); A01B 63/00 (2006.01); G06N 3/02 (2006.01); G06V 20/10 (2022.01)
CPC A01B 79/005 (2013.01) [A01B 63/002 (2013.01); G06N 3/02 (2013.01); G06V 20/188 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method implemented using one or more edge computing devices, the method comprising:
obtaining, by one or more of the edge computing devices, a first image captured by one or more vision sensors transported across an agricultural field by a vehicle, wherein the first image depicts one or more plants growing in an agricultural area;
processing, by one or more of the edge computing devices, the first image to generate one or more agricultural inferences about one or more of the plants growing in the agricultural area, wherein the processing is based on a machine learning model;
determining, by one or more of the edge computing devices, a quality metric for the one or more agricultural inferences using one or more of the edge computing devices, wherein the quality metric appraises or quantifies a value or reliability of one or more of the inferences; and
while the vehicle continues to travel across the agricultural field, and based on the quality metric:
triggering, by one or more of the edge computing devices, one or more hardware adjustments to one or more of the vision sensors, or
triggering, by one or more of the edge computing devices, an adjustment in an operation of the vehicle.