U.S. patent application number 16/376005 was filed with the patent office on 2019-08-01 for vision-based system for acquiring crop residue data and related calibration methods.
This patent application is currently assigned to CNH Industrial America LLC. The applicant listed for this patent is CNH Industrial America LLC. Invention is credited to John Posselius.
Application Number | 20190236359 16/376005 |
Document ID | / |
Family ID | 62186291 |
Filed Date | 2019-08-01 |
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United States Patent
Application |
20190236359 |
Kind Code |
A1 |
Posselius; John |
August 1, 2019 |
VISION-BASED SYSTEM FOR ACQUIRING CROP RESIDUE DATA AND RELATED
CALIBRATION METHODS
Abstract
A method for calibrating crop residue data for a field acquired
using a vision-based system may include receiving image data
associated with an imaged portion of the field, analyzing the image
data using a first residue-estimating technique to determine a
first estimated value of a crop residue parameter for the imaged
portion of the field, and analyzing the image data using a second
residue-estimating technique to determine a second estimated value
of the crop residue parameter for the imaged portion of the field.
In addition, when a differential exists between the first and
second estimated values, the method may also include adjusting at
least one of the first estimated value or one or more additional
estimated values of the crop residue parameter determined using the
first residue-estimating technique based on at least one of the
second estimated value or the differential between first and second
estimated values.
Inventors: |
Posselius; John; (Ephrata,
PA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
CNH Industrial America LLC |
New Holland |
PA |
US |
|
|
Assignee: |
CNH Industrial America LLC
|
Family ID: |
62186291 |
Appl. No.: |
16/376005 |
Filed: |
April 5, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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15596145 |
May 16, 2017 |
10262206 |
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16376005 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A01B 49/027 20130101;
A01B 76/00 20130101; G06K 2209/17 20130101; G06K 9/00657 20130101;
A01B 79/005 20130101; A01B 63/32 20130101 |
International
Class: |
G06K 9/00 20060101
G06K009/00; A01B 49/02 20060101 A01B049/02; A01B 63/32 20060101
A01B063/32; A01B 79/00 20060101 A01B079/00; A01B 76/00 20060101
A01B076/00 |
Claims
1-20. (canceled)
21. A method for calibrating crop residue data for a field acquired
using a vision-based system, the method comprising: receiving, with
a computing device, image data associated with one or more imaged
portions of a field from one or more imaging devices provided in
operative association with at least one of an implement or a work
vehicle coupled to the implement; analyzing, with the computing
device, the image data using a first residue-estimating technique
to generate a first set of residue data associated with a crop
residue parameter for the one or more imaged portions of the field;
analyzing, with the computing device, the image data using a second
residue-estimating technique to generate a second set of residue
data associated with the crop residue parameter for the one or more
imaged portions of the field, the second residue-estimating
technique differing from the first residue-estimating technique;
and calibrating, with the computing device, the first set of
residue data generated using the first residue-estimating technique
based at least in part on the second set of residue data generated
using the second residue-estimating technique.
22. The method of claim 21, wherein receiving the image data
associated with the one or more imaged portions of the field
comprises receiving the image data as the implement is being
traversed across the field to perform an agricultural
operation.
23. The method of claim 22, further comprising actively adjusting
the operation of at least one of the implement or the work vehicle
when an estimated value for the crop residue parameter determined
based on the calibrated data differs from a target value set for
the crop residue parameter.
24. The method of claim 21, wherein the crop residue parameter
corresponds to a percent crop residue coverage associated with the
imaged portion of the field.
25. The method of claim 21, wherein analyzing the image data using
the first residue-estimating technique comprises analyzing the
image data using a computer vision-based image processing
technique.
26. The method of claim 25, wherein the computer vision-based image
processing technique corresponds to a vision-based blob analysis of
the image data to generate the first set of residue data.
27. The method of claim 21, wherein analyzing the image data using
the second residue-estimating technique comprises analyzing the
image data using a computer vision-based line transect method.
28. The method of claim 27, wherein analyzing the image data using
the computer vision-based line transect method comprises: accessing
a plurality of images of the image data that collectively depict a
continuous imaged section of the field, the continuous imaged
section extending across a predetermined length; applying a known
scale to the continuous imaged section of the field such that a
plurality of reference points are associated with the continuous
imaged section; and determining a percentage of the plurality of
reference points that are aligned with or intersect crop residue
within the plurality of images.
29. A method for generating crop residue data, the method
comprising: receiving, with the computing device, image data
associated with an imaged portion of a field from one or more
imaging devices provided in operative association with at least one
of an implement or a work vehicle coupled to the implement;
analyzing, with the computing device, the image data using a
residue-estimating technique, the analysis comprising: accessing a
plurality of images of the image data that collectively depict a
continuous imaged section of the field, the continuous imaged
section extending across a predetermined length; applying a known
scale to the continuous imaged section of the field such that a
plurality of reference points are associated with the continuous
imaged section; and determining a percentage of the plurality of
reference points that are aligned with or intersect crop residue
within the plurality of images; and determining an estimated value
of a crop residue parameter for the imaged portion of the field
based at least in part on the percentage of the plurality of
reference points that are aligned with or intersect crop residue
within the plurality of images.
30. The method of claim 29, wherein receiving the image data
associated with the imaged portion of the field comprises receiving
the image data as the implement is being traversed across the field
to perform an agricultural operation.
31. The method of claim 30, further comprising actively adjusting
the operation of at least one of the implement or the work vehicle
when the estimated value for the crop residue parameter differs
from a target value set for the crop residue parameter.
32. The method of claim 29, wherein the crop residue parameter
corresponds to a percent crop residue coverage associated with the
imaged portion of the field.
33. The method of claim 29, wherein determining the percentage of
the plurality of reference points that are aligned with or
intersect crop residue within the plurality of images comprises
determining the percentage of the plurality of reference points
that are aligned with or intersect crop residue that exceeds a
given size threshold.
34. The method of claim 29, wherein applying the known scale to the
continuous imaged section of the field comprises applying the known
scale such that the plurality of reference points are spaced apart
evenly across the predetermined length.
35. The method of claim 29, further comprising: accessing a second
plurality of images of the image data that collectively depict one
or more additional continuous imaged sections of the field, each of
the one or more additional continuous imaged sections of the field
extending across the predetermined length; applying the known scale
to the one more additional continuous imaged sections of the field
such that a plurality of reference points are associated with each
of the one or more additional continuous imaged sections of the
field; determining a percentage of the plurality of reference
points that are aligned with or intersect crop residue within the
second plurality of images for each of the one or more additional
continuous imaged sections of the field; and determining the
estimated value of the crop residue parameter based on an average
of the determined percentages associated with the continuous image
section of the field and the one or more additional continuous
imaged sections of the field.
