Patent Publication Number: US-2023143025-A1

Title: Air seeding turn compensation using yaw rate from sensor on towing vehicle

Description:
FIELD OF THE DESCRIPTION 
     The present description relates to agricultural equipment. More specifically, the present description relates to a system for performing seeding turn compensation by sensing yaw rate on a towing vehicle. 
     BACKGROUND 
     There are a wide variety of different types of agricultural equipment that can be used to plant seeds or apply other commodities to a field. Such equipment can include planters which have row units. Each row unit has a seed tank that carries seed that is to be planted by that row unit. The seed is metered and singulated from the tank on each row unit and can be dropped into a furrow created by the row unit or it can be actively moved to the furrow. Other equipment can include air seeders. Air seeders have a central seed or commodity tank. The seed or commodity tank is metered and delivered to furrows through tubes using air delivery. The furrows are opened by a furrow opener. 
     When applying seed or fertilizer or other materials, it is important to apply the correct amount per acre. Over-seeding can result in wasted product, while under-seeding can result in lower yield per acre than the field could otherwise support. For fertilizer, over application can result in damage to the plant, while under-application can reduce the efficacy of the application. 
     As a planting tool (or seeding tool) travels around a curve, the outer end of the seeding tool moves over the field more quickly than the inner end of the seeding tool. Therefore, if a static seeding rate is maintained during a curve, than the outer portion of the seeding tool under-seeds while the inner portion of the seeding tool over-seeds. Therefore, some seeding tools include curve compensation functionality. This type of functionality varies the seeding rate across the seeding tool while seeding around a corner, such as around the borders of the field and when going around water holes in the field, and other obstacles. The seed rate is varied in order to more closely obtain a uniform seeding rate on the ground. Therefore, the seed delivery rate is controlled to be higher on the part of the seeding tool that is navigating the outer part of the turn and lower on the part of the seeding tool that is navigating the inner part of the turn. 
     Some current curve compensation functionality uses a yaw rate sensor mounted on the seeding tool frame or speed sensors mounted on the extremities of the seeding tool frame. The instantaneous yaw rate is used to compensate the speed of the seed meter to vary the planting rate as the planting tool travels around the curve. 
     The discussion above is merely provided for general background information and is not intended to be used as an aid in determining the scope of the claimed subject matter. 
     SUMMARY 
     A yaw rate is sensed on a towing vehicle that is towing an air application implement. The sensed yaw rate is used to predict a future yaw rate on the air application implement. An application rate of material is varied across the application implement based upon the predicted yaw rate across the implement. 
     Example 1 is an agricultural system, comprising: 
     a towing vehicle; 
     an agricultural machine, coupled to the towing vehicle, including an application tool that applies material to a field at work points distributed along a transverse axis of the application tool; 
     an instantaneous yaw rate detector detecting an instantaneous yaw rate of the towing vehicle; 
     a tool yaw rate prediction system predicting, based on the instantaneous yaw rate detected on the towing vehicle, a plurality of different yaw rate values, each predicted yaw rate value of the plurality of different predicted yaw rate values corresponding to each work point of a set of the work points distributed along the transverse axis of the application tool; and 
     a meter controller generating a control signal to control a meter that controls a rate at which the material is provided to the work points based on the plurality of different predicted yaw rate values. 
     Example 2 is the agricultural system of any or all previous examples wherein the agricultural machine comprises: 
     an air cart that provides the material to the application tool through the meter. 
     Example 3 is the agricultural system of any or all previous examples and further comprising: 
     a yaw rate aggregator aggregating a plurality of detected instantaneous yaw rates to obtain a set of aggregated instantaneous yaw rates. 
     Example 4 is the agricultural system of any or all previous examples wherein the tool yaw rate prediction system is configured to predict, based on the aggregated instantaneous yaw rates, the plurality of different yaw rate values. 
     Example 5 is the agricultural system of any or all previous examples wherein the tool yaw rate prediction system comprises: 
     a curve/table accessing system configured to access a pre-defined correlation that correlates instantaneous yaw rate values to predicted yaw rate values to obtain the plurality of different predicted yaw rate values. 
     Example 6 is the agricultural system of any or all previous examples wherein the tool yaw rate prediction system comprises: 
     a runtime calculation system configured to perform a run time calculation based on the instantaneous yaw rate values to obtain the plurality of different predicted yaw rate values. 
     Example 7 is the agricultural system of any or all previous examples wherein the meter controller comprises: 
     a curve/table accessing system configured to access a pre-defined correlation that correlates predicted yaw rate values to control signal values to obtain the control signal. 
     Example 8 is the agricultural system of any or all previous examples wherein the meter controller comprises: 
     a runtime calculation system configured to perform a run time calculation based on the predicted yaw rate values to obtain the control signal. 
     Example 9 is the agricultural system of any or all previous examples wherein the instantaneous yaw rate detector comprises: 
     a wheel angle detector configured to detect a wheel angle of a wheel on the towing vehicle. 
     Example 10 is the agricultural system of any or all previous examples wherein the instantaneous yaw rate detector comprises: 
     a steering wheel angle detector configured to detect a steering wheel angle of a steering wheel on the towing vehicle. 
     Example 11 is a computer-implemented method of controlling an agricultural machine, comprising: 
     detecting, on a towing vehicle, an instantaneous yaw rate of the towing vehicle, the towing vehicle towing an application tool that applies material to a field at work points distributed along a transverse axis of the application tool; 
     predicting, based on the instantaneous yaw rate detected on the towing vehicle, a plurality of different yaw rate values, each predicted yaw rate value of the plurality of different predicted yaw rate values corresponding to each work point of a set of the work points distributed along the transverse axis of the application tool; and 
     generating a control signal to control a meter that controls a rate at which the material is provided to the work points based on the plurality of different predicted yaw rate values. 
