Method for generating an application map for treating a field with an agricultural equipment

Patent metadata

Field	Value
Publication number	US-12290063-B2
Application number	US-202017626694-A
Country	US
Kind code	B2
Filing date	Jul 13, 2020
Priority date	Jul 15, 2019
Publication date	May 6, 2025
Grant date	May 6, 2025

Abstract

Method for generating an application map ( 20 ) for treating a field with an agricultural equipment comprising the following steps: providing (S 10 ) a field map ( 10 ) of a field to be treated; determining (S 20 ) areas in the field map ( 10 ) with a weed and/or pest infestation by using an image classification algorithm; and generating (S 30 ) an application map ( 20 ) specifying areas for treating the field with an agricultural equipment, wherein the application map ( 20 ) is based on the determined areas infested by weed and/or pest infestation; wherein the method further comprises the step of providing boundary data with respect to the field.

First claim

What is claimed is:

1. A method comprising:
generating, based at least in part on boundary data associated with a field to be treated, path data associated with a path to be travelled by an image collection device to collect a set of images associated with the field;
generating, based on the set of images, a field map of the field to be treated;
determining, using an image classification algorithm applied to the set of images, one or more infestation areas in the field map comprising one or more of a weed infestation or a pest infestation; and
generating an application map specifying one or more cells relating to the one or more infestation areas of the field to be treated using agricultural equipment.

2. The method according to claim 1 , further comprising generating control data configured to be used to control the agricultural equipment, wherein the agricultural equipment is at least one of a spraying machine or a control device.

3. The method according to claim 1 , wherein the field map is generated based on the set of images by stitching together images from the set of images.

4. The method according to claim 1 , wherein the image collection device is an aircraft device.

5. The method according to claim 1 , further comprising generating image collection path data for at least one image collection device.

6. The method according to claim 5 , wherein the at least one image collection device comprises a communication interface configured to send the set of images to a computer device, wherein the computer device is configured to execute the image classification algorithm to generate the application map.

7. The method according to claim 1 , wherein the application map is divided in cells, and wherein for each cell, at least one of a weed infestation value or a pest infestation value is provided as a percent value.

8. The method according to claim 7 , wherein control data is divided in cells corresponding to the cells of the application map, and wherein a threshold value for each cell is applied when generating the control data such that the cells having the at least one of the weed infestation value or pest infestation value above the threshold value are treated by the agricultural equipment.

9. The method according to claim 8 , wherein when generating the control data, one or more neighboring cells of an identified cell having the at least one of the weed infestation value or pest infestation value above the threshold value are treated by the agricultural equipment.

10. The method according to claim 7 , wherein control data comprises one or more of application rate data, recommended herbicides, or insecticide data.

11. The method according to claim 1 , wherein the image classification algorithm is based on results of a machine learning algorithm.

12. The method according to claim 1 , further comprising generating, based on the application map, control data to be used to control the agricultural equipment.

13. The method according to claim 1 , wherein the path data comprises data associated with one or more of path locations, position marks, flight heights, landing zones, or image locations.

14. A system comprising:
at least one processing unit configured to generate, based at least in part on boundary data associated with a field to be treated, path data associated with a path to be travelled by an image collection device to collect a set of images associated with the field;
at least one processing unit configured to generate, based on the set of images, a field map of the field to be treated;
at least one processing unit configured to determine, using an image classification algorithm applied to the set of images, one or more infestation areas in the field map comprising one or more of a weed infestation or a pest infestation; and
at least one processing unit configured to generate an application map specifying one or more cells relating to the one or more infestation areas of the field to be treated using agricultural equipment.

15. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing device, cause the one or more processors to:
generating, based at least in part on boundary data associated with a field to be treated, path data associated with a path to be travelled by an image collection device to collect a set of images associated with the field;
generating, based on the set of images, a field map of the field to be treated;
determining, using an image classification algorithm applied to the set of images, one or more infestation areas in the field map comprising one or more of a weed infestation or a pest infestation; and
generating an application map specifying one or more cells relating to the one or more infestation areas of the field to be treated using agricultural equipment.

Assignees

• Basf Agro Trademarks Gmbh

Inventors

• Lopes Agnese Mauricio
• Schikora Marek Piotr
• Ilbasi Umit Baran
• Hoffmann Holger
• Rommel Thomas
• Wahabzada Mirwaes
• Selinger Sandra

Classifications

• B64U2201/104

  using satellite radio beacon positioning systems, e.g. GPS · CPC title

• G06T2207/30188

  Vegetation; Agriculture · CPC title

• G06T2207/20081

  Training; Learning · CPC title

• G06T2207/10032

  Satellite or aerial image; Remote sensing · CPC title

• G06T7/0012

  Biomedical image inspection · CPC title