36. A vision-based system for estimating and adjusting crop residue
parameters as an implement is being towed across a field by a work
vehicle, the system comprising: an imaging device installed
relative to one of the work vehicle or the implement such that the
imaging device is configured to capture images of the field; a
controller communicatively coupled to the imaging device, the
controller including a processor and associated memory, the memory
storing instructions that, when implemented by the processor,
configure the controller to: receive, from the imaging device,
image data associated with one or more imaged portions of the
field; analyze the image data using a first residue-estimating
technique to generate a first set of residue data associated with a
crop residue parameter for the one or more imaged portions of the
field; analyze the image data using a second residue-estimating
technique to generate a second set of residue data associated with
the crop residue parameter for the one or more imaged portions of
the field, the second residue-estimating technique differing from
the first residue-estimating technique; and calibrate the first set
of residue data generated using the first residue-estimating
technique based at least in part on the second set of residue data
generated using the second residue-estimating technique.
37. The system of claim 36, wherein the imaging device comprises a
camera.
38. The system of claim 36, wherein the imaging device is installed
relative to one of the work vehicle or the implement such that a
field of view of the imaging device is directed either parallel or
perpendicular to a travel direction of the work vehicle.
39. The system of claim 36, wherein the crop residue parameter
corresponds to a percent crop residue coverage associated with the
imaged portion of the field.
40. The system of claim 36, wherein the second residue-estimating
technique corresponds to a computer vision-based line transect
method and wherein, when analyzing the image data using the
computer vision-based line transect method, the controller is
configured to: access a plurality of images of the image data that
collectively depict a continuous imaged section of the field, the
continuous imaged section extending across a predetermined length;
apply a known scale to the continuous imaged section of the field
such that a plurality of reference points are associated with the
continuous imaged section; and determine a percentage of the
plurality of reference points that are aligned with or intersect
crop residue within the plurality of images.
Description
FIELD OF THE INVENTION
[0001] The present subject matter relates generally to a
vision-based system for automatically acquiring crop residue data
while an operation a tillage operation is being performed within a
field and, more particularly, to related methods for calibrating a
vision-based system used to acquire crop residue data.
BACKGROUND OF THE INVENTION
[0002] Crop residue generally refers to the vegetation (e.g.,
straw, chaff, husks, cobs) remaining on the soil surface following
the performance of a given agricultural operation, such as a
harvesting operation or a tillage operation. For various reasons,
it is important to maintain a given amount of crop residue within a
field following an agricultural operation. Specifically, crop
residue remaining within the field can help in maintaining the
content of organic matter within the soil and can also serve to
protect the soil from wind and water erosion. However, in some
cases, leaving an excessive amount of crop residue within a field
can have a negative effect on the soil's productivity potential,
such as by slowing down the warming of the soil at planting time
and/or by slowing down seed germination. As such, the ability to
monitor and/or adjust the amount of crop residue remaining within a
field can be very important to maintaining a healthy, productive
field, particularly when it comes to performing tillage
operations.
[0003] In this regard, vision-based systems have been developed
that attempt to estimate crop residue coverage from images captured
of the field. However, such vision-based systems suffer from
various drawbacks or disadvantages, particularly with reference to
the accuracy of the crop residue estimates provided through the use
of computer-aided image processing techniques.
[0004] Accordingly, an improved vision-based system for acquiring
crop residue data and related methods for calibrating such a system
to improve the accuracy of the crop residue estimates provided
therewith would be welcomed in the technology.
BRIEF DESCRIPTION OF THE INVENTION
[0005] Aspects and advantages of the invention will be set forth in
part in the following description, or may be obvious from the
description, or may be learned through practice of the
invention.
[0006] In one aspect, the present subject matter is directed to a
method for calibrating crop residue data for a field acquired using
a vision-based system. The method may include controlling, with a
computing device, an operation of at least one of an implement or a
work vehicle as the implement is being towed by the work vehicle
across the field and receiving, with the computing device, image
data associated with an imaged portion of the field. In addition,
the method may include analyzing, with the computing device, the
image data using a first residue-estimating technique to determine
a first estimated value of a crop residue parameter for the imaged
portion of the field and analyzing, with the computing device, the
image data using a second residue-estimating technique to determine
a second estimated value of the crop residue parameter for the
imaged portion of the field, wherein the second residue-estimating
technique differs from the first residue-estimating technique.
Moreover, when a differential exists between the first and second
estimated values, the method may also include adjusting at least
one of the first estimated value or one or more additional
estimated values of the crop residue parameter determined using the
first residue-estimating technique based on at least one of the
second estimated value or the differential between first and second
estimated values.
[0007] In another aspect, the present subject matter is directed to
a vision-based system for estimating and adjusting crop residue
parameters as an implement is being towed across a field by a work
vehicle. The system may include an imaging device installed
relative to one of the work vehicle or the implement such that the
imaging device is configured to capture images of the field. The
system may also include a controller communicatively coupled to the
imaging device, with the controller including a processor and
associated memory. The memory may store instructions that, when
implemented by the processor, configure the controller to receive,
from the imaging device, image data associated with an imaged
portion of the field, analyze the image data using a first
residue-estimating technique to determine a first estimated value
of a crop residue parameter for the imaged portion of the field,
and analyze the image data using a second residue-estimating
technique to determine a second estimated value of the crop residue
parameter for the imaged portion of the field, wherein the second
residue-estimating technique differs from the first
residue-estimating technique. Moreover, when a differential exists
between the first and second estimated values, the controller may
be configured to adjust at least one of the first estimated value
or one or more additional estimated values of the crop residue
parameter determined using the first residue-estimating technique
based on at least one of the second estimated value or the
differential between first and second estimated values.
[0008] These and other features, aspects and advantages of the
present invention will become better understood with reference to
the following description and appended claims. The accompanying
drawings, which are incorporated in and constitute a part of this
specification, illustrate embodiments of the invention and,
together with the description, serve to explain the principles of
the invention.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] A full and enabling disclosure of the present invention,
including the best mode thereof, directed to one of ordinary skill
in the art, is set forth in the specification, which makes
reference to the appended figures, in which:
[0010] FIG. 1 illustrates a perspective view of one embodiment of a
work vehicle towing an implement in accordance with aspects of the
present subject matter;
[0011] FIG. 2 illustrates a perspective view of the implement shown
in FIG. 1;
[0012] FIG. 3 illustrates a schematic view of one embodiment of a
vision-based system for acquiring crop residue data in accordance
with aspects of the present subject matter;
[0013] FIG. 4 illustrates an example, simplified view of an image
of a field acquired using an imaging device(s) of the disclosed
system, particularly illustrating how the image may be analyzed
using one embodiment of a vision-based residue-estimating technique
in accordance with aspects of the present subject matter;
[0014] FIG. 5 illustrates an example, simplified view of a
continuous imaged section of a field acquired using an imaging
devices) of the disclosed system, particularly illustrating how the
images associated with the continuous imaged section of the field
may be analyzed using another embodiment of a vision-based
residue-estimating technique in accordance with aspects of the
present subject matter;
[0015] FIG. 6 illustrates a flow diagram of one embodiment of a
method for calibrating crop residue data for a field acquired using
a vision-based system in accordance with aspects of the present
subject matter.
