NZ758463B2 - An agricultural system - Google Patents
An agricultural systemInfo
- Publication number
- NZ758463B2 NZ758463B2 NZ758463A NZ75846318A NZ758463B2 NZ 758463 B2 NZ758463 B2 NZ 758463B2 NZ 758463 A NZ758463 A NZ 758463A NZ 75846318 A NZ75846318 A NZ 75846318A NZ 758463 B2 NZ758463 B2 NZ 758463B2
- Authority
- NZ
- New Zealand
- Prior art keywords
- data
- baler
- field
- route
- bale
- Prior art date
Links
- 239000000463 material Substances 0.000 claims description 58
- 238000000034 method Methods 0.000 description 13
- 239000000446 fuel Substances 0.000 description 5
- 238000004590 computer program Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000004566 IR spectroscopy Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 239000010902 straw Substances 0.000 description 2
- 230000001052 transient effect Effects 0.000 description 2
- 244000025254 Cannabis sativa Species 0.000 description 1
- 241000209140 Triticum Species 0.000 description 1
- 235000021307 Triticum Nutrition 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000003028 elevating effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
Classifications
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01B—SOIL WORKING IN AGRICULTURE OR FORESTRY; PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES OR IMPLEMENTS, IN GENERAL
- A01B69/00—Steering of agricultural machines or implements; Guiding agricultural machines or implements on a desired track
- A01B69/007—Steering or guiding of agricultural vehicles, e.g. steering of the tractor to keep the plough in the furrow
- A01B69/008—Steering or guiding of agricultural vehicles, e.g. steering of the tractor to keep the plough in the furrow automatic
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/0088—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
-
- G05D2201/0201—
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
Abstract
system comprising a controller (104) associated with an agricultural vehicle (100). The controller (104) is configured to determine route-plan-data (112) that is representative of a route to be taken by the agricultural vehicle (100) in an agricultural field (102), based on bale-location-data (110). The bale-location-data (110) is representative of the location of bales (108) in the agricultural field (102). ). The bale-location-data (110) is representative of the location of bales (108) in the agricultural field (102).
Description
AN AGRICULTURAL SYSTEM
Background of the Invention
Determining an accurate route plan for an agricultural machine in an agricultural
field can enable crop material to be picked up in an efficient way, in terms of the length of
time the operation takes, and the amount of fuel used by the machine, for example. In
some applications, agricultural machines can be operated autonomously using such a
route plan.
Summary of the Invention
It is an object of the invention to provide a system and method to determine an
accurate route plan for an agricultural machine in an agricultural field to enable crop
material to be picked up in an efficient way or which at least provides the public or industry
with a useful choice.
According to a first aspect of the invention, there is provided a system comprising:
a controller associated with an baler, the controller configured to: determine route-plan-
data that is representative of a route to be taken by the baler in an agricultural field, based
on bale-location-data, wherein the bale-location-data is representative of the location of
bales in the agricultural field.
The controller may be configured to determine the route-plan-data such that the
agricultural vehicle will avoid the locations of the bales.
The controller may be configured to determine the route-plan-data such that the
agricultural vehicle will deposit future bales in the vicinity of the locations of the bales in
the agricultural field.
The agricultural vehicle may be a baler.
The controller may be further configured to: receive field-data that is representative
of crop material that is to be picked up from the agricultural field by the baler; and
determine the route-plan-data also based on the field-data.
The controller may be configured to receive updated field-data as the agricultural
machine picks up the crop material from the agricultural field.
The controller may be configured to determine the route-plan-data by modifying
an earlier route plan whilst the baler is in use in the agricultural field.
The route-plan-data may comprise a sequence of locations that the baler will pass.
The controller may be configured to determine vehicle-control-instructions for the
baler, based on the route-plan-data. The vehicle-control-instructions may comprise
vehicle-steering-instructions for automatically controlling the direction of travel of the
baler. The vehicle-control-instructions may further comprise route-speed-instructions for
automatically controlling the speed of the baler at locations along the route.
The system may further comprise: an unmanned vehicle configured to acquire:
field-data, representative of an agricultural field that has one or more bales located in it;
and field-location-data associated with the field-data.
The controller may be configured to determine the bale-location-data based on the
field-data and the field-location-data.
The controller may be further configured to: determine bale-dimension-data that is
representative of the size of the one or more bales, based on the field-data; and determine
the bale-location-data based on the bale-dimension-data.
The controller may be configured to: receive baler-data from a baler that deposits
the bales in the agricultural field; and determine the bale-location-data based on the baler-
data.
