Terrain confidence and control

Abstract

A mobile agricultural machine receives a topographic map indicating topographic characteristics of a worksite, where the topographic characteristics are based on data collected at or before a first time and supplemental data received indicating characteristics related to the worksite, the supplemental data collected after the first time. Based on the topographic map and the supplemental data, a topographic confidence output is generated indicating a level of confidence in aspects of the topographic characteristics of the worksite indicated by the topographic map. In some examples, an action signal is generated based on the topographic confidence output to control an action.

Description

TECHNICAL FIELD

[0001] This specification generally relates to the use of a wide variety of different mobile work machines in a wide variety of operations. More specifically, this description relates to the use of computing systems in improving the control and performance of a wide variety of different operating machines in a wide variety of operations. BACKGROUND

[0002] There are a wide variety of different types of machines, such as agricultural machines, forestry machines, and construction machines. These types of machines are often operated by an operator and have sensors that generate information during operation. Additionally, operators of these types of machines can rely on various terrain data (e.g., a topographical map of a worksite) related to a worksite for controlling and operating various types of machines.

[0003] Agricultural machines can include a wide variety of machines, such as harvesters, sprayers, planters, cultivators, etc. Agricultural machines can be operated by an operator and have many different mechanisms that are controlled by the operator. The machines can have a number of different mechanical, electrical, hydraulic, pneumatic, electromechanical (and other) subsystems, some or all of which can be controlled by the operator at least to some extent. Some or all of these subsystems can communicate information obtained from sensors on the machine (and from other inputs). Additionally, the operator can rely on the information communicated by the subsystems and various types of other information, such as terrain data, to control the various subsystems. For example, the operator can rely on terrain information, such as a topographical map of a field, for setting the height of various subsystems, such as the height from the surface of the field.

[0004] The accuracy and freshness of the information provided to the operator is important to ensure that the operating parameters of the machine are set to a desired level. Current systems can experience difficulties in providing accurate and fresh information to the operator for the purpose of setting the control of the machine.

[0005] The above discussion is provided only for general background information and does not intend to help in determining the scope of the claimed subject matter. SUMMARY

[0006] A mobile agricultural machine receives a topographical map indicating topographical characteristics of a worksite, where the topographical characteristics are based on data collected at or before a first time, and receives supplemental data indicating characteristics related to the worksite, the supplemental data being collected after the first time. Based on the topographical map and the supplemental data, a topographical confidence output is generated indicating a level of confidence in aspects of the topographical characteristics of the worksite indicated by the topographical map. In some examples, an action signal is generated based on the topographical confidence output to control an action.

[0007] This Summary is provided to introduce some concepts in a simplified form that are further described below in the DETAILED DESCRIPTION. This Summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used to determine 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 DRAWINGS

[0008] Figure 1 is a partially graphical, partially schematic illustration showing one example of a mobile agricultural machine.

[0009] Figure 2 is a perspective view showing one example of a mobile agricultural machine.

[0010] Figure 3 is a block diagram of one example of a computing system architecture of a mobile agricultural machine shown in Figures 1 to 2

[0011] Figure 4 is a block diagram of one example of a terrain confidence system in more detail.

[0012] Figure 5 is a flow diagram showing example operations of the terrain confidence system shown in Figure 4

[0013] Figures 6 to 11 is a partial graphical illustration showing example maps that can be generated by the terrain confidence system shown in Figure 4

[0014] Figure 12 is a block diagram showing one example of an architecture deployed in a remote server architecture shown in Figure 3

[0015] shows an example of a mobile device that can be used with the architecture(s) shown in the preceding figure(s). Figures 13 to 15

[0016] Figure 16 is a block diagram showing one example of a computing environment that can be used in the architecture(s) shown in the preceding figure(s). DETAILED DESCRIPTION

[0017] In current agricultural systems, autonomous control of various agricultural machines and human operators can rely on a topographical map of the worksite (e.g., field) on which they are operating for purposes of controlling machine settings and various other operational parameters. For example, an operator can control the height of a header of a combine harvester from the surface of a field, the height of a spray bar of a sprayer from the surface of a field, the application of a sprayed substance to the surface of a field, etc. ​​​​

[0018] Surveys of the field, such as aerial surveys, can be conducted, from which topographical maps can be generated. While these maps can be made with an accuracy as low as at least a few centimeters at the time of data collection, events (e.g., weather events, fires, waves / tides, volcanoes, earthquakes, floods, human events, etc.) that can dynamically change the topography of the field (and other characteristics of the field) can occur in the time lapse between the surveying and the operation of the agricultural machine on the field. For example, but not by way of limitation, due to events that occur in the time lapse between the surveying and the operation of the agricultural machine on the field, washouts, ruts, drifts, shallow trenches, valley slopes, erosion, material / deposits deposits or accumulations (e.g., ridge of soil, soil drift, etc.), and various other conditions can exist on the field. These changes in the topography of the field will not be represented in the topographical maps provided to the operator (or control system) of the agricultural machine. Thus, machine settings and other operating parameters commanded by the operator (or control system) of the machine can result in errors or other deviations in the performance of the agricultural machine.

[0019] The agricultural machine can have on-board sensors that can provide near real-time information indicative of the topography of the field. However, these sensors typically have a limited field of view, and thus they can not capture information and feed it back to the operator (or control system) of the agricultural machine fast enough to adjust machine settings or operating parameters of the agricultural machine to avoid errors or deviations in performance.

[0020] Some systems can even utilize a perception system, such as an imaging system mounted on the agricultural machine, or an additional surveying system that works in conjunction with the agricultural machine, such as a drone that flies ahead of the agricultural machine. However, these systems can not be able to observe changes that can occur to the field in a timely or reliable manner. For example, vegetation growth on the field can obscure the view of such a system. Further, additional surveying can be performed closer in time to when the operation (e.g., a harvesting operation, a spraying operation, etc.) is to be performed, to, for example, revise or otherwise supplement the original (e.g., baseline) topographical map. However, and particularly in the case of utilizing certain operations, the characteristics of the work site can make it so that additional measurements are not able to accurately establish accurate topographical information. For example, at or near the time when the operation is to be performed, the vegetation on the field can be very dense and tall, and thus the ability of the sensors on the surveying machine to collect topographical data can be diminished or otherwise hindered, as the view of the surface of the field is not consistently visible, if not completely obscured. Thus, the topographical information for a particular field can be incomplete, or will not otherwise accurately reflect the topography of the field, and thus, control of the machine can be suboptimal.

[0021] For example, the height or inclination of the header on a harvester can be controlled based on a topographic map of the field. However, the topographic map may not show new soil ridges formed on the field (e.g., by wind or water) within a timeframe after the data used for mapping the topography. Therefore, the position of the header (e.g., height, orientation, inclination, etc.) can cause it to travel onto new soil ridges. In another example, the position of the spray boom on a sprayer (e.g., height, orientation, inclination, etc.) can be controlled based on a topographic map of the field. However, the topographic map may not show scour zones formed on the field (e.g., by water, such as heavy rain or floods) within a timeframe after the data used for mapping the topography. Therefore, as the sprayer travels across the field, it may encounter and enter scour zones, which may cause the spray boom to lower its height so that it no longer travels over the crop canopy but instead travels through the crop, potentially affecting the quality of the spraying operation and the effectiveness of the sprayed material. These are just a few examples.

[0022] To address at least some of these difficulties, this specification provides a control system that includes a terrain confidence system. As will be discussed further below, the control system acquires a topographic map of the field to be operated on (e.g., as a baseline or reference). The control system also acquires supplementary data related to the field, which is collected between the time when the data for the baseline topographic map is collected and the operation to be performed on the field (or before the operation is performed at a specific geographic location on the field). The control system performs confidence analysis on the baseline topographic map based on the supplementary data and various algorithmic processes, and generates terrain confidence outputs, such as the terrain confidence level of the field or a terrain confidence map, which in particular indicates the confidence level of the terrain characteristics of the field indicated by the baseline map. The system uses the terrain confidence outputs to generate various action signals. The action signals can be used to automatically or semi-automatically control the machine to improve overall performance by, for example, by automatically controlling machine subsystems, providing operator assistance features, and providing indications on interfaces or interface mechanisms representing various information (including, but not limited to, terrain confidence outputs, such as the terrain confidence level of the field or a terrain confidence map).

[0023] This description can be applied to any of the various types of mobile agricultural machinery 100. The two described herein are merely examples. Figure 1 Harvester 101 is shown, and Figure 2 Sprayer 201 is shown. Again, these are merely examples of the different types of mobile agricultural machinery envisioned in this specification.

[0024] Figure 1 This is a partial graphical, schematic illustration of a mobile agricultural machine 100, in which the mobile machine 100 is a combine harvester (also referred to as combine harvester 101 or mobile machine 101). Figure 1As can be seen, the combine harvester 101 illustratively includes an operator's compartment 103, which can have various different operator interface mechanisms for controlling the combine harvester 101. The operator's compartment 103 can include one or more operator interface mechanisms that allow an operator to control and manipulate the combine harvester 101. The operator interface mechanisms in the operator's compartment 103 can be any of a variety of different types of mechanisms. For example, they can include one or more input mechanisms, such as a steering wheel, levers, joysticks, buttons, pedals, switches, etc. In addition, the operator's compartment 103 can include one or more operator interface display devices, such as monitors, or mobile devices supported within the operator's compartment 103. In this case, the operator interface mechanisms can also include one or more user-actuatable elements, such as icons, links, buttons, etc., that are displayed on the display devices. The operator interface mechanisms can include one or more microphones in which voice recognition is provided on the combine harvester 101. They can also include one or more audio interface mechanisms (e.g., speakers), one or more haptic interface mechanisms, or a variety of other operator interface mechanisms. The operator interface mechanisms can also include other output mechanisms, such as dials, gauges, meter outputs, lights, audible or visual alarms, or haptic outputs, etc.

[0025] The combine harvester 101 includes a set of front-end machines that form a cutting platform 102, which includes a header 104 with a cutter (generally indicated at 106). It can also include a feedhouse 108, a feed accelerator 109, and a threshing machine, generally indicated at 111. The threshing machine 111 illustratively includes a threshing cylinder 112 and a set of concaves 114. Further, the combine harvester 101 can include a separator 116, which includes a separator cylinder. The combine harvester 101 can include a grain cleaning subsystem (or grain cleaning house) 118, which can itself include a grain cleaning fan 120, a sieve cleaner 122, and a sieve 124. The material handling subsystem in the combine harvester 101 can include (in addition to the feedhouse 108 and the feed accelerator 109) an unloading beater 126, a residue elevator 128, a clean grain elevator 130 (which moves clean grain into a clean grain tank 132), and an unloading auger 134 and a spout 136. The combine harvester 101 can also include a residue subsystem 138, which can include a chopper 140 and a spreader 142. The combine harvester 101 can also have a propulsion subsystem, which includes an engine (or other power source) that drives ground-engaging elements 144, such as wheels, tracks, etc. It should be noted that the combine harvester 101 can also have more than one of any of the subsystems mentioned above (e.g., left and right grain cleaning houses, separators, etc.).

[0026] As Figure 1As shown, the header 104 has a main frame 107 and an attachment frame 110. The header 104 is attached to the feeder house 108 by attachment mechanisms on the attachment frame 110 that cooperate with attachment mechanisms on the feeder house 108. The main frame 107 supports the cutterbar 106 and reel 105 and is movable relative to the attachment frame 110, for example, by actuators (not shown). Additionally, the attachment frame 110 is movable to controllably adjust the position of the front end assembly 102 relative to the surface (e.g., a field) on which the combine 101 is traveling in the direction indicated by arrow 146, and thus controllably adjust the position of the header 104 from the surface, by operation of actuators 149. In one example, the main frame 107 and the attachment frame 110 can be raised and lowered together to set the height of the cutterbar 106 above the surface on which the combine 101 is traveling. In another example, the main frame 107 can be tilted relative to the attachment frame 110 to adjust the angle of tilt of the cutterbar 106 to engage crops on the surface. Also, in one example, the main frame 107 can be rotated or otherwise moved relative to the attachment frame 110 to improve ground following performance. In this manner, the roll, pitch, and / or yaw of the header relative to the agricultural surface can be controllably adjusted. Movement of the main frame 107 together with the attachment frame 110 can be driven by actuators, such as hydraulic, pneumatic, mechanical, electromechanical, or electric actuators, among various other actuators, based on operator input or automatic input.

[0027] In operation, and as outlined, the height of the header 104 is set and the combine 101 moves over the field in the direction indicated by arrow 146. As the header moves, the header 104 engages the crops to be harvested and gathers them toward the cutterbar 106. After the crops are cut, they can be engaged by the reel 105, which moves the crops to the feeding system. The feeding system moves the crops to the center of the header 104 and then through the central feeding system in the feeder house 108 toward the feed accelerator 109, which accelerates the crops into the threshing machine 111. The crops are then threshed by the cylinder 112, which rotates the crops against the concaves 114. The threshed crops are moved by the separator cylinder in the separator 116, where some of the residue is moved by the discharge discharge beater 126 toward the residue subsystem. It can be chopped by the residue chopper 140 and spread on the field by the spreader 142. In other implementations, the residue is simply dropped in a pile rather than being chopped and spread.

[0028] The grain falls into the clean grain bin (or clean grain subsystem) 118. The sieve 122 separates some of the larger material from the grain, and the screen 124 separates some of the finer material from the clean grain. The clean grain falls onto an auger in the clean grain elevator 130, which moves the clean grain upward and stores it in the clean grain bin 132. Residue can be removed from the clean grain bin 118 by the airflow generated by the clean grain fan 120. This residue can also be moved rearward in the combine 100 toward the residue handling subsystem 138.

[0029] The residue can be moved back to the threshing machine 110 by the residue elevator 128, where it can be re-threshed. Alternatively, the residue can also be passed (also using a residue elevator or another transport mechanism) to a separate re-threshing mechanism, where it is also re-threshed.

[0030] Figure 1 It is also shown that, in one example, the combine 101 can include a variety of one or more sensors 180, some of which are shown schematically. For example, the combine 100 can include a ground speed sensor 147, one or more separator loss sensors 148, a clean grain camera 150, one or more clean grain bin loss sensors 152, and one or more perception systems 156 (e.g., imaging systems such as cameras). The ground speed sensor 147 senses the travel speed of the combine 100 over the ground schematically. This can be accomplished by sensing the speed of rotation of ground engaging elements 144, drive shafts, axles, or various other components. The travel speed can also be sensed by a positioning system, such as a global positioning system (GPS), a dead reckoning system, a LORAN system, or various other systems or sensors that provide an indication of travel speed. The perception system 156 is mounted to the front of and / or around (e.g., to the sides, rear, etc.) the combine 101 relative to the direction of travel 146 and senses the field (and its characteristics) in front of and / or around the combine 101 relative to the direction of travel 146 schematically and generates sensor signal(s) (e.g., images) indicative of these characteristics. For example, the perception system 156 can generate sensor signals indicative of changes in the terrain in the field in front of and / or around the combine 101. While shown in a particular location in Figure 1 It is noted that the perception system 156 can be mounted at different locations on the combine 101 and is not limited to the depiction shown in Figure 1 Additionally, while only one perception system 156 is shown, it is noted that the combine 101 can include any number of perception systems 156 mounted at any number of locations within the combine 101.