DETAILED DESCRIPTION OF THE INVENTION
[0016] Reference now will be made in detail to embodiments of the
invention, one or more examples of which are illustrated in the
drawings. Each example is provided by way of explanation of the
invention, not limitation of the invention. In fact, it will be
apparent to those skilled in the art that various modifications and
variations can be made in the present invention without departing
from the scope or spirit of the invention. For instance, features
illustrated or described as part of one embodiment can he used with
another embodiment to yield a still further embodiment. Thus, it is
intended that the present invention covers such modifications and
variations as come within the scope of the appended claims and
their equivalents.
[0017] In general, the present subject matter is directed to a
vision-based system for acquiring crop residue data associated with
a field. In addition, the present subject matter is directed to
methods for calibrating crop residue acquired using a vision-based
system. Specifically, in several embodiments, one or more imaging
devices (e.g., a camera(s)) may be provided in operative
association with a work vehicle and/or an associated implement to
capture images of a field as an operation (e.g., a tillage
operation) is being performed within the field. The images may then
be automatically analyzed via an associated controller using two
different computer vision-based techniques to estimate a crop
residue parameter for the imaged portion of the field (e.g., the
percent crop residue coverage). For instance, a first vision-based
residue-estimating technique (e.g., a computer vision-based blob
analysis or other data extraction techniques) may be used to
determine a first estimated value for the crop residue parameter
associated with the imaged portion of the field while a second
vision-based residue-estimating technique (e.g., a computer
vision-based linear transact method) may be used to determine a
second estimated value for the crop residue parameter associated
with same imaged portion of the field. The first and second
estimated values determined using the differing residue-estimating
techniques may then be compared to determine whether a differential
exists between the estimated values. In the event that the separate
residue-estimating techniques provide differing values for the crop
residue parameter, the estimated value determined using one of the
residue-estimating techniques may be calibrated or adjusted based
on the estimated value determined using the other
residue-estimating technique (or based on the differential between
the two estimated values) to improve the accuracy of the crop
residue data.
[0018] Referring now to drawings, FIGS. 1 and 2 illustrate
perspective views of one embodiment of a work vehicle 10 and an
associated agricultural implement 12 in accordance with aspects of
the present subject matter. Specifically, FIG. 1 illustrates a
perspective view of the work vehicle 10 towing the implement 12
(e.g., across a field). Additionally, FIG. 2 illustrates a
perspective view of the implement 12 shown in FIG. 1. As shown in
the illustrated embodiment, the work vehicle 10 is configured as an
agricultural tractor. However, in other embodiments, the work
vehicle 10 may be configured as any other suitable agricultural
vehicle.
[0019] As particularly shown in FIG. 1, the work vehicle 10
includes a pair of front track assemblies 14, a pair or rear track
assemblies 16 and a frame or chassis 18 coupled to and supported by
the track assemblies 14, 16. An operator's cab 20 may be supported
by a portion of the chassis 18 and may house various input devices
for permitting an operator to control the operation of one or more
components of the work vehicle 10 and/or one or more components of
the implement 12. Additionally, as is generally understood, the
work vehicle 10 may include an engine 22 (FIG. 3) and a
transmission 24 (FIG. 3) mounted on the chassis 18. The
transmission 24 may be operably coupled to the engine 22 and may
provide variably adjusted gear ratios for transferring engine power
to the track assemblies 14, 16 via a drive axle assembly (not
shown) (or via axles if multiple drive axles are employed).
[0020] Moreover, as shown in FIGS. 1 and 2, the implement 12 may
generally include a carriage frame assembly 30 configured to be
towed by the work vehicle via a pull hitch or tow bar 32 in a
travel direction of the vehicle (e.g., as indicated by arrow 34).
As is generally understood, the carriage frame assembly 30 may be
configured to support a plurality of ground-engaging tools, such as
a plurality of shanks, disk blades, leveling blades, basket
assemblies, and/or the like. In several embodiments, the various
ground-engaging tools may be configured to perform a tillage
operation across the field along which the implement 12 is being
towed.
[0021] As particularly shown in FIG. 2, the carriage frame assembly
30 may include aft extending carrier frame members 36 coupled to
the tow bar 32. In addition, reinforcing gusset plates 38 may be
used to strengthen the connection between the tow bar 32 and the
carrier frame members 36. In several embodiments, the carriage
frame assembly 30 may generally function to support a central frame
40, a forward frame 42 positioned forward of the central frame 40
in the direction of travel 34 of the work vehicle 10, and an aft
frame 44 positioned aft of the central frame 40 in the direction of
travel 34 of the work vehicle 10. As shown in FIG. 2, in one
embodiment, the central frame 40 may correspond to a shank frame
configured to support a plurality of ground-engaging shanks 46. In
such an embodiment, the shanks 46 may be configured to till the
soil as the implement 12 is towed across the field. However, in
other embodiments, the central frame 40 may be configured to
support any other suitable ground-engaging tools.
[0022] Additionally, as shown in FIG. 2, in one embodiment, the
forward frame 42 may correspond to a disk frame configured to
support various gangs or sets 48 of disk blades 50. In such an
embodiment, each disk blade 50 may, for example, include both a
concave side (not shown) and a convex side (not shown). In
addition, the various gangs 48 of disk blades 50 may be oriented at
an angle relative to the travel direction 34 of the work vehicle 10
to promote more effective tilling of the soil. However, in other
embodiments, the forward frame 42 may be configured to support any
other suitable ground-engaging tools.
[0023] Moreover, similar to the central and forward frames 40, 42,
the aft frame 44 may also be configured to support a plurality of
ground-engaging tools. For instance, in the illustrated embodiment,
the aft frame is configured to support a plurality of leveling
blades 52 and rolling (or crumbler) basket assemblies 54. However,
in other embodiments, any other suitable ground-engaging tools may
be coupled to and supported by the aft frame 44, such as a
plurality closing disks.
[0024] In addition, the implement 12 may also include any number of
suitable actuators (e.g., hydraulic cylinders) for adjusting the
relative positioning, penetration depth, and/or down force
associated with the various ground-engaging tools 46, 50, 52, 54.
For instance, the implement 12 may include one or more first
actuators 56 coupled to the central frame 40 for raising or
lowering the central frame 40 relative to the ground, thereby
allowing the penetration depth and/or the down pressure of the
shanks 46 to be adjusted. Similarly, the implement 12 may include
one or more second actuators 58 coupled to the disk forward frame
42 to adjust the penetration depth and/or the down pressure of the
disk blades 50. Moreover, the implement 12 may include one or more
third actuators 60 coupled to the aft frame 44 to allow the aft
frame 44 to be moved relative to the central frame 40, thereby
allowing the relevant operating parameters of the ground-engaging
tools 52, 54 supported by the aft frame 44 (e.g., the down pressure
and/or the penetration depth) to be adjusted.