     Example 12 is the computer-implemented method of any or all previous examples and further comprising: 
     aggregating a plurality of detected instantaneous yaw rates to obtain a set of aggregated instantaneous yaw rates. 
     Example 13 is the computer-implemented method of any or all previous examples wherein predicting comprises: 
     predicting, based on the aggregated instantaneous yaw rates, the plurality of different yaw rate values. 
     Example 14 is the computer-implemented method of any or all previous examples wherein predicting comprises: 
     accessing a pre-defined correlation that correlates instantaneous yaw rate values to predicted yaw rate values to obtain the plurality of different predicted yaw rate values. 
     Example 15 is the computer-implemented method of any or all previous examples wherein predicting comprises: 
     performing a run time calculation based on the instantaneous yaw rate values to obtain the plurality of different predicted yaw rate values. 
     Example 16 is the computer-implemented method of any or all previous examples wherein generating a control signal comprises: 
     accessing a pre-defined correlation that correlates predicted yaw rate values to control signal values to obtain the control signal. 
     Example 17 is the computer-implemented method of any or all previous examples wherein generating a control signal comprises: 
     performing a run time calculation based on the predicted yaw rate values to obtain the control signal. 
     Example 18 is the computer-implemented method of any or all previous examples wherein detecting an instantaneous yaw rate of the towing vehicle comprises: 
     detecting a wheel angle of a wheel on the towing vehicle. 
     Example 19 is the computer-implemented method of any or all previous examples wherein detecting an instantaneous yaw rate of the towing vehicle comprises: 
     detecting a steering wheel angle of a steering wheel on the towing vehicle. 
     Example 20 is a computer system, comprising: 
     at least one processor; and 
     a data store storing computer executable instructions which, when executed by the at least one processor, causes the at least one processor to perform steps to control an agricultural machine, comprising: 
     receiving an instantaneous yaw rate of the towing vehicle, the towing vehicle towing an application tool that applies material to a field at work points distributed along a transverse axis of the application tool; 
     predicting, based on the instantaneous yaw rate detected on the towing vehicle, a plurality of different yaw rate values, each predicted yaw rate value of the plurality of different predicted yaw rate values corresponding to each work point of a set of the work points distributed along the transverse axis of the application tool; and 
     generating a control signal to control a meter that controls a rate at which the material is provided to the work points based on the plurality of different predicted yaw rate values. 
     This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. The claimed subject matter is not limited to implementations that solve any or all disadvantages noted in the background. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a partial pictorial, partial block diagram illustrating an agricultural system in which an air seeder is towed by a tractor. 
         FIG.  2    is a top view of an air seeder in which the seeding tool is between the towing vehicle and the air cart. 
         FIG.  3    is a top view of an air seeder in which the seeding tool is towed by the air cart, which is, itself, towed by the tractor. 
         FIG.  4    is a block diagram of one example of a look-ahead planting control system. 
         FIG.  5    is a flow diagram illustrating one example of the operation of the look-ahead planting control system. 
         FIG.  6    is a flow diagram illustrating one example of how a future yaw rate is predicted across a planting tool. 
         FIG.  7    is a block diagram of one example of a remote server architecture. 
         FIGS.  8 - 10    show examples of mobile devices that can be used in the systems and architectures shown in the previous FIGS. 
         FIG.  11    is a block diagram of one example of a computing environment that can be used in the systems and architectures shown in the previous FIGS. 
     
    
    
     DETAILED DESCRIPTION 
     As discussed above, some planters employ curve compensation functionality in an attempt to maintain a relatively constant seed rate, even as a seeding tool navigates around a curve. The instantaneous yaw rate sensed on the frame of the planter may be used to vary the planting rate (or application rate of other material). As described herein, the yaw of a machine is the rotation of that machine around its yaw axis, changing the heading of the machine to the left or right of its direction of motion. The yaw rate is the angular velocity of the yaw. The yaw rate on the planter itself may provide adequate performance for planters, because, when the seed is placed in the furrow using a seed tube the seed drops from the meter into the seed furrow in a fraction of a second. The seed may be placed even more quickly when using an active seed delivery system. 
     However, on an air seeder, it can take between 3 and 7 seconds (or more) for the seed to travel from the meter on the air cart to the seed furrow. Therefore, using the instantaneous yaw rate of the seeding tool frame to vary the seeding rate provides inadequate performance because by the time the seed travels from the meter to the furrow, the seeding tool has traveled 3 to 7 seconds along its path. For example, when traveling at 5 mph, the towing vehicle travels approximately 35 feet in 10 seconds. Therefore, if the seeding tool is being used to seed around the perimeter of the field, the instantaneous yaw rate on the tool itself is unacceptable because the seeding tool may have already passed through the turn and be running straight by the time the seed reaches the furrow. Thus, the variation in seed rate is not applied during the turn, but after the turn. The result is that, during the turn, the inside of the curve is over-seeded and the outside of the curve is under-seeded. During the exit from the turn, the seed distribution is uneven across the tool for a time that is equivalent to the duration of the turn. 