[0031] The clean grain bin loss sensors 152 illustratively provide output signals indicative of the amount of grain loss on the right and left sides of the clean grain bin 118. In one example, the sensors 152 are impact sensors that count the number of particle impacts per unit of time (or per unit of distance traveled) to provide an indication of clean grain bin particle loss. The impact sensors for the left and right sides of the clean grain bin can provide separate signals, or a combined or aggregated signal. It should be noted that the sensors 152 can also include a single sensor rather than separate sensors for each clean grain bin.

[0032] The separator loss sensors 148 provide signals indicative of grain loss in the left and right separators. The sensors associated with the left and right separators can provide separate grain loss signals or a combined or aggregated signal. This can also be implemented using various different types of sensors. It should be noted that the separator loss sensors 148 can also include only a single sensor rather than separate left and right sensors.

[0033] It should be understood, and as will be discussed further herein, that the sensors 180 can include Figure 1Various other sensors are not shown. For example, they can include a residue setting sensor configured to sense whether the combine 100 is configured to chop residue, drop a pile of material, etc. They can include a clean grain bin fan speed sensor that can be configured proximate the fan 120 to sense the speed of the fan. They can include a threshing gap sensor that senses the gap between the cylinder 112 and the concave 114. They can include a threshing cylinder speed sensor that senses the speed of the cylinder 112. They can include a separator gap sensor that senses the size of the openings in the separator 122. They can include a sieve gap sensor that senses the size of the openings in the sieve 124. They can include a material other than grain (MOG) moisture sensor that can be configured to sense the moisture level of material other than grain passing through the combine 101. They can include machine setting sensors configured to sense various configuration settings on the combine 101. They can also include machine orientation sensors that can be any of various different types of sensors that sense the orientation of the combine 101 and / or components thereof. They can include crop property sensors that can sense various different types of crop properties, such as crop type, crop moisture, and other crop properties. The crop property sensors can also be configured to sense properties of the crop as it is processed by the combine 101. For example, the sensor can sense the rate of grain feed as the grain travels through the clean grain elevator 120. They can sense the mass flow of grain through the elevator 130, or provide other output signals indicative of other sensed variables. The sensors 180 can include soil property sensors that can sense various different types of soil properties, including but not limited to soil type, soil compaction, soil moisture, soil structure, etc.

[0034] Some additional examples of types of sensors that can be used are described below, including but not limited to various position sensors that can generate sensor signals indicative of the position of the combine 101 on a field over which the combine 101 is traveling or the position of various components of the combine 101 (e.g., the header 104) relative to, for example, the field over which the combine 101 is traveling.

[0035] As the combine harvester 101 moves in the direction indicated by arrow 146, it is possible that the ground beneath, in front of, or around the combine harvester 101 can contain obstacles or changes in terrain. In operation, an operator sets the position of the header 104 to a certain height from the field such that the header 104 effectively harvests the crop. Obstacles and / or changes in the terrain of the field can result in a change in the distance of the header 104 from the field and, thus, result in the header 104 improperly or otherwise undesirably harvesting the crop. Such errors can especially affect the crop yield produced by the combine harvester 101. Additionally, sudden changes in the terrain of the field or encountering obstacles can result in the header 104 colliding with the field.

[0036] Figure 2 is a perspective view illustrating one example of a mobile agricultural machine in an example in which the mobile machine 100 is an agricultural sprayer (also referred to as a sprayer 201 or mobile machine 201). In Figure 1 As can be seen in Figure 2 , the agricultural sprayer 201 includes a spray system 202 having a tank 204 containing liquid to be applied to a field 206 as the agricultural sprayer travels in the direction shown by arrow 246. The tank 204 is fluidly connected to spray nozzles 208 by a delivery system including a set of conduits defining a flow path of the liquid from the tank 204 to the one or more spray nozzles 208. A fluid delivery system (e.g., a fluid pump) is configured to deliver the liquid from the tank 204 through the conduits to and through the spray nozzles 208. Operation of the fluid delivery system is adjustable (such as automatically or manually) to change the pressure, flow rate of the liquid, and various other fluid characteristics of the spray system 202. The spray nozzles 208 are connected to and spaced apart along a spray boom 210. In one example, the operation and position of the spray nozzles 208 can be adjusted, such as automatically or manually. For example, the position (e.g., height, orientation, tilt, etc.) of the nozzles 208 and the volume or flow rate of the liquid through the nozzles 208 (such as by operation of controllable valves) can be adjusted. The spray boom 210 includes arms 212 and 214 that can be articulated or pivoted relative to a central frame 216. Thus, the arms 212 and 214 are movable between a storage or transport position and an extended or deployed position (shown in

[0037] In Figure 2In the example shown in FIG. 1, the sprayer 201 includes a towed implement 218 that carries the spray system 202 and is towed by a towing or support machine 220 (exemplarily a tractor) having an operator’s compartment 203 that can have various different operator interface mechanisms for controlling the sprayer 201. The operator’s compartment 203 can include one or more operator interface mechanisms that allow an operator to control and manipulate the sprayer 201. The operator interface mechanisms in the operator’s compartment 203 can be any of a variety of different types of mechanisms. For example, they can include one or more input mechanisms such as steering wheels, levers, joysticks, buttons, pedals, switches, etc. In addition, the operator’s compartment 203 can include one or more operator interface display devices such as monitors or mobile devices supported within the operator’s compartment 203. In this case, the operator interface mechanisms can also include one or more user-actuatable elements such as icons, links, buttons, etc. that are displayed on the display devices. The operator interface mechanisms can include one or more microphones where voice recognition is provided on the sprayer 201. They can also include audio interface mechanisms (e.g., speakers), one or more haptic interface mechanisms, or a variety of other operator interface mechanisms. The operator interface mechanisms can also include other output mechanisms such as dials, gauges, meter outputs, lights, audible or visual alarms, or haptic outputs, etc.

[0038] The sprayer 201 includes a set of ground-engaging elements 244 such as wheels, tracks, etc. The sprayer 201 can also have a propulsion subsystem that includes an engine (or other power source) that drives the ground-engaging elements 244. It should be noted that in other examples, the sprayer 201 is self-propelled. That is, the machine that carries the spray system is not towed by a towing machine, but also includes a propulsion and steering system.

[0039] In operation, and as outlined, the height of the boom 210 (or arms 212 and 214) is set, and the sprayer 201 moves over the field 206 in the direction indicated by arrow 246. As it moves, liquid is delivered from the tank 204 through conduits in the boom 210 to the nozzles 208 and through the nozzles to be applied to the plants on the field 206. The application of the liquid over the field 206 can be controllably adjusted. For example, but not limited to, by changing the height of the boom 210 (or arms 212 and 214) from the field 206, changing the position of the nozzles 208 (e.g., height, orientation, tilt, etc.), changing the flow characteristics of the liquid through the spray system, etc.

[0040] Figure 2It is also shown that, in one example, the sprayer 201 can include a variety of one or more sensors 280, some of which are shown schematically. For example, the sprayer 201 can include one or more ground speed sensors 247, as well as one or more perception systems 256 (e.g., imaging systems such as cameras). The ground speed sensors 247 sense the speed of travel of the sprayer 201 over the field 206, schematically. This can be accomplished by sensing the speed of rotation of ground engaging elements 244, drive shafts, axles, or various other components. The speed of travel can also be sensed by a positioning system, such as a global positioning system (GPS), a dead reckoning system, a LORAN system, or various other systems or sensors that provide an indication of the speed of travel. The perception systems 256 (identified as 256-1 through 256-3) are mounted at different locations within the sprayer 201 and sense, schematically, the field (and its characteristics) in front of and / or around (e.g., sides, rear, etc.) the sprayer 201 (relative to the direction of travel 246) and generate sensor signal(s) (e.g., images) indicative of these characteristics. For example, a forward-looking perception system 256 can generate a sensor signal indicative of changes in the terrain of the field 206 in front of or around the sprayer 201. While shown in Figure 2 particular locations in Figure 2 , it should be noted that the perception systems 256 can be mounted at different locations within the sprayer 201 and are not limited to the depictions shown in

[0041] Additionally, while a particular number of perception systems 256 are shown in the illustrations, it should be noted that any number of perception systems can be placed at any number of locations within the sprayer 201. Figure 2 It is shown that the perception systems 256 can be mounted at one or more locations within the sprayer 201. For example, they can be mounted on the tractor vehicle 220, as shown by perception system 256-1. They can be mounted on the implement 218, as shown by perception system 256-2. They can be mounted on the spray boom 210 (including each of the spray boom arms 212 and 214) and spaced apart along the spray boom, as shown by perception system 256-3. The perception systems 256 can be forward-looking systems configured to view in front of components of the sprayer 201, side-looking systems configured to view to the sides of components of the sprayer 201, or rear-looking systems configured to view behind components of the sprayer 201. The perception systems 256 can be mounted on the sprayer 201 so that they travel above or below the canopy of vegetation on the agricultural surface 206. Note that these are merely some examples of locations for the perception systems 256, and the perception systems 256 can be mounted at one or more of these locations or at various other locations within the sprayer 201 or any combination thereof.

[0042] It should be appreciated, and as will be discussed further herein, that the sensors 280 can include Figure 2 Various other sensors not shown in FIG. 2. For example, they can include machine setting sensors configured to sense various configuration settings on the sprayer 201. The sensors 280 can also include machine orientation sensors, which can be any of various different types of sensors that sense an orientation of the sprayer 201 or an orientation of a component of the sprayer 201. The sensors 208 can include crop property sensors that can sense various different types of crop properties, such as crop type, crop moisture, and other crop properties. The sensors 208 can include soil property sensors that can sense various different types of soil properties, including but not limited to soil type, soil compaction, soil moisture, soil structure, and the like.

[0043] Some additional examples of types of sensors that can be used are described below, including but not limited to various position sensors that can generate sensor signals indicative of a position of the sprayer 201 on a field (on which the sprayer 201 is traveling) or a position of various components of the sprayer 201 (e.g., (e.g., the nozzles 208, the boom 210, the arms 212 and 214, etc.) relative to, for example, a field (on which the sprayer 201 is traveling).

[0044] Figure 3 is a block diagram of one example of a computing architecture 300 having, among other things, a mobile machine 100 (e.g., a combine 101, a sprayer 201, etc.) configured to perform operations (e.g., harvesting, spraying, etc.) on a worksite, such as a field 206. Some items are similar to Figures 1 to 2 items shown in FIG. 1, which are similarly numbered. Figure 3 The architecture 300 is shown to include the mobile machine 100, a network 359, one or more operator interfaces 360, one or more operators 362, one or more user interfaces 364, one or more remote users 366, one or more remote computing systems 368, one or more vehicles 370, and can also include other items 390. The mobile machine 100 can include one or more controllable subsystems 302, a control system 304, a communication system 306, one or more data stores 308, one or more sensors 310, one or more processors, controllers, or servers 312, and it can also include other items 313. The controllable subsystems 302 can include a position subsystem 314, a steering subsystem 316, a propulsion subsystem 318, and can also include other items 320, such as other subsystems, including but not limited to those described above with reference to Figures 1 to 2The described subsystems. The position subsystem 314 can itself include a header position subsystem 322, a boom position subsystem 324, and it can include other items 326.

[0045] The control system 304 can include one or more processors, controllers, or servers 312, a communication controller 328, a terrain confidence system 330, and it can include other items 334. The data storage 308 can include map data 336, supplemental data 338, and it can include other data 340.

[0046] Figure 3 It is also shown that the sensors 310 can include any number of different types of sensors that sense or detect any number of characteristics. For example, characteristics related to the environment of the mobile machine 100 (e.g., the agricultural surface 206) and the environment of other components in the computing architecture 300. Further, the sensors 310 can sense or otherwise detect characteristics related to components in the computing architecture 300, for example, operating characteristics of the mobile machine 100 or the vehicle 370, such as current position information related to a header of the combine harvester 101 or a boom of the sprayer 201. In the illustrated example, the sensors 310 can include one or more perception systems 342 (such as the 156 and / or 256 described above), one or more position sensors 344, one or more geo-location sensors 346, one or more terrain sensors 348, one or more weather sensors 350, and it can also include other sensors 352, such as any of the sensors (e.g., the sensors 180 or 280) described above. The geo-location sensors 346 can itself include one or more position sensors 354, one or more heading / speed sensors 356, and it can include other items 358. Figures 1 to 2

[0047] The control system 304 is configured to control other components and systems of the computing architecture 300, such as components and systems of the mobile machine 100 or the vehicle 370. For example, the communication controller 328 is configured to control the communication system 306. The communication system 306 is used to communicate between components of the mobile machine 100 or to communicate with other systems, such as the vehicle 370 or the remote computing system 368, over a network 359. The network 359 can be any of a variety of different types of networks, such as the Internet, a cellular network, a wide area network (WAN), a local area network (LAN), a controller area network (CAN), a near field communication network, or any of a variety of other networks or combinations of networks or communication systems.

[0048] ​The remote user 366 is shown interacting with the remote computing system 368, e.g., through a user interface 364. The remote computing system 368 can be various different types of systems. For example, the remote computing system 368 can be in a remote server environment. Further, it can be a remote computing system such as a mobile device, a remote network, a farm manager system, a supplier system, or various other remote systems. The remote computing system 368 can include one or more processors, controllers, or servers 374, a communication system 372, and it can include other items 376. As shown in the example shown, the remote computing system 368 can also include one or more data stores 308 and control systems 304. For example, data stored and accessed by various components in the computing architecture 300 can be remotely located in the data stores 308 on the remote computing system 368. Additionally, various components of the computing architecture 300 (e.g., the controllable subsystems 202) can be controlled by the control systems 304 remotely located at the remote computing system 368. Thus, in one example, the remote user 366 can remotely control the mobile machine 100 or vehicle 370, such as by user input received by the user interface 364. These are merely some examples of operation of the computing architecture 300.

[0049] The vehicle 370 (e.g., a UAV, a ground vehicle, etc.) can include one or more data stores 378, one or more controllable subsystems 380, one or more sensors 382, one or more processors, controllers, or servers 384, a communication system 385, and it can include other items 386. In the illustrated example, the vehicle 370 can also include the control system 304. The vehicle 370 can be used to perform operations on a worksite, such as a spraying or harvesting operation on an agricultural surface. For example, a UAV or ground vehicle 370 can be controlled to travel on a worksite, including in front of or behind the mobile machine 100. The sensors 382 can include any number of various sensors, such as the sensors 310. For example, the sensors 382 can include the perception system 342. In a particular example, the vehicle 370 can travel in a field in front of the mobile machine 100 and detect any number of characteristics that can be used to control the mobile machine 100, such as detecting terrain characteristics in front of a combine 101 or a sprayer 201 to control a height of a header 102 or a spray boom 110 from a surface of the worksite (e.g., a field 206), as well as to control various other operating parameters of various other components. In another example, the vehicle 370 can travel in a field behind the mobile machine 100 and detect any number of characteristics that can be used in control of the mobile machine 100, such that the vehicle 370 can implement closed loop control of the mobile machine 100. In another example, the vehicle 370 can be used to perform a reconnaissance operation to collect additional data related to the worksite or a particular geographic location of the worksite, such as terrain data.