[0025] It should be appreciated that the configuration of the work
vehicle 10 described above and shown in FIG. 1 is provided only to
place the present subject matter in an exemplary field of use.
Thus, it should be appreciated that the present subject matter may
be readily adaptable to any manner of work vehicle configuration.
For example, in an alternative embodiment, a separate frame or
chassis may be provided to which the engine, transmission, and
drive axle assembly are coupled, a configuration common in smaller
tractors. Still other configurations may use an articulated chassis
to steer the work vehicle 10, or rely on tires/wheels in lieu of
the track assemblies 14, 16.
[0026] It should also be appreciated that the configuration of the
implement 12 described above and shown in FIGS. 1 and 2 is only
provided for exemplary purposes. Thus, it should be appreciated
that the present subject matter may be readily adaptable to any
manner of implement configuration. For example, as indicated above,
each frame section of the implement 12 may be configured to support
any suitable type of ground-engaging tools, such as by installing
closing disks on the aft frame 44 of the implement 12.
[0027] Additionally, in accordance with aspects of the present
subject matter, the work vehicle 10 and/or the implement 12 may
include one or more imaging devices coupled thereto and/or
supported thereon for capturing images or other image data
associated with the field as an operation is being performed via
the implement Specifically, in several embodiments, the imaging
devices) may be provided in operative association with the work
vehicle 10 and/or the implement 12 such that the imaging device(s)
has a field of view directed towards a portion(s) of the field
disposed in front of, behind, and/or along one or both of the sides
of the work vehicle 10 and/or the implement 12 as the implement 12
is being towed across the field. As such, the imaging device(s) may
capture images from the tractor 10 and/or implement 12 of one or
more portion(s) of the field being passed by the tractor 10 and/or
implement 12.
[0028] In general, the imaging device(s) may correspond to any
suitable device(s) configured to capture images or other image data
of the field that allow the field's soil to be distinguished from
the crop residue remaining on top of the soil. For instance, in
several embodiments, the imaging device(s) may correspond to any
suitable camera(s), such as single-spectrum camera or a
multi-spectrum camera configured to capture images in the visible
light range and/or infrared spectral range. Additionally, in a
particular embodiment, the camera(s) may correspond to a single
lens camera configured to capture two-dimensional images or a
stereo camera(s) having two or more lenses with a separate image
sensor for each lens to allow the camera(s) to capture
stereographic or three-dimensional images. Alternatively, the
imaging device(s) may correspond to any other suitable image
capture device(s) and/or vision system(s) that is capable of
capturing "images" or other image-like data that allow the crop
residue existing on the soil to be distinguished from the soil.
[0029] It should be appreciated that work vehicle 10 and/or
implement 12 may include any number of imaging device(s) 104
provided at any suitable location that allows images of the field
to be captured as the vehicle 10 and implement 12 traverse through
the field. For instance, FIGS. 1 and 2 illustrate examples of
various locations for mounting one or more imaging device(s) for
capturing images of the field. Specifically, as shown in FIG. 1, in
one embodiment, one or more imaging devices 104A may be coupled to
the front of the work vehicle 10 such that the imaging device(s)
104A has a field of view 106 that allows it to capture images of an
adjacent area or portion of the field disposed in front of the work
vehicle 10. For instance, the field of view 106 of the imaging
device(s) 104A may be directed outwardly from the front of the work
vehicle 10 along a plane or reference line that extends generally
parallel to the travel direction 34 of the work vehicle 10. In
addition to such imaging device(s) 104A (or as an alternative
thereto), one or more imaging devices 104B may also be coupled to
one of the sides of the work vehicle 10 such that the imaging
device(s) 104B has a field of view 106 that allows it to capture
images of an adjacent area or portion of the field disposed along
such side of the work vehicle 10. For instance, the field of view
106 of the imaging device(s) 104B may be directed outwardly from
the side of the work vehicle 10 along a plane or reference line
that extends generally perpendicular to the travel direction 34 of
the work vehicle 10.
[0030] Similarly, as shown in FIG. 2, in one embodiment, one or
more imaging devices 104C may be coupled to the rear of the
implement 12 such that the imaging device(s) 104C has a field of
view 106 that allows it to capture images of an adjacent area or
portion of the field disposed aft of the implement. For instance,
the field of view 106 of the imaging device(s) 104C may be directed
outwardly from the rear of the implement 12 along a plane or
reference line that extends generally parallel to the travel
direction 34 of the work vehicle 10. In addition to such imaging
device(s) 104C (or as an alternative thereto), one or more imaging
devices 1041) may also be coupled to one of the sides of the
implement 12 such that the imaging device(s) 104D has a field of
view 106 that allows it to capture images of an adjacent area or
portion of the field disposed along such side of the implement 12.
For instance, the field of view 106 of the imaging device 104D may
be directed outwardly from the side of the implement 12 along a
plane or reference line that extends generally perpendicular to the
travel direction 34 of the work vehicle 10.
[0031] It should be appreciated that, in alternative embodiments,
the imaging device(s) 104 may be installed at any other suitable
location that allows the device(s) to capture images of an adjacent
portion of the field, such as by installing an imaging device(s) at
or adjacent to the aft end of the work vehicle 10 and/or at or
adjacent to the forward end of the implement 10. It should also be
appreciated that, in several embodiments, the imaging devices 104
may be specifically installed at locations on the work vehicle 10
and/or the implement 12 to allow images to be captured of the field
both before and after the performance of a field operation by the
implement 12. For instance, by installing the imaging device 104A
at the forward end of the work vehicle 10 and the imaging device
104C at the aft end of the implement 12, the forward imaging device
104A may capture images of the field prior to performance of the
field operation while the aft imaging device 104C may capture
images of the same portions of the field following the performance
of the field operation.
[0032] Referring now to FIG. 3, a schematic view of one embodiment
of a vision-based system 100 for estimating crop residue parameters
is illustrated in accordance with aspects of the present subject
matter. In general, the system 100 will be described herein with
reference to the work vehicle 10 and the implement 12 described
above with reference to FIGS. 1 and 2. However, it should be
appreciated that the disclosed system 100 may generally be utilized
with work vehicles having any suitable vehicle configuration and/or
implements have any suitable implement configuration.
[0033] In several embodiments, the system 100 may include a
controller 102 and various other components configured to be
communicatively coupled to and/or controlled by the controller 102,
such as one or more imaging devices 104 and/or various components
of the work vehicle 10 and/or the implement 12. As will be
described in greater detail below, the controller 102 may be
configured to receive images or other image data from the imaging
device(s) 104 that depict portions of the field as an operation
(e.g., a tillage operation) is being performed within the field.
