Detecting and measuring the size of clods and other soil features from imagery
AssigneesCNH Industrial Canada, Ltd., Autonomous Solutions, Inc.
InventorsLuca Ferrari, John H. Posselius, James W. Henry, Taylor C. Bybee
Life of this patent
Estimating the term…
Abstract
The present disclosure provides systems and methods that measure soil roughness in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned clod detection model to determine a soil roughness value for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. For example, the imaging device can be a camera positioned in a downward-facing direction and physically coupled to a work vehicle or an implement towed by the work vehicle through the field.
Claims20
A computing system, comprising:
- one or more processors;
- and
- one or more non-transitory computer-readable media that collectively store:
- a machine-learned clod detection model configured to receive imagery and to process the imagery to detect soil clods depicted by the imagery;
- and
- instructions that, when executed by the one or more processors, configure the computing system to perform operations, the operations comprising:
- obtaining image data that depicts a portion of a field;
- inputting the image data into the machine-learned clod detection model;
- receiving one or more bounding shapes as an output of the machine-learned clod detection model, wherein each of the one or more bounding shapes indicates a respective location of a respective soil clod detected by the machine-learned clod detection model in the image data;
- and
- determining a soil roughness value for at least the portion of the field based at least in part on the one or more bounding shapes.
A computer-implemented method, comprising:
- obtaining, by a computing system comprising one or more computing devices, image data that depicts a portion of a field;
- inputting, by the computing system, the image data into machine-learned clod detection model configured to receive imagery and to process the imagery to detect soil clods depicted by the imagery;
- receiving, by the computing system, one or more bounding shapes as an output of the machine-learned clod detection model, wherein each of the one or more bounding shapes indicates a respective location of a respective soil clod detected by the machine-learned clod detection model in the image data;
- and
- determining, by the computing system, a soil roughness value for at least the portion of the field based at least in part on the one or more bounding shapes.
An agricultural work vehicle or implement, comprising:
- one or more imaging devices;
- and
- a controller comprising one or more processors and one or more non-transitory computer-readable media that collectively store:
- a machine-learned clod detection model configured to receive imagery and to process the imagery to detect soil clods depicted by the imagery;
- and
- instructions that, when executed by the one or more processors, configure the controller to perform operations, the operations comprising:
- obtaining image data that depicts a portion of a field;
- inputting the image data into the machine-learned clod detection model;
- receiving one or more bounding shapes as an output of the machine-learned clod detection model, wherein each of the one or more bounding shapes indicates a respective location of a respective soil clod detected by the machine-learned clod detection model in the image data;
- determining a soil roughness value for at least the portion of the field based at least in part on the one or more bounding shapes;
- and
- controlling operation of one or more ground-engaging tools based at least in part on the soil roughness value.
Dependencies are inferred from the claim text.