The baler-data may comprise: baler-location-data representative of the location of
the baler at an instant in time that the baler deposits a bale in the field; and / or bale-
dimension-data that is representative of the size of the bale.
The route-plan-data may be representative of a route to be taken by the baler for
an entire unprocessed portion of the agricultural field. In this way, the route-plan-data can
use a (revised) map of the unprocessed swath, based on the actual path that the baler
has already taken in the field. This would not necessarily have been known at the start of
the operation, because the route-plan may have been dynamically modified after the start
of the operation.
The system may further comprise an baler that is configured to be operated in
accordance with the vehicle-control-instructions.
There may be provided a computer-implemented method of:
determining route-plan-data that is representative of a route to be taken by
an baler in an agricultural field, based on bale-location-data, wherein the bale-location-
data is representative of the location of bales in an agricultural field.
There may be provided a method of controlling an agricultural machine, the
method comprising:
determining route-plan-data that is representative of a route to be taken by
an baler in an agricultural field, based on bale-location-data, wherein the bale-location-
data is representative of the location of bales in the agricultural field;
determining vehicle-control-instructions for the baler, based on the route-
plan-data; and
operating the baler in accordance with the vehicle-control-instructions.
There may be provided a computer program, which when run on a computer,
causes the computer to configure any apparatus, including a controller, processor,
machine, vehicle or device disclosed herein or perform any method disclosed herein. The
computer program may be a software implementation, and the computer may be
considered as any appropriate hardware, including a digital signal processor, a
microcontroller, and an implementation in read only memory (ROM), erasable
programmable read only memory (EPROM) or electronically erasable programmable read
only memory (EEPROM), as non-limiting examples.
The computer program may be provided on a computer readable medium, which
may be a physical computer readable medium such as a disc or a memory device, or may
be embodied as a transient signal. Such a transient signal may be a network download,
including an internet download.
Brief Description of the Drawings
Embodiments of the present invention will now be described by way of example
and with reference to the accompanying drawings in which:
Figure 1 shows an example of an agricultural field;
Figure 2 shows schematically a system that is associated with determining a route
for an agricultural vehicle to follow in an agricultural field;
Figure 3 shows schematically another system that is associated with determining
a route that a baler can follow in an agricultural field; and
Figure 4 shows schematically a further system that is associated with determining
a route for a baler to follow in an agricultural field.
Detailed Description of the Drawings
Figure 2 shows schematically a system that is associated with determining a route
for an agricultural vehicle to follow in an agricultural field 102, as shown in Figure 1. In
this example, the agricultural vehicle is a baler 100. The system includes a controller 104
that is associated with the baler 100. It will be appreciated that the controller 104 can be
located on the baler 100, or remotely from the baler 100. For example, the functionality
of the controller 104 can be performed on a remote server, such as one “in the cloud”.
The field 102 includes rows of crop material, which may be hay, straw or similar
products that have been left in the field 102 in the form of swaths 106. The swaths 106
are elongate rows of the products in question that are heaped in the transverse centre
and tend to flatten at the respective transverse edges. Typically a field 102 that has
undergone harvesting contains many, essentially mutually parallel, swaths 106, as shown
in Figure 1. The swaths are spaced from one another by largely consistent gaps. The
crop material in the swaths 106 can be picked up by the baler 100, and then deposited in
the field 102 as bales 108. The field 102 that is shown in Figure 1 has been partly
processed, in that it includes both rows of swath 106 for baling, and also completed bales
108. It will be appreciated that more than one baler 100 may be working in the same field
102 simultaneously.
The controller 104 associated with the baler 100 receives bale-location-data 110
that is representative of the location of the bales 108 in the agricultural field 102, and
determines route-plan-data 112. The route-plan-data 112 is representative of a route to
be taken by the baler 100 in the agricultural field, based on the bale-location-data 110.
As will be discussed in detail below, such processing can enable a route plan for the baler
100 to be adapted in real-time, whilst the baler 100 is in the field 102, to avoid the locations
of bales 108 that have been dropped in the field 102 after the baler 100 (or another baler)
started processing the swaths 106 in the field 102.
In some examples the controller 104 can determine the route-plan-data 112 by
modifying an earlier route plan whilst the baler 100 is in use in the field 102. For instance,
an initial route plan can be generated for the baler 100 to pick up the swaths 106 of crop
material. However, when that initial route plan is generated, it may not be possible to
accurately determine where the baler 100 is going to deposit bales 108 in the field. If a
bale 108a is deposited near a headland at the end of a row of swath 106a, then that bale
108a may inhibit the baler 100 from turning into an adjacent row of swath 106a from a
certain direction. That is, if the baler 100 turned into the adjacent row of swath 106a with
a left turn, then the baler 100 (or a tractor pulling the baler if it is not self-powered) may
drive over the bale 108a and destroy it. Whereas, if the baler 100 turned into the adjacent
row of swath 106a with a right turn, then the baler 100 can avoid the bale 108a.