Based on an analysis of the image data received from the imaging
device(s) 104, the controller 102 may be configured to estimate a
first value for a crop residue parameter associated with the field
(e.g., a percent crop residue coverage) using a first
residue-estimating technique. Thereafter, the controller 102 may be
configured to analyze the same or similar images or other image
data to estimate a second value for the crop residue parameter
using a second residue-estimating technique that differs from the
first residue-estimating technique. Based on a comparison between
the estimated values for the crop residue parameter determined
using the two differing techniques, the controller may, if
necessary or desired, calibrate the crop residue date being
generated using one of the residue-estimating technique, such as by
adjusting the first estimated value for the crop residue parameter
determined using the first residue-estimating technique based on
the second estimated value determined using the second
residue-estimating technique.
[0034] In general, the controller 102 may correspond to any
suitable processor-based device(s), such as a computing device or
any combination of computing devices. Thus, as shown in FIG. 3, the
controller 102 may generally include one or more processor(s) 110
and associated memory devices 112 configured to perform a variety
of computer-implemented functions (e.g., performing the methods,
steps, algorithms, calculations and the like disclosed herein). As
used herein, the term "processor" refers not only to integrated
circuits referred to in the art as being included in a computer,
but also refers to a controller, a microcontroller, a
microcomputer, a programmable logic controller (PLC), an
application specific integrated circuit, and other programmable
circuits. Additionally, the memory 112 may generally comprise
memory element(s) including, but not limited to, computer readable
medium (e.g., random access memory (RAM)), computer readable
non-volatile medium (e.g., a flash memory), a floppy disk, a
compact disc-read only memory (CD-ROM), a magneto-optical disk
(MOD), a digital versatile disc (DVD) and/or other suitable memory
elements. Such memory 112 may generally be configured to store
information accessible to the processor(s) 110, including data 114
that can be retrieved, manipulated, created and/or stored by the
processor(s) 110 and instructions 116 that can be executed by the
processor(s) 110.
[0035] In several embodiments, the data 114 may be stored in one or
more databases. For example, the memory 112 may include an image
database 118 for storing image data received from the imaging
devices) 104. For example, the imaging device(s) 104 may be
configured to continuously or periodically capture images of
adjacent portion(s) of the field as an operation is being performed
with the field. In such an embodiment, the images transmitted to
the controller 102 from the imaging device(s) 104 may be stored
within the image database 118 for subsequent processing and/or
analysis. It should be appreciated that, as used herein, the term
image data may include any suitable type of data received from the
imaging device(s) 104 that allows for the crop residue coverage of
a field to be analyzed, including photographs and other
image-related data (e.g., scan data and/or the like).
[0036] Additionally, as shown in FIG. 3, the memory 12 may include
a crop residue database 120 for storing information related to crop
residue parameters for the field being processed. For example, as
indicated above, based on the image data received from the imaging
device(s) 104, the controller 102 may be configured to estimate or
calculate one or more values for one or more crop residue
parameters associated with the field, such as a value(s) for the
percent crop residue coverage for an imaged portion(s) of the field
(and/or a value(s) for the average percent crop residue coverage
for the field). The crop residue parameter(s) estimated or
calculated by the controller 102 may then be stored within the crop
residue database 120 for subsequent processing and/or analysis.
[0037] Moreover, in several embodiments, the memory 12 may also
include a location database 122 storing location information about
the work vehicle/implement 10, 12 and/or information about the
field being processed (e.g., a field map). Specifically, as shown
in FIG. 3, the controller 102 may be communicatively coupled to a
positioning device(s) 124 installed on or within the work vehicle
10 and/or on or within the implement 12. For example, in one
embodiment, the positioning device(s) 124 may be configured to
determine the exact location of the work vehicle 10 and/or the
implement 12 using a satellite navigation position system (e.g. a
GPS system, a Galileo positioning system, the Global Navigation
satellite system (GLONASS), the BeiDou Satellite Navigation and
Positioning system, and/or the like). In such an embodiment, the
location determined by the positioning device(s) 124 may be
transmitted to the controller 102 (e.g., in the form coordinates)
and subsequently stored within the location database 122 for
subsequent processing and/or analysis.
[0038] Additionally, in several embodiments, the location data
stored within the location database 122 may also be correlated to
the image data stored within the image database 118. For instance,
in one embodiment, the location coordinates derived from the
positioning device(s) 124 and the image(s) captured by the imaging
device(s) 104 may both be time-stamped. In such an embodiment, the
time-stamped data may allow each image captured by the imaging
device(s) 104 to be matched or correlated to a corresponding set of
location coordinates received from the positioning device(s) 124,
thereby allowing the precise location of the portion of the field
depicted within a given image to be known (or at least capable of
calculation) by the controller 102.
[0039] Moreover, by matching each image to a corresponding set of
location coordinates, the controller 102 may also be configured to
generate or update a corresponding field map associated with the
field being processed. For example, in instances in which the
controller 102 already includes a field map stored within its
memory 112 that includes location coordinates associated with
various points across the field, each image captured by the imaging
device(s) 104 may be mapped or correlated to a given location
within the field map. Alternatively, based on the location data and
the associated image data, the controller 102 may be configured to
generate a field map for the field that includes the geo-located
images associated therewith.
[0040] Referring still to FIG. 3, in several embodiments, the
instructions 116 stored within the memory 112 of the controller 102
may be executed by the processor(s) 110 to implement an image
analysis module 126. In general, the image analysis module 126 may
be configured to analyze the images received by the imaging
device(s) 104 using one or more residue-estimating techniques to
allow the controller 102 to estimate one or more crop residue
parameters associated with the field currently being processed. For
instance, in several embodiments, the image analysis module 126 may
be configured to implement two different residue-estimating
techniques (e.g., first and second residue-estimating techniques),
with each residue-estimating technique being based on a different
computer-vision algorithm or any other suitable image-processing
technique that allows the controller 102 to identify crop residue
remaining on top of the soil. By identifying all or a portion of
the crop residue contained within each image (or within a subset of
the images) using the two different residue-estimating techniques,
the controller 102 may then determine two values for the crop
residue parameter(s) associated with a given imaged portion of the
field. Such values may then be stored within the crop residue
database 120.
[0041] It should be appreciated that, in general, the
residue-estimating techniques used by the image analysis module 126
to estimate the crop residue parameter(s) may correspond to any
suitable computer-vision algorithms or image-processing techniques
that allow the controller 102 to identify crop residue remaining on
top of the soil. For instance, as will be described below with
reference to FIGS. 4 and 5, in one embodiment, the image analysis
module may be configured to utilize both a computer vision-based
blob analysis and a computer vision-based linear transact method to
estimate values for the crop residue parameter(s). The estimated
values determined using each of such residue-estimating techniques
may then be stored within the crop residue database 120 for
subsequent analysis and/or processing. However, in other
embodiments, the image analysis module 126 may be configured to
implement any other suitable vision-based residue-estimating
techniques to estimate the crop residue parameter(s).
