System confidence display and control for mobile machines

Abstract

A mobile agricultural machine includes a sensor that senses a characteristic of an environment in which the mobile agricultural machine is operating and generates a sensor signal indicative of the characteristic. The mobile agricultural machine also accesses a data store having stored data indicative of the characteristic that can affect an ability of the mobile agricultural machine to perform an operation. Further, the mobile agricultural machine includes a confidence system configured to receive the stored data and generate, based on the stored data, a confidence level value indicative of a confidence in an aspect of the ability of the mobile agricultural machine to perform the operation, and an action signal generator configured to generate, based on the confidence level value, an action signal for controlling an action of the mobile agricultural machine.

Description

[0001] This application is a divisional application of patent application (filed on October 21, 2021, application number 202111226582.1, entitled "System Confidence Display and Control for Mobile Machinery").

[0002] Cross-reference to related applications

[0003] This application is based on and claims the benefit of U.S. Provisional Patent Application Serial No. 63 / 104,654, filed on October 23, 2020, the contents of which are incorporated herein by reference in their entirety. Technical Field

[0004] This manual covers agricultural machinery, forestry machinery, construction machinery, and lawn management machinery. Background Technology

[0005] There are various types of machinery performing various operations in different types of work sites, such as agricultural machinery, forestry machinery, construction machinery, and lawn management machinery. These machines are typically operated by operators and have sensors that generate information during operation. Many of these machines include various sensors that can be used to sense various characteristics, such as characteristics related to the environment in which the machine operates, characteristics related to the machine's operation, etc.

[0006] Machinery can have many different mechanisms and subsystems, such as multiple different mechanical, electrical, hydraulic, pneumatic, electromechanical (and other) mechanisms and subsystems, some or all of which can be controlled by the operator at least to some extent. The operator can rely on information generated by sensors, as well as various other types of information, to control the various mechanisms and subsystems.

[0007] The above discussion is provided to provide general background information only and is not intended to help determine the scope of the subject matter for which protection is sought. Summary of the Invention

[0008] A mobile agricultural machine includes sensors that sense characteristics of the environment in which the mobile agricultural machine operates and generate sensor signals indicating those characteristics. The mobile agricultural machine also accesses a data storage device having stored data indicating characteristics that can affect the ability of the mobile agricultural machine to perform operations. Further, the mobile agricultural machine includes a confidence system configured to receive the stored data and generate confidence level values ​​based on the stored data indicating confidence in the ability of the mobile agricultural machine to perform operations; and an action signal generator configured to generate action signals for controlling the actions of the mobile agricultural machine based on the confidence level values.

[0009] This summary is provided to introduce some concepts in a simplified form, which will be further described in the detailed description below. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to help determine the scope of the claimed subject matter. The claimed subject matter is not limited to embodiments that address any or all of the deficiencies pointed out in the background art. Attached Figure Description

[0010] Figure 1 It is an illustrative diagram of an example of a machine.

[0011] Figure 2 This is a block diagram of an example computing architecture.

[0012] Figure 3 This is a more detailed block diagram of an example of a data storage device.

[0013] Figure 4 This is a more detailed block diagram of an example of a confidence system.

[0014] Figure 5 It is shown Figure 4 The flowchart shows an example operation of the confidence system.

[0015] Figure 6 This is a block diagram of an example interface display.

[0016] Figure 7 It is a partial block diagram and partial illustration of an example of a machine.

[0017] Figure 8 This is a partial block diagram and a partial top view of an example of a machine.

[0018] Figure 9 It shows Figure 8 An example of a side view of a row unit of a machine is shown in the figure.

[0019] Figure 10 This is a partial block diagram and a partial side view showing an example of the machine.

[0020] Figure 11 This shows the deployment in a remote server architecture. Figure 2 The diagram shows the architecture.

[0021] Figures 12 to 14 An example of a mobile device that can be used in the architecture shown in the preceding figures is illustrated.

[0022] Figure 15 This is a block diagram illustrating an example of a computing environment that can be used in the architecture shown in the previous figures. Detailed Implementation

[0023] While some examples described herein take place in scenarios involving specific machinery (e.g., agricultural spraying machinery), it should be understood that the various systems and methods described herein are applicable to and can be used with any number of machines, including any number of agricultural, forestry, construction, or lawn management machines, some of which will be described herein. Additionally, although some examples described herein take place in scenarios involving specific sensors or sensor systems and specific control devices, it will be noted that the various systems and methods described herein are applicable to and can be used with any number of sensors or sensor systems and any number of control devices, some of which will be described herein. Furthermore, while the examples described herein take place in scenarios involving specific operations (such as spraying operations), it should be understood that the systems and methods described herein are applicable to and can be used with any number of operations performed by any number of different types of machinery. Further, it should be understood that the confidence system (described herein) can be applied to and can be used with any number of different types of machinery performing any number of operations.

[0024] The system described herein can utilize various sensors in the control of agricultural machinery. One such example is the use of sensing systems (e.g., imaging systems) on agricultural spraying machinery to control operating parameters related to the application of the sprayed substance (such as herbicides). For instance, the sensing system can generate sensor signals indicating the characteristics of weeds on the agricultural surface to be sprayed (such as a field), such as weed location, weed density, weed type, and various other weed characteristics. Based on the sensor signals, the control system on the agricultural spraying machinery can automatically adjust the operating parameters of the controllable subsystems of the agricultural spraying machinery. For example, but not limited to, the control system can control the position of the spray boom or boom arm, the characteristics of the spray (such as volume, rate, operating pressure, etc.), the actuation or deactivation of the nozzle, the position or orientation of the nozzle, and various other operations of the controllable subsystems controlling the application of herbicides to weeds.

[0025] In addition to various other advantages, this control can improve operational efficiency. For example, in a spraying scenario, a spraying system can utilize broadcast spraying, which applies the material evenly (or substantially evenly) to the entire target area, i.e., widely across the entire field. In this way, the operator can relatively ensure that the material will effectively cover all weeds in the field. However, broadcast spraying can be inefficient because some of the material may be applied to areas of the field where it is not needed, and thus a significant amount of material may be wasted throughout the entire spraying operation across the field. This can increase operational costs and put pressure on the environment, among other disadvantages, and potentially harm crops or otherwise detrimentally affect crop value. Therefore, by employing a control system that uses the detection and control of the desired areas to be sprayed (such as the location of weeds in the field) to apply the material only to those desired areas, the operator can be confident that the material is applied as desired while minimizing waste.

[0026] In various other mobile machinery, such as other mobile agricultural machinery (e.g., harvesters, tillage machinery, planting / seeding machinery, etc.) and various other machinery (e.g., forestry machinery, construction machinery, and lawn management machinery), the operating parameters of the machinery can be automatically controlled based on various sensor inputs. For example, in a harvester, the position of the cutterhead can be automatically controlled based on, for example, the characteristics of the field (e.g., terrain) or the sensed distance of the machinery (or its components) from the surface of the field. Alternatively, the operator can manually control the position of the cutterhead. In planting and tillage machinery, the depth of the working tools (e.g., furrow openers, discs, handles, etc.) can be automatically controlled based on, for example, the sensed characteristics of the field (e.g., terrain) or the sensed distance of the machinery (or its components) from the surface of the field. Alternatively, the operator can manually control the depth of the working tools. These are merely some examples of the operation of some of the machinery envisioned herein. Various other operations and various other machinery can be envisioned.