[0050] Additionally, the control system 304 can be located on the vehicle 370, such that the vehicle 370 can generate action signals to control actions of the mobile machine 100 (e.g., adjust operating parameters of one or more controllable subsystems 302) based on characteristics sensed by the sensors 382. Further, a confidence map can be generated by the control system 304 on the vehicle 370 for use in controlling the mobile machine 100.

[0051] As shown, the vehicle 370 can include a communication system 385 that is configured to communicate with other components of the computing architecture 300, such as with the mobile machine 100 or the remote computing system 368, as well as to communicate between components of the vehicle 370.

[0052] Figure 3Also shown is one or more operators 362 interacting with the mobile machine 100, the remote computing system 368, and the vehicle 370, such as through the operator interface 360. The operator interface 360 can be located on the mobile machine 100 or the vehicle 370, for example in an operator’s cabin (e.g., 103 or 203, etc.), such as a cab, or they can be another operator interface communicably connected to various components in the computing architecture 300, such as a mobile device or other interface mechanism.

[0053] Before discussing the overall operation of the mobile machine 100, a brief description of some of the items in the mobile machine 100 and their operation will first be provided.

[0054] The communication system 306 can include a wireless communication logic system that can be substantially any wireless communication system that can be used by the systems and components of the mobile machine 100 to communicate information to other items, such as items among the control system 304, the data storage 308, the sensors 310, the controllable subsystems 302, and the terrain confidence system 330. In another example, the communication system 306 communicates through a controller area network (CAN) bus (or another network, such as Ethernet, etc.) to communicate information between these items. Such information can include various sensor signals and output signals generated by sensor characteristics and / or sensing characteristics, among other items.

[0055] The perception system 342 is configured to sense various characteristics of the environment related to the surroundings of the mobile machine 100, such as characteristics related to the work surface. For example, the perception system 342 can be configured to sense characteristics related to vegetation on the work surface (e.g., crop stage, stress, damage, lodging, density, height, leaf area index, etc.), characteristics related to work surface terrain (e.g., washboard, ruts, drift, soil erosion, soil deposition, soil accumulation, obstacles, etc.), characteristics related to soil (e.g., type, compactness, structure, etc.), characteristics related to soil cover (e.g., residue, cover crops, etc.), and various other characteristics. The perception system 342 can also sense terrain characteristics of the work surface ahead of the mobile machine 100 so that changes in the terrain can be determined and the height of the header 104 or the boom 210 can be adjusted. In one example, the perception system 342 can include an imaging system, such as a camera.

[0056] The position sensors 344 are configured to sense position information related to various components of the agricultural spraying system 102. For example, multiple position sensors 344 can be disposed at different locations within the mobile machine 100. As such, they can detect the position (e.g., height, orientation, tilt, etc.) of various components of the mobile machine 100, such as the height of the header 104 or spray boom 210 (or spray booms 212 and 214) above the agricultural surface 110, the height or orientation of the spray nozzles 208, and position information related to various other components. The position sensors 344 can be configured to sense position information related to any number of items for various components of the mobile machine 100, such as position information related to the work surface, position information related to other components of the mobile machine 100, and various other items. For example, the position sensors 344 can sense the height of the header 104, spray boom 210, or spray nozzles 208 from the top of detected vegetation on the work surface. In another example, by knowing the dimensions of the mobile machine 100, the position and orientation of other items can be calculated based on the sensor signals.

[0057] The geo-position sensors 346 include position sensors 354, heading / speed sensors 356, and can also include other sensors 358. The position sensors 354 are configured to determine the geo-position of the mobile machine on the work surface (e.g., the field 206). The position sensors 354 can include, but are not limited to, GNSS receivers that receive signals from Global Navigation Satellite System satellites (GNSS). The position sensors 354 can also include Real Time Kinematic (RTK) components configured to enhance the accuracy of the position data derived from the GNSS signals. The position sensors 354 can include various other sensors, including other satellite-based sensors, cellular triangulation sensors, dead reckoning sensors, etc.

[0058] The heading / speed sensors 356 are configured to determine the heading and speed of the mobile machine 100 through the work site during operation. This can include sensors that sense the motion of ground engaging elements (e.g., wheels or tracks 144 or 244), or can utilize signals received from other sources, such as the position sensors 354.

[0059] The terrain sensors 348 are configured to sense characteristics of the work surface (e.g., the field 206) on which the mobile machine 100 is traveling. For example, the terrain sensors 348 can detect the terrain of the work site (which can be downloaded as a terrain map or sensed by the sensors) to determine the slope of various areas of the work site, detect the boundaries of the field, detect obstacles or other objects (e.g., rocks, root masses, trees, etc.) on the field, etc.

[0060] The weather sensors 350 are configured to sense various weather characteristics related to the work site. For example, the weather sensors 350 can detect the direction and speed of the wind propagating over the work site. The weather sensors 350 can detect precipitation, humidity, temperature, and many other conditions. This information can also be obtained from a remote weather service.

[0061] The other sensors 352 can include, for example, operational parameter sensors configured to sense characteristics related to machine settings or operations of various components of the mobile machine 100 or the vehicle 370.

[0062] The sensors 310 can include any number of different types of sensors, such as potentiometers, Hall effect sensors, various mechanical and / or electrical sensors. The sensors 310 can also include various electromagnetic radiation (ER) sensors, optical sensors, imaging sensors, thermal sensors, LIDAR, RADAR, sonar, radio frequency sensors, audio sensors, inertial measurement units, accelerometers, pressure sensors, flow meters, etc. Additionally, while multiple sensors are shown to detect or otherwise sense respective characteristics, the sensors 310 can include sensors configured to sense or detect a variety of different characteristics and can produce a single sensor signal indicative of multiple characteristics. For example, the sensors 310 can include imaging sensors mounted at various locations within the mobile machine 100 or the vehicle 370. The imaging sensors can generate images indicative of multiple characteristics related to both the mobile machine 100 and the vehicle 370 and their environment (e.g., the agricultural surface 110). Further, while multiple sensors are shown, more or fewer sensors 310 can be utilized.

[0063] Additionally, it will be appreciated that some or all of the sensors 310 can be controllable subsystems of the mobile machine 100. For example, the control system 304 can generate various action signals to control the operation, position (e.g., height, orientation, tilt, etc.), and various other operational parameters of the sensors 310. For example, because vegetation on the work site can obstruct the line of sight of the perception system 342, the control system 304 can generate action signals to adjust the position or orientation of the perception system 342, thereby adjusting their line of sight. These are just examples. The control system 304 can generate various action signals to control any number of operational parameters of the sensor(s) 310.

[0064] The controllable subsystems 302 illustratively include a position subsystem 314, a steering subsystem 316, a propulsion subsystem 318, and can also include other subsystems 320. The controllable subsystems 302 will now be briefly described.

[0065] The position subsystem 314 is generally configured to control the position (e.g., height, orientation, tilt, etc.) of various components of the mobile machine 100 or otherwise actuate various components of the mobile machine 100 to move. The position subsystem 314 can itself include a header position subsystem 322, a boom position subsystem 324, and can also include other position subsystems 326. The header position subsystem 322 is configured to controllably adjust the position (e.g., height, orientation, tilt, etc.) of the header 104 on the combine 101 or otherwise actuate the header 104 on the combine 101 to move. The header position subsystem 322 can include a number of actuators (such as electrical, hydraulic, pneumatic, mechanical, or electromechanical actuators, among many others) that are connected to various components to adjust the position (e.g., height, orientation, tilt, etc.) of the header 104 relative to a work surface (e.g., the surface of a field). For example, upon detecting an upcoming change in the terrain on the work surface (e.g., detecting a rut or soil accumulation, an obstacle, etc.), an action signal can be provided to the header position subsystem 322 to adjust the position (e.g., height, orientation, tilt, etc.) of the header 104 relative to the work surface.

[0066] The boom position subsystem 324 is configured to controllably adjust the position (e.g., height, orientation, tilt, etc.) of the boom 210 (including the individual boom arms 212 and 214) or otherwise actuate the boom 210 (including the individual boom arms 212 and 214) to move. For example, the boom position subsystem 324 can include a number of actuators (such as electrical, hydraulic, pneumatic, mechanical, or electromechanical actuators, among many others) that are connected to various components to adjust the position or orientation of the boom 210 or the individual boom arms 212 and 214. For example, upon detecting a characteristic related to the terrain of the agricultural surface 206 (e.g., detecting a rut, soil accumulation, obstacle, etc. on the agricultural surface 206), an action signal can be provided to the boom position subsystem 324 to adjust the position of the boom 210 or the boom arms 212 or 214 relative to the agricultural surface 206.

[0067] Other position subsystems 326 can include a nozzle position subsystem configured to controllably adjust the position (e.g., height, orientation, tilt, etc.) of the nozzles 208 or otherwise actuate the nozzles 208 to move. The nozzle position subsystem can include a plurality of actuators (such as electrical, hydraulic, pneumatic, mechanical, or electromechanical actuators, among many other types of actuators) connected to various components to adjust the position (e.g., height, orientation, tilt, etc.) of the nozzles 208. For example, upon detecting an upcoming change in the terrain on the agricultural surface 206 (e.g., detecting a rut, soil accumulation, obstacle, etc.) or an upcoming change in the height of vegetation (e.g., the height of crops, weeds, etc.), an action signal can be provided to the nozzle position subsystem to adjust the position (e.g., height, orientation, tilt, etc.) of the nozzles 208 relative to the agricultural surface 206 or relative to the vegetation on the agricultural surface 206.

[0068] The turning subsystem 316 is configured to control the heading of the mobile machine 100 by turning the ground-engaging elements (e.g., the wheels or tracks 144 or 244). The turning subsystem 316 can adjust the heading of the mobile machine 100 based on action signals generated by the control system 304. For example, based on sensor signals generated by the sensors 310 indicating a change in the terrain, the control system 304 can generate action signals to control the turning subsystem 316 to adjust the heading of the mobile machine 100. In another example, the control system 304 can generate action signals to control the turning subsystem 316 to adjust the heading of the mobile machine 100 to conform to a command-controlled route, such as an operator or user command-controlled route, or a route based on a terrain confidence map generated by the terrain confidence system 330 as will be described in greater detail below, among various other command-controlled routes. The command-controlled route can also be based on characteristics of the environment in which the mobile machine 100 is operating as sensed or otherwise detected by the sensors 310, such as characteristics sensed or detected by the perception system 342 on the mobile machine 100 or the vehicle 370. For example, based on upcoming changes in the terrain at the worksite (such as ruts) sensed by the perception system 342, a route can be generated by the control system 304 to change the heading of the mobile machine 100 to avoid the ruts.

[0069] The propulsion subsystem 318 is configured to propel the mobile machine 100 over a worksite surface, such as by driving motion of ground engaging elements (e.g., wheels or tracks 144 or 244). It can include a power source (such as an internal combustion engine or other power source), a set of ground engaging elements, and other powertrain components. In one example, the propulsion subsystem 318 can adjust a speed of the mobile machine 100 based on action signals generated by the control system 304, which can be based on various properties sensed or detected by the sensors 310, a terrain confidence map generated by the terrain confidence system 330, and various other bases, such as operator or user input.

[0070] The other subsystems 320 can include various other subsystems, such as a material delivery subsystem on the sprayer 202. The material delivery subsystem can include one or more pumps, one or more material tanks, flow paths (e.g., conduits), controllable valves (e.g., pulse width modulated valves, solenoid valves, etc.), one or more nozzles (e.g., nozzles 208), and various other items. The one or more pumps can be controllably operated to pump material (e.g., herbicide, pesticide, insecticide, fertilizer, etc.) along flow paths defined by conduits to the nozzles 208, which can be mounted along the spray boom 210 and spaced apart, or at other locations within the sprayer 202. In one example, a plurality of controllable valves (e.g., associated with each of the nozzles 208) can be placed along the flow paths, which can be controlled between an open (e.g., on) and closed (e.g., off) position to control a flow (e.g., control the flow) of material through the valves.

[0071] The material tanks can include a plurality of hoppers or tanks, each configured to individually contain a material that can be controllably and selectively pumped by the one or more pumps through the flow paths to the nozzles 208. The operating parameters of the one or more pumps can be controlled to adjust a pressure or flow of the material, as well as various other properties of the material to be delivered to the worksite.

[0072] The nozzles 208 are configured to apply material to a worksite (e.g., the field 206), such as by atomizing the material. The nozzles 208 can be controllably operated, such as by action signals received from the control system 304 or manually by the operator 264. For example, the nozzles 208 can be controllably operated between an open (e.g., on) and closed (e.g., off) position. Additionally, the nozzles 208 can be individually operated to vary properties of a spray emitted by the nozzles 208, such as a motion (e.g., rotational motion) of the nozzles 208 that widens or narrows a flow path through and out of the nozzles 208 to affect a pattern, volume, and various other properties of the spray.

[0073] The control system 304 is configured to receive or otherwise obtain various data and other inputs, such as sensor signals, user or operator inputs, data from data stores, and various other types of data or inputs. Based on the data and inputs, the control system 304 can make various determinations and generate various action signals.

[0074] The control system 304 can include a terrain confidence system 330. The terrain confidence system 330 can determine a confidence level of a terrain characteristic of a worksite indicated by a previous or prior terrain map based on information accessed in a data store (e.g., 208, 378, etc.) or data received from a sensor (e.g., 310, 382, etc.) and generate a variety of terrain confidence outputs indicating the determined terrain confidence level. For example, the terrain confidence system 330 can generate a terrain confidence output as a representation indicating a terrain confidence level for a worksite or for portions of a worksite. These representations can be numerical, such as a percentage (e.g., 0% to 100%) or a scalar value, a grayscale or scaled value (e.g., A to F, “high, medium, low,” 1 to 10, etc.), a recommendation (e.g., caution, proceed, slow, scout first, no crops, etc.), and a variety of other representations. Additionally, the terrain confidence system 330 can generate a terrain confidence map as a terrain confidence output indicating a terrain confidence level for a worksite or a particular portion of a worksite.

[0075] The terrain confidence output can be used by the control system 304 to generate various action signals to control actions of the mobile machine 100 and other components of the computing architecture 300, such as the vehicle 370, the remote computing system 368, etc. For example, based on the terrain confidence output, the control system 304 can generate action signals to provide an indication (e.g., an alert, a display, a notification, a recommendation, etc.) on various interfaces or interface mechanisms, such as the operator interface 360 or the user interface 364. The indication can include audio, visual, or haptic output. In another example, based on the terrain confidence output, the control system 304 can generate action signals to control actions of one or more of the various components of the computing architecture 300, such as to control an operating parameter of one or more of the controllable subsystems 302 or the controllable subsystems 380. For example, based on the terrain confidence output, the control system 304 can generate action signals to control the position subsystem 314 to control a position (e.g., a height, an orientation, a tilt, etc.) of the cutting table 104 or the spray boom 210. The control system 304 can also control the steering subsystem 316 to control a heading of the mobile machine 100 and the propulsion subsystem 318 to control a speed of the mobile machine 100. The control system 304 can also control various other subsystems, such as a material delivery subsystem, to control delivery of material to a worksite. These are just examples. The control system 304 can generate any number of action signals based on the terrain confidence output generated by the terrain confidence system 330 to control any number of actions of components in the computing architecture 300.