[0042] Moreover, as shown in FIG. 3, the instructions 116 stored
within the memory 112 of the controller 102 may also be executed by
the processor(s) 110 to implement a calibration module 128. In
general, the calibration module 128 may be configured to calibrate
the crop residue data generated by the image analysis module 126
based on the estimated values determined using the differing
residue-estimating techniques. Specifically, in several
embodiments, the calibration module 128 may be configured to
compare the estimated value(s) of the crop residue parameter(s)
determined using the first residue-estimating technique to the
corresponding estimate value(s) of the crop residue parameter(s)
determined using the second residue-estimating technique. In such
embodiments, when a differential exists between the estimate
value(s) determined using the first residue-estimating technique
and the corresponding estimate value(s) determined using the second
residue-estimating technique, the calibration module 128 may be
configured to calibrate or adjust the estimated value(s) determined
using one of the residue-estimating techniques based on the
estimated value(s) determined using the other residue-estimating
technique,
[0043] For instance, in one embodiment, the estimated value(s)
determined using the second residue-estimating technique may be
used to calibrate or adjust the estimate value(s) determined using
the first residue-estimating technique. As an example, assuming
that residue-estimating techniques are being used to determine
estimated values of the percent crop residue coverage within the
field, the image analysis module 126 may analyze one or more images
of an imaged portion of the field and determine a first estimated
value of 45% crop residue coverage using the first
residue-estimating technique and a second estimated value of 50%
crop residue coverage using the second residue-estimating
technique. The calibration module 128 may then compare the first
and estimated values and determine that a 1-5% differential exists
between the estimated values. The calibration module 128 may then,
in one embodiment, adjust the first estimated value and/or any
future/past estimated values determined using the first
residue-estimating technique based on the second estimated value
and/or the differential determined between the first and second
estimated values. For instance, the calibration module 128 may be
configured to increase the first estimated value and/or any
future/past estimated values determined using the first
residue-estimating technique by 5% to ensure that the crop residue
data generated using the first residue-estimating technique is
consistent with the crop residue data generated using the second
residue-estimating technique.
[0044] It should be appreciated that, in addition to analyzing the
estimated values determined for a singled imaged portion of the
field or as an alternative thereto, the calibration module 128 may
be configured to analyze the estimated values determined for
various different imaged portions of the field. In such an
embodiment, the calibration module 128 may be configured to compare
the estimated values determined using the first and second
residue-estimating techniques for each imaged portion of the field
to determine an average differential existing between the first and
second estimated values. The calibration module 128 may then adjust
the first estimated value and/or any future/past estimated values
determined using the first residue-estimating technique based on
the average differential determined across the various imaged
portions of the field.
[0045] Additionally, it should be appreciated that, although the
present subject matter is generally described herein as using the
second estimated value(s) determined via the second
residue-estimating technique to calibrate or adjust the first
estimate value(s) determined via the first residue-estimating
technique, the configuration may be reversed, with the first
estimated value(s) being used to calibrate or adjust the second
estimated value(s). In general, the residue-estimating technique
used as the calibration source may be selected based on any number
of factors, including accuracy considerations, computer processing
requirements, standards or regulations set for crop residue data
and/or the like.
[0046] Referring still to FIG. 3, the instructions 116 stored
within the memory 112 of the controller 102 may also be executed by
the processor(s) 110 to implement a control module 129. In general,
the control module 129 may be configured to adjust the operation of
the work vehicle 10 and/or the implement 12 by controlling one or
more components of the implement/vehicle 12, 10. Specifically, in
several embodiments, when the estimated crop residue parameter
determined by the controller 102 differs from a given target set
for such parameter, the control module 129 may be configured to
fine-tune the operation of the work vehicle 10 and/or the implement
12 in a manner designed to adjust the amount of crop residue
remaining in the field. For instance, when it is desired to have a
percent crop residue coverage of 30%, the control module 129 may be
configured to adjust the operation of the work vehicle and/or the
implement 12 so as to increase or decrease the amount of crop
residue remaining in the field when the estimated percent crop
residue coverage for a given imaged portion of the field (or an
average estimated percent crop residue coverage across multiple
imaged portions of the field) differs from the target
percentage.
[0047] It should be appreciated that the controller 102 may be
configured to implement various different control actions to adjust
the operation of the work vehicle 10 and/or the implement 12 in a
manner that increases or decreases the amount of crop residue
remaining in the field. In one embodiment, the controller 102 may
be configured to increase or decrease the operational or ground
speed of the implement 12 to affect an increase or decrease in the
crop residue coverage. For instance, as shown in FIG. 3, the
controller 102 may be communicatively coupled to both the engine 22
and the transmission 24 of the work vehicle 10. In such an
embodiment, the controller 102 may be configured to adjust the
operation of the engine 22 and/or the transmission 24 in a manner
that increases or decreases the ground speed of the work vehicle 10
and, thus, the ground speed of the implement 12, such as by
transmitting suitable control signals for controlling an engine or
speed governor (not shown) associated with the engine 22 and/or
transmitting suitable control signals for controlling the
engagement/disengagement of one or more clutches (not shown)
provided in operative association with the transmission 24.
[0048] In addition to the adjusting the ground speed of the
vehicle/implement 10, 12 (or as an alternative thereto), the
controller 102 may also be configured to adjust an operating
parameter associated with the ground-engaging tools of the
implement 12. For instance, as shown in FIG. 3, the controller 102
may be communicatively coupled to one or more valves 130 configured
to regulate the supply of fluid (e.g., hydraulic fluid or air) to
one or more corresponding actuators 56, 58, 60 of the implement 12.
In such an embodiment, by regulating the supply of fluid to the
actuator(s) 56, 58, 60, the controller 102 may automatically adjust
the penetration depth, the down force, and/or any other suitable
operating parameter associated with the ground-engaging tools of
the implement 12.
[0049] Moreover, as shown in FIG. 3, the controller 102 may also
include a communications interface 132 to provide a means for the
controller 102 to communicate with any of the various other system
components described herein. For instance, one or more
communicative links or interfaces 134 (e.g., one or more data
buses) may be provided between the communications interface 132 and
the imaging device(s) 104 to allow images transmitted from the
imaging device(s) 104 to be received by the controller 102.
Similarly, one or more communicative links or interfaces 136 (e.g.,
one or more data buses) may be provided between the communications
interface 132 and the positioning device(s) 124 to allow the
location information generated by the positioning device(s) 124 to
be received by the controller 102. Additionally, as shown in FIG.
3, one or more communicative links or interfaces 138 (e.g., one or
more data buses) may be provided between the communications
interface 132 and the engine 22, the transmission 24, the control
valves 130, and/or the like to allow the controller 102 to control
the operation of such system components.
[0050] Referring now to FIG. 4, an example, simplified image of a
portion of a field that may be provided by one of the imaging
device(s) 104 of the disclosed system 100 is illustrated in
accordance with aspects of the present subject matter, particularly
illustrating the field including crop residue 160 (indicated by
cross-hatching) positioned on the top of the soil 162. As indicated
above, the image analysis module 126 of the controller 102 may
generally be configured to utilize any suitable computer-vision
algorithms or image-processing techniques that allow the controller
102 to identify crop residue 160 remaining on top of the soil 162.