     The present description thus describes a system that senses the instantaneous yaw rate on the towing vehicle and generates a predicted yaw rate of the tool at a look-ahead time in the future. Depending on the speed of the towing vehicle and the distance between the yaw rate sensor on the towing vehicle and the work point of the implement being towed, for which the yaw rate is being predicted, the instantaneous yaw rate of the towing vehicle may be used as the predicted yaw rate (adjusted for the variation in speed across the seeding tool). However, in other configurations, such as where the seeding tool is towed behind the air cart, the work point of the tool arrives at the location of the tractor much later than when the seeding tool is towed between the towing vehicle and the air cart. In that case, the present description describes a system which predicts the yaw rate across the seeding tool in a way that accommodates for the extra distance between the seeding tool and the towing vehicle. For example, the present description describes a system which may aggregate a set of instantaneous yaw rate values from the yaw rate sensor on the tractor (such as a rolling table of yaw rate values) which can then be used to predict a yaw rate across the seeding tool at a time in the future when the seeding tool reaches the location where the instantaneous values of the towing vehicle were taken. These and other techniques for predicting a yaw rate value across the seeding tool can be used. The seed rate (or other application rate) can then be controlled across the seeding tool based upon the predicted yaw rate across the seeding tool. 
     The present description will proceed with respect to the application tool being an air seeder that has an air cart and a seeding tool. The air cart has a meter and delivery system that meters and delivers seed to different work points on the seeding tool, where furrows are opened by openers on the seeding tool. However, the application tool could be an implement that applies fertilizer or other material as well. 
       FIG.  1    is a side view of an example of an agricultural system  100  which includes an agricultural implement, in particular an air or pneumatic seeder  102 . In the example shown in  FIG.  1   , the seeder  102  comprises a tilling implement (or seeding tool)  104  (also sometimes called a drill) towed between a tractor (or other towing vehicle)  106  and a commodity cart (also sometimes called an air cart)  108 . The commodity cart  108  has a frame  110  upon which a series of product tanks  112 ,  114 ,  116 , and  118 , and wheels  120  are mounted. Each product tank has a door (a representative door  122  is labeled) releasably sealing an opening at its upper end for filling the tank with product, most usually a commodity of one type or another. A metering system  124  is provided at a lower end of each tank (a representative one of which is labeled) for controlled feeding or draining of product (most typically granular material) into a pneumatic distribution system  126 . The tanks  112 ,  114 ,  116 , and  118  can hold, for example, a material or commodity such as seed or fertilizer to be distributed to the soil. The tanks can be hoppers, bins, boxes, containers, etc. The term “tank” shall be broadly construed herein. Furthermore, one tank with multiple compartments can also be provided instead of separated tanks. 
     The tilling implement or seeding tool  104  includes a frame  128  supported by ground wheels  130 . Frame  128  is connected to a leading portion of the commodity cart  108 , for example by a tongue style attachment (not labeled). The commodity cart  108  as shown is sometimes called a “tow behind cart,” meaning that the cart  108  follows the tilling implement  104 . In an alternative arrangement, the cart  108  can be configured as a “tow between cart,” meaning the cart  108  is between the tractor  106  and tilling implement  104 . In yet a further possible arrangement, the commodity cart  108  and tilling implement  104  can be combined to form a unified rather than separated configuration. These are just examples of additional possible configurations. Other configurations are even possible and all configurations should be considered contemplated and within the scope of the present description. 
     In the example shown in  FIG.  1   , tractor  106  is coupled by couplings  103  to seeding tool  104  which is coupled by couplings  105  to commodity cart  108 . The couplings  103  and  105  can be mechanical, hydraulic, pneumatic, and electrical couplings and/or other couplings. The couplings  103  and  105  can include wired and wireless couplings as well. 
     The pneumatic distribution system  126  includes a fan (not shown) connected to a product delivery conduit structure having multiple product flow passages  132 . The fan directs air through the flow passages  132 . Each product metering system  124  controls delivery of product from its associated tank at a controllable rate to the transporting airstreams moving through flow passages  132 . In this manner, each flow passage  132  carries product from the tanks to a secondary distribution tower  134  on the tilling implement  104 . Typically, there will be one tower  134  for each flow passage  132 . Each tower  134  includes a secondary distributing manifold  136 , typically located at the top of a vertical tube. The distributing manifold  136  divides the flow of product into a number of secondary distribution lines  138 . Each secondary distribution line  138  delivers product to one of a plurality of ground engaging tools  140  (also known as ground openers) that define the locations of work points on seeding tool  104 . The ground engaging tools  140  open a furrow in the soil  144  and facilitates deposit of the product therein. The number of flow passages  132  that feed into secondary distribution may vary from one to eight or ten or more, depending at least upon the configuration of the commodity cart  108  and tilling implement  104 . Depending upon the cart and implement, there may be two distribution manifolds  136  in the air stream between the meters  124  and the ground engaging tools  140 . Alternatively, in some configurations, the product is metered directly from the tank or tanks into secondary distribution lines that lead to the ground engaging tools  140  without any need for an intermediate distribution manifold. The product metering system  124  can be configured to vary the rate of delivery of seed to each work point on tool  104  or to different sets or zones of work points on tool  104 . The configurations described herein are only examples. Other configurations are possible and should be considered contemplated and within the scope of the present description. 
     A firming or closing wheel  142  associated with each ground engaging tool  140  trails the tool and firms the soil over the product deposited in the soil. In practice, a variety of different types of tools  140  are used including, but not necessarily limited to, tines, shanks and disks. The tools  140  are typically moveable between a lowered position engaging the ground and a raised position riding above the ground. Each individual tool  140  may be configured to be raised by a separate actuator. Alternatively, multiple tools  140  may be mounted to a common component for movement together. In yet another alternative, the tools  140  may be fixed to the frame  128 , the frame being configured to be raised and lowered with the tools  140 . 
     Examples of air or pneumatic seeder  102  described above should not be considered limiting. The features described in the present description can be applied to any seeder configuration, or other material application machine, whether specifically described herein or not. 
       FIG.  1    also shows that agricultural system  100  includes look-ahead planting control system  150 . System  150  senses the yaw rate on tractor  106  and uses that yaw rate to predict the yaw rate across the frame  128  of implement  104 , at the different work points where seeds are delivered to the furrows. System  150  is described in greater detail below. 