[0076] The control system 304 can include various other items 334, such as other controllers. For example, the control system 304 can include a dedicated controller corresponding to each of the various controllable subsystems. Such dedicated controllers can include a spray subsystem controller, a spray boom position subsystem controller, a steering subsystem controller, a propulsion subsystem controller, and various other controllers for various other controllable subsystems. Additionally, the control system 304 can include various logic components, such as an image processing logic circuit. The image processing logic circuit can process images generated by the sensors 310 (e.g., images generated by the perception system 342) to extract data from the images. The image processing logic circuit can utilize various image processing techniques or methods, such as RGB, edge detection, black / white analysis, machine learning, neural networks, pixel testing, pixel clustering, shape detection, and any number of other suitable image processing and data extraction techniques and / or methods.

[0077] Figure 3It is also shown that the data storage 308 can include map data 336, supplemental data 338, and various other data 340. The map data 336 can include one or more topographic maps of the worksite that indicate topographic characteristics (e.g., slope, elevation, etc.) at geographic locations of the worksite. The topographic maps can include georeferenced data represented in various ways, such as geotagged data, rasters, polygons, point clouds, and georeferenced data represented in various other ways. The maps can be generated based on output from sensors, such as imaging sensors (e.g., stereo, lidar, etc.) during a survey of the worksite or a flyover of the worksite, and output from previous passes or operations of mobile machines on the worksite. These topographic maps can be generated (particularly when based on nadir imaging) based on data collected during bare ground conditions when the field surface is substantially free of obscuring due to vegetation, such as during post-harvest, pre-plant, immediately post-plant, etc. The topographic maps can be used for control of the mobile machine as it travels on the worksite, or as a baseline as will be further described below.

[0078] The supplemental data 338 can include various data that indicates various characteristics related to the worksite or related to the environment of the worksite that are obtained or collected at times later than the times at which data for previous or a priori topographic maps were collected. In one example, the supplemental data 338 includes any of a variety of data that can indicate characteristics or conditions that can affect the topography of the worksite. This can include data obtained or collected prior to the mobile machine 100 operating on the worksite as well as in-field data (e.g., data from the sensors 310 or 382). The supplemental data can include weather data (e.g., rain, snow, ice, hail, wind, and weather events such as tornadoes, hurricanes, storms, tsunamis, etc.), environmental data (e.g., waves and tides), event data (e.g., fires, volcanoes, floods, earthquakes, etc.), additional topographic data (e.g., generated by sensors on machines traveling on the worksite, such as surveys, flyovers, additional operations, etc.), vegetation data (e.g., images of vegetation, crop types, weed types, density, height, vegetation indices, vegetation state data, etc.), activity data (e.g., data indicating that human activity has occurred on the worksite, such as operations of other machines, etc.), additional images of the worksite, and various other supplemental data. The supplemental data can be obtained from a variety of sources, such as machines that survey the worksite or fly over the worksite, various other sensors, weather stations, news sources, operator or user input, and various other sources. The supplemental data can also be obtained or collected and received from sensors on the mobile machine 100 or the vehicle 370 during operation (e.g., in-field) or prior to operation.

[0079] Supplemental data can indicate various characteristics related to the worksite or the environment of the worksite. Based on the supplemental data, the terrain confidence system 330 can determine a confidence in the terrain characteristics of the worksite indicated by the previous or prior terrain map. In one example, the terrain confidence system 330 can determine whether a change in the terrain of the worksite has occurred or is likely to have occurred based on indications provided by the supplemental data. For example, if a particular weather condition (e.g., a particular level of rainfall) has occurred after the data used for the previous or prior terrain map was collected, the terrain confidence system 330 can determine that the terrain at the worksite or at a particular geographic location within the worksite has changed or is likely to have changed. This is merely an example. The terrain confidence system 330 can determine a confidence in the terrain characteristics of the worksite or at a particular geographic location within the worksite based on any number of indications provided by the supplemental data and any combination thereof. Further, it will be noted that in one example, the term "likely" means a threshold likelihood or probability that the current terrain characteristic deviates from the characteristic indicated by the previous or prior terrain map by a threshold amount. In one example, the threshold can be input by an operator or user or automatically set by the terrain confidence system indicating a level of deviation from the characteristic indicated by the previous or prior terrain map.

[0080] Other data 340 can include various other data such as historical data related to operations on the worksite, historical data related to characteristics and conditions of the worksite (e.g., historical terrain characteristics) or the environment of the worksite (e.g., historical data related to previous events), and historical data indicating occurrences of changes in the terrain of the worksite due to various events (e.g., weather). This type of information can be used by the terrain confidence system 330 to determine the likelihood of a change in terrain characteristics that is currently occurring or has occurred.

[0081] Figure 4 is a block diagram showing one example of the terrain confidence system 330 in more detail. The terrain confidence system 330 can include the communication system 306, one or more processors, controllers, or servers 312, a terrain confidence analyzer 400, a map generator 402, a data capture logic system 404, an action signal generator 406, a threshold logic system 408, a machine learning logic system 410, and can also include other items 412. The terrain confidence analyzer 400 can itself include a terrain change detector 420, and it can also include other items 432. The map generator 402 can itself include a corrected terrain map generator 440, a terrain confidence map generator 442, and can also include other items 444. The data capture logic system 404 can itself include a sensor access logic system 434, a data storage device access logic system 436, and it can also include other items 438.

[0082] In operation, the terrain confidence system 330 determines a confidence level of a terrain characteristic related to a worksite based on available supplemental data related to the worksite or an environment of the worksite as indicated by a previous or a prior terrain map of the worksite. The terrain confidence system 330 can generate a variety of terrain confidence outputs, such as various representations of the terrain confidence level, a corrected terrain map or a terrain confidence map, and various other outputs. The terrain confidence system 330 can generate action signals to control operation of a variety of components of the computing architecture 300 (e.g., the mobile machine 100, the vehicle 370, the remote computing system 368, etc.), as well as control operation of various components or items of components of the computing architecture 300, such as controllable subsystems 302 of the mobile machine 100. Further, the terrain confidence system 330 can generate action signals to provide indications, such as displays, recommendations, alerts, notifications, and various other indications on interfaces or interface mechanisms, such as the operator interface 360 or the user interface 364. The indications can include audio, visual, or haptic outputs.

[0083] The terrain confidence level can indicate a confidence that a terrain characteristic of the worksite is the same (or substantially the same) as the terrain characteristic in the previous or prior terrain map of the worksite, or additionally, a confidence that the terrain characteristic of the worksite is accurately or reliably represented by the terrain characteristic in the previous or prior terrain map of the worksite. In some examples, the terrain confidence level can indicate a likelihood that a terrain characteristic of the worksite has changed as indicated by the previous or prior terrain map, or the terrain confidence level can indicate a likelihood that a terrain characteristic of the worksite is the same (or substantially the same) as the previous or prior terrain map of the worksite as indicated by the previous or prior terrain map, or additionally, a likelihood that the terrain characteristic of the worksite is accurately or reliably represented by the previous or prior terrain map of the worksite. In some examples, a representation of the terrain confidence level can simultaneously indicate a likelihood that a terrain characteristic of the worksite is the same (or substantially the same) as the terrain characteristic in the previous or prior terrain map as indicated by the previous or prior terrain map, or additionally, a likelihood that the terrain characteristic of the worksite is accurately or reliably represented by the terrain characteristic in the previous or prior terrain map; and a likelihood that the terrain characteristic as indicated by the previous or prior terrain map has changed. For example, a representation in the form of a percentage, such as "80%", can indicate that a likelihood that a terrain characteristic of the worksite is the same (or substantially the same) as the previous or prior terrain map or a likelihood that the terrain characteristic of the worksite is accurately or reliably represented by the previous or prior terrain map is 80%, and thus the representation simultaneously indicates that a likelihood that the terrain characteristic of the worksite has changed is 20%. This is merely an example.

[0084] Data capture logic system 404 captures or obtains data that can be used by other items in terrain confidence system 330. Data capture logic system 404 can include sensor access logic system 434, data storage access logic system 436, and other logic system 438. Sensor access logic system 434 can be used by terrain confidence system 330 to obtain or otherwise access sensor data (or values indicative of sensed variables / characteristics) provided from sensors 310, as well as other sensors such as sensors 382 of vehicle 370, which can be used to determine terrain confidence levels. To illustrate, but not by way of limitation, sensor access logic system 434 can obtain sensor signals indicative of characteristics related to the terrain of the worksite at which mobile machine 100 or vehicle 300 is operating. These characteristics can be indicative of changes in the terrain of the field (such as gullies or ruts, soil ridges, washouts), as well as various other characteristics.

[0085] Additionally, data storage access logic system 436 can be used to obtain or otherwise access data previously stored on data storage 308 or 378, or data stored at remote computing system 368. This can include map data 336, supplemental data 338, as well as various other data 340, for example.

[0086] After obtaining various data, terrain confidence analyzer 400 analyzes the data to determine a confidence level for the terrain characteristics indicated or otherwise provided by the previous or a prior terrain map. In one example, this analysis can include comparing the characteristics on the previous or prior terrain map with the obtained data, such as supplemental data 338. Terrain confidence analyzer 400 can include terrain change detector 420, and it can include other items 432. Terrain change detector 420 can itself include weather logic system 422, vegetation logic system 424, soil logic system 426, event logic system 428, as well as various other logic systems 430.

[0087] Based on the terrain confidence level, the terrain confidence system 330 can use the action signal generator 406 to generate various action signals to control operation of components of the computing architecture 300 (e.g., the mobile machine 100, the remote computing system 368, the vehicle 370), or to provide an indication on an interface or interface mechanism, such as a display, a recommendation, or other indication (e.g., an alert). The indication can include audio, visual, or haptic output. For example, based on the terrain confidence level, the terrain confidence system 330 can generate action signals to control the position of various components of the mobile machine 100 (e.g., the position of the header 104, the position of the spray boom 210, etc.). In another example, based on the terrain confidence level, a display, a recommendation, and / or other indication can be generated and presented to the operator 362 on the operator interface 360, or to the remote user 366 on the user interface 364. Based on the generated display, the operator 362 or the remote user 366 can manually (e.g., through input on the interface) adjust settings or operation of components of the computing architecture 300. These are merely examples, and the terrain confidence system 330 can generate any number of action signals to control any number of settings or operations of any number of machines, or generate any number of displays, recommendations, or other indications.

[0088] It should be noted that the terrain confidence analyzer 400 can implement or otherwise utilize various techniques, such as various image processing techniques, statistical analysis techniques, various models (e.g., soil models, soil erosion models, vegetation models, and various other models), numerical equations, neural networks, machine learning, knowledge systems (e.g., expert knowledge systems, operator or user knowledge systems, etc.), fuzzy logic systems, rule-based systems, and various other techniques and any combination thereof.

[0089] The terrain change detector 420 detects a change (e.g., a deviation) or a likelihood of a change in a characteristic of the worksite from a characteristic indicated by a previous or a prior terrain map. In some examples, detecting a change includes detecting a change or a likely change in a terrain characteristic of the worksite that is not indicated by a previous or a prior terrain map. In other examples, detecting a change includes detecting a characteristic of the worksite or a characteristic of the environment of the worksite that indicates a likely change in a terrain characteristic of the worksite. For example, detecting a weather condition (e.g., heavy rain and various other characteristics) or a weather event (e.g., a flood) that indicates a likely change in a terrain characteristic of the worksite. In another example, detecting a characteristic of the worksite (e.g., a fallen crop, an area of a field where crop growth is stunted, and various other characteristics) that indicates a likely change in a terrain characteristic of the worksite. It should be noted that while a single characteristic can indicate a change or a likely change in a terrain characteristic of the worksite, multiple characteristics can also form the basis for detecting or determining that a change or a likely change has occurred. For example, such characteristics can include consideration of weather conditions (e.g., precipitation levels), soil characteristics of the worksite or a particular area of the worksite, and previously known slopes of the worksite or a particular area of the worksite.

[0090] The weather logic system 422 is configured to analyze weather data accessed from the data store, received from sensors such as the weather sensors 350 or operator or user input or other sources such as remote weather services or stations. The weather logic system 422 determines whether a change in the terrain of the worksite (as indicated by a previous or a prior terrain map) has changed or is likely to have changed. For example, the weather logic system 422 can receive various data indicating weather conditions (such as types and levels of precipitation (e.g., hail, rain, snow, various other precipitation), temperature, humidity, wind speed and direction, and various other weather conditions) that occurred within a time period after data was collected for a previous or a prior map. As an example, assume the weather logic system 422 receives weather data indicating that the worksite received 4 inches of rain within a certain time period (e.g., 24 hours). The weather logic system 422 can determine that a change in a terrain characteristic of the worksite or a particular geographic location within the worksite (such as a washout) has occurred or is likely to have occurred. Such a determination can be based on the weather data alone, or it can be based on a combination of the weather data and other characteristics of the worksite or the environment (such as tillage history, residue coverage, soil compaction, soil type, slope, or various other soil characteristics).

[0091] In another example, the weather logic system 422 can receive or otherwise obtain various data indicative of weather events (such as storms, tornadoes, hurricanes, tsunamis, floods, high winds, and various other weather events) that occurred within a time after data was collected for a previous or prior map. For example, the weather logic system 422 can receive weather data indicative of a worksite being flooded and can determine that a change in topographical characteristics of the worksite or a particular geographic location within the worksite has occurred or can have occurred. The weather logic system 422 can make these determinations based on various models, such as weather models, water gauge readings, and various other models.

[0092] The vegetation logic system 424 is configured to analyze vegetation data, which can be accessed from a data store, which can be received from sensors, such as imaging sensors that image the worksite during flyovers, and various other data sources of vegetation. The vegetation logic system 424 determines whether a change in topography of the field indicated by a previous or prior topographical map has occurred or can have occurred. For example, the vegetation logic system 424 can receive various data indicative of vegetation characteristics or conditions that occurred or otherwise presented within a time after data was collected for a previous or prior map. This data can include crop status data (e.g., data indicative of crop health, growth, standing, blown down, lodged crops, direction of lodged crops, and various other crop status data), vegetation type (e.g., crop type, weed type, cultivar or hybrid variety, etc.), crop stage, crop stress, crop density, crop height, leaf area index (LAI), vegetation index (VI) data (including, for example, Normalized Difference Vegetation Index (NDVI)), and various other vegetation data. For example, the vegetation logic system 424 can receive vegetation data (e.g., LAI, NDVI, etc.) indicative of vegetation at the worksite or a particular geographic location of the worksite being less vigorous than expected and can determine that a change in topographical characteristics of the worksite or a particular geographic location within the worksite has occurred or can have occurred. For example, less vigorous vegetation growth or density and vegetation status data indicative of less healthy vegetation can be an indicator of a change in topographical characteristics of the worksite, such as development of a shallow ditch, gully, or scour, and material deposition. Such determinations can be based on vegetation data alone or can be based on a combination of vegetation data and other characteristics of the worksite or environment of the worksite. For example, based on vegetation data (e.g., growth, health, crop status, etc.) and weather data (e.g., rainfall levels), the vegetation logic system 424 can determine that a scour can have occurred at the worksite or a particular geographic location within the worksite.