For instance, in one embodiment, the vision-based technique used by
the image analysis module 126 may rely upon the identification of
one or more image characteristics captured by the imaging device(s)
104 to distinguish the crop residue 160 from the soil 162 contained
within each image. For instance, when the imaging device(s) 104
corresponds to a camera capable of capturing the distinction
between the reflective characteristics of the soil 162 and the crop
residue 160, the controller 102 may be configured to implement a
computer-vision algorithm that identifies the differences in the
reflectivity or spectral absorption between the soil 162 and the
crop residue 160 contained within each image being analyzed.
Alternatively, the controller 102 may be configured to utilize an
edge-finding algorithm to identify or distinguish the crop residue
160 from the soil 162 contained within each image.
[0051] Additionally, upon distinguishing the crop residue 160 from
the soil 162, the controller 102 may be configured to utilize any
suitable technique or methodology for calculating the percent crop
residue coverage for the portion of the field contained within each
image. For instance, as indicated above, the controller 102 may, in
one embodiment, utilize a "blob analysis" in which the crop residue
identified within each image via the associated computer-vision
technique is represented as a "blob" or plurality of "blobs"
encompassing a given area within the image. Specifically, as shown
in FIG. 4, the crop residue 160 depicted within the image is
represented as cross-hatched blobs overlaying the soil 162. In such
an embodiment, the image analysis module 126 may be configured to
calculate the percent crop residue coverage for the imaged portion
of the field using the following equation (Equation 1):
Percent Crop Residue = ( 1 - ( total image area - blob area ) total
image area ) * 100 ( 1 ) ##EQU00001##
[0052] wherein, the total image area corresponds to the total area
defined within the image (e.g., as a function of the total number
of pixels of the image) and the blob area corresponds to the total
area represented by crop residue 160 within the image (e.g., as a
function of the total number of pixels representing the identified
crop residue).
[0053] Referring now to FIG. 5, an example, simplified view of a
continuous section 170 of an imaged portion of a field is
illustrated in accordance with aspects of the present subject
matter. Specifically, FIG. 5 illustrates a plurality of images
captured by one or more of the imaging device(s) 104 of the
disclosed system 100 that collectively depict a continuous section
170 of the field. For instance, the field of view 106 of the
imaging device(s) 104 may allow the imaging device(s) 104 to
capture an image of the field that spans a given field distance. In
such an embodiment, to analyze a continuous section 170 of an
imaged portion of the field that extends across a predetermined
field length 172 that is greater than the field distance captured
within each image, multiple images may be stitched together or
otherwise analyzed in combination. For instance, in the example
view shown in FIG. 5, a plurality of images captured by one of the
imaging device(s) 104 have been stitched together (e.g., the
separate images being indicated by the dashed horizontal lines) to
provide a view of a continuous section 170 of the field that spans
across a predetermined field length 172.
[0054] It should be appreciated that the controller 102 (e.g., the
image analysis module 126) may be configured to identify which
images can be used to collectively depict a continuous section of
the field using any suitable methodology or technique. For
instance, as indicated above, the images provided by the imaging
device(s) 104 may be time-stamped. In such an embodiment, by
knowing the ground speed of the work vehicle/implement 10, 12 and
the field of view 106 of the imaging device(s) 104 relative to the
field, the controller 102 may be configured to stitch together or
otherwise access the images captured by the imaging device(s) 104
that collectively depict a continuous field section 170 spanning
across the predetermined field length 172. Alternatively, the
controller 102 may be configured to utilize any suitable
image-processing algorithm that allows the controller 102 to
identify the images (or portions of images) that collectively
depict a continuous section of the field.
[0055] By capturing images that collectively depict a continuous
section 170 of the field, the image analysis module 126 of the
controller 102 may, in several embodiments, be configured to
implement a computer vision-based line transact method to estimate
the percent crop residue coverage for the imaged portion of the
field. Specifically, in several embodiments, the image analysis
module 126 may access the images collectively depicting the
continuous imaged section 170 of the field and apply a known scale
174 to such continuous imaged section 170 of the field such that a
plurality of reference points 176 are defined along the continuous
imaged field section 170 that are spaced apart evenly across the
predetermined field length 172. Thereafter, the images may be
analyzed to identify the number or percentage of reference points
176 that are aligned with or intersect crop residue within the
continuous imaged section 170 of the field. Such identified number
or percentage of the reference points 176 may then correspond to or
may be used to calculate the percent crop residue coverage within
the continuous imaged section 170 of the field. For example, in one
embodiment, the percent crop residue coverage for the continuous
imaged section 170 of the field may be calculated using the
following equation (Equation 2):
Percent Crop Residue = ( identified reference points total
reference points ) * 100 ( 2 ) ##EQU00002##
[0056] wherein, the "identified reference points" correspond to the
total number of reference points 176 identified by the image
analysis module 126 that are aligned with or intersect crop residue
with the analyzed images and the "total reference points"
correspond to the total number of reference points 176 defined
across the predetermined field length 172 via the applied scale
174.
[0057] In several embodiments, the scale 174 applied to the
continuous imaged section 170 of the field may divide the
predetermined field length 172 into one hundred distinct field
sections such that one hundred reference points 176 are evenly
spaced apart along the predetermined field length 170. In such an
embodiment, it may be desirable for the continuous imaged section
170 of the field to correspond to a continuous field section
spanning one hundred feet (i.e., such that the predetermined field
length 172 is equal to one hundred feet). As a result, the imposed
scale 174 may divide the predetermined field length 172 into one
hundred one-foot sections, with a reference point 176 being defined
at each foot mark along the predetermined field length 172.
However, in other embodiments, the predetermined field length 172
may correspond to any other suitable field length, such as a fifty
foot field section, a twenty-five foot field section or any other
suitable field length. Similarly, any other suitable scale 174 may
be applied to the continuous imaged section 170 of the field to
allow any suitable number of evenly spaced reference points 176 to
be defined across the predetermined field length 172. For instance,
in alternative embodiments, a fifty-point scale or a
twenty-five-point scale may be applied such that fifty or
twenty-five evenly spaced reference points 176, respectively, are
defined across the predetermined field length 172.
[0058] It should be appreciated that, in several embodiments, the
image analysis module 126 may only be configured to identify the
reference points 176 within the images that are aligned with or
intersect crop residue that exceeds a given residue size threshold
for purposes of calculating the percent crop residue coverage for
the continuous imaged section 170 of the field. Specifically, in
several embodiments, the size threshold for the crop residue may be
selected based on the minimum residue size capable of intercepting
rain drops. For instance, in one embodiment, the residue size
threshold may correspond to a residue diameter of one-eighth of an
inch (1/8''). In such an embodiment, if the crop residue aligned
with or intersecting one of the reference points 176 is determined
to have a cross-wise dimension within the image that exceeds 1/8''
(e.g., via a suitable image analysis technique), such reference
point 176 may be counted for purposes of calculating the percent
crop residue coverage for the continuous imaged section 170 of the
field. However, if the crop residue aligned with or intersecting
one of the reference points 176 is determined to have a cross-wise
dimension within the image that is less than 1/8'', such reference
point 176 may not be counted for purposes of calculating the
percent crop residue coverage.