     It will be appreciated, that different portions of system  150  can reside on tractor  106 , on tool or implement  104 , and/or on air cart  108 , or all of the elements of system  150  can be located at one place (e.g., on tractor  106 ). Elements of system  150  can be distributed to a remote server architecture or in other ways as well. 
       FIG.  2    is a top view of agricultural system  100 , in which some items are similar to those shown in  FIG.  1    and are similarly numbered.  FIG.  2    shows that implement  104  has a plurality of work points  104 - 1  to  104 - 18  distributed along a transverse axis  160  of implement  104 .  FIG.  2    also shows that tractor  106  has now turned at an angle relative to implement  104 . Thus, when implement  104  travels forward, a first end  152  of implement  104  will travel along an outside of a curve generally along the path indicated by arrow  154 . A second end  156  of implement  104  will travel along the inside of a curve generally indicated by arrow  158 . Therefore, the first portion  152  of implement  104  will be traveling more quickly over the ground  144  than the second portion  156 . In that case, look-ahead planting control system  150  uses the yaw rate sensed on tractor  106  to predict the yaw rate at the different work points  104 - 1  to  104 - 18  across the transverse axis  160  of implement  104  so that the seeding rate (or other application rate) from air cart  108  across implement  104  can be controlled to more closely conform to a uniform application rate, even through the curve. In the example shown  FIG.  2   , implement  104  is coupled between tractor  106  and air cart  108 . Therefore, depending on the speed of tractor  106 , and the distance from the yaw rate sensor  106  to the work points  104 - 1  to  104 - 18 , it may be that the sensed yaw rate on tractor  106  can be used to predict the yaw rate across the work points on the frame  128  of implement  104 . 
       FIG.  3    shows a top view of an agricultural system  100  which is similar to that shown in  FIG.  2   , and in which similar items are similarly numbered. However, in  FIG.  3   , it can be seen that implement  104  is now towed behind air cart  108  so that the delay between when tractor  106  travels over ground and when the work points  104 - 1  to  104 - 18  on implement  104  reaching that position on the ground  106  is greater than that delay for the configuration shown in  FIG.  2   . Therefore, in the configuration shown in  FIG.  3   , look-ahead planting control system  150  may use a set of instantaneous yaw rate values sensed on tractor  106  in order to predict the yaw rate across the work points on the transverse axis  160  of implement  104 . 
     In the various configurations shown in  FIGS.  1 - 3   , the yaw rate predicted across the work points  104 - 1  to  104 - 18  along the transverse axis  160  of implement  104  can be used to control the metering systems on air cart  108  so that the seed is metered at a higher rate to the first end  152  of implement  104  and at a lower rate to the second end  156  of implement  104  while the implement  104  is traveling through the curve, in order to more closely conform to a consistent application rate through the curve. 
       FIG.  4    is a block diagram of one example of look-ahead planting control system  150 . Again, while  FIG.  4    shows an example in which all of the elements of system  150  are deployed in one spot, the elements can be distributed among the different pieces of agricultural system  100  (e.g., on tractor  106 , implement  104 , and air cart  108 ) or they can be distributed in other ways, such as to a remote server environment or otherwise. In the example shown in  FIG.  4   , look-ahead planting control system  150  includes one or more processors or servers  162 , data store  164 , known path yaw rate prediction system  166 , instantaneous yaw rate detector  168 , yaw rate aggregator  170 , tool yaw rate prediction system  172 , meter controller  174 , operator interface system  176 , and other items  178 . Data store  164  includes machine dimensions  180 , aggregated yaw rate values  182 , pre-defined predicted yaw rate look-up tables, curves, etc.  184 , pre-defined meter control lookup tables, curves, etc.  186 , and other items  188 . Tool yaw rate prediction system  172  includes data store interaction system  190 , curve/table accessing system  192 , run time calculation system  194 , and other items  196 . Meter controller  174  includes data store interaction system  198 , control signal generator  200  (which, itself, includes curve/table accessing system  202 , runtime calculation system  204 , and other items  206 ), control signal output system  208 , and other items  210 . Before describing the overall operation of look-ahead planting control system  150  in more detail, a discussion of some of the items in system  150 , and their operation, will first be provided. 
     Machine dimensions  180  may include the physical dimensions of implement  104  and tractor  106 , such as the distance of the work points where the seed is dropped by implement  104  relative to the location of the yaw rate sensor on tractor  106  and relative to the metering system on air cart  108 , etc. The machine dimensions  180  may include the transverse width of implement  104  and/or other machine dimensions. 
     Aggregated yaw rate values  182  may be generated by yaw rate aggregator  170  aggregating instantaneous yaw rate values sensed by instantaneous yaw rate detector  168 . Detector  168 , may, for instance, be an inertial measurement unit (IMU—such as an accelerometer, a gyroscope, etc.) or a global navigation satellite system (GNSS) receiver from which the yaw rate can be derived. Instantaneous rate detector  168  can be a sensor that senses a proxy of yaw rate, such as a wheel angle that senses the angle of the wheels on tractor  106 , a steering wheel angle sensor that senses the angle of a steering wheel on tractor  106 , an articulation angle sensor that senses an articulation angle of an articulated tractor frame, or other instantaneous yaw rate detectors that detect a variable either indicative of the instantaneous yaw rate, or the yaw rate itself. Yaw rate aggregator  170  can aggregate a rolling table of instantaneous yaw rate values which can be used to predict the yaw rate at the work points  104 - 1  to  104 - 18  across the transverse axis  160  of implement  104 . Those values can be stored as aggregated yaw rate values  182 . 