[0027] However, in such systems, the quality of the machinery's performance depends on many factors. In the spraying example described above, the quality of material application (such as whether the herbicide is applied as desired to weeds) depends on sensor signals that accurately indicate the location of weeds in the field. The quality of the spraying machinery's performance also depends on the response time of the pumps, valves, or nozzles when attempting to apply material to detected weeds, as well as the response time of various actuators. Additionally, various operating characteristics or mechanical settings of the spraying machinery, and various characteristics of the environment in which the spraying machinery is operating (such as various characteristics of the field or various weather conditions), can also affect the performance of the spraying machinery. Because these factors can vary, the operator cannot always be certain that the target material application operation of the spraying machinery is being performed ideally, and therefore the operator may choose to follow the default broadcasting method. In other examples, such as the harvester example described above, and the planting and tillage examples, the quality of the machinery's performance using automatic controls (such as automatic header height, automatic tool depth, etc.) may depend on many factors, including the characteristics of the machinery, the characteristics of the environment in which the machine operator is located, and the ability of sensors to accurately and reliably sense the characteristics of interest.

[0028] The control system described herein includes a confidence system that determines a confidence level and generates a confidence level value indicating the machine's ability to perform a desired operation. The confidence level can depend on numerous factors, such as the reliability or accuracy of sensor signals generated by various sensors or sensor systems of the machine, various characteristics of the environment in which the machine operates, various mechanical characteristics (such as operating characteristics or machine settings), and various other factors. Based on this confidence level value, the confidence system can generate various action signals for controlling the actions of the machine. For example, but not limited to, action signals can provide an indication of the confidence level value (such as on an interface mechanism), control the operation of the machine, and various other actions to an operator or user. In some examples, the operator or user can provide a confidence level value threshold that the control system uses to determine what action to take. The confidence system can generate various action signals, for example, based on a comparison of the confidence level value with the confidence level value threshold.

[0029] Furthermore, it will be noted that while some examples described herein take place in the context of specific agricultural machinery (such as agricultural spraying machinery), it should be understood that the various systems and methods described herein are applicable to and can be used in conjunction with any number of different types of machinery, including any number of agricultural machinery, forestry machinery, construction machinery, and lawn management machinery, some of which will be described herein. Additionally, although some examples described herein take place in the context of specific sensors and sensor systems and specific control devices, it will be noted that the various systems and methods described herein are applicable to and can be used in conjunction with any number of different sensors or sensor systems and any number of different control devices, some of which will be described herein. Moreover, although the examples described herein take place in the context of specific operations (such as spraying operations), it should be understood that the systems and methods described herein are applicable to and can be used in conjunction with any number of different types of operations performed by any number of different types of machinery. Further, it should be understood that the confidence system (described below) can be applied to and can be used in conjunction with any number of different types of machinery performing any number of different types of operations.

[0030] Additionally, it should be understood that the operators of various machines can be local human operators, remote human operators, or automated systems (both local and remote).

[0031] Figure 1 An agricultural environment 100 is shown, in which a mobile machine 101 includes an agricultural spraying system 102. In operation, and as an overview, the spraying system 102, shown together with a towing vehicle 104 towing the towed implement 106, moves over an agricultural surface 110 (such as a field) in the direction indicated by arrow 130. In the example shown, the implement 106 includes a tank 108 containing a substance to be applied to the agricultural surface 110. The tank 108 is fluidly connected to a nozzle 112 via a delivery system that includes conduits among other things, such as valves. A fluid pump is configured to pump the substance from the tank 108 through the conduits and through the nozzle 112. The nozzles 112 are mounted to and spaced apart along a spray bar 116. The spray bar 116 includes spray bar arms 118 and 120 that can be hinged or pivoted relative to a central frame 122, thus allowing the spray bar arms 118 and 120 to move between a storage or transport position and an extended or deployed position. Additionally, the spray boom 116 can be moved between various positions relative to, for example, an agricultural surface 110. For example, when in the extended position, the height of the spray boom 116 above the agricultural surface 110 can be adjusted.

[0032] exist Figure 1In the example shown, vehicle 104 is a tractor with an operator's cab or driver's cab 124, which may have various interface mechanisms for controlling the sprayer system 102 or providing various displays. The operator's cab 124 may include interface mechanisms that allow the operator to control and manipulate the sprayer system 102. The interface mechanisms in the operator's cab 124 can be any of a variety of different types of mechanisms. For example, they may include input mechanisms such as a steering wheel, control lever, joystick, button, pedal, switch, etc. Furthermore, the operator's cab 124 may include one or more interface display devices (such as a monitor), or mobile devices supported within the operator's cab 124. In this case, the interface mechanisms may also include actuable elements displayed on the display devices, such as icons, links, buttons, etc. The interface mechanisms may include one or more microphones therein providing voice recognition on the sprayer machinery 102. They may also include audio interface mechanisms (such as speakers), tactile interface mechanisms, or various other interface mechanisms. The interface mechanisms may also include other output mechanisms such as dials, meters, instrument outputs, lights, audible or visual alarms, or tactile output mechanisms, etc.

[0033] Vehicle 104 also includes ground engagement elements, such as wheels 126. These ground engagement elements can also be tracks or various other ground engagement elements. It should be noted that in other examples, the spraying system 102 is self-propelled. That is, the machinery carrying the spraying system is not towed by the towing vehicle 104, but also includes propulsion and steering systems, etc.

[0034] The spraying system 102 also includes a plurality of sensors 128 (identified as 128-1 to 128-3) which are placed at different locations on components of the spraying system 102. In one example, the sensors 128 are sensing sensor systems, such as imaging systems (e.g., cameras and image processing systems). The sensors 128 may be located at various other locations on the towing vehicle 104, the implement 106 including the spray boom 116, and the spraying system 102.

[0035] As will be discussed in more detail herein, in one example, sensor 128 is configured to sense various characteristics of the environment surrounding spraying system 102, including characteristics related to vegetation on agricultural surface 110, such as the location, type, and density of weeds. Sensor 128 generates sensor signals indicating various characteristics. These sensor signals can be received by a control system configured to generate action signals to command the operation of spraying system 102. For example, action signals of interface mechanisms in control room 124 to present indications (such as displays, alarms, etc.), action signals to control the operation of spraying system 102 (such as adjusting the position or orientation of spray boom 116, adjusting the operation of nozzle 112, etc.). In an illustrative example, sensor 128 may generate sensor signals indicating the location of weeds on agricultural surface 110, and the control system may generate action signals based on the location of the weeds to control the operation of spraying system 102 so that material is desiredly applied to the location of the weeds.