The route-plan-data 112 can comprise a sequence of locations for the baler 100
to pass when picking up the crop material in the swaths 106. For example, the controller
104 can determine a shortest possible route for picking up all of the crop material, whilst
avoiding the bales 108 that have already been deposited in the field 102.
In examples where the baler 100 is pulled by a tractor, the route-plan-data 112
can include baler-route-plan-data and tractor-route-plan-data. In this way, the controller
104 can ensure that both the baler 100 and the tractor avoid the bales 108. It may only
be necessary to provide the tractor-route-plan-data as an output because it is this data
that can be used by an operator to drive the tractor such that the baler 100 follows the
desired route. Alternatively, the tractor can be controlled autonomously using the tractor-
route-plan-data, such that the baler 100 follows the desired route. It will be appreciated
that any description in this document of controlling the baler 100, can equally apply to
controlling a tractor that is pulling the baler 100. This is because any such control of the
tractor can be considered as indirectly controlling the baler 100.
The route-plan-data 112 can be representative of a route to be taken by the baler
100 / tractor for an entire unprocessed / un-baled portion of the field 102. That is, the
route-plan-data 112 can be determined such that it takes into account the portions of the
field 102 that have already been baled, whilst ensuring that a route is planned for baling
the crop material in each of the remaining swaths 106.
Figure 3 shows schematically another system that is associated with determining
a route that a baler 200 can follow in an agricultural field (as shown in Figure 1). The
system includes a controller 204 and the baler 200. The controller 204 can be used to
autonomously control the baler 200 (or a tractor that pulls the baler 200). That is, the
system can be considered as including the baler 200 that is configured to be operated in
accordance with vehicle-control-instructions.
In this example the controller 204 receives baler-data 214, and determines bale-
location-data 210 based on the baler-data 214. The baler-data 214 can be received from
a baler 200 that deposits the bales in the agricultural field. This could be the same baler
200 that the route is being prepared for, or a different baler if more than one baler is
working the same field. For instance, inter-vehicle communication can be used if there is
more than one machine / baler working on the field. In this way, they can communicate
to share their information about obstacles / bales. This communication can be direct or
indirect, such as through “the cloud”.
As will be appreciated from the following description, if the “other vehicle” is
another (autonomous) baling machine, then it can send one or more of the estimated
location, orientation, dimensions and drop time of bales that have already been dropped,
and / or a future bale that is to be dropped, for example using a bale-drop-estimation
algorithm. An example of a bale-drop-estimation algorithm will be discussed in more detail
below.
The baler-data 214 can include baler-location-data representative of the location
of the baler 200 at instants in time that the baler 200 deposits bales in the field. Such
information may be stored, and made available, each time the baler 200 deposits a bale.
The controller 204 can determine the bale-location-data 210 as a single set of coordinates
for each bale. The single set of coordinates may be representative of the location of the
expected centre of the bale, for example, and could be calculated by the controller 204
applying an offset to the location of the baler 200 (as determined from the baler-location-
data) when the bale was dropped. The offset can be indicative of a distance between: (i)
a location-determining-module (such as a GPS receiver) that is fitted to the baler 200; and
(ii) an exit point of the baler 200 from which the bale is dropped. The controller 204 can
apply the offset to the location of the baler 200 in a direction that is opposite to the direction
of travel of the baler 200 when the bale was dropped.
In some examples, the baler-data provided by the baler 200 may also include bale-
dimension-data, which is representative of the size and / or shape of the bale. The bale-
dimension-data may be fixed / hard-coded for a specific baler, or it may be determined
using one or more sensors that measures the dimensions of each individual bale that is
produced. In such examples, the controller 204 can determine the bale-location-data 210
as multiple sets of coordinates for each bale. The multiple sets of coordinates may be
representative of the locations of one or more corners of the bale, for example, and may
be sufficient such that, together, they can be used to determine the perimeter of a two-
dimensional footprint of the bale (when viewed from above), or to determine the perimeter
of the three-dimensional volume of the bale.
The controller 204 can determine the multiple sets of coordinates by applying
offsets to the location of the baler (baler-location-data) when the bale was dropped. The
controller 204 can determine the offsets based on the bale-dimension-data. Optionally,
the controller 204 can also determine the offsets based on a distance between: (i) a
location-determining-module that is fitted to the baler 200; and (ii) an exit point of the baler
200 from which the bale is dropped.