[0093] In another example, the vegetation logic system 424 can receive vegetation data indicating vegetation that has been blown down or otherwise laid down or bent over instead of standing as it should. The vegetation data can indicate windblown tumbleweeds or other vegetation debris on the worksite, and can determine that a change in the topographical characteristics of the worksite or a particular geographic location within the worksite has occurred or can have occurred. For example, detecting vegetation that has been blown by the wind can indicate sediment or material drift, such as erosion (e.g., lowering of the soil level) or deposition (e.g., accumulation of soil level, such as soil berms) due to high winds, flooding, etc. Such determinations can be based on the vegetation data alone, or can be based on a combination of the vegetation data and other characteristics of the field. Additionally, the vegetation logic system 424 can make these determinations based on various models, such as crop models as well as various other models.

[0094] The soil logic system 426 is configured to analyze soil data accessed from data storage, received from sensors such as soil characteristic sensors, or received from operator or user inputs as well as various other soil data sources. The soil logic system 426 can determine whether a change in the topography of the worksite has occurred or can have occurred from the topography indicated by a previous or defined topographic map. For example, the soil logic system 426 can receive various data indicating soil characteristics (such as soil type, soil compactness, soil structure, soil surface characteristics (e.g., shallow gullies, gullies, scour, erosion, deposition, etc.), soil moisture, soil composition, soil cover (e.g., residue levels, such as crop residue), as well as various other soil characteristics) that have presented since the time at which data was collected for a previous or prior map. For example, the soil logic system 426 can receive soil data indicating that the soil at the worksite or at a particular geographic location within the worksite is at a certain level of compactness, and based on the level of compactness as well as the amount of wind or rain, the soil logic system 426 can determine that it is more or less likely that some erosion has occurred.

[0095] In other examples, such determinations can be based on soil data alone or on a combination of soil data and other characteristics of the worksite or the worksite's environment. For example, erosion can be more or less based on the type of soil (e.g., loose topsoil, clay base, sandy soil, etc.), how much wind or rain the worksite has experienced, and the amount of crop residue (e.g., from a previous harvest) left on the worksite to absorb humidity or provide wind protection. The soil logic system 426 can determine that a change in the topographical characteristics of the worksite or a particular geographic location within the worksite has occurred or can have occurred based on soil data (e.g., soil type, soil composition, and various other soil data), weather data (e.g., rainfall levels, wind, weather events, and various other weather data), and vegetation data (e.g., crop residue coverage levels on the worksite), and various other data. Additionally, the soil logic system 426 can make these determinations based on various models, such as soil erosion models, sediment transport models, water runoff models, geomorphology models, and various other models.

[0096] The event logic system 428 is configured to analyze event data accessed from data stores, received from sensors, received from operator or user inputs, and various other event data sources, such as news sources. The event logic system 428 can determine whether a change in the topography of the worksite has occurred or can have occurred from the topography indicated by a previous or prior topographic map. For example, the event logic system 428 can receive various data indicating events that have occurred within a time after the data used for the previous or prior map was collected, such as event data indicating the occurrence of natural events (e.g., volcanoes, fires, earthquakes, and various other natural events) and event data indicating human activities, and various other event data. As an example, the event logic system 428 can receive event data indicating that a fire or volcanic eruption has occurred proximate (or close enough) to the worksite such that ash from the fire(s) or volcano(s) or other sediment deposition can have occurred and can determine that a change in the topographical characteristics of the worksite or a particular geographic location within the worksite has occurred or can have occurred. This determination can be based on event data alone or can be based on a combination of event data and other characteristics of the worksite or the worksite's environment. For example, the event logic system 428 can determine that sediment deposition has occurred or can have occurred at the worksite or a particular geographic location within the worksite based on event data indicating the occurrence of the fire or volcanic eruption and weather characteristics (e.g., wind speed and direction during the time of the fire or volcanic eruption).

[0097] In another example, the event logic system 428 can receive various event data indicative of the occurrence of non-natural activity occurring at the worksite within a time after data was collected for a previous or prior map, such as event data indicative of another operation occurring (e.g., an agricultural planting operation, an agricultural spraying operation, an agricultural tilling operation, an agricultural irrigation operation, etc.), or event data indicative of an event occurring during another operation (such as a machine getting stuck at a location in a field) and can determine that a change in a terrain characteristic has occurred or can have occurred. For example, the event logic system 428 can receive event data indicative of a planting operation occurring at the worksite after data was collected for a previous or prior map and before a harvesting operation is to be performed, and determine that a change in a terrain characteristic has occurred or can have occurred at the worksite or at a particular geographic location within the worksite. In other examples, the event logic system 428 can receive event data indicative of a tilling operation occurring at the worksite after data was collected for a previous or prior map and before a harvesting operation is to be performed, and determine that a change in a terrain characteristic has occurred or can have occurred at the worksite or at a particular geographic location within the worksite, such as a ridge till operation that creates tillage ridges. In another example, the event logic system 428 can receive event data indicative of an irrigation operation occurring at the worksite after data was collected for a previous or prior map and before a harvesting operation is to be performed, and determine that a change in a terrain characteristic has occurred or can have occurred at the worksite or at a particular geographic location within the worksite, such as ruts being formed in the soil during the irrigation operation. The event logic system 428 can also consider various other data (such as soil moisture data) in making such determinations to determine the likelihood of a change in a terrain characteristic of the field, such as ruts appearing due to a planting operation. These are merely examples. Additionally, the event logic system 428 can use various models to make these determinations, such as sediment drift or deposition models, ash drift models, seismic models, and various other models.

[0098] Other logic systems 430 can include various other logic systems configured to analyze various other data (e.g., data accessed from data stores, data received from sensors, operator / user inputs, and various other data sources) and determine whether a change in a terrain of the worksite has occurred or can have occurred (as indicated by a previous or prior terrain map).

[0099] It should be appreciated that determining that a change in the terrain of the worksite at a particular geographic location within the worksite has occurred or can have occurred can be based on a single type of data or a combination of data, and can be based on a single characteristic or a combination of multiple characteristics. In some examples, the number of indications can influence the terrain confidence level. For example, the presence of a single characteristic (e.g., vegetation being blown by the wind) can indicate that a terrain change has occurred or can have occurred, whereas the presence of multiple characteristics can indicate that a terrain change has occurred or can have occurred to a greater or lesser degree. For example, while the presence of some crop lodging or less crop growth at a certain location on the worksite can indicate the presence of, for example, a washout, this indication can influence the confidence value for the terrain feature (as indicated by the previous or a prior terrain map) at this particular location to a greater degree in combination with, for example, weather data indicating heavy rain or flooding. For example, it can result in a determination that a washout has occurred with a relatively high degree of likelihood. Similarly, the presence of some crop lodging or less crop growth at a certain location on the worksite can influence the confidence value to a lesser degree in the absence of a concomitant indication that the worksite experienced heavy rain or flooding. For example, it can result in a determination that a washout can have occurred with a relatively low degree of likelihood. These are merely examples.

[0100] The map generator 402 is configured to generate a variety of maps based on a previous or a prior map and supplemental data. In some examples, the supplemental data provides an indication of a detectable change in a terrain characteristic of the worksite. In this case, the corrected terrain map generator 440 can combine the changed terrain characteristic indicated by the supplemental data with the previous or a prior terrain map to generate a corrected terrain map. For example, in some cases, a characteristic of the worksite is detectable or visible to the various sensor(s) used to generate the supplemental data such that a change in the terrain characteristic of the worksite (as indicated by the previous or a prior map) can be determined with a degree of certainty. For example, the presence or emergence of a ridge, a washout, a gully, a furrow, and various other characteristics can be clearly detected such that their presence can be detected. In this case, the corrected terrain map generated by the corrected terrain map generator 440 will reflect the change in the terrain of the worksite.

[0101] In some examples, the supplemental data provides an indication of a characteristic or condition at the worksite or the environment of the worksite that can indicate that a change in the terrain of the worksite can have occurred, but cannot be confirmed with a certain level of certainty by the system (e.g., sensors) or person collecting or otherwise inputting the data. This can occur when the surface of the worksite is not visible due to vegetation cover or various other obstructions. In such examples, the terrain confidence map generator 442 can generate a terrain confidence map that indicates, among other things, terrain confidence values at the worksite or at particular geographic locations within the worksite. The terrain confidence map (some examples of which are provided below) can be generated as an interactive layer on the interactive map, enabling the user or operator to manipulate the functionality of the layer or map. For example, the user or operator can be able to toggle the display between the terrain confidence map and the prior or a priori terrain map, or generate a split screen with one portion showing the prior or a priori terrain map and another portion showing the terrain confidence map. Additionally, the user or operator can manipulate the display of the confidence value representation for the worksite or for particular geographic locations of the worksite, such as by changing the representation of the confidence value, or by displaying both the representation of the confidence value and the corresponding terrain feature indicated by the prior or a priori terrain map. Additionally, the map display can also include an indication of the location of the mobile machine 100 on the worksite represented by the map. These are merely examples.

[0102] It will also be appreciated that in some examples, the map generator 402 can generate a map that includes both corrected terrain characteristics and terrain confidence levels. For example, for areas of the worksite where terrain characteristics can be detected with a certain degree of certainty (e.g., the surface of the worksite is actually visible or otherwise detectable), corrected or updated terrain characteristics can be provided, and for areas of the worksite where terrain characteristics cannot be detected with a certain degree of certainty (e.g., the surface of the worksite is not visible), terrain confidence levels can be provided for those areas. In this manner, the map can be a mix of corrected terrain characteristics and terrain confidence levels.

[0103] As Figure 4As shown, the terrain confidence system 330 can include an action signal generator 406. The action signal generator 406 can generate various action signals for controlling actions of components of the computing architecture 300. For example, the action signals can be used to control operations of the mobile machine 100, such as raising or lowering a header 104, raising or lowering a spray boom 210, adjusting a speed of the mobile machine 100, adjusting a heading of the mobile machine 100, adjusting operation of a spray subsystem, and various other operations or machine settings. In another example, the action signals are used to provide displays, recommendations, and / or other indications (e.g., alerts) on an interface or interface mechanism, such as providing displays, recommendations, and / or other indications (e.g., alerts) to an operator 362 on an operator interface 360 or to a remote user 366 on a user interface 364. The indications can include audio, visual, or haptic outputs. The indications can indicate terrain confidence values or be representations of terrain confidence values, corrected terrain maps, terrain confidence maps, and various other displays. Additionally, the action signal generator 406 can generate action signals to control operation of a vehicle 370 to, for example, travel to a location on a field to further scout the location to collect additional data. Similarly, action signals can be generated to suggest that an operator or user dispatch a human scout to a location on a field to further scout the location to collect additional data. In other examples, the action signal generator 406 can generate action signals to direct (such as by providing indications on an interface mechanism) a human to drive, ride, or walk to an area to scout the area to collect additional data. This can include visually scouting the area or include the assistance of various sensing devices operated by a person or on a vehicle operated by a person, such as a handheld device. The directions can be given by at least one of audio, visual, or haptic guidance. These are merely examples. The terrain confidence system 330 can generate any number of various action signals for controlling any number of actions of any number of components of the computing architecture 300.

[0104] The threshold logic system 408 is configured to compare various characteristics of the field to various thresholds. The thresholds can be automatically generated by the system 330 (such as by the machine learning logic system 410), input by an operator or user, or generated in various other ways. For example, a threshold can be used to determine a level of deviation from an expected value, or a level of deviation from surrounding areas of the field, to determine areas of the field that can have a terrain feature change. For example, if crop growth (measured by NDVI) of a crop at a particular geographic location within the field deviates from an expected level of crop growth or a threshold amount compared to crops of surrounding areas of the field, the terrain confidence system 330 can be controlled to generate a terrain confidence value for the field or the particular geographic location within the field indicating that a terrain change can have occurred.

[0105] Additionally, the threshold logic system 408 is configured to compare the various terrain confidence values to various thresholds. The thresholds can be automatically generated by the system 330, such as by the machine learning logic system 410, input by an operator or user, and generated in various other manners. The thresholds can be used to determine the degree to which the terrain characteristics of the worksite (as indicated by the supplemental data and the corresponding terrain confidence level) can deviate from the terrain characteristics indicated by the pre-existing terrain map prior to adjusting the controls of the machine or prior to providing a display, recommendation, or other indication (e.g., an alert) on an interface or interface structure. Such indications can include audio, visual, or haptic outputs. For example, an operator or user can input a threshold of 95% for the terrain confidence level, such that some action signal is generated only when the terrain confidence level is below 95%. Additionally, the thresholds can be used for the assignment of representations of the confidence values. For example, in the example where “high, medium, and low” are representations of the terrain confidence level, the thresholds can indicate the range of terrain confidence levels assigned to each representation. For example, 90% to 99% can be represented as “high,” 70% to 89% can be represented as “medium,” and anything below 70% can be represented as “low.” This is just an example.

[0106] Figure 4 It is also shown that the terrain confidence system 330 can include a machine learning logic system 410. The machine learning logic system 410 can include a machine learning model, which can include machine learning algorithms such as, but not limited to, memory networks, Bayesian systems, decision trees, feature vectors, eigenvalues and machine learning, evolutionary and genetic algorithms, expert systems / rules, engines / symbolic reasoning, generative adversarial networks (GANs), graph analysis and ML, linear regression, logistic regression, LSTMs and recurrent neural networks (RNNs), convolutional neural networks (CNNs), MCMC, random forests, reinforcement learning or reward-based machine learning, etc.

[0107] The machine learning logic system 410 can improve the determination of the terrain confidence level by improving the algorithmic process used for the determination of the terrain confidence level, such as by improving the identification of characteristics and conditions of the worksite or the environment of the worksite that are indicative of modifications to the terrain characteristics of the worksite. For example, the machine learning logic system 410 can learn relationships between characteristics, factors, or conditions that affect the terrain of the worksite. The machine learning logic system 410 can also utilize a closed loop learning algorithm, such as one or more forms of supervised machine learning.

[0108] Figure 5 is shownFigure 4 The terrain confidence system 330 shown in FIG. 3 is a flowchart of an example of operations in determining a confidence level of a terrain characteristic of a work site indicated by a previous or prior terrain map based on supplemental data and generating a terrain confidence output based on the determination. It should be understood that the operations can be performed at any time or at any point by an agricultural operation, or even if the agricultural operation is not currently being performed. Further, while the operations will be described in terms of the mobile machine 100, it should be understood that other machines having the terrain confidence system 330 can also be used.

[0109] The process begins at block 502, where the data capture logic system 404 obtains a terrain map of a work site. The terrain map can be based on a survey of the work site (e.g., an aerial survey, a satellite survey, a ground vehicle survey, etc.) as indicated at block 504, data from previous or prior operations on the work site (e.g., row data, pass data, etc.) as indicated at block 506, and based on various other data as indicated at block 508.

[0110] Once the terrain map of the work site is obtained at block 502, the process continues at block 510, where the data capture logic system 404 obtains supplemental data for the work site. The supplemental data can be obtained or otherwise received from various sensors as indicated at block 512, operator / user input as indicated at block 514, various external sources (e.g., weather stations, the Internet, etc.) as indicated at block 516, and from various other supplemental data sources as indicated at block 518.