[0036] Figure 1 The sensors are shown to be mounted at one or more locations within the spraying system 102. For example, they may be mounted on a towing vehicle 104, as shown by sensor 128-1. They may be mounted on implement 106, as shown by sensor 128-2. They may be mounted on the spray boom 116 (including each of boom arms 118 and 120) and spaced apart along the boom, as shown by sensor 128-3. Sensor 128 may be a forward-looking sensor configured to sense the front of components of the spraying system 102, a side-looking sensor configured to sense the sides of components of the spraying system 102, or a rear-looking sensor configured to sense the rear of components of the spraying system 102. In some examples, the viewing angle of sensor 128 may be adjusted, for example, such that sensor 128 is positioned with a viewing angle of up to 360 degrees around the spraying system 102. Sensor 128 may be mounted on the spraying system 102 such that they travel above or below the vegetation canopy on the agricultural surface 110. Note that these are just some examples of the locations of sensor 128, and sensor 128 may be installed in one or more of these locations or in various other locations within the spraying system 102 or any combination thereof.

[0037] Figure 2 This is a block diagram of an example computing architecture 200, which, among other things, includes an agricultural spraying system 102 configured to perform spraying operations on agricultural surfaces such as field 110. Some items are similar. Figure 1 The items shown are numbered similarly. Figure 2The architecture 200 shown includes an agricultural spraying system 102, one or more operator interfaces 260, one or more operators 262, a network 264, a remote computing system 266, one or more user interfaces 268, one or more remote users 270, and one or more vehicles 300. The agricultural spraying system 102 may include one or more controllable subsystems 202, a control system 204, a communication system 206, one or more data storage devices 208, one or more sensors 210, and may include other items 212. The controllable subsystem 202 may include a spraying subsystem 214, a boom position subsystem 216, a steering subsystem 218, a propulsion subsystem 220, and may include other items 222, such as other controllable subsystems. The spraying subsystem 214 itself may include one or more valves 215, one or more pumps 224, one or more material tanks 108, one or more nozzles 112, and may include other items 226.

[0038] Figure 2 It is also shown that sensor 210 may include any number of different types of sensors that sense or otherwise detect any number of characteristics. For example, sensor 210 may sense characteristics related to the environment of components in computing architecture 200 (such as characteristics of agricultural surface 110), as well as characteristics related to components in computing architecture 200 (such as operational characteristics or mechanical settings of components of spraying system 102 or vehicle 300, such as operational characteristics or mechanical settings of controllable subsystems 202 or 308). In the example shown, sensor 210 includes one or more sensing sensors 128, one or more relative position sensors 236, one or more geographic location sensors 238, one or more material handling sensors 240, one or more spraying sensors 242, one or more terrain sensors 244, one or more weather sensors 246, and sensor 210 may include other items 248 (including other sensors). Geographic location sensor 238 may include one or more position sensors 250, one or more heading / speed sensors 252, and may include other items 254.

[0039] Spraying system 102 may include towed implements and towing vehicles (such as...) Figure 1(As shown), or it can be self-propelled. Control system 204 is configured to control the components and systems of spraying system 102. For example, communication controller 228 is configured to control communication system 206. Communication system 206 is used for communication between components of spraying system 102 or with other systems such as vehicle 300 or remote computing system 266 via network 266. Network 266 can be any of a variety of different types of networks, such as the Internet, cellular network, wide area network (WAN), local area network (LAN), controller area network (CAN), near field communication network, or any combination of various other networks or communication systems.

[0040] A remote user 270 is shown interacting with a remote computing system 266, for example, via a user interface 268. The user interface 268 may include various interface mechanisms, including interface display mechanisms, i.e., interface mechanisms configured to display information or including displays such as interactive displays. The remote computing system 266 may be various different types of systems. For example, the remote computing system 266 may be in a remote server environment. Further, the remote computing system 266 may be a remote computing system (such as a mobile device), a remote network, a farm manager system, a vendor system, or various other remote systems. The remote computing system 266 may include one or more processors, servers or controllers 274, communication systems 272, and may include other items 276. As shown in the example, the remote computing system 266 may also include a data storage device 208 and a control system 204. For example, data stored and accessed by various components in the computing architecture 200 may be located remotely in the data storage device 208 on the remote computing system 266. Additionally, various components of the computing architecture 200 (such as a controllable subsystem 202) may be controlled by the control system 204 located remotely at the remote computing system 266. Therefore, in one example, remote user 270 can remotely control spraying system 102 or vehicle 300, such as by providing user input through user interface 268. These are just some examples of the operation of computing architecture 200.

[0041] Vehicle 300 (e.g., unmanned aerial vehicle (UAV), ground vehicle, etc.) may include one or more data storage devices 302, one or more sensors 304, control system 204, one or more controllable subsystems 308, one or more processors, controllers, or servers 310, and may include other items 312. Vehicle 300 can be used to perform operations on agricultural surfaces, such as spraying operations performed by spraying system 102 on field 110. For example, UAV or ground vehicle 300 can be controlled to travel on agricultural surfaces and utilize sensors 304 to sense various characteristics associated with the agricultural surface. For example, vehicle 300 can travel in front of or behind spraying system 102. Sensors 304 may include any number of various sensors, including but not limited to any one of the multiple sensors 210. For example, sensor 304 may include sensing sensor 128. In a specific example, during a spraying operation, vehicle 300 can travel in front of spraying system 102 to detect the location of weeds on field 110, or behind spraying system 102 to detect characteristics related to the application of materials to field 110, such as material coverage. Control system 204 can be located on vehicle 300, enabling vehicle 300 to generate action signals based on characteristics sensed by sensor 304 to control the operation of spraying system 102, such as adjusting the operating parameters of one or more controllable subsystems 202.

[0042] As shown in the figure, vehicle 300 may include communication system 306, which is configured to communicate with communication system 206 via network 264 or, for example, with remote computing system 266.

[0043] Figure 2 An operator 262, such as an operator interface 262, interacts with the spraying system 102. The interface 260 may include various interface mechanisms, including interface display mechanisms, i.e., interface mechanisms configured to display information or including displays such as interactive displays. The interface 260 may be located on the spraying system 102, such as in the above... Figure 1 The operating room 124 may also be another interface mechanism, such as a mobile device, that is communicatively coupled to various components in the computing architecture 200.

[0044] Before discussing the overall operation of the agricultural spraying system 102, a brief description of some of the items in the spraying system 102 and their operation will be provided first.

[0045] Communication system 206 may include wired and wireless communication logic systems, which can essentially be any communication system that can be used by the systems and components of spraying system 102 to transmit information to other items such as control system 204, sensor 210, controllable subsystem 202, and confidence system 230. In another example, communication system 206 communicates via a controller area network (CAN) bus (or another network, such as Ethernet, to transmit information between these items). This information may include various sensor signals and output signals generated by sensor characteristics and / or sensing characteristics, as well as other items.

[0046] Sensing sensor 128 is configured to sense various characteristics related to the environment surrounding spraying machinery 100. For example, sensing sensor 128 may be configured to sense characteristics related to vegetation (e.g., weeds, crops, etc.) on agricultural surface 110, such as, but not limited to, the presence, location, quantity, density, and type of weeds on agricultural surface 110. For illustrative purposes and not limiting, sensing sensor 128 may be used in conjunction with relative position sensor 236 to determine the geographical location of weeds on field 110. In one example, sensing sensor 128 may include an imaging system, such as a camera.