The controller 204 can then determine route-plan-data 212, which is
representative of a route to be taken by the baler 200 in the agricultural field, based on
the bale-location-data 210 that was calculated using the baler-data 214.
In this example, the controller 204 determines vehicle-control-instructions 218 for
the baler 200, based on the route-plan-data 212.
The vehicle-control-instructions 218 can comprise vehicle-steering-instructions for
automatically controlling the direction of travel of the baler 200, such that the baler 200
follows a specific route through the agricultural field. In this way, the baler 200 can be
autonomously controlled such that it follows a specific route through the agricultural field
in order to pick up crop material from the field. In addition to, or instead of, avoiding bales
that have already been deposited in the field, as discussed above, the route can be
planned such that it provides one or more advantages, for example:
(i) efficient baler / tractor usage, such as low overall fuel consumption to pick up
and bale all of the crop material from the field;
(ii) efficient baling in terms of the time required to bale all of the crop material in
the field; and
(iii) prioritising pick up of crop material with particular characteristics (as defined
by crop-property-data for example, as will be discussed below), such as portions of swath
that have a high volume of crop material; and
(iv) dropping bales close to each other, for example, to drop future bales in the
vicinity of existing bales, where possible. This can make the subsequent collection of the
bales more efficient. “In the vicinity of” can be implemented by an algorithm that minimises
the distance between adjacent bales and / or attempts to drop future bales less than a
threshold-distance away from an adjacent bale.
A route that is planned so that bales are dropped close to each other can find
particular application for grass baling, for example if there are a lot of small fields to be
baled, with small / short swaths. In such examples, less than 1 bale may be generated
per row of swath, in which case the route can be planned such that bales are dropped in
adjacent swaths to optimize the gathering of the bales. Also, in some specific situations,
the route can be planned such that the baler skips a part of the swath (for example by
elevating a pick-up on the baler) in order to optimize bale drop locations. Then the skipped
portions of the swath can be picked up and baled afterwards. Although this might add
some time to the baling process, it can gain efficiency during bale gathering.
In some examples, the controller 204 can also use baler-location data and / or
baler-direction-data, that is representative of a current location and direction of travel of
the baler 200 for which the route plan is being determined, to determine the route-plan-
data 212.
The vehicle-control-instructions can also comprise route-speed-instructions for
automatically controlling the speed of the baler 200 at locations along the route. For
instance, the vehicle-control-instructions can also comprise vehicle-steering-instructions
and route-speed-instructions such that the baler 200 can make a turn in the field with a
desired turning angle, at an appropriate speed for the turn, such that the baler 200 avoids
bales that have already been deposited in the field.
In this example, the controller 204 also receives field-data 216, which is
representative of an agricultural field that is to be processed by the baler 200. For
example, the field-data 216 is representative of the swaths of crop material that are to be
picked up from the field by the baler. In one instance, the field-data 216 can be
representative of the location of the swaths of crop material that are still to be baled. The
field-data 216 can also be representative of one or more properties of the swaths of crop
material. In some examples, the controller 204 receives updated field-data 216 as the
baler 200 picks up the crop material from the field.
The controller 204 can determine the route-plan-data 212 also based on the field-
data 216. In this way, both the locations of the bales, and properties of the un-baled
swaths (such as the locations of the swaths), can be used to determine the route-plan-
data 212. In other examples, the field-data 216 can be used to determine the bale-
location-data 210, as will be discussed detail below with reference to Figure 4.
As indicated above, a bale-drop-estimation algorithm can be used to determine
bale-location-data that is representative of the location at which bales will be dropped in
the agricultural field in the future. This can allow the baler 200 to adapt its trajectory before
a bale has been physically dropped. For example, where the 3D volume data of the swath
is available, the bale-drop-estimation algorithm can estimate a future bale drop location
based on a density-setting that the machine is using (which is representative of the
intended crop density in the bale). This approach can also optionally use material-density-
values that are representative of the density of the uncompressed swath when it is lying
in in the field. The material-density-value may have a predetermined / assumed value. In
some examples, the bale-drop-estimation algorithm can dynamically adjust the material-
density-value based on a feedback signal. For example, the feedback signal may be
representative of the swath-volume-data and / or a measured bale weight at the bale
chute. If the swath-volume-data is available, then a controller can determine the volume
(for example in m³) of uncompressed crop that has been used to form a bale. Then, when
the bale is formed, the weight of the bale can measured (for example in kg) when it is on
the bale chute. Therefore, the controller can divide the bale weight [kg] by the
uncompressed crop volume [m³], to determine the average swath-density [kg/m³] for that
bale, and the controller can use this value as an estimation of the likely density for future
bales.