[0111] Once the data is obtained at blocks 502 and 510, the process continues at block 520, where, based on the terrain map and the supplemental data, the terrain change detector 420 of the terrain confidence system 330 detects a change or a possible change in a terrain characteristic of the work site (as indicated by the terrain map) based on a characteristic of the work site or an environment of the work site indicated by the supplemental data. These characteristics can be weather characteristics indicated by weather data and analyzed by the weather logic system 422 as indicated at block 522, vegetation characteristics indicated by vegetation data and analyzed by the vegetation logic system 424 as indicated at block 524, soil characteristics indicated by soil data and analyzed by the soil logic system 426 as indicated at block 526, event characteristics indicated by event data and analyzed by the event logic system 428 as indicated at block 528, and various other characteristics analyzed by various other logic systems as indicated at block 530.

[0112] The process continues at block 532, where, based on the detected change or possible change in the terrain characteristic of the work site, the terrain confidence analyzer 400 of the terrain confidence system 330 determines a terrain confidence level that indicates a confidence level of the terrain characteristic of the work site or a particular geographic location within the work site as indicated by the terrain map.

[0113] Processing continues at block 534, where terrain confidence system 330 generates a terrain confidence output based on the terrain confidence level. The terrain confidence output can include a representation of the terrain confidence level (as indicated at block 536), a map (as indicated at block 538), and various other outputs (as indicated at block 540). The representation at block 536 can include a numerical representation, such as a percentage or a scalar value (as indicated at block 542), a grayscale and / or scaled value (such as, for example, A to F, “high, medium, low,” 1-10) (as indicated at block 544), a suggested representation (such as, for example, caution, proceed, slow, scout first, no crop) (as indicated at block 546), and various other representations (including various other metrics and / or values) (as indicated at block 548).

[0114] The map at block 538 can be generated by map generator 402 and can include a corrected terrain map (as indicated at block 550), a terrain confidence map (as indicated at block 552), and various other maps (as indicated at block 554). In one example, the other maps can include maps that include both corrected terrain information and terrain confidence levels.

[0115] In one example, once the terrain confidence output is generated at block 534, processing continues at block 556, where action signal generator 406 generates one or more action signals. In one example, the action signals can be used to control operation of one or more machines, such as operation of one or more controllable subsystems 302 of mobile machine 100, vehicle 370, and the like, as indicated at block 558. For example, action signal generator 406 can generate action signals to control a speed of mobile machine 100 or a route of mobile machine 100, adjust a position of header 104 or boom 210 above a surface of a work site, adjust an operating parameter of a spray subsystem of sprayer 201, and various other operations or machine settings. In another example, a display, recommendation, or other indication can be generated to operator 362 on operator interface 360 or to remote user 366 on user interface 364. The display can include an indication of the terrain confidence level, a display of a map (such as a corrected terrain map or a terrain confidence map). Any number of a variety of other action signals can be generated by action signal generator 406 based on the terrain confidence output, as indicated at block 562.

[0116] Processing continues at block 564, where it is determined whether operation of mobile machine 100 is complete at the work site. If, at block 564, it is determined that the operation is not complete, processing continues at block 510, where additional supplemental data is obtained. If, at block 564, it is determined that the operation is complete, processing ends.

[0117] Figures 6 to 11 may be generated byFigure 4 FIG. 6 is a diagram of an example of various maps that can be used or generated by the terrain confidence system 330.

[0118] Figure 6 is one example of an existing terrain map 600 of a worksite that can be obtained and used by the terrain confidence system 330. The existing terrain map 600 illustrates terrain characteristics of a worksite 602 on which the mobile machine 100 will operate. The terrain map 600 can include contour lines 604, a compass rose 606, a terrain representation 607, and a mobile machine indicator 608. Although Figure 6 Certain items are illustrated in FIG. 6, but it should be understood that the terrain map 602 can include various other items. Generally, the prior or a priori terrain map 600 indicates terrain characteristics of the worksite 602, such as the elevation of the surface of the worksite 602 relative to a reference value, typically sea level, as indicated by the terrain representation 607. The terrain map 600 also includes the compass rose 606 to indicate the setting of the worksite 602 and items on the map 600 or the worksite 602 relative to north, south, east, and west. The terrain map 600 can also include an indication of the location and / or heading of the mobile machine 100, such as represented by the indicator 608 showing the southwest corner of the worksite 602 facing north. The contour lines 604 can also indicate other terrain characteristics in addition to the location of the elevation represented by the terrain representation 607, such as the characteristics of the slope of the worksite 602. For example, the distance between the contour lines 604 generally indicates the slope of the terrain at the worksite 602.

[0119] Figure 7 is one example of a terrain confidence map 610 that can be generated by the terrain confidence system 330 based on a prior or a priori terrain map, such as the map 600 and supplemental data related to the worksite 602 or the environment of the worksite 602. The terrain confidence map 610 generally indicates a level of confidence in the terrain characteristics of the worksite 602 illustrated on the prior or a priori terrain map 600. As can be seen, the terrain confidence map 610 can include terrain confidence zones 614 (shown as 614-1 through 614-3) and a terrain confidence level representation 617. Figure 7 A number of different examples of the terrain confidence representation 617 are illustrated in FIG. 6. For example, Figure 7 The representation 617 can be a numerical representation (e.g., 95%) as well as a grayscale and / or scaled representation (e.g., A through F, 1-10, "high, medium, low," etc.). As can be seen, the terrain confidence level and the corresponding terrain confidence level representation can vary across the worksite 602, as indicated by the confidence zones 614-1 through 614-3.

[0120] In one example, the terrain confidence system 330 can have received supplemental data indicating that the worksite 602 received heavy rain (e.g., 4 inches in an hour), that crop residue coverage on the worksite 602 is only 5%, and that the tillage direction is from east to west. Based on this supplemental data, the terrain confidence system 330 can determine that a change in the terrain characteristics of the worksite 602 and / or a particular geographic location within the worksite 602 has occurred or can have occurred. For example, based on the terrain characteristics of the worksite 602 (such as elevation, slope, etc.) as indicated by the previous or a prior terrain map 600, the amount of rainfall, the tillage direction, and the amount of crop residue coverage, the terrain confidence system 330 can determine that the area of the field represented by 614-1 can have experienced a change in terrain due to erosion on the worksite 602 (which can result in a build-up of material or sediment in the area of the field represented by 614-1) and, therefore, indicate a confidence level for the terrain characteristics for this area as “low” (or some other indication). This is because when the worksite 602 experiences heavy rain, material and sediment from higher areas on the field (such as 614-2) can be washed away and accumulate in lower and flatter areas of the field (e.g., 614-1). Additionally, due to the relative size of the area represented by 614-1, the amount or severity of deviation from the terrain characteristics for this area as indicated by the previous or a prior terrain map can be greater and, therefore, the confidence can be relatively lower. Similarly, while the area represented by 614-2 can have experienced some change in terrain characteristics as indicated by the previous or a prior terrain map, due to the relative size of the area of the field represented by 614-2, the amount or severity of deviation from the terrain characteristics for this area as indicated by the previous or a prior terrain map can be less and, therefore, the confidence value can be relatively higher. For example, the confidence level for zone 614-2 can be “medium” because a change can still have occurred in this area, but due to the relative size of the area, the change can be less likely to be significant (e.g., the change can be more gradual or gradual across the area). In contrast to the areas represented by 614-1 and 614-2, in the case of the area represented by 614-3 extending further west on the worksite 602, the confidence system 330 can determine that it is less likely that erosion (or some other form of erosion) has occurred or, at least, that something has occurred that would affect or likely affect the terrain characteristics as indicated by the previous or a prior terrain map 600. The terrain confidence system 330, therefore, indicates a confidence level for the terrain characteristics aspects for this area as “high” (or some other indication). For example, it can be “high” because zone 614-3 is higher, flatter, larger, and, therefore, less likely to experience a change or a significant change in terrain characteristics when the worksite 602 experiences heavy rain as compared to the surrounding areas of the worksite 602.

[0121] It will be noted that this is merely an example, and various other characteristics of the worksite or the environment of the worksite, including various other characteristics indicated by the supplemental data, can be considered by the terrain confidence system 330. In the example provided, the terrain characteristics of elevation and slope, as well as characteristics provided by the supplemental data (e.g., precipitation, tillage direction, and crop residue) can have an impact on water runoff at the worksite 602, and thus can impact the likelihood and / or level of erosion and / or material or sediment accumulation or drift at the worksite 602. Additionally, it will be appreciated that the terrain confidence system 330 can use any number of models in determining the terrain confidence level, such as the water runoff model or the erosion model in the example provided.

[0122] Figure 8 is an example of a terrain confidence map 620 that can be generated by the terrain confidence system 330 based on a prior or a priori terrain map, such as the map 600, and supplemental data related to the worksite 602 and / or supplemental data related to the environment of the worksite 602. The terrain confidence map 620 is similar to the terrain confidence map 610, except that the terrain confidence level is represented by a suggested terrain confidence level representation 627, which can indicate a suggested action to take or an action to take while operating on the worksite 602 or prior to operating on the worksite 602. As noted above, the terrain confidence level can change across the worksite 602, as represented by the terrain confidence zones 614, shown as 614-1 through 614-3. Each of the zones 614 can have a different suggested terrain confidence level, as represented by 627. In this way, control of the machine 100 while operating on the worksite 602 can also change depending on which confidence zone 614 the machine is operating within. In one example, the confidence zones 614 can act as a“control zone” for the mobile machine 100, such that the mobile machine 100 is controlled in some manner in one control zone as compared to another control zone.

[0123] For example, continuing the example provided above in Figure 7 zone 614-1, where it is determined that a change in terrain characteristics can occur, or at least that the confidence level of the terrain characteristics indicated by the prior or a priori terrain map 600 is“low,” the terrain confidence system 330 can provide a suggested terrain confidence level representation 627, such as“scout first,”“avoid,”“no crop,”“repair,” and various other suggested representations. These suggested representations can be used to automatically control machine operations (e.g., by the control system 304), or can be used by an operator / user to control operations of various machines, such as the mobile machine 100, the vehicle 370, and various other components of the computing architecture 300.

[0124] For example, in the "first scout" example, the terrain confidence system 330 can generate a motion signal to automatically control a vehicle (e.g., vehicle 370) to travel to zone 614-1 to collect additional data (e.g., via sensors 382) before mobile machine 100 operates in zone 614-1, and generate a motion signal to provide a display, alert, recommendation, or some other indication on an interface or interface mechanism (e.g., at operator interface 360, user interface 364, and various other interfaces or interface mechanisms) that zone 614-1 should be first scouted (e.g., by a person, by a vehicle, etc.) before mobile machine 100 operates in zone 614-1. The indication can include audio, visual, or haptic output. In other examples, the terrain confidence system 330 can generate a route and motion signal to automatically control the heading of mobile machine 100 such that the mobile machine travels along the edge of zone 614-1 but does not enter zone 614-1. In such examples, the mobile machine 100 can perform a scouting operation such that sensors (e.g., sensors 310) on the mobile machine 100 or an operator 362 can detect characteristics within zone 614-1 before operating within zone 614-1 as it travels along the edge of zone 614-1. The terrain confidence system 330 can also generate a motion signal to provide a display, alert, recommendation, or some other indication on an interface or interface mechanism, such as a recommended route for mobile machine 100 to traverse through worksite 602. The indication can include audio, visual, or haptic output. Once additional data for zone 614-1 is collected, the terrain confidence level can be dynamically re-determined by terrain confidence system 330 such that operations on worksite 602 can be adjusted. Additionally, terrain characteristics for zone 614-1 can be generated, such as in the form of a supplemented or corrected terrain map, where the additional data has a sufficient level of certainty.

[0125] In the "avoid" example, the terrain confidence system 330 can generate a route and motion signal to automatically control the heading of mobile machine 100 such that it avoids traveling into zone 614-1, and generate a motion signal to provide a display, alert, recommendation, or some other indication on an interface or interface mechanism, such as a recommended route for mobile machine 100 to traverse through worksite 602. The indication can include audio, visual, or haptic output. In one example of "avoid," the "no crop" suggested representation 627 can be displayed instead. For example, it can be that the supplemental data can indicate that there are no crops to be harvested in zone 614-1, and thus there is no need for mobile machine 100 to operate there, nor additional scouting or data collection.

[0126] In the example of "repair," the terrain confidence system 330 can generate action signals to automatically control a machine (e.g., the vehicle 370) to travel to the zone 614-1 to perform a repair operation on the zone 614-1 to correct the undesirable terrain characteristic (e.g., fill in the scour, correct the accumulation or drift of material or sediment by regrading the terrain), and in some examples, return the terrain to the level indicated by the map 600, or to some other level that the control system 304 or the operator 362 or user 366 can desire or determine. Additionally, the terrain confidence system 330 can generate action signals to provide a display, warning, recommendation, or some other indication on an interface or interface mechanism that the zone 614-1 should first be repaired (e.g., by a person, by the vehicle 370, other machine, etc.) before the mobile machine 100 operates within the zone 614-1. The indication can include audio, visual, or haptic output.

[0127] In the example of zone 614-2 (wherein, in Figure 7 In the example of zone 614-2 (wherein, in

[0128] For example, in the “careful” or “slow” example, the terrain confidence system 330 can generate action signals (e.g., by controlling the propulsion subsystem 318 of the mobile machine 100) to automatically control the machine to travel at a slower speed than other areas throughout zone 614-2, or at a speed slow enough that sensor signals generated by sensors on the machine (e.g., sensor 310) are used to control the machine’s operation in a timely manner to avoid the consequences of terrain conditions on site 602. As an example, the propulsion subsystem 318 of the mobile machine 100 can be controlled to propel the mobile machine 100 at a speed that allows sensor signals generated by the sensing system 342, indicating an impending scour or material buildup, to be used to adjust the height or orientation of the header 104 or the boom 210 to compensate for terrain changes caused by the impending scour or material buildup, so that the header 104 does not hit the ground or miss the crop, or that the boom 210 remains in a desired position, such as above the crop canopy. Additionally, the terrain confidence system 330 can generate action signals to provide displays, warnings, recommendations, or other indications on the interface or interface mechanism, such as instructing the operator or user that the machine speed should be reduced, that the operator should pay particular attention to the work surface in front of the machine, or various other indications. Indications may include audio, visual, or tactile outputs.

[0129] In section 614-3, Figure 7 In the example, it is determined that a change in the terrain characteristics of site 602 is unlikely, or at least that the confidence level regarding the terrain characteristics indicated by a prior or a priori topographic map is "high". Therefore, the terrain confidence system 330 can provide a suggested terrain confidence level representation 627, such as "forward" or various other suggested representations. For example, the terrain confidence system 330 can generate action signals to automatically control a machine (e.g., mobile machine 100) to operate based on the terrain characteristics indicated by a prior or a priori topographic map 600. Furthermore, the terrain confidence system 330 can generate action signals to provide displays, warnings, recommendations, or other instructions to an operator or user on an interface or interface mechanism, enabling the operator or user to use the prior or a priori topographic map 600 to operate the mobile machine 100. Instructions may include audio, visual, or tactile output. At least within zones 614-3, the terrain confidence system 330 can generate control signals to control various other components of the computing architecture 300 and various other machines.