[0047] The relative position sensor 236 is configured to sense the relative positions of various components of the agricultural spraying system 102 relative to each other or relative to the frame of the sprayer 102. For example, multiple relative position sensors 236 may be positioned at multiple locations within the spraying system 102 (e.g., spaced apart along the boom 116, positioned by the nozzles 112, etc.). The sensor 236 can thus detect the position or orientation (e.g., tilt) of various components of the spraying system 102. For example, the sensor 236 can sense the height of the boom 116 (or boom arms 118 and 120) above the agricultural surface 110, the height or orientation of the nozzles 112 relative to each other, relative to the ground or weeds, or relative to the frame of the spraying system 102, and determine positional information of some components relative to various other components. The relative position sensor 236 can sense the height of the boom 116 or nozzles 112 above detected weed locations on the agricultural surface 110. In another example, once the position of sensor 236 is detected, the position and orientation of other items can be calculated by knowing the size of sprayer 102.

[0048] The geolocation sensor 238 can sense the geolocation and other derived variables corresponding to the spraying system 102. Sensor 238 may include a position sensor 250, a heading / velocity sensor 252, and may also include other sensors 254. The position sensor 250 is configured to determine the geolocation of the spraying system 102 on the field 110. The position sensor 250 may include, but is not limited to, a GNSS receiver that receives signals from a Global Navigation Satellite System (GNSS) satellite transmitter. The position sensor 250 may also include a Real-Time Kinematic (RTK) component configured to enhance the accuracy of the position data derived from the GNSS signals. The position sensor 250 may include a variety of other sensors, including other satellite-based sensors, cellular triangulation sensors, dead reckoning sensors, etc.

[0049] The heading / speed sensor 252 is configured to determine the heading and speed of the spraying system 102 as it traverses the field 110 during spraying operations. This may include sensors that sense movement of ground-engaging elements (e.g., wheels or tracks 126), or may utilize signals received from other sources such as the position sensor 250.

[0050] The material handling sensor 240 is configured to sense characteristics related to the material to be sprayed by the spraying system 102. For the purpose of illustration and not limitation, the material handling sensor 240 may sense the pressure of the fluid in the material tank 108, the pressure of the material pumped by the pump 270, the viscosity, temperature or other characteristics of the material, the flow rate of the material through a fluid path (e.g., a conduit, valve, etc.), the pressure of the fluid in the fluid path, and various other characteristics of the material to be sprayed within the spraying system 102.

[0051] The spray sensor 242 is configured to sense the characteristics of the spray from the nozzle(s) 112. For example, but not limited to, the spray sensor 242 may sense spray distance (e.g., distance from the nozzle tip to the target), spray volume, spray angle, spray coverage, spray impact, spray pattern shape (e.g., fan-shaped, cone-shaped, solid flow, flat, etc.), and various other characteristics related to the spray from the nozzle(s) 112.

[0052] The terrain sensor 244 is configured to sense the characteristics of the agricultural surface (e.g., field 110) over which the spraying system 102 travels. For example, the terrain sensor 244 can detect the terrain of the field (which can be downloaded as a topographic map or sensed using sensors such as accelerometers, inertial measurement units, etc.) to determine the slope of various areas of the field. The sensor 244 can detect field boundaries, obstacles, or other objects on the field (such as rocks, rootstocks, trees, etc.).

[0053] Weather sensor 246 is configured to sense various weather characteristics relative to the agricultural surface. For example, weather sensor 246 can detect the direction and speed of wind traveling on the agricultural surface over which the spraying system 102 travels. They can detect precipitation, humidity, temperature, and many other conditions. This information can also be obtained from remote weather services.

[0054] Sensor 210 may include any number of sensors of different types. For example, sensor 210 may include potentiometers, Hall effect sensors, and various mechanical and / or electrical sensors. Sensor 210 may 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, although multiple sensors are shown, sensor 210 may include a single sensor configured to sense various different characteristics and may generate a single sensor signal indicating multiple characteristics. For example, sensor 210 may include an imaging sensor mounted on spraying system 102 or vehicle 300. The imaging sensor may generate images indicating multiple characteristics related to both spraying system 102 and vehicle 300 and their environment (e.g., agricultural surface 110). Furthermore, although multiple sensors are shown, more or fewer sensors 210 may be used. For example, one or more sensors may be multifunctional because they can sense various different characteristics. For example, a single sensor can sense both location information and characteristics associated with the agricultural surface 110.

[0055] Additionally, it should be understood that some or all of the sensors 210 can be controlled by the control system 204 as a controllable subsystem 202. For example, the control system 204 can generate various action signals to control the operation, position, orientation, and various other operating parameters or settings of the sensors 210. For instance, because vegetation on the agricultural surface 110 may obstruct the line of sight of, for example, sensing sensors 128, the control system 204 can generate action signals to adjust the position or orientation of sensing sensors 128, thereby adjusting their line of sight. These are merely examples. The control system 204 can generate various action signals to control any number of operating parameters of the sensors 210.

[0056] The controllable subsystem 202 illustratively includes a spraying subsystem 214, a boom position subsystem 216, a steering subsystem 218, and a propulsion subsystem 220, and may also include other subsystems 222. The controllable subsystem 202 will now be briefly described.

[0057] The spraying subsystem 214 includes one or more pumps 224 configured to pump a substance (e.g., herbicide, insecticide, fungicide, etc.) from one or more substance tanks 108 through a fluid path (e.g., conduit, valve, etc.) to one or more nozzles 112, which may be mounted, for example, on a spray boom and at various other locations on the spraying system 102. The spraying subsystem 214 may also include other items 226. For example, the spraying subsystem 214 may include a valve subsystem (or a valve assembly of one or more valves) 215, which may include any number of controllable valves placed at different locations within the spraying system 102. The controllable valves 215 may be positioned along a fluid path (e.g., a conduit extending from the pump 224 to the nozzle 112) to control the flow of the substance through the fluid path. Some or each of the nozzles 112 may have associated valves (e.g., pulse width modulation valves, solenoid valves, etc.) that can be controllably operated. For example, valve 215 may be controllable between open (e.g., on) and closed (e.g., closed) positions. (Multiple) valves 215 may also be proportional valves, which can be used to proportionally control the flow of substances through the valve (e.g., flow rate).