In another example, the bale-drop-estimation algorithm can receive an input-signal
that is representative of measured / sensed material-density-values. This can enable the
algorithm to more accurately predict the locations of further bale drops. Irrespective of
how the material-density-values are determined, it will be appreciated that the bale-drop-
estimation algorithm can apply a correction to the material-density-value for the specific
type of crop that is being processed.
Inputs for a bale-drop-estimation algorithm that can be performed for bales that
are to be dropped by “an other” baler, or the baler 200, can include one or more of:
• swath-location-data, which is representative of the location of swath that is still to
be baled;
• crop-property-data, which, as discussed below can be representative of the crop
material in the agricultural field, and can include material-density-values;
• driving speed, which can be current driving-speed or planned future driving-speed
of the baler as it follows a route;
• GPS-data, which can be current GPS-data;
• length wheel-data (data coming from a starwheel in a bale chamber), which can
be used as a feedback signal to check if the estimated slice thickness corresponds with
the actual slice thickness. If there is an error, then parameters of the bale-drop-estimation
algorithm can be adjusted so that the estimated slice thickness more closely corresponds
with the actual slice thickness, and therefore the accuracy of the bale-drop-estimation
algorithm can be improved;
• knotter signal, which is representative of when a bale has ended and a new bale
has started to form. It can also be used as a feedback signal for fine-tuning parameters
of the bale-drop-estimation algorithm; and
• desired trajectory, which can be representative of a planned route for the baler.
Figure 4 shows schematically a further system that is associated with determining
a route for a baler 300 to follow in an agricultural field 302. Features of Figure 4 that are
also shown in Figure 2 or Figure 3 have been given corresponding reference numbers in
the 300 series, and will not necessarily be described again here.
The system includes a vehicle 320. In this example the vehicle is an unmanned
vehicle 320. The unmanned vehicle 320 can be an unmanned aerial vehicle (sometimes
referred to as a drone). In other examples, the vehicle 320 could be a land vehicle, which
may or may not be unmanned.
The unmanned vehicle 320 can include one or more sensors for obtaining field-
data 316, and a field of view 326 of such a sensor is shown schematically in Figure 4.
In this example, the unmanned vehicle 320 includes a sensor 322 that can acquire
field-data 316. In this example the sensor 322 is a camera that can acquire field-image-
data. The field-image-data can be two-dimensional-image-data or three-dimensional-
image-data, and in some examples the camera can be a 3D-scanner or 3D-camera.
Alternatively, or additionally, the field-data 316 can include: field-radar-data
acquired by a radar, field-LIDAR-data acquired by a LIDAR sensor; field-moisture-data
acquired by a moisture-sensor, field-IR-data acquired by an infra-red-sensor, ultrasonic-
data acquired by an ultrasonic sensor, or any other type of field-data from any type of
sensor that can acquire information about the agricultural field 302 or the crop material in
the agricultural field 302. The controller 304 can process one or more of these different
types of field-data 316, either directly or indirectly, in order to determine the route-plan-
data 312, and optionally vehicle-control-instructions (not shown).
In some examples, the controller 304 can determine crop-property-data that is
representative of the crop material in the agricultural field 302, based (directly or indirectly)
on the field-data 316. For instance, the controller 304 can perform an object recognition
algorithm on the field-image-data in order to determine one or more of crop-type; length
of stalks in the material, material density, and stub-height-information. The stub height is
the height at which the crop is cut off. In some conditions, such as for wheat straw, the
swath lays on top of the stubs, which causes the swath to look bigger than it actually is.
In some examples, the controller 304 can also, or instead, process different types
of field-data to determine the crop-property-data. For instance, the controller 304 can
process field-IR-data to determine the temperature of crop material, or the controller 304
can process field-moisture-data to determine the humidity / wetness of crop material.
In one example, the crop-property-data can include material-size-data that is
representative of the size of the crop material in the agricultural field 302. Such material-
size-data can include the height, width, cross-sectional area, volume, or shape of the
swath 306. The crop-property-data can therefore represent one-dimensional, two-
dimensional or three-dimensional physical characteristics of the crop material, and can be
determined based on two-dimensional-image-data or three-dimensional-image-data.