     Pre-defined predicted yaw rate look-up tables or curves  184  can be look-up tables that store predicted yaw rate values across the transverse axis  160  of implement  104  based on a variety of inputs, such as based on the machine configuration (e.g., a model of the physical dimensions of various machines, the position of implement  104  relative to tractor  106  and air cart  108 , the speed of tractor  106 , the instantaneous yaw rate value measured at tractor  106 , and other values). Those input values can be used to access a predefined correlation between the instantaneous yaw rate on tractor  106  and predicted yaw rates, such as a curve or table that gives the predicted yaw rate values at the different work points  104 - 1  to  104 - 18  across implement  104 . 
     Once the predicted yaw rate values are known for the work points across the transverse axis  160  of implement  104 , then predefined meter control look up tables or curves  186  can be accessed to identify the control signal values that will be applied to the meters on air cart  108  to control metering of seed or other applied material based upon the predicted yaw rate values on implement  104 . 
     Tool yaw rate prediction system  172  receives the instantaneous yaw rate value or the aggregated values and predicts the yaw rate values at the work points across the transverse axis  160  of implement  104 . Data store interaction system  190  can interact with data store  164  to obtain machine dimensions  180 , aggregated yaw rate values  182 , or other information. Curve/table accessing system  192  can access the predefined predicted yaw rate look up tables or curves  184  to identify the predicted yaw rate values across the work points on transverse axis  160  of implement  104 . Runtime calculation system  194  can obtain the instantaneous yaw rate value or aggregated yaw rate values and the machine dimensions and perform a runtime calculation to obtain the predicted yaw rate values across the transverse axis  160  of implement  104 . Thus, runtime calculations system  194  can calculate the predicted yaw rate values instead of having curve/table accessing system  192  look those values up in the pre-defined predicted yaw rate look up tables or curves  184 . 
     The predicted yaw rate values are output to meter controller  174  which generate meter control signals to control the meters on air cart  108  based upon the predicted yaw rate values that are predicted across the transverse axis  160  of implement  104 . Data store interaction system  198  interacts with data store  164  to obtain information so that control signal generator  200  can generate control signals, or determine which control signals to generate, for the meters on air cart  108 , based upon the predicted yaw rates across the transverse axis  160  of implement  104 . Curve/table accessing system  202  can access a predefined correlation between predicted yaw rate values and meter control signal values, such as the predefined meter control lookup tables/curves  186  based upon the predicted yaw rates across the work points of transverse axis  160  of implement  104  to identify a meter control signal for controlling the meters that provide commodity at those different work points across implement  104 . In another example, runtime calculation system  204  can calculate the meter control signals that are to be used to control the meters based upon the predicted yaw rates. 
     Control signal generator  200  can use other mechanisms  206  to identify the control signals in other ways as well. Control signal output system  208  then applies the control signals to the meters on air cart  108  to control the meters, based upon the predicted yaw rates, to supply seed or other commodity to the work points across the transverse access  160  of implement  104 . The seed or other commodity will be provided at different rates to the different work points across the transverse access  160  as implement  104  travels through a curve, so that the material or seed can be applied to the ground at a consistent rate. 
     Operator interface system  176  can include operator interface mechanisms, such as a steering wheel, joysticks, pedals, levers, linkages, buttons, dials, etc. The operator interface mechanisms can include one or more display screens, speakers, and other audio, visual, and/or haptic devices. Operator interface system  176  can control the operator interface mechanisms to generate a display or other output indicative of how the predicted yaw rates are generated, how the meter control signals are generated, the value of the predicted yaw rates and meter control signals, or other information indicative of the seed rate (or other application rate) that is being varied across the transverse access  160  of implement  104  in order to accomplish a consistent seed rate on the ground, even when implement  104  is moving through a curve. 
     Before describing the operation of system  100  in more detail, it will first be noted that, in some examples, tractor  106  will be autonomously or otherwise automatically controlled to follow a known path, at a known speed. It such an example, known path yaw rate prediction system  166  can generate the predicted future yaw rate values on tool  104  given the known path and the known speed. However, in other scenarios, the towing vehicle  106  will not be operated automatically or autonomously according to a known path at a known speed. Instead, towing vehicle  106  may be manually controlled or it may be at least manually controlled through turns. In these scenarios, system  150  generates the predicted yaw rate values as described below. 
       FIG.  5    is a flow diagram illustrating one example of the operation of the agricultural system  100  in controlling seed rate of an air seeder as it is traveling through a curve. It is first assumed that a planting/seeding system, such as an air seeder, a fertilizer, etc. is operating in a field, as indicated by block  220  in the flow diagram of  FIG.  5   . The planting/seeding system is illustratively configured with access to a look-ahead planting control system  150 , as indicated by block  222 . As discussed above, the planting/seeding system can access the look-ahead planting control system  150  in a remote server architecture, or in other distributed environment, or the system  150  can be fully deployed on tractor  106  or elsewhere. The planting/seeding system can be operating in a field in other ways as well, as indicated by block  224 . 
     The instantaneous yaw rate detector  168  then detects an instantaneous yaw rate on the towing vehicle, such as tractor  106 , as indicated by block  226  in the flow diagram of  FIG.  5   . A proxy of the instantaneous yaw rate can be detected as well, such as by using a wheel angle sensor that senses the angle of one or more of the wheels on tractor  106 , a steering wheel angle sensor that senses the angle of the steering wheel on tractor  106 , an articulation angle sensor that senses the articulation angle of an articulated frame on tractor  106 , or other proxy values, as indicated by block  228 . The instantaneous yaw rate detector  168  can be an inertial measurement unit, such as an accelerometer or gyroscope, as indicated by block  230 . The instantaneous yaw rate detector  168  can be a global navigation satellite system GNSS) receiver, as indicated by block  232 . The instantaneous yaw rate on the towing vehicle can be detected in other ways, using other sensors as well, as indicated by block  234 . 