[0130] The indicator 608 provides an indication of the position and heading of the mobile machine 100 on the worksite 602, and in some examples, the terrain confidence system 330 can generate action signals to control operation of the mobile machine 100, as well as provide a display, alert, recommendation, or some other indication on an interface or interface mechanism based on the position of the mobile machine 100 on the worksite 602. The indication can include audio, visual, or haptic output. For example, the terrain confidence system 330 can automatically control the machine to change operation as it exits one zone 614 and enters another zone 614, such as automatically adjusting the speed of the machine as it exits zone 614-3 and enters zone 614-2. Additionally, the terrain confidence system 330 can provide an indication to the operator that the machine has entered a different zone.

[0131] Figure 9 is an example of a corrected terrain map 630 of a worksite generated by the terrain confidence system 330 based on supplemental data related to the worksite 602 or the environment of the worksite 602. As described above, in some cases, the supplemental data collected will provide an accurate or relatively accurate indication of the terrain characteristics of the worksite, such that an actual or effective approximation of the actual terrain characteristics of the worksite can be determined by the terrain confidence system 330. For example, a subsequent aerial survey of the worksite 602 (performed at some time after the data was collected for the previous or prior terrain map 600) can provide sensor signals (e.g., images) that provide an accurate indication of the terrain characteristics of the worksite 602. For example, the subsequent aerial survey can have been performed while the surface of the worksite 602 was still detectable (e.g., vegetation had not yet obscured detection). In one example, the corrected terrain map 630 can be generated and used as a new baseline to replace the previous or prior terrain map 600. In another example, and particularly if the corrected terrain map 630 is generated in time close enough to the performance of operations (e.g., harvesting, spraying, etc.) on the worksite 602, the corrected terrain map 630 can be used by the control system 304 or the operator 362 or user 366 to control the mobile machine 100 and other components of the computing architecture 300.

[0132] As shown in Figure 9 the corrected terrain map 630 is similar to the previous or prior terrain map 600. The corrected terrain map 630 can include a terrain representation 637 indicating the corrected elevation of the surface of the worksite 602 relative to a reference level (e.g., sea level), and can also include corrected contour lines 634. In the example shown, the corrected terrain map 630 can include a terrain representation 607 indicating the elevation of the surface of the worksite 602 relative to a reference level indicated by the previous or prior terrain map 600. As shown in Figure 9As shown, the terrain representations 607 are bracketed so that the operator or user can distinguish them from the corrected terrain values represented by the terrain representations 637, although this need not be the case. The representations 607 and 637 can be distinguished in a variety of ways, such as different colors, different fonts, and various other stylistic differences. Additionally, the prior or a priori contours indicated by the prior or a priori terrain map 600 can also be displayed on the corrected terrain map 630 and distinguished in a variety of ways, such as using dashed lines, different colors, and various other stylistic differences. In another example, the prior or a priori terrain features, such as those represented by the terrain representations 607, need not be displayed. As Figure 9 As shown, the corrected terrain map 630 shows that the worksite 602 has undergone changes in terrain, such as erosion (or erosion) in the higher areas of the field, thus lowering their elevations, which subsequently resulted in the accumulation of material in the lower areas of the field, thus increasing the elevations of the lower areas of the field.

[0133] Figure 10 is an example of a hybrid terrain map 640 for the worksite that can be generated by the terrain confidence system 330 based on a prior or a priori terrain map, such as the map 600, and supplemental data related to the worksite 602 or related to the environment of the worksite 602. In some examples, for at least some areas of the worksite, the supplemental data can provide an indication of terrain features of the worksite 602 with a sufficient level of certainty or accuracy such that corrected terrain features can be generated, while for other areas of the worksite, some of the supplemental data can be used to determine a confidence level of the terrain features indicated by the prior or a priori terrain map. For example, in some areas of the worksite 602, the surface of the worksite 602 can be detectable such that an elevation of the surface relative to a reference (e.g., sea level) can be determined, while for other areas, the surface of the worksite can be undetectable. For example, vegetation (and other obstructions) can prevent detection in certain areas while not preventing detection in other areas.

[0134] In such examples, a hybrid terrain map 640 can be generated that includes representations of corrected terrain features (as indicated by the corrected contours 634 and the corrected terrain representations 637) as well as representations of terrain confidence levels (as indicated by the confidence regions 614 and the confidence level representations 617 and 627). In this way, an operator or user can be provided with a map that indicates corrected terrain features for areas of the field for which terrain features are known with a certain level of precision or certainty (which can be based on a threshold as described above). For areas of the field for which terrain features are not known with a certain level of precision or certainty, the map 640 can show the confidence levels in the terrain features indicated by the prior or a priori terrain map.

[0135] Figure 11 is an example of a terrain confidence map 650 that can be generated by the terrain confidence system 330 based on a prior or a priori terrain map, such as the map 600, and supplemental data related to the worksite 602 or the environment of the worksite 602. As shown, the terrain confidence map 650 also includes an indication of a route 652 along which a machine (e.g., the mobile machine 100) is to travel that is generated by the terrain confidence system 330. The route 652 can be used by the control system 304 to automatically control operation of the mobile machine 100 as the mobile machine travels through the worksite 602. For example, the route 652 can be used by the control system 304 to generate action signals to control one or more controllable subsystems 302 of the mobile machine 100, such as a steering subsystem 316 for controlling a heading of the mobile machine 100.

[0136] Additionally, control of the mobile machine 100 as it operates on the worksite 602 can change based on a location of the mobile machine within the confidence zones 614 or proximity of the mobile machine to the confidence zones 614. For example, in the confidence zone 614-3, the mobile machine 100 can be controlled based on terrain characteristics indicated by a prior or a priori terrain map, such as the map 600, as the terrain confidence level indication 617 is “high” and the recommendation indication 627 is “proceed.” However, in the zone 614-2, the mobile machine 100 can be controlled to adjust speed (e.g., travel more slowly) as the terrain confidence level indication 617 is “medium” and the recommendation indication 627 is “slow.” As can be further seen, the route 652 can direct the mobile machine 100 to travel around a perimeter or edge of the zone 614-1, but avoid traveling into the zone 614-1, as the terrain confidence level indication 617 is “low” and the recommendation indication 627 is “recon.” It should also be noted that the route 652 can be generated and displayed to an operator or user while operation of the machine (e.g., heading) is still controlled by the operator or user. In other examples, the route 652 can be used directly by the mobile machine operating in a semi-autonomous or autonomous mode. The indicator 608 can provide an indication of a location of the machine and, in the case of operator or user control, can provide an indication of a deviation from a recommended travel path, such as a line showing where the machine is actually traveling.

[0137] It should be noted that, Figures 6 to 11 The various maps shown in FIGS. 6-8 do not include an exhaustive list, and the terrain confidence system 330 can generate any number of maps that indicate or otherwise display any number of characteristics, conditions, and / or items on or related to a worksite. It should also be understood that the above description of the various maps is not intended to be limiting, and that the terrain confidence system 330 can generate any number of maps that indicate or otherwise display any number of characteristics, conditions, and / or items on or related to a worksite. Figures 6 to 11Any and all of the figures described herein can include layers that can be generated by the terrain confidence system 330 and can be displayed over other layers (e.g., as an overlay) and / or can be individually selected or toggled by an operator or user, such as by input on an actuatable input mechanism on a display screen (e.g., touch screen) on an interface mechanism. For example, an operator 362 of the mobile machine 100 can desire to toggle between display of the prior or a priori terrain map 600, the terrain confidence map 610, and the terrain confidence map 620 during operation. In this manner, the operator 362 can be provided with an indication of what the last known terrain characteristics are (e.g., by the map 600), what the terrain confidence is over the worksite (e.g., by the map 610), and what the suggested operation of the mobile machine 100 is over the worksite (e.g., by the map 620).

[0138] The current discussion has mentioned processors and servers. In one embodiment, the processors and servers include computer processors with associated memory and timing circuitry, not separately shown. They are part of the overall system or device in which they are included and exist in function with other components or items of those systems.

[0139] Also, a number of user interface displays have been discussed. They can take a variety of different forms and can have a variety of different user actuatable input mechanisms provided therewith. For example, the user actuatable input mechanisms can be text boxes, check boxes, icons, links, drop-down menus, search boxes, etc. They can also be actuated in a variety of different ways. For example, they can be actuated using a point and click device such as a trackball or mouse. They can be actuated using hardware buttons, switches, joysticks, or keyboards, thumb switches or thumb pads, etc. They can also be actuated using virtual keyboards or other virtual actuators. Furthermore, 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 voice commands.

[0140] Some data storage devices have also been discussed. Notably, they can each be divided into multiple data storage devices. All of the data storage devices can be local to the system that accesses them, all of the data storage devices can be remote, or some of the data storage devices can be local and some remote. All of these configurations are contemplated herein.

[0141] Furthermore, the drawings illustrate a number of blocks that are representative of functions in the embodiments. It should be noted that the functions can be carried out by fewer blocks, or a single block, or by more blocks, depending on the functionality of the device. Further, the blocks can be implemented by hardware, software, or a combination of hardware and software.

[0142] It should be noted that the above discussion has described various different systems, components, and / or logic systems. It should be understood that such systems, components, and / or logic systems can be made up of hardware items such as processors and associated memory, or other processing components, some of which will be described below, that perform the functions associated with those systems, components, and / or logic systems. In addition, the systems, components, and / or logic systems can be made up of software that is loaded into memory and subsequently executed by a processor or server or other computing component, as will be described below. The systems, components, and / or logic systems can also be made up of different combinations of hardware, software, firmware, etc., some examples of which will be described below. These are just a few examples of different structures that can be used to form the systems, components, and / or logic systems described above. Other structures can also be used.

[0143] Various terrain confidence outputs can also be output to the cloud.

[0144] Figure 12 is a block diagram of a remote server architecture showing that components of the computing architecture 300 can communicate with elements in a remote server architecture, or that components of the computing architecture 300 can be located at a remote server location and can be accessed by other components of the computing architecture 300 at the remote server location. In example embodiments, the remote server architecture 700 can provide computing, software, data access, and storage services that do not require end users to know the physical location or configuration of the system that delivers the services. In various example embodiments, the remote server can deliver services over a wide area network, such as the Internet, using appropriate protocols. For example, the remote server can deliver an application over a wide area network, and the remote server can be accessed through a web browser or any other computing component. Figure 3 The software or components shown in and the corresponding data can be stored on servers at remote locations. The computing resources in the remote server environment can be consolidated at a remote data center location, or they can be dispersed. The remote server infrastructure can deliver services through a shared data center, even though they appear to users as a single point of access. Thus, the components and functionality 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 directly or otherwise on a client device.

[0145] In Figure 12 In example embodiments shown in Figure 3 are numbered similarly. Figure 12It is specifically shown that the control system 304 can be located at a remote server location 702. Thus, the mobile machine 100, the operator 362, and / or the remote user(s) 366 access these systems through a remote server at the location 702.

[0146] Figure 12 Another embodiment of a remote server architecture is also depicted. Figure 12 It is shown that some elements of Figure 3 are located at the remote server location 702, while others are not. As an example, the data store 704 or the control system 304 can be located at a location separate from the location 702 and accessed through a remote server at the location 702. Regardless of where they are located, they can be accessed directly by the mobile machine 100 and / or the operator(s) 362 and one or more remote users 366 (via user devices 706) through a network (wide area or local area), they can be hosted by a service at the remote site, or they can be provided as a service or accessed by a connectivity service that resides at the remote location. Also, data can be stored at substantially any location and accessed intermittently by or forwarded to interested parties. For example, a physical carrier wave can be used instead of or in addition to an electromagnetic wave carrier. In such an example embodiment, another mobile machine, such as a fuel truck, can have an automatic information collection system in the event of poor or non-existent cell coverage. The system automatically collects information from the mobile machine using any type of dedicated wireless connection as the mobile machine approaches the fuel truck for refueling. The collected information can be forwarded to the main network when the fuel truck reaches a location with cellular coverage (or other wireless coverage). The fuel truck can enter a covered location, for example, when traveling to refuel other machines or at a main fuel storage location. All of these architectures are contemplated herein. Further, information can be stored on the mobile machine until the mobile machine enters a covered location. The harvester itself can then transmit the information to the main network.

[0147] It should also be noted that Figure 3 elements or portions thereof can be located on a variety of different devices. Some of these devices include servers, desktop computers, laptop computers, tablet computers, or other mobile devices such as palmtop computers, cell phones, smart phones, multimedia players, personal digital assistants, and the like.

[0148] Figure 13 is a simplified block diagram of one illustrative example embodiment of a handheld or mobile computing device that can be used as a handheld device 16 of a user or customer in which the present system (or a portion thereof) can be deployed. For example, the mobile device can be deployed in the operator's compartment of the harvester 100 for generating, processing, or displaying rootstock width and location data.Figures 13 to 15 is an example of a handheld or mobile device.

[0149] Figure 13 A general block diagram of components of a client device 16 is provided, which can run some of the components and / or interact with these components as shown in FIG. 1. Figure 3 In device 16, a communication link 13 is provided that allows the handheld device to communicate with other computing devices, and in some embodiments a channel for automatically receiving information (e.g., by scanning) is provided. Examples of communication links 13 include allowing communication over one or more communication protocols, such as wireless services for providing cellular access to a network, and protocols for providing local wireless connections to a network.

[0150] In other embodiments, applications can be received on a removable Secure Digital (SD) card connected to an interface 15. Interface 15 and communication link 13 are in communication with processor 17 (which can also implement processor 108 from FIG. 1) along bus 19, which is also connected to memory 21 and input / output (I / O) components 23, as well as clock 25 and positioning system 27. Figure 1

[0151] In one embodiment, I / O components 23 are provided to facilitate input and output operations. I / O components 23 of various embodiments of 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 display devices, speakers, and / or printer ports). Other I / O components 23 can also be used.

[0152] Clock 25 illustratively includes a real-time clock component that outputs time and date. Illustratively, it can also provide timing functions for processor 17.

[0153] Positioning system 27 illustratively includes components that output a current geographic position of device 16. This can include, for example, a Global Positioning System (GPS) receiver, a LORAN system, a dead reckoning system, a cellular triangulation system, or other positioning system. It can also include, for example, mapping software or navigation software that generates desired maps, navigation routes, and other geographic functions.

[0154] ​Memory 21 stores operating system 29, network settings 31, application programs 33, application configuration settings 35, data storage device 37, communication driver 39, and communication configuration settings 41. Memory 21 may include all types of tangible, volatile, and non-volatile computer-readable storage devices. It may 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. Processor 17 may also be activated by other components to facilitate their functionality.

[0155] Figure 14 An embodiment of a tablet computer 800 is shown, in which device 16 is illustrated. Figure 15 In the diagram, computer 800 is shown as having a user interface display screen 802. Screen 802 may be a touchscreen or a pen-enabled interface that receives input from a pen or stylus. It may also utilize an on-screen virtual keyboard. Alternatively, it may be attached to a keyboard or other user input device, for example, via a suitable attachment structure (such as a wireless connector or USB port). Computer 800 may also schematically receive voice input.

[0156] Figure 14 Similar to Figure 16 In addition to being a telephone, it is a smartphone 71. The smartphone 71 has a touch-sensitive display 73 that shows icons, blocks, or other user input mechanisms 75. Users can use the mechanisms 75 to run applications, make calls, perform data transfer operations, etc. Generally, the smartphone 71 is built on a mobile operating system and offers more advanced computing power and connectivity than feature phones.