[0058] Material tank 108 may include multiple hoppers or containers, each configured to separately contain a material. For example, material tank 108 may separately contain different types of materials or different compositions of the same type of material (e.g., different compositions of herbicides), which can be controllably and selectively pumped through a fluid path and to nozzle 112 by pump 224 under the control of valve 215. For example, when sensor 210 senses the presence of weeds on agricultural surface 110 and generates a sensor signal indicating the presence of weeds, control system 204 may generate control signals to control pump 224, valve 215, and nozzle 112 to pump material from one of the multiple hoppers or containers containing the desired material (e.g., herbicide) based on the sensor signal. In another example, control system 204 may control pump 224, valve 215, and nozzle 112 to achieve desired operating variables (e.g., pressure, speed, flow rate, etc.). For example, when sensor 210 senses the geographic location of weeds on agricultural surface 110 and generates a sensor signal indicating the geographic location, control system 204 can generate control signals to control pump 224, valve 215, and nozzle 112 to adequately cover the geographic location of the weeds. For example, control system 204 can generate control signals to increase or decrease the operating pressure or speed of pump 224, the position of valve 215 controlling the flow rate of the material, the position or orientation of nozzle 112, and various other controls. In one example, the material in material tank 108 can be mixed with a substance that increases the visibility of the material, such as a dye or colorant.

[0059] Nozzle 112 is configured to apply or direct a substance onto agricultural surface 110. Control system 204 can control nozzle 112 individually or separately. For example, control system 204 can turn nozzle 112 on (e.g., open) and off (e.g., close). Additionally, control system 204 can control nozzle 112 to change its position or orientation (e.g., tilt). In another example, control system 204 can control nozzle 112 to change the characteristics of the spray emitted by nozzle 112. For example, control system 204 can control the movement of nozzle 112, such as by controlling one or more actuators to induce movement, such as rotational movement, which widens or narrows the fluid passages through nozzle 112 to affect the spray pattern, spray volume, and various other spray characteristics.

[0060] The boom positioning subsystem 216 is configured to actuate the movement of the boom 116 (including individual boom arms 118 and 120). For example, the boom positioning subsystem 216 may include multiple actuators (such as electro-, hydraulic, pneumatic, mechanical, or electromechanical actuators) connected to various components to adjust one or more of the position or orientation of the boom 116 or the individual boom arms 118 and 120. For example, the boom positioning subsystem 216 may adjust the height of the boom 116 above the agricultural surface 110. For example, when characteristics related to vegetation on the agricultural surface 110 are detected, the control system 204 may control the boom positioning subsystem 216 to raise or lower the boom 116. As an example, when the control system 204 detects characteristics related to weeds on the field 110 (e.g., quantity, type, location, height, density, etc.), the control system 204 may generate an action signal to the boom positioning subsystem 216 to adjust the position of the boom 116 relative to the field 110.

[0061] The steering subsystem 218 is configured to control the heading of the spraying system 102 by steering ground engagement elements (e.g., wheels or tracks 126). The control system 204 can generate action signals to control the steering subsystem 218 to adjust the heading of the spraying system 102. For example, when the control system 204 receives sensor signals indicating the geographic location of weeds generated by sensor 210, the control system 204 can generate action signals to control the steering subsystem 218 to adjust the heading of the spraying system 102. In another example, the control system 204 can generate action signals to control the steering subsystem 218, thereby adjusting the heading of the spraying system 102 to conform to a commanded route, such as a route commanded by an operator or user, a spray application map, etc. The control system 204 (or another) can generate a spray application map based on the characteristics of the agricultural surface sensed by one or more sensors 210. For example, the control system 204 can generate a spray application map based on signals from one or more of the sensing sensors 128 and sensors 308 on the vehicle 300 traveling on the agricultural surface 110 in front of the spraying system 102.

[0062] The propulsion subsystem 220 is configured to propel the spraying system 102 across an agricultural surface, such as by moving ground engagement elements (e.g., wheels or tracks 126). The propulsion subsystem 220 may include a power source (such as an internal combustion engine or other power source) and a transmission mechanism to drive the set of ground engagement elements 126. In one example, the control system 204 may receive sensor signals generated by sensor 210, confidence levels determined by confidence system 230, and various other signals, and control the propulsion subsystem 220 to adjust the speed of the spraying system 102.

[0063] The control system 204 is configured to receive or acquire various data, including historical data, pre-existing data, data indicating environmental characteristics related to the agricultural spraying system 102 or vehicle(s) 300, such as the characteristics of the agricultural surface 110, data indicating factors or characteristics that can affect the performance of sensors in the architecture 200, characteristics related to the operation of the agricultural spraying system 102 or vehicle 300, including the operating characteristics or mechanical settings of its various components, and various other data, as will be further described herein.

[0064] Additionally, and as will be described in more detail herein, the confidence system 230 of the control system 204 can determine a confidence level regarding the ability of the mobile machinery 101 to perform or carry out a desired task based on various information, such as information received or acquired by the control system 204, including information accessed within the data storage device 208 or data received from the sensor 210, and various other data from various other sources. In the example of the spraying system 102, the confidence level can indicate the ability of the spraying system 102 to apply the sprayed material as desired to a desired location on, for example, an agricultural surface 110 (such as the location of weeds sensed by the sensor 210), as in the case of target material application operation. The confidence level may be affected by various factors or characteristics, such as the quality or accuracy of the sensor signals provided by the sensors on the mobile machinery 101, the response time of the controllable subsystem, the current operating characteristics or mechanical settings of the mobile machinery 101, the characteristics of the environment in which the mobile machinery 101 is operating, and many other factors or characteristics. These various factors or characteristics that can affect the confidence level can be indicated by various information received or obtained by the confidence system 230. The confidence system 230 can generate a confidence level value as output, indicating the determined confidence level. The confidence level value can be indicated by a representation. The representation can be a number, such as a percentage (e.g., 0% to 100%) or a scalar value, a grayscale or scaling value (e.g., AF, "high, medium, low", 1-10, etc.), a suggestion (e.g., "change operation", "cannot be detected", "slow", etc.), and various other representations.

[0065] Control system 204 can generate various action signals based on confidence level values ​​to control the actions of spraying system 102 (and other components of computing architecture 200, such as vehicle 300, telecomputing system 266, etc.). For example, based on confidence level values, control system 204 can generate action signals to present instructions (e.g., alarms, displays, notifications, etc.) to operator 262 on operator interface 266 or to user 270 on user interface 268. In another example, based on confidence level values, control system 204 can generate action signals to control the actions of one or more of the various components of computing architecture 200, such as, but not limited to, operating parameters or settings of one or more of controllable subsystems 202 or 308. For example, based on confidence level values, control system 204 can generate action signals to control spraying subsystem 214 to switch between target spraying and spread spraying, such as by actuating or deactivating one or more nozzles 112. These are just examples. The control system 204 can generate any number of action signals to control any number of actions of components in the computing architecture 200, including any number of action signals based on confidence values ​​generated by the confidence system 230.

[0066] The control system 204 may also include various other items 234, including but not limited to other controllers. For example, the control system 204 may include dedicated controllers corresponding to each of various controllable subsystems, such as a spraying subsystem controller (and controllers for various components of the spraying subsystem, such as nozzle controllers), a 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 204 may include various logic components, such as an image processing logic system. The image processing logic system can process images generated by sensor 210, such as images generated by sensing sensor 128, to extract data (e.g., as values) from the images. The image processing logic system can utilize various image processing techniques or methods, including but not limited to 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 or methods.