     Tool yaw rate prediction system  172  then predicts the yaw rates at the work points across the transverse axis  160  of tool  104 , as indicated by block  236  in the flow diagram of  FIG.  5   . Predicting the yaw rate values is described in greater detail below with respect to  FIG.  6   . 
     Meter controller  174  then generates meter control signals to control the seed meters or other commodity meters on air cart  108  based upon the predicted yaw rate values, as indicated by block  238  in the flow diagram  FIG.  5   . Curve/table accessing system  202  can access the predefined meter control look up tables or curves  186  to identify the particular meter control signals that are to be used based upon the predicted yaw rate values, as indicated by block  240 . Runtime calculation system  204  can perform a runtime calculation to identify the meter control signals based upon the predictive yaw rate values, as indicated by block  242 . The meter control signals can be identified and generated in other ways as well, as indicated by block  244 . Control signal output system  208  then applies the meter control signals to control the meters on air cart  108  based upon the predicted yaw rate values across  104 . Applying the control signals to the meters is indicated by block  246  in the flow diagram of  FIG.  5   . 
     Operator interface system  176  can then generate an operator output based upon the predicted yaw rates and/or the meter control signals, as indicated by block  248 . The operator output can be a visual output showing how the meters are variably controlled as tool  104  moves through a curve. The operator output can be a graphical output, an audible output, or any of a wide variety of other outputs. 
       FIG.  6    is a flow diagram illustrating one example of how tool yaw rate prediction system  172  predicts the yaw rates at the work points across the transverse axis  160  of tool  104 , based upon the instantaneous yaw rate detected on tractor  106 , in more detail. It is first assumed that tool yaw rate prediction system  172  receives the detected yaw rate values on the towing vehicle  106 , as indicated by block  250  in the flow diagram of  FIG.  6   . The yaw rate that is received may be the instantaneous yaw rate generated by instantaneous yaw rate detector  168 , or a rolling average of yaw rate values, or another aggregation of yaw rate values generated by yaw rate aggregator  170 , as indicated by block  252  in the flow diagram of  FIG.  6   . The yaw rate can be received in other ways as well, as indicated by block  254 . 
     Data store interaction system  190  can then access data store  164  to identify the machine configuration and dimensions which can then be used by tool yaw rate prediction system  172  to identify the predicted yaw rate values. Identifying the machine configuration and dimensions is indicated by block  256  in the flow diagram of  FIG.  6   . 
     Tool yaw rate prediction system  172  then identifies the predicted yaw rate values at the work points across the transverse axis  160  of tool  104 , as indicated by block  258 . 
     Depending upon the speed of the towing vehicle  106  (which may be detected by vehicle speed detector, a GNSS receiver, etc.) and depending upon the machine configuration (such as how far behind the towing vehicle  106  the work points on implement  104  are located), it may be that runtime calculation system  194  simply uses a filtered, detected yaw rate value from the towing vehicle  106 , as the predicted yaw rate value on the tool  104 , and adjusted based upon the location of the work points across the transverse axis  160 . Using a filtered, detected yaw rate on the towing vehicle  106 , as the predicted value, is indicated by block  260  in the flow diagram of  FIG.  6   . 
     In another example, curve/table accessing system  192  can access the predefined predicted yaw rate lookup tables and/or curves  184  based upon the instantaneous yaw rate value generated by detector  168  and/or the aggregated values generated by aggregator  170  to identify the predicted yaw rates at the work points across tool  104 . Accessing the predefined curve or lookup tables  184  is indicated by block  262  in the flow diagram of  FIG.  6   . In another example, runtime calculation system  194  can perform a runtime calculation to identify the predicted yaw rate values at the work points across tool  104 , as indicated by block  264 . 
     It will also be noted that tool yaw rate prediction system  172  can generate the predicted yaw rate values for individual work points across tool  104 , or for sections of work points across tool  104 , as indicated by block  266 . The predicted yaw rate values can be identified in other ways as well, as indicated by block  268 . 
     Tool yaw rate prediction system  172  then outputs the predicted yaw rate values to meter controller  174  for control of the meters on air seeder  108 . Outputting the predicted yaw rate values is indicated by block  270  in the flow diagram of  FIG.  6   . 
     It can thus be seen that the present system uses the instantaneous yaw rate detected on the towing vehicle (or an aggregated set of those values) to predict the yaw rate values at work points across the seeding tool. These yaw rates can then be used to identify meter control signals that are applied to the meters providing material to those work points so that the material application rate can be consistently controlled, even around curves. It will also be noted that, instead of generating predictive yaw rates for the work points, the predefined predicted curves and tables  184  and  186  can be combined so that, given an instantaneous yaw rate, or an aggregated set of instantaneous yaw rate values, the meter control signals can be directly obtained without first obtaining the predicted yaw rate values and then obtaining the control signal values. 
     It will also be noted that different yaw rate look-up tables or curves can be generated for different seeding configurations, for different size seeders, for different models of seeders, or for other variations. Also, different meter control look-up tables and curves  186  can be generated for different models of meters, for different seeders, or for different seeder configurations or other variations. 
     The present discussion has mentioned processors and servers. In one example, the processors and servers include computer processors with associated memory and timing circuitry, not separately shown. The processors and servers are functional parts of the systems or devices to which they belong and are activated by, and facilitate the functionality of the other components or items in those systems. 