The controller 304 can then determine the route-plan-data 312 for the baler 300
based on one or more of the above types of crop-property-data. In some examples, the
controller 304 determines vehicle-control-instructions for the baler 300 based on one or
more of the above types of crop-property-data. For example, the controller 304 may
cause the baler 300 to travel: (i) more slowly over large portions of crop material (for
instance portions that have a material-size-data (such as cross-sectional area) that is
greater than a size-threshold-value); (ii) more quickly over thin portions of crop material
(for instance portions that have a density that is less than a density-threshold-value), (iii)
in a zig-zag path over very narrow swaths to get a good feeding of a pre-compression
chamber of the baler 300; and (iv) not changing the speed too aggressively (for example
such that the acceleration / deceleration of the baler 300 is not greater than a speed-
change-threshold) if there is a small interruption of the swath 306 to improve driver comfort
(for example, a small interruption can be identified as a height of the swath 306 that is
less than a swath-height-threshold for a length of the path that is less than a path-length-
threshold).
It will be appreciated that the above examples are non-limiting and that the baler
can be automatically controlled based on crop-property-data in numerous other ways. In
some examples, different options can be selected by the operator of the baler/tractor,
such as when starting a baling operation. For instance, when starting a field, the operator
may be able to enter a ‘setting’ such as the following:
- If I hit a wet spot: how should the controller control the baler / tractor - slow
down the speed and continue baling or lift the pick-up; and / or
- If a highly compressed swath is detected: how should the controller control
the baler / tractor - slow down the speed and continue baling or lift the pick-up.
In this way, the controller can determine vehicle-control-instructions for the baler
300 based on: (i) one or more of the above types of crop-property-data; and (ii) user input.
Therefore, in a number of ways, the controller 304 can determine vehicle-control-
instructions and / or route-plan-data 312 based on the crop-property-data. For instance,
the controller 304 may plan the route for the baler 300 such that regions of the crop
material with a higher density are picked up before regions of the crop material that have
a lower density. This may be advantageous so that the most valuable crop material (in
terms of volume of crop per distance travelled by the baler 300) is picked up first. In
another example, the controller 304 may plan the route such that the baler 300 picks up
regions of the crop material that have a lower humidity before regions of the crop material
that have a higher humidity. In this way, the more humid crop material will have longer to
dry out. As a further example, the controller 304 can determine the route-plan-data 312
for the baler 300 based on the time of day that the crop material is to be picked up and /
or a measured or predicted temperature of the crop material. It can be advantageous for
the crop material to be as cool as possible for baling (for better friction properties).
Therefore, the route-plan-data 312 can be planned such that the crop material that is
picked up is likely to be below a crop-temperature-threshold. As yet further example, the
controller 304 can determine the route-plan-data for the baler 300 based on the humidity
/ wetness of crop material such that wet spots of the crop material can be baled after each
other so as not to mix wet and dry crop in the same bales.
The controller 304 can determine field-property-data that is representative of a
property of the agricultural field 302, based on the field-data 316. For instance, the
controller 304 can determine first regions of field-data that correspond to the swaths 306
of crop material, and second regions of the field-data that correspond to the agricultural
field 302 (outside the perimeter of the first regions of field-data). As discussed above, the
controller 304 can determine crop-property-data based on data that corresponds to the
first regions of field-data. The controller 304 can also determine field-property-data based
on the second regions, and then determine the vehicle-control-instructions and / or route-
plan-data 312 based on the field-property-data.
The field-property-data can include field-wetness-data that is representative of the
wetness of the agricultural field 302. In such an example, the controller 304 can process
field-data to identify the locations of the second regions of the field-data that correspond
to the agricultural field 302, and then determine the field-wetness-data based on field-
moisture-data acquired by a moisture-sensor for the identified second regions. The
controller 304 can then control the speed of the baler 300 accordingly, for example to
prevent the baler 300 from travelling faster than a speed-threshold-value in parts of the
field 302 that have a field-wetness-data that exceeds a wetness-threshold-value.
The field-property-data can also include field-contour-data that is representative
of contours of the agricultural field 302. A user can provide the field-contour-data to the
controller 304 in some examples because this data acquisition can be considered as a
one-time job. In other examples, the controller 304 can determine the field-contour-data
based on the field-image-data or field-radar-data, for example. The controller 304 can
then determine the vehicle-control-instructions and / or route-plan-data 312 based on the
field-contour-data. For instance, for regions of the agricultural field 302 that have a steep
slope (for example, field-contour-data that is representative of a gradient that is greater
than a gradient-threshold-value), the controller 304 may determine route-speed-
instructions for automatically controlling the speed of the baler 300 such that it does not
exceed a speed-threshold-value. Also, in such circumstances, the controller 304 may
determine vehicle-steering-instructions that prevent a steering angle of the baler 300 from
exceeding a steering-angle-threshold-value. As another example, the controller 304 can
determine the route-plan-data for the baler 300 based on the field-contour-data. For
example, the controller 304 can calculate a route that, for a big swath on a flank, results
in the baler 300 picking up the crop material as it is travelling down a slope that has a
gradient that is greater than a gradient-threshold-value. This can provide advantages
because in some applications, a tractor that is pulling baler 300 may not have sufficient
power to maintain its optimal speed.