[0067] Figure 3 This is a block diagram showing an example of the data storage device 208 in more detail. Although Figure 3 Only data storage device 208 is shown, but it should be noted that various other data storage devices, such as data storage device 302, can be used. Additionally, Figure 3 Some or all of the items shown may be located on various other data storage devices, including data storage device 302. Figure 3The data storage device 208 is shown to include pre-existing data 310, sensor data 312, environmental data 314, system data 315, and may also include other data 316. The pre-existing data 310 itself includes historical data 318, one or more graphs 320, and may include other pre-existing data 322. The sensor data 312 itself may include one or more sensor signals 324, one or more sensor characteristics 326, and may include other sensor data 328. The environmental data 314 itself may include surface characteristic data 330, weather data 332, and may include other environmental data 334.

[0068] Various other components of the computing architecture 200 can access the data in the data storage device 208. For example, the data in the data storage device 208 can be used by the control system 204. For example, the data in the data storage device 208 can be accessed or otherwise obtained by the confidence system 230, such as by the communication system 206 or the data storage device access logic system 366 (discussed below), and used to generate confidence level values ​​that indicate the machine's ability to perform a desired task or operation.

[0069] The pre-existing data 310 may include any data accessible or otherwise available to components in the computing unit 200 prior to the commencement of mechanical operation (such as the commencement of spraying operation by the spraying system 102 at field 110). The pre-existing data includes historical data 318. Historical data 318 may include, for example, data from prior operations of the machinery, prior operation data at a specific work site, etc. For example, in the case of a spraying operation, historical data 318 may include prior indications of vegetation characteristics from prior operations of the machinery or prior operations at a specific site. For example, it may include stored image data of various weeds detected at a specific site (or other site). In this way, the current image generated by the sensing sensor 128 can be compared with previous images by the confidence system 230. Historical data 318 may also include previous confidence determinations or previous confidence level values ​​generated by the confidence system 230, such as confidence determinations made with a specific sensor, or confidence determinations made in previous operations (including previous confidence determinations made under conditions similar to the current operation).

[0070] Figure 320 may include images of the work site (including the current work site), such as images of the work site taken by a satellite during a flyover operation, by an aircraft such as UAV 300, or by a vehicle 300 traveling through the work site before the operation of the machinery. Figure 320 may also include maps generated by various data collection operations, such as maps generated based on data collected during previous operations of the machinery on the work site (e.g., row data, pass data, etc.), and maps generated based on images taken as described above. For example, in the case of spraying, a map of a specific field may be generated, indicating, among other things, the type, quantity, density, location, etc., of various vegetation on the field, including the type, quantity, density, location, etc., of various weeds on the field. In this way, the sensor signal generated by sensor 210 during the current operation can be compared with the pre-existing indications of the map using confidence level 230.

[0071] Sensor data 312 may include stored sensor signals 324, which may include previously generated sensor signals from previous operations or from an earlier time or another location at the work site, as well as real-time or near-real-time sensor signals generated by sensor 210. For example, in an image scenario, the current image generated by sensing sensor 128 may be compared by confidence system 230 with a previous image generated by sensing sensor 128, for example, to determine the quality (such as sharpness) of the current image compared to the previous image. In another example, the current sensor signal from a particular sensor may be compared by confidence system 230 with a sensor signal generated by another sensor. For example, in a combine harvester harvesting operation scenario, a threshing drum pressure sensor that generates a pressure signal indicating the biomass of the crop being processed by the combine harvester may be compared with an image generated by an imaging system of vegetation in front of the combine harvester (such as sensing sensor 128). In this way, the confidence system 230 can consider whether the sensor signal accurately corresponds to the expected value indicated by another sensor when determining the confidence level (e.g., is the biomass indicated by the pressure sensor meaningful given the characteristics of the vegetation indicated by an image of the vegetation in front of the combine harvester?). Additionally, it will be noted that the current sensor signal can be compared by the confidence system 230 with more than one other sensor signal generated by more than one other other sensor.

[0072] Sensor data 312 may also include sensor characteristic data 326, which may include data indicating various characteristics of the sensor device. For example, sensor operating characteristics, including the operational capabilities of a particular sensor device and the operating characteristics or settings of the sensor device when the current sensor signal is generated. In this way, when determining the confidence level, the confidence system 230 can consider the sensor's operating characteristics or settings (e.g., the sensor's operating characteristics or settings given the characteristics of the environment in which the sensor signal is generated). For example, in the scenario of an imaging system, shutter speed, zoom, focal plane, etc. In another example, sensor characteristic data 326 may include status data of various sensors 210, such as the current signal strength of the sensor device. For example, in the scenario of a geolocation sensor 238, the signal strength between the sensor and a satellite. In another example, status data may include calibration data (e.g., the last time the sensor was calibrated, sensor degradation, etc.), as well as the sensor model, sensor type or model, sensor age, etc.

[0073] Environmental data 314 may include surface characteristic data 330. Surface characteristic data 330 may include various data indicating characteristics related to the work site (such as agricultural surface 110). In this way, the confidence system 230 can consider the conditions or characteristics of the environment in which sensor signals are generated and machinery operates. For example, the characteristics of vegetation on field 110 in a scenario where sensing sensor 128 detects weeds during a spraying operation. For example, the type, quantity, density, and location of vegetation on the field. For illustration and not limitation, based on the density and type of vegetation on field 110, the confidence system 230 may determine the possible visibility of characteristics of interest (such as the location of weeds) in determining the confidence level.

[0074] Environmental data 314 may include weather data 332. Weather data 332 may be provided by weather sensor 246 or received from a remote weather service. The weather data may include various data indicating real-time or near-real-time weather conditions related to the work site, as well as historical weather data. In this way, when determining the confidence level, confidence system 230 may consider the weather conditions in which sensor 210 generates sensor signals and the weather conditions in which mobile machinery operates. For example, precipitation at the work site may affect the reliability of images generated by sensing sensor 128.

[0075] System data 315 may include various data indicating the characteristics of the machinery (e.g., spraying system 102) being used in operation. These include, but are not limited to, operating characteristics and machinery settings, current operating system information (e.g., operating system or software version), maintenance information, component deterioration, and various other data. In this way, the confidence system 230 can take into account the characteristics and condition of the machinery when determining the confidence level regarding the machinery's ability to perform a desired task. For example, a newer version of image recognition software may be available but not currently being used by the machinery. In other examples, operating characteristics or machinery settings may affect the machinery's ability to perform a desired task and thus affect the confidence level determined by the confidence system 230. For example, in the scenario of spraying system 102, spraying system 102 may move too fast, the spray boom may be too high or too low, the operating pressure or speed of pump 224 may be too high or too low, and one or more of valves 215 or nozzles 212 may be blocked, preventing spraying system 102 from performing the target spray application. These are just some examples of operational characteristics or mechanical settings that may affect the ability of mobile machinery 101 to perform desired tasks. Various other operational characteristics and mechanical settings may be included in system data 315 and used by confidence system 230 when determining confidence levels.

[0076] It should be understood that these are merely examples, and data storage device 208 (and other data storage devices such as data storage device 302) may include any of a wide variety of data, including any of a wide variety of data indicating factors or characteristics that may affect the ability of mobile machinery 101 to perform desired tasks and thus affect the confidence level determined by confidence system 230. Additionally, in determining the confidence level and generating confidence level values, confidence system 230 may consider any of a wide variety of data and any combination thereof.