[0157] Note that other forms of device 16 are possible.

[0158] Figure 3 It is one of the deployable ones Figure 16 An embodiment of a computing environment, including components or portions thereof. References Figure 3 An example system for implementing some embodiments includes a general-purpose computing device in the form of a computer 910. Components of the computer 910 may include, but are not limited to, a processing unit 920 (which may include processors 312, 374, and / or 384), system memory 930, and a system bus 921 connecting various system components, including the system memory, to the processing unit 920. The system bus 921 may be any of several types of bus architectures, including a memory bus or memory controller, a peripheral bus, and a local bus using any of various bus architectures. Regarding... Figure 16 The described memory and program can be deployed in Figure 16 In the corresponding part.

[0159] Computer 910 typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer 910 and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media can 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 910. Communication media can embody computer readable instructions, data structures, program modules or other data in a modulated data signal or carrier wave. 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.

[0160] System memory 930 includes computer storage media in the form of volatile and / or nonvolatile memory such as read only memory (ROM) 931 and random access memory (RAM) 932. A basic input / output system 933 (BIOS), containing the basic routines that help to transfer information between elements within computer 910, such as during start-up, is typically stored in ROM 931. RAM 932 typically contains data and / or program modules that are immediately accessible to and / or presently being operated on by processing unit 920. By way of example, and not limitation, as Figure 16 Operating system 934, application programs 935, other program modules 936, and program data 937 are shown.

[0161] Computer 910 can also include other removable / non-removable volatile / nonvolatile computer storage media. By way of example only, Figure 16 Hard disk drive 941, which reads from or writes to non-removable, nonvolatile magnetic media, is shown. Optical disk drive 955, which reads from or writes to a non-removable, nonvolatile optical disk 956, such as a CD or other optical media, is also shown. Hard disk drive 941 and optical disk drive 955 are connected to system bus 921 via non-removable memory interface(s) such as interface 940. For example, interface 940 can include at least one of an S ATA interface, a SCSI interface, an advanced technology attachment (ATA) interface, such as serial ATA (SATA) interface, a fiber channel

[0162] Alternatively or additionally, the functions described herein may be performed at least in part by one or more hardware logic system components. For example, but not limited to, illustrative types of hardware logic system components that may 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 (SoCs), complex programmable logic devices (CPLDs), and the like.

[0163] The above discussion and Figure 16 The driver and its associated computer storage media shown provide storage for computer-readable instructions, data structures, program modules, and other data for the computer 910. For example, in Figure 16 In this diagram, the hard disk drive 941 is shown storing the operating system 944, application programs 945, other program modules 946, and program data 947. Note that these components may be the same as or different from the operating system 934, application programs 935, other program modules 936, and program data 937.

[0164] Users can input commands and information into computer 910 through input devices such as keyboard 962, microphone 963, and pointing devices 961 (such as mouse, trackball, or touchpad). Other input devices (not shown) may include joysticks, game controllers, dish satellite dishes, scanners, etc. These and other input devices are typically connected to processing unit 920 via user input interface 960 connected to the system bus, but may also be connected via other interfaces and bus structures. Visual display 991 or other types of display devices are also connected to system bus 921 via an interface such as video interface 990. In addition to the monitor, the computer may also include other peripheral output devices, such as speakers 997 and printers 996, which can be connected via peripheral output interface 995.

[0165] Computer 910 operates in a networked environment using a logical system connection (such as a local area network (LAN) or wide area network (WAN)) to one or more remote computers (such as remote computer 980).

[0166] When used in a LAN networking environment, computer 910 connects to LAN 971 via a network interface or adapter 970. When used in a WAN networking environment, computer 910 typically includes modem 972 or other devices for establishing communication via WAN 973 (such as the Internet). In a networking environment, program modules may be stored in a remote memory storage device. ​ For example, it is shown that remote application 985 can reside on remote computer 980.

[0167] It should also be noted that different embodiments described herein can be combined in different ways. That is, parts of one or more embodiments can be combined with parts of one or more other embodiments. All such combinations are contemplated in the present disclosure.

[0168] Example 1 is a method of controlling a mobile agricultural machine, comprising:

[0169] receiving a topographic map of a work site indicative of topographic characteristics of the work site, wherein the topographic characteristics are based on data collected at a first time;

[0170] receiving supplemental data indicative of characteristics related to the work site, the supplemental data being collected after the first time;

[0171] generating, based on the topographic map and the supplemental data, a topographic confidence output indicative of a confidence level of the topographic characteristics of the work site indicated by the topographic map; and

[0172] generating an action signal based on the topographic confidence output to control an action.

[0173] Example 2 is the method of any or all previous examples, wherein generating the confidence output further comprises:

[0174] determining the confidence level, wherein the confidence level is indicative of a likelihood that the topographic characteristics of the work site indicated by the topographic map have changed; and

[0175] generating a representation of the confidence level.

[0176] Example 3 is the method of any or all previous examples, wherein generating the confidence output further comprises:

[0177] generating a map of the work site including an indication of the confidence level.

[0178] Example 4 is the method of any or all previous examples, wherein generating the confidence output comprises:

[0179] determining a plurality of confidence levels, wherein each of the plurality of confidence levels is indicative of a likelihood that a corresponding one of a plurality of geographic locations within the work site has changed.

[0180] Example 5 is the method of any or all previous examples, further comprising:

[0181] determining a plurality of confidence zones, each of the plurality of confidence zones corresponding to a respective one of the plurality of confidence levels, wherein operation of the mobile agricultural machine is based on a presence of the mobile agricultural machine in one of the plurality of confidence zones.

[0182] Example 6 is the method of any or all previous examples, wherein generating the action signal to control the action comprises:

[0183] controlling a vehicle to collect additional data corresponding to the worksite.

[0184] Example 7 is the method of any or all previous examples, wherein generating the action signal to control the action comprises:

[0185] controlling an actuator of a mobile agricultural machine to drive a component of the mobile agricultural machine to move to change a position of the component relative to a surface of the worksite.

[0186] Example 8 is the method of any or all previous examples, wherein generating the action signal to control the action comprises:

[0187] controlling a propulsion subsystem of the mobile agricultural machine to adjust a speed at which the mobile agricultural machine travels over the worksite.

[0188] Example 9 is the method of any or all previous examples, wherein generating the action signal to control the action comprises:

[0189] controlling a steering subsystem of the mobile agricultural machine to adjust a heading of the mobile agricultural machine as the mobile agricultural machine travels over the worksite.

[0190] Example 10 is the method of any or all previous examples, wherein generating the action signal to control the action comprises:

[0191] controlling an interface mechanism communicably connected to the mobile agricultural machine to provide an indication of the terrain confidence output.

[0192] Example 11 is a mobile agricultural machine comprising:

[0193] a control system comprising:

[0194] a terrain confidence system configured to:

[0195] receive a terrain map of a worksite indicative of terrain characteristics of the worksite, wherein the terrain characteristics are based on data collected at a first time;

[0196] receive supplemental data indicative of characteristics related to the worksite, the supplemental data being collected after the first time; and

[0197] generate, based on the terrain map and the supplemental data, a terrain confidence output indicative of a level of confidence in the terrain characteristics of the worksite indicated by the terrain map; and

[0198] an action signal generator configured to generate an action signal based on the terrain confidence output.

[0199] Example 12 is the mobile agricultural machine of any or all previous examples, wherein the terrain confidence system further comprises:

[0200] a terrain change detector that determines, based on the supplemental data, a likelihood that a terrain characteristic of the work site indicated by the terrain map has changed; and

[0201] a terrain confidence analyzer that determines a terrain confidence level based on the likelihood that the terrain characteristic of the work site indicated by the terrain map has changed.

[0202] Example 13 is the mobile agricultural machine of any or all previous examples, wherein the terrain confidence output comprises a representation of the terrain confidence level.

[0203] Example 14 is the mobile agricultural machine of any or all previous examples, wherein the terrain confidence system further comprises:

[0204] a map generator that generates a map of the work site that includes an indication of the confidence level.

[0205] Example 15 is the mobile agricultural machine of any or all previous examples, wherein the action signal is provided to an actuator of the mobile agricultural machine to drive a component of the mobile agricultural machine to move to change a position of the component relative to a surface of the work site.

[0206] Example 16 is the mobile agricultural machine of any or all previous examples, wherein the action signal is provided to a propulsion subsystem of the mobile agricultural machine to adjust a speed at which the mobile agricultural machine travels over the work site.

[0207] Example 17 is the mobile agricultural machine of any or all previous examples, wherein the action signal is provided to a steering subsystem of the mobile agricultural machine to adjust a heading of the mobile agricultural machine as the mobile agricultural machine travels over the work site.

[0208] Example 18 is the mobile agricultural machine of any or all previous examples, wherein the action signal is provided to an interface mechanism communicably connected to the mobile agricultural machine to generate an interface display indicating the terrain confidence output.

[0209] Example 19 is the mobile agricultural machine of any or all previous examples, wherein the action signal is provided to the interface mechanism to provide an indication that directs a human to collect additional data corresponding to the work site.

[0210] Example 20 is a method of controlling a mobile agricultural machine, comprising:

[0211] receiving a topographic map of the worksite indicative of topographic characteristics of the worksite, wherein the topographic characteristics are based on data collected at a first time;

[0212] receiving supplemental data indicative of characteristics related to the worksite, the supplemental data being collected after the first time;

[0213] based on the supplemental data, determining a topographic confidence level indicative of a likelihood that the topographic characteristics of the worksite indicated by the topographic map have changed;

[0214] generating a topographic confidence map of the worksite, the topographic confidence map indicating the topographic confidence level at a plurality of geographic locations within the worksite;

[0215] based on an indication on the topographic confidence map of a presence of the mobile agricultural machine within one of the plurality of geographic locations, generating an action signal to control an action of the mobile agricultural machine.

[0216] 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.

Claims

1. A method of controlling a mobile agricultural machine (100), comprising: receiving a topographic map (600) of a work site (602) indicative of a topographic characteristic of the work site (602), wherein the topographic characteristic is based on data collected at a first time; receiving supplemental data (338) indicative of a characteristic related to the work site (602), the supplemental data being collected after the first time, wherein a type of the characteristic related to the work site is different from a type of the topographic characteristic; based on the topographic map (600) and the supplemental data (338), generating a topographic confidence output (610, 620, 640, 650) indicative of a confidence level of the topographic characteristic of the work site (602) indicated by the topographic map (600); and controlling one or more controllable subsystems of the mobile agricultural machine based on the topographic confidence output (610, 620, 640, 650), the one or more controllable subsystems comprising one or more of: (i) an actuator of the mobile agricultural machine, the actuator configured to position a component of the mobile agricultural machine relative to a surface of the work site; (ii) a propulsion subsystem of the mobile agricultural machine, the propulsion subsystem configured to control a speed at which the mobile agricultural machine travels over the work site; or (iii) a steering subsystem of the mobile agricultural machine, the steering subsystem configured to control a heading of the mobile agricultural machine as the mobile agricultural machine travels over the work site.

2. The method of claim 1, wherein generating the topographic confidence output (610, 620, 640, 650) further comprises: determining the confidence level (617, 627), wherein the confidence level is indicative of a likelihood that the topographic characteristic of the work site (602) indicated by the topographic map (600) has changed; and generating a representation of the confidence level (617, 627).

3. The method of claim 1, wherein generating the confidence output (610, 620, 640, 650) further comprises: generating a map of the work site (602) including an indication of the confidence level (617, 627).

4. The method of claim 1, wherein generating the confidence output (610, 620, 640, 650) comprises: determining a plurality of confidence levels (617, 627), wherein each of the plurality of confidence levels (617, 627) is indicative of a likelihood that the topographic characteristic of a corresponding one of a plurality of geographic locations within the work site (602) has changed.

5. The method of claim 4, and further comprising: ​ determining a plurality of confidence zones (614-1, 614-2, 614-3), each of the plurality of confidence zones (614-1, 614-2, 614-3) corresponding to a respective one of the plurality of confidence levels (617, 627), wherein operation of the mobile agricultural machine (100) is based on the mobile agricultural machine (100) being present in one of the plurality of confidence zones (614-1, 614-2, 614-3).

6. The method of claim 1, further comprising: controlling a vehicle, different from the mobile agricultural machine, to collect additional data corresponding to the worksite (602).

7. The method of claim 1, further comprising: controlling an interface mechanism (360, 364) communicably connected to the mobile agricultural machine to provide an indication of the terrain confidence output (610, 620, 640, 650).

8. The method of claim 1, wherein the characteristics related to the worksite include one or more of: weather characteristics; event characteristics; environmental characteristics; activity characteristics; soil characteristics; or vegetation characteristics.

9. A mobile agricultural machine (100), comprising: a control system (304), the control system comprising: a terrain confidence system (330) configured to: receive a terrain map (600) of a worksite (602) indicative of terrain characteristics of the worksite (602), wherein the terrain characteristics are based on data collected at a first time; receive supplemental data (338) indicative of characteristics related to the worksite (602), the supplemental data (338) being collected after the first time and before a time at which the mobile agricultural machine is to perform an operation at the worksite, wherein a type of the characteristics related to the worksite is different from a type of the terrain characteristics; determine, based on the supplemental data, a likelihood that the terrain characteristics of the worksite indicated by the terrain map have changed; generate, based on the determined likelihood that the terrain characteristics of the worksite indicated by the terrain map have changed, a terrain confidence output (610, 620, 640, 650) indicative of a confidence level (617, 627) of the terrain characteristics of the worksite (602) indicated by the terrain map (600); and an action signal generator (406) configured to control, based on the terrain confidence output (610, 620, 640, 650), one or more controllable subsystems of the mobile agricultural machine, the one or more controllable subsystems comprising one or more of: (i) an actuator of the mobile agricultural machine configured to position a component of the mobile agricultural machine relative to a surface of the worksite; (ii) a propulsion subsystem of the mobile agricultural machine configured to control a speed at which the mobile agricultural machine travels over the worksite; or (iii) a sensor of the mobile agricultural machine configured to collect data related to the worksite. (iii) a steering subsystem of the mobile agricultural machine, the steering subsystem configured to control a heading of the mobile agricultural machine as the mobile agricultural machine travels over the work site.

10. The mobile agricultural machine of claim 9, wherein the terrain confidence output includes a representation of the confidence level.

11. The mobile agricultural machine of claim 9, wherein the terrain confidence system further comprises: a map generator (402) that generates a map of the work site (602) that includes an indication of the confidence level (617, 627).

12. The mobile agricultural machine of claim 9, wherein the action signal generator is configured to control an interface mechanism to cause the interface mechanism (360, 364) communicably connected to the mobile agricultural machine (100) to generate an interface display indicative of the terrain confidence output (610, 620, 640, 650).

13. The mobile agricultural machine of claim 9, wherein the action signal generator is configured to control an interface mechanism to cause the interface mechanism (360, 364) to provide an indication that directs a human to collect additional data corresponding to the work site.

14. The mobile agricultural machine of claim 9, wherein the characteristic related to the work site includes one or more of: a vegetation characteristic, an activity characteristic, or an event characteristic.

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