In some examples, the vehicle 320 can include a height-measurement-sensor for
acquiring material-height-data representative of the height of the crop material. The
controller 304 can then determine the vehicle-control-instructions and / or route-plan-data
312 based on the material-height-data. For instance, the controller 304 may set the route-
speed-instructions for the baler 300 based on the material-height-data, such that the baler
300 travels more slowly when the height of the crop material is relatively large. The height
measurement can be used as an indicator of the size of the swath 306. If multiple height
measurements are taken whilst the vehicle 320 is moving, they can be combined in order
to provide a 3D-scan. The height-measurement-sensor can also be used to measure
stub-height-information, which is representative of stub height, if the stub density is high
enough. Irrespective of how the stub height is determined, in some examples the
controller 304 can subtract the stub height from the measured height of the crop in order
to determine swath-height-data. The controller 304 can then determine the vehicle-
control-instructions and / or route-plan-data 312 based on the swath-height-data.
In some examples, the controller 304 can determine a bale-count, representative
of an estimate of the number of bales that will be attained by picking up all of the crop
material, based on the field-data 316. For instance, the controller 304 can process
material-size-data (representative of the size of the crop material), and calculate total-
crop-amount that is representative of the total amount of crop that is to be picked up. The
controller 304 can then divide the total-crop-amount by the volume of a single bale to
determine the bale-count. Providing the bale-count as an output can be useful for
planning the operation of picking up the crop material. For instance, the number of trucks
that will be needed to collect the bales 308, and how long the job will take, can be
estimated in advance. This type of information can be particularly advantageous inputs
for work planning. For instance, the controller 304 can process the total-crop-volume and
/ or bale-count in order to determine energy requirements of the baler 300. For example,
if the total-crop-volume is very large, then the controller 304 can determine that the baler
300 will have to return at some point to a location where it can refill with more energy /
fuel. Therefore, the controller 304 can determine a route that takes this into account, and
/ or can automatically control the baler 300 such that its available energy / fuel is used in
an appropriate way for the required future refill of energy / fuel. The controller 304 can
determine both an initial bale-count and / or energy requirements prior to the operation of
picking up the crop material, and an updated bale-count and energy requirements during
the operation.
The vehicle 320 can acquire: (i) field-data 316 that is representative of the
agricultural field 302 that has one or more bales 308 located in it; and (ii) field-location-
data (not shown) associated with the field-data 316. The controller 304 can optionally
determine the route-plan-data 312 based on the field-data 316 and the field-location-data.
In this example, the vehicle 320 acquires field-location-data associated with field-
image-data. For example, the vehicle 320 may have a location-determining-system 324,
such as GPS, that provides vehicle-location-data that is representative of the location of
the vehicle 320 when the field-image-data is acquired. The controller 304 may also
receive camera-direction-data and vehicle-altitude-data. The camera-direction-data may
be representative of the direction that the camera is facing relative to the vehicle 320. The
camera-direction-data may be hard coded if the camera is non-movably fixed to the
vehicle 320. If the camera is movably mounted to the vehicle 320, then the camera-
direction-data can take different values, which may be received as an input-signal at the
controller 304 from the vehicle 320. The controller 304 can then use a simple
trigonometric algorithm to attribute field-location-data to objects / areas that are
represented by the field-image-data based on the vehicle-location-data, the camera-
direction-data, a vehicle-altitude-data (if the vehicle 320 is an aerial vehicle), and a
direction of travel of the vehicle 320, as is known in the art.
Also, in this example, the controller 304 determines bale-location-data 310 based
on the field-data 316 and the field-location-data. The controller 304 can also determine
bale-dimension-data that is representative of the size of the one or more bales, based on
the field-data and / or the field-location-data. As discussed above, the controller 304 can
then determine the bale-location-data 310 also based on the bale-dimension-data.
Use of an aerial vehicle 320 can enable field-data 316 to be acquired from a
relatively high altitude to obtain an overview of the field 302, thereby providing a wide field
of view. Subsequently or alternatively, the aerial vehicle 320 can stay with the baler 300
at a lower altitude. The gathered field-data 316 can be streamed to the controller 304 and
/ or “the cloud”. When the aerial vehicle 320 stays with the baler, one or more of the
following strategies can be deployed. Firstly, the aerial vehicle 320 can fly above the baler
300 to get information about the surroundings of the baler 300. In this way, it can detect
objects ahead of the baler 300 and also map the bales 308 dropping from the back of the
baler 300. Secondly, the aerial vehicle 320 can fly ahead of the baler 300 to scan the
future trajectory of the baler 300 for objects. Thirdly, the aerial vehicle 320 can scan the
whole field 302 to get an overview of any obstacles, including bales 308. During baling,
another strategy can be used: fourthly, the aerial vehicle can fly behind the baler 300 to
scan the produced bales for precise coordinates and dimensions (referred to above as
bale-location-data / bale-dimension-data).