[0077] Figure 4This is a block diagram illustrating an example of a confidence system 230 in more detail. The confidence system 230 may include a confidence determination system 350, a data acquisition logic system 352, a communication system 206, (multiple) processors / (multiple) controllers / (multiple) servers 232, a display generator 354, an action signal generator 356, a confidence map generator 357, a threshold logic system 358, a machine learning logic system 359, and may also include other items 370. The sensor confidence determination system 350 may include a confidence logic system 360, a confidence value tracking logic system 361, a confidence publishing logic system, and may also include other items 363. The data acquisition logic system 352 may include a sensor access logic system 364, a data storage device access logic system 366, and may also include other items 368.

[0078] In operation, the confidence system 230 determines a confidence level regarding the ability of the mobile machinery 101 to perform a desired task or operation. For example, the confidence level regarding the ability of the spraying system 102 to perform a targeted material application operation (whereby the spraying system 102 attempts to apply a substance, such as a herbicide, only to weeds on field 110, rather than uniformly applying it across the field as in a broadcast material application operation). In other examples, the confidence level regarding the ability of a harvester to maintain a desired header height relative to the field surface, the confidence level regarding the ability of a planter to maintain the depth of a furrow opener, or the confidence level regarding the ability of a tiller to maintain the depth of its working tools. These are merely examples. The confidence system 230 can determine confidence levels regarding the ability of various machines to perform various operations. The confidence system 230 generates confidence level values ​​that indicate the determined confidence level regarding the ability of the mobile machinery 101 to perform the desired task. For example, the confidence level system 230 can generate a confidence level value as a digital representation (percentage (e.g., 0% to 100%) or scalar value, grayscale or scaled representation (e.g., AF, "high, medium, low", 1-10, etc.), suggestion representation (e.g., "change operation", "cannot detect", "slow", etc.), and various other representations). In this way, the operator or control system can know the level of reliability or trust in the indications used to control the machinery. In determining the confidence level and generating the confidence level value, the confidence level system 230 can generate various action signals via the action signal generator 356 for, for example, controlling the operation of mobile machinery 101 (e.g., spraying system 102) or providing displays, suggestions, and / or other indications (e.g., alarms) to the operator 262 on the operator interface 260 or to the remote user 270 on the user interface 268.

[0079] It should be noted that the confidence system 230 can determine the confidence level of the mobile machinery 101 in its ability to perform the desired task or operation any number of times and under any given number of mechanical states. For example, the confidence system 230 can determine the confidence level of the mobile machinery 101 in its ability to perform the desired task or operation during, before, or after operation. The confidence system 230 can determine the confidence level of the mobile machinery 101 in its ability to perform the desired task or operation when the machinery is stationary or when the machinery is moving. The confidence system 230 can determine the confidence level of the mobile machinery 101 in its ability to perform the desired task or operation when the machinery is in a "key-on" state such that power (e.g., from a battery) is supplied to at least some components of the machinery, but for example, when the engine is not running.

[0080] Data capture logic system 352 captures or acquires data that can be used by other items on confidence system 230. Data capture logic system 352 may include sensor access logic system 364, data storage access logic system 266, and other logic systems 368. Sensor access logic system 364 may be used by sensor confidence determination system 350 to acquire sensor data (or values ​​indicating sensed variables or characteristics) from sensor 210 and other sensors such as sensor 304 of vehicle 300, which can be used to determine confidence levels. For illustration and not limitation, sensor access logic system 364 may acquire sensor signals indicating characteristics of weeds on field 110 (e.g., type, quantity, density, location, etc.).

[0081] Additionally, the data storage device access logic system 366 can be used to obtain data previously stored on a data storage device (e.g., one or more data storage devices 208, 302, etc.) or data previously stored at a remote computing system 266. For example, this can include any or all data in the data storage device, such as... Figure 3 As shown.

[0082] Upon receiving or acquiring various data, the confidence level determination system 350 can determine a confidence level indicating the confidence that the mobile machinery 101 is capable of performing a desired task or operation, and generate a confidence level value indicating the confidence level. As discussed above, the confidence level value can be represented as an output in various ways. In some examples, the confidence level value represents the expected accuracy or error of the mobile machinery 101 in performing the task. For example, an 80% confidence level value can indicate that the machinery will perform the desired task 80% of the time. In the example of a targeted spraying task, this can translate to applying material to weeds 80% of the time, or applying material to 80% of the detected weeds. Various factors and characteristics indicated or otherwise represented in the various data can affect the confidence level determined by the confidence level determination system 350. For example, characteristics and factors affecting the reliability or accuracy of sensor signals or characteristics indicated by sensor signals, the operating characteristics and mechanical settings of the mobile machinery 101, the characteristics of the environment in which the mobile machinery 101 is operating, and various other factors and characteristics. The confidence logic system 360 receives or acquires various data and determines a confidence level of confidence in the ability of the mobile machinery 101 to perform a desired task based on the various data.

[0083] For example, in an example where the desired task is a target substance application operation performed by a spraying system (such as spraying system 102), the confidence level indicates the confidence that the spraying system can apply the substance to a target location on the field (such as applying a herbicide to the location of detected weeds on the field). The ability of a spraying system to perform a target substance application operation can be affected by a variety of factors and characteristics. For example, the spraying system and its sensors must be able to accurately detect and generate sensor signals indicating the location of weeds on the field. The accuracy or reliability of the sensor signals can be affected by many factors and characteristics. For example, the characteristics of the environment in which the spraying system is operating, such as weather and field characteristics, sensor characteristics, and the operating characteristics and mechanical settings of the spraying system. For example, if the field is experiencing heavy rain or other precipitation, or if the vegetation on the field is particularly dense, the ability of sensing sensor 128 to sense and subsequently accurately detect the location of weeds may be affected. Additionally, the characteristics of the sensors may also affect the accuracy of the detected location of weeds. For example, sensor calibration may be required; sensor operating parameters may be suboptimal (such as their position or orientation (shutter speed, zoom, focal plane, etc. in the case of sensing sensor 128)); sensor signal strength may be insufficient (such as the signal strength of the position sensor 238 communicating with a satellite); and various other sensor characteristics may also affect the accuracy of weed location detection in the field. Furthermore, characteristics of the spraying system (such as operating characteristics and mechanical settings) may influence the accuracy of weed location detection in the field. For example, if the spraying system travels at excessively high speeds, the sensor's ability to detect weed location in the field may be adversely affected. These are merely examples.

[0084] The ability of a spraying system to perform the application of a target substance can also be affected by the characteristics of the environment in which the system is operating. For example, weather conditions in a field can affect the system's ability to apply a substance to a specific location on the field. For instance, if the field is experiencing relatively high wind speeds, the spray may be carried away by the wind, preventing the substance from being applied to the desired location. This is just one example; various characteristics of the environment in which mobile machinery operates can affect its ability to perform its intended task.