     Also, a number of user interface displays have been discussed. The displays can take a wide variety of different forms and can have a wide variety of different user actuatable input mechanisms disposed thereon. For instance, the user actuatable input mechanisms can be text boxes, check boxes, icons, links, drop-down menus, search boxes, etc. The mechanisms can also be actuated in a wide variety of different ways. For instance, the mechanisms can be actuated using a point and click device (such as a track ball or mouse). The mechanisms can be actuated using hardware buttons, switches, a joystick or keyboard, thumb switches or thumb pads, etc. The mechanisms can also be actuated using a virtual keyboard or other virtual actuators. In addition, where the screen on which they are displayed is a touch sensitive screen, they can be actuated using touch gestures. Also, where the device that displays them has speech recognition components, they can be actuated using speech commands. 
     A number of data stores have also been discussed. It will be noted the data stores can each be broken into multiple data stores. All can be local to the systems accessing them, all can be remote, or some can be local while others are remote. All of these configurations are contemplated herein. 
     Also, the figures show a number of blocks with functionality ascribed to each block. It will be noted that fewer blocks can be used so the functionality is performed by fewer components. Also, more blocks can be used with the functionality distributed among more components. 
     It will be noted that the above discussion has described a variety of different systems, components and/or logic. It will be appreciated that such systems, components and/or logic can be comprised of hardware items (such as processors and associated memory, or other processing components, some of which are described below) that perform the functions associated with those systems, components and/or logic. In addition, the systems, components and/or logic can be comprised of software that is loaded into a memory and is subsequently executed by a processor or server, or other computing component, as described below. The systems, components and/or logic can also be comprised of different combinations of hardware, software, firmware, etc., some examples of which are described below. These are only some examples of different structures that can be used to form the systems, components and/or logic described above. Other structures can be used as well. 
       FIG.  7    is a block diagram of system  100 , shown in  FIG.  1   , except that system  100  communicates with elements in a remote server architecture  500 . In an example, remote server architecture  500  can provide computation, software, data access, and storage services that do not require end-user knowledge of the physical location or configuration of the system that delivers the services. In various examples, remote servers can deliver the services over a wide area network, such as the internet, using appropriate protocols. For instance, remote servers can deliver applications over a wide area network and they can be accessed through a web browser or any other computing component. Software or components shown in previous FIGS. as well as the corresponding data, can be stored on servers at a remote location. The computing resources in a remote server environment can be consolidated at a remote data center location or they can be dispersed. Remote server infrastructures can deliver services through shared data centers, even though they appear as a single point of access for the user. Thus, the components and functions described herein can be provided from a remote server at a remote location using a remote server architecture. Alternatively, they can be provided from a conventional server, or they can be installed on client devices directly, or in other ways. 
     In the example shown in  FIG.  7   , some items are similar to those shown in previous FIGS. and they are similarly numbered.  FIG.  7    specifically shows that system 150  can be located at a remote server location  502 . Therefore, system  100  accesses those systems through remote server location  502 . 
       FIG.  7    also depicts another example of a remote server architecture.  FIG.  7    shows that it is also contemplated that some elements of previous FIGS are disposed at remote server location  502  while others are not. By way of example, data store  164  or tool yaw rate prediction system  172  can be disposed at a location separate from location  502 , and accessed through the remote server at location  502 . Regardless of where they are located, they can be accessed directly by system  100 , through a network (either a wide area network or a local area network), they can be hosted at a remote site by a service, or they can be provided as a service, or accessed by a connection service that resides in a remote location. Also, the data can be stored in substantially any location and intermittently accessed by, or forwarded to, interested parties. For instance, physical carriers can be used instead of, or in addition to, electromagnetic wave carriers. In such an example, where cell coverage is poor or nonexistent, another mobile machine (such as a fuel truck) can have an automated information collection system. As the tractor comes close to the fuel truck for fueling, the system automatically collects the information from the tractor using any type of ad-hoc wireless connection. The collected information can then be forwarded to the main network as the fuel truck reaches a location where there is cellular coverage (or other wireless coverage). For instance, the fuel truck may enter a covered location when traveling to fuel other machines or when at a main fuel storage location. All of these architectures are contemplated herein. Further, the information can be stored on the tractor until the tractor enters a covered location. The tractor, itself, can then send the information to the main network. 
     It will also be noted that the elements of previous FIGS., or portions of them, can be disposed on a wide variety of different devices. Some of those devices include servers, desktop computers, laptop computers, tablet computers, or other mobile devices, such as palm top computers, cell phones, smart phones, multimedia players, personal digital assistants, etc. 
       FIG.  8    is a simplified block diagram of one illustrative example of a handheld or mobile computing device that can be used as a user&#39;s or client&#39;s hand held device  16 , in which the present system (or parts of it) can be deployed. For instance, a mobile device can be deployed in the operator compartment of tractor  106  for use in generating, processing, or displaying the yaw rate or meter control data.  FIGS.  9 - 10    are examples of handheld or mobile devices. 
       FIG.  8    provides a general block diagram of the components of a client device  16  that can run some components shown in previous FIGS., that interacts with them, or both. In the device  16 , a communications link  13  is provided that allows the handheld device to communicate with other computing devices and under some examples provides a channel for receiving information automatically, such as by scanning. Examples of communications link  13  include allowing communication though one or more communication protocols, such as wireless services used to provide cellular access to a network, as well as protocols that provide local wireless connections to networks. 
     In other examples, applications can be received on a removable Secure Digital (SD) card that is connected to an interface  15 . Interface  15  and communication links  13  communicate with a processor  17  (which can also embody processors or servers from previous FIGS.) along a bus  19  that is also connected to memory  21  and input/output (I/O) components  23 , as well as clock  25  and location system  27 . 
     I/O components  23 , in one example, are provided to facilitate input and output operations. I/O components  23  for various examples of the device  16  can include input components such as buttons, touch sensors, optical sensors, microphones, touch screens, proximity sensors, accelerometers, orientation sensors and output components such as a display device, a speaker, and or a printer port. Other I/O components  23  can be used as well. 