It will be appreciated that one or more of the functions of the vehicle 320 that are
described with reference to Figure 4 could be implemented by the agricultural vehicle /
baler 300 itself in some examples. For example, field-data and crop-property-data could
be determined by processing signals acquired by sensors on the agricultural vehicle /
baler 300.
One or more of the examples disclosed herein can improve the safety with which
a baler operates because collisions with objects, such as bales, are less likely.
Systems described herein can dynamically map obstacles in the field during
baling, and can utilise technology to gather the data for mapping the obstacles,
determining a route for the baler and / or automatically controlling the baler. In some
examples, a drone can be used for mapping the objects. Also, information about the bales
that is produced by the baler itself, can be used.
It will be appreciated that any of the control operations disclosed herein, such as
setting the speed or direction of travel of the baler or an associated tractor, can be
performed by comparing data with one or more threshold values, applying an algorithm to
data, or using a look-up-table / database to determine a control value based on received
/ determined data.
Claims (14)
1. A system comprising: a controller associated with an baler, the controller configured to determine route- plan-data that is representative of a route to be taken by the baler in an agricultural field, 5 based on bale-location-data, the bale-location-data is representative of the location of bales in the agricultural field, wherein the controller is configured to determine the route- plan-data such that the baler will avoid the locations of the bales in the agricultural field and wherein the controller is configured to determine the route-plan-data such that the baler will deposit future bales in the vicinity of the locations of the bales in the agricultural 10 field.
2. The system of claim 1, wherein the controller is further configured to: receive field-data that is representative of crop material that is to be picked up from the agricultural field by the baler; and 15 determine the route-plan-data also based on the field-data.
3. The system of claim 2, wherein the controller is configured to receive updated field- data as the agricultural machine picks up the crop material from the agricultural field. 20
4. The system of any of the preceding claims, wherein the controller is configured to determine the route-plan-data by modifying an earlier route plan whilst the baler is in use in the agricultural field.
5. The system of any of the preceding claims, wherein the controller is configured to 25 determine vehicle-control-instructions for the baler, based on the route-plan-data.
6. The system of claim 5, wherein the vehicle-control-instructions comprise vehicle- steering-instructions for automatically controlling the direction of travel of the baler. 30
7. The system of claim 6, wherein the vehicle-control-instructions further comprise route-speed-instructions for automatically controlling the speed of the baler at locations along the route.
8. The system of any of the preceding claims, further comprising: an unmanned vehicle configured to acquire: field-data, representative of an agricultural field that has one or more bales located in it; and 5 field-location-data associated with the field-data; and wherein the controller is configured to determine the bale-location-data based on the field-data and the field-location-data.
9. The system of claim 8, wherein the controller is further configured to: 10 determine bale-dimension-data that is representative of the size of the one or more bales, based on the field-data; and determine the bale-location-data based on the bale-dimension-data.
10. The system of any of the preceding claims, wherein the controller is configured to: 15 receive baler-data from a baler that deposits the bales in the agricultural field; and determine the bale-location-data based on the baler-data.
11. The system of claim 10, wherein the baler-data comprises: baler-location-data representative of the location of the baler at an instant in time 20 that the baler deposits a bale in the field; and bale-dimension-data that is representative of the size of the bale.
12. The system of any of the preceding claims, wherein the route-plan-data is representative of a route to be taken by the baler for an entire unprocessed portion of the 25 agricultural field.
13. The system of claim 5, wherein the system further comprises an baler that is configured to be operated in accordance with the vehicle-control-instructions. 30
14. The system of claim 1 as hereinbefore described with reference to the figures.
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
BE2017/5336A BE1024459B1 (en) | 2017-05-09 | 2017-05-09 | AGRICULTURAL SYSTEM |
BE2017/5336 | 2017-05-09 | ||
PCT/EP2018/061901 WO2018206592A1 (en) | 2017-05-09 | 2018-05-08 | An agricultural system |
Publications (2)
Publication Number | Publication Date |
---|---|
NZ758463A NZ758463A (en) | 2021-06-25 |
NZ758463B2 true NZ758463B2 (en) | 2021-09-28 |
Family
ID=
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