[0059] It should also be appreciated that, in several embodiments,
the image analysis module 126 may be configured to perform the
above-referenced analysis for multiple imaged sections of the
field. For example, the image analysis module 126 may access images
captured by the imaging device(s) 104 that collectively depict
several different continuous imaged sections of the field, with
each continuous imaged field section spanning a predetermined field
length. Thereafter, for each continuous imaged section of the
field, the image analysis module 126 may apply a known scale to
such continuous imaged field section such that a plurality of
reference points are defined along the continuous imaged field
section that are spaced apart evenly across the predetermined field
length. The images associated with each continuous imaged section
of the field may then be analyzed to identify the number or
percentage of reference points that are aligned with or intersect
crop residue within such continuous imaged section of the field,
thereby allowing a value for the percent crop residue coverage to
be determined for each continuous imaged field section. In such an
embodiment, the image analysis module 126 may then calculate an
average percent crop residue coverage based on the residue coverage
values calculated for the various continuous imaged field sections.
In doing so, it may be desirable for the average percent crop
residue coverage to be calculated based on the residue coverage
values determined for at least five continuous imaged field
sections, thereby allowing a desirable confidence level to be
obtained for the calculated average.
[0060] Referring now to FIG. 6, a flow diagram of one embodiment of
a method 200 for calibrating crop residue data acquired using a
vision-based system is illustrated in accordance with aspects of
the present subject matter. In general, the method 200 will be
described herein with reference to the work vehicle 10 and the
implement 12 shown in FIGS. 1 and 2, as well as the various system
components shown in FIG. 3. However, it should be appreciated that
the disclosed method 200 may be implemented with work vehicles
and/or implements having any other suitable configurations and/or
within systems having any other suitable system configuration. In
addition, although FIG. 6 depicts steps performed in a particular
order for purposes of illustration and discussion, the methods
discussed herein are not limited to any particular order or
arrangement. One skilled in the art, using the disclosures provided
herein, will appreciate that various steps of the methods disclosed
herein can be omitted, rearranged, combined, and/or adapted in
various ways without deviating from the scope of the present
disclosure.
[0061] As shown in FIG. 6, at (202), the method 200 may include
controlling the operation of at least one of an implement or a work
vehicle as the implement is being towed by the work vehicle across
a field. Specifically, as indicated above, the controller 102 of
the disclosed system 100 may be configured to control the operation
of the work vehicle 10 and/or the implement 12, such as by
controlling one or more components of the work vehicle 10 and/or
the implement 12 to allow an operation to be performed within the
field (e.g., a tillage operation).
[0062] Additionally, at (204), the method 200 may include receiving
image data associated with an imaged portion of the field.
Specifically, as indicated above, the controller 102 may be coupled
to one or more imaging devices 104 configured to capture images of
various portions of the field.
[0063] Moreover, at (206), the method 200 may include analyzing the
image data using a first residue-estimating technique to determine
a first estimated value of a crop residue parameter for the imaged
portion of the field. For instance, as indicated above, the image
analysis module 126 of the controller 102 may be configured to
implement a vision-based residue-estimating technique to estimate a
crop residue parameter for the imaged portion of the field, such as
by estimating the percent crop residue coverage for the imaged
portion of the field using a computer vision-based blob analysis or
using a computer vision-based line transact method.
[0064] Referring still to FIG. 6, at (208), the method 200 may
include analyzing the image data using a second residue-estimating
technique to determine a second estimated value of the crop residue
parameter for the imaged portion of the field. Specifically, as
indicated above, the image analysis module 126 of the controller
102 may, in accordance with aspects of the present subject matter,
be configured to implement two different vision-based
residue-estimating techniques for estimating a given crop residue
parameter for the imaged portion of the field. For instance, in an
embodiment in which the first residue-estimating technique
corresponds to a computer vision-based blob analysis, the second
residue estimating technique may, for example, correspond to a
computer vision-based line transact method or vice versa. As such,
the controller 102 may determine two separate estimated values for
the crop reside parameter using the two different
residue-estimating techniques.
[0065] Additionally, at (210), the method 200 may include adjusting
at least one of the first estimated value or one or more additional
estimated values of the crop residue parameter obtained using the
first residue-estimating technique based on at least one of the
second estimated value or the differential between first and second
estimated values. Specifically, as indicated above, when a
differential exists between the first and second estimated values,
the controller 102 may be configured to adjust the first estimated
value determined using the first residue-estimated technique based
on the second estimated value determined using the second
residue-estimated technique and/or based on the differential
existing between the first and second estimated values. For
example, assuming that a percent crop residue coverage of 40% is
determined using the first residue-estimating technique and a
percent crop residue coverage of 32% is determined using the second
residue-estimating technique, the controller 102 may, in one
embodiment, the adjust the estimated percent crop residue coverage
associated with the first residue-estimating technique to match the
percent crop residue coverage associated with the second
residue-estimating technique (e.g., by reducing the percent crop
residue coverage from 40% to 32%). In addition, the controller 102
may also utilize the differential defined between the first and
second estimated values to adjust any past or future estimated
values determined using the first residue-estimating technique,
such as by applying a -8% modifier to each estimated value
determined using the first residue-estimating technique.
[0066] It should be appreciated that, although not shown, the
method 200 may also include any additional steps or method elements
consistent with the disclosure provided herein. For example, the
method 200 may also include actively adjusting the operation of the
implement 12 and/or the work vehicle 10 when the adjusted value for
the first estimated value and/or the adjusted value(s) for the one
or more additional estimated values determined using the first
residue-estimating technique differs from a target value set for
crop residue parameter. Specifically, as indicated above, when the
estimated crop residue parameter differs from a target value set
for such parameter, the controller 102 may be configured to
actively adjust the operation of the work vehicle 10 and/or the
implement 12 in a manner that increases or decreases the amount of
crop residue remaining within the field following the operation
being performed (e.g., a tillage operation), such as by adjusting
the ground speed at which the implement 12 is being towed and/or by
adjusting one or more operating parameters associated with the
ground-engaging elements of the implement 12.
[0067] This written description uses examples to disclose the
invention, including the best mode, and also to enable any person
skilled in the art to practice the invention, including making and
using any devices or systems and performing any incorporated
methods. The patentable scope of the invention is defined by the
claims, and may include other examples that occur to those skilled
in the art. Such other examples are intended to be within the scope
of the claims if they include structural elements that do not
differ from the literal language of the claims, or if they include
equivalent structural elements with insubstantial differences from
the literal languages of the claims.
* * * * *