     Clock  25  illustratively comprises a real time clock component that outputs a time and date. It can also, illustratively, provide timing functions for processor  17 . 
     Location system  27  illustratively includes a component that outputs a current geographical location of device  16 . This can include, for instance, a global positioning system (GPS) receiver, a LORAN system, a dead reckoning system, a cellular triangulation system, or other positioning system. System  27  can also include, for example, mapping software or navigation software that generates desired maps, navigation routes and other geographic functions. 
     Memory  21  stores operating system  29 , network settings  31 , applications  33 , application configuration settings  35 , data store  37 , communication drivers  39 , and communication configuration settings  41 . Memory  21  can include all types of tangible volatile and non-volatile computer-readable memory devices. Memory  21  can also include computer storage media (described below). Memory  21  stores computer readable instructions that, when executed by processor  17 , cause the processor to perform computer-implemented steps or functions according to the instructions. Processor  17  can be activated by other components to facilitate their functionality as well. 
       FIG.  9    shows one example in which device  16  is a tablet computer  600 . In  FIG.  9   , computer  600  is shown with user interface display screen  602 . Screen  602  can be a touch screen or a pen-enabled interface that receives inputs from a pen or stylus. Computer  600  can also use an on-screen virtual keyboard. Of course, computer  600  might also be attached to a keyboard or other user input device through a suitable attachment mechanism, such as a wireless link or USB port, for instance. Computer  600  can also illustratively receive voice inputs as well. 
       FIG.  10    shows that the device can be a smart phone  71 . Smart phone  71  has a touch sensitive display  73  that displays icons or tiles or other user input mechanisms  75 . Mechanisms  75  can be used by a user to run applications, make calls, perform data transfer operations, etc. In general, smart phone  71  is built on a mobile operating system and offers more advanced computing capability and connectivity than a feature phone. 
     Note that other forms of the devices  16  are possible. 
       FIG.  11    is one example of a computing environment in which elements of previous FIGS., or parts of it, (for example) can be deployed. With reference to  FIG.  11   , an example system for implementing some embodiments includes a general-purpose computing device in the form of a computer  810  programmed to operate as described above. Components of computer  810  may include, but are not limited to, a processing unit  820  (which can comprise processors or servers from previous FIGS.), a system memory  830 , and a system bus  821  that couples various system components including the system memory to the processing unit  820 . The system bus  821  may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. Memory and programs described with respect to previous FIGS. can be deployed in corresponding portions of  FIG.  11   . 
     Computer  810  typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer  810  and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media is different from, and does not include, a modulated data signal or carrier wave. It includes hardware storage media including both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computer  810 . Communication media may embody computer readable instructions, data structures, program modules or other data in a transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. 
     The system memory  830  includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM)  831  and random access memory (RAM)  832 . A basic input/output system  833  (BIOS), containing the basic routines that help to transfer information between elements within computer  810 , such as during start-up, is typically stored in ROM  831 . RAM  832  typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit  820 . By way of example, and not limitation,  FIG.  11    illustrates operating system  834 , application programs  835 , other program modules  836 , and program data  837 . 
     The computer  810  may also include other removable/non-removable volatile/nonvolatile computer storage media. By way of example only,  FIG.  11    illustrates a hard disk drive  841  that reads from or writes to non-removable, nonvolatile magnetic media, an optical disk drive  855 , and nonvolatile optical disk  856 . The hard disk drive  841  is typically connected to the system bus  821  through a non-removable memory interface such as interface  840 , and optical disk drive  855  are typically connected to the system bus  821  by a removable memory interface, such as interface  850 . 
     Alternatively, or in addition, the functionality described herein can be performed, at least in part, by one or more hardware logic components. For example, and without limitation, illustrative types of hardware logic components that can be used include Field-programmable Gate Arrays (FPGAs), Application-specific Integrated Circuits (e.g., ASICs), Application-specific Standard Products (e.g., ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), etc. 
     The drives and their associated computer storage media discussed above and illustrated in  FIG.  11   , provide storage of computer readable instructions, data structures, program modules and other data for the computer  810 . In  FIG.  11   , for example, hard disk drive  841  is illustrated as storing operating system  844 , application programs  845 , other program modules  846 , and program data  847 . Note that these components can either be the same as or different from operating system  834 , application programs  835 , other program modules  836 , and program data  837 . 
     A user may enter commands and information into the computer  810  through input devices such as a keyboard  862 , a microphone  863 , and a pointing device  861 , such as a mouse, trackball or touch pad. Other input devices (not shown) may include a joystick, game pad, satellite dish, scanner, or the like. These and other input devices are often connected to the processing unit  820  through a user input interface  860  that is coupled to the system bus, but may be connected by other interface and bus structures. A visual display  891  or other type of display device is also connected to the system bus  821  via an interface, such as a video interface  890 . In addition to the monitor, computers may also include other peripheral output devices such as speakers  897  and printer  896 , which may be connected through an output peripheral interface  895 . 
     The computer  810  is operated in a networked environment using logical connections (such as a controller area network—CAN, local area network—LAN, or wide area network WAN) to one or more remote computers, such as a remote computer  880 . 
     When used in a LAN networking environment, the computer  810  is connected to the LAN  871  through a network interface or adapter  870 . When used in a WAN networking environment, the computer  810  typically includes a modem  872  or other means for establishing communications over the WAN  873 , such as the Internet. In a networked environment, program modules may be stored in a remote memory storage device.  FIG.  11    illustrates, for example, that remote application programs  885  can reside on remote computer  880 . 
     It should also be noted that the different examples described herein can be combined in different ways. That is, parts of one or more examples can be combined with parts of one or more other examples. All of this is contemplated herein. 
     Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.