[0085] The ability of a spraying system to perform the application of a target substance can also be affected by the characteristics of the spraying system, such as its operating characteristics and mechanical settings. For example, the operating characteristics or settings of a spraying subsystem may affect the system's ability to apply the substance to the desired location on the field. For instance, the operating pressure or speed of the pump may be suboptimal, the position or orientation of the nozzles may prevent them from applying the substance to the desired location, and nozzles, valves, or conduits may be completely or partially blocked, thus affecting the flow or application characteristics of the substance. In other examples, the spray boom on the spraying system may be too far above the surface of the field, such that the nozzles mounted on the boom cannot ideally apply the substance to a specific location on the field. Furthermore, the speed of the spraying system 102 may be too high, such that the substance cannot be sprayed precisely to a specific location on the field. These are merely examples; various mechanical characteristics, including various operating characteristics and mechanical settings, can affect the ability of mobile machinery to perform a desired task.

[0086] It should be understood that the confidence level determination system 350 can determine confidence levels and generate corresponding confidence level values ​​for any number of desired tasks or operations to be performed by any number of different types of machinery. Furthermore, the confidence level determination system 350 can determine confidence levels and generate corresponding confidence level values ​​for multiple desired tasks or operations performed by machinery during the same agricultural operation. For example, in the example of a spraying system (such as spraying system 102), the confidence level determination system 350 can determine corresponding confidence levels and generate corresponding confidence level values ​​for multiple desired tasks or operations of the spraying system, such as corresponding confidence levels and values ​​for material application operations and corresponding confidence levels and values ​​for boom height operations, where the control system attempts to maintain the boom at a desired height above the surface based on various inputs, such as sensor data indicating the topography of the field or topographic values ​​provided by a topographic map of the field.

[0087] It is important to note that these are merely examples. The techniques, methods, and data used to determine confidence levels and generate confidence level values ​​can vary depending on many variables. These include, but are not limited to, the type of operation, the type of machinery, the type of sensor, the type of vegetation (e.g., multiple crops, multiple weeds, etc.), the multiple characteristics being detected, the controlled conditions, and many other variables.

[0088] Based on the generated confidence level values, the confidence system 230 can generate various action signals(s) via the action signal generator 356 for, for example, controlling the operation of machinery (such as the spraying system 102), or providing displays, suggestions, or other indications (e.g., alarms) to the operator 262 on the operator interface 260 or to the remote user 270 on the user interface 268. For example, based on the generated confidence level values, the confidence system 230 can generate action signals to switch between target material application operations and spread material application operations. In another example, based on the generated confidence level values, displays, suggestions, or other indications can be provided to the operator 262 on the operator interface 260 or to the remote user 270 on the user interface 268, such as displays, suggestions, or other indications generated by the display generator 354. Examples include displays indicating confidence level values, suggestions for adjusting machinery operation, etc. In another example, the confidence system 230 may provide operator- or user-actuable elements on an interface display that, when actuated, alter the operation of the machinery, such as changing the operation of the spraying system 102 between a target material application operation and a spread material application operation. In yet another example, based on displays, suggestions, or other indications generated by the confidence system 230, the operator or user may manually (e.g., through user input on the interface) adjust the operation of the machinery. These are merely examples; the confidence system 230 may generate any number of various action signals for controlling any number of operations of any number of machines, including providing any number of displays, suggestions, or other indications on various interfaces.

[0089] The confidence level tracking logic system 361 can track and detect changes in confidence level values, which can indicate various characteristics (e.g., sensor degradation, problems at the work site, etc.). Based on changes in confidence level values, the confidence system 230 can generate various action signals via the action signal generator 356 for, for example, controlling the operation of machinery (such as the spraying system 102), or providing displays, suggestions, or other indications (e.g., alarms). For example, based on detected changes in confidence level values, the confidence system 230 can provide an indication to the operator or user to change the material application operation, such as switching between target material application and spread application. For example, a previously generated confidence level value high enough to perform the target material application operation may have caused the confidence system, operator, or user to switch to or maintain the target material application operation, and based on changes in confidence level values ​​(such as a confidence level value dropping below a threshold confidence level value), the confidence system 230 can suggest to the operator or user that the confidence level value is now too low for the utilization of the target material application.

[0090] The confidence level tracking logic system 361 can track and (e.g., in a data storage device) the generated confidence level values ​​across operations, across work sites, across single events at work sites, across multiple seasons, and across various other time spans. The confidence level map generator 357 can generate a confidence level map based on the tracked confidence level values, indicating the confidence level values ​​generated across work sites (e.g., various confidence level values ​​at different geographical locations on the work site). The confidence level map generator 357 can also indicate the confidence level values ​​at different locations on the work site (e.g., locations with relatively low confidence level values ​​(e.g., relative to a threshold, or relative to the average / median of confidence values ​​across work sites, or relative to historical confidence values)). The confidence graphs generated by the confidence graph generator 357 can be displayed on the operator interface 260 for the operator 262 or on the user interface 268 for the remote user 270, for the control of the mobile machinery 101, or stored in a data storage device (such as data storage device 208 or 302) for reference. These are merely examples; the confidence graph generator 357 can generate any number of different graphs indicating confidence level value characteristics (including, but not limited to, various statistical summary characteristics indicating confidence level values ​​across work sites, across operations, across multiple work sites or operations, etc.).

[0091] The confidence problem logic system 362 can determine one or more problems that adversely affect the confidence level based on various data, such as data provided by the data capture logic system 352, and confidence levels or confidence level values. For example, identifying a characteristic as a confidence problem causes the confidence level value to fail to meet a confidence level threshold. For example, the confidence problem logic system can identify one or more environmental characteristics, mechanical characteristics, or sensor characteristics as confidence problems. As an example, the confidence problem logic system 362 can determine that precipitation in a field adversely affects the confidence level, the speed of machinery adversely affects the confidence level, or the current orientation of a sensing sensor adversely affects the confidence level. These are merely examples. The confidence problem logic system 362 can generate a confidence problem output indicating the one or more identified confidence problems. Based on the confidence problem output, various action signals can be generated by the action signal generator 356, such as control signals adjusting the speed of machinery or adjusting the position or orientation of a sensing sensor to adjust the sensor's line of sight, and action signals providing an indication of the one or more identified confidence problems to an operator or user.

[0092] like Figure 4As shown, the confidence system 230 may also include a threshold logic system 358. The threshold logic system 358 is configured to compare a generated confidence level value with a confidence level threshold and generate a threshold output indicating the difference between the comparison or the generated confidence level value and the confidence level threshold. The confidence level threshold may be automatically generated by the confidence system 230 (such as by the machine learning logic system 359), input by an operator or user, or generated in various other ways. In one example, based on the threshold output, the confidence system 230 may generate various action signals via an action signal generator 356 for, for example, controlling the operation of machinery (such as the spraying system 102), or providing displays, suggestions, or other indications (such as alarms). As an example, the confidence level value may be output as a percentage confidence level value (e.g., 0% to 100%), and the confidence level threshold may be a corresponding percentage, such as 75%. In some examples, the confidence level threshold may include a range, such as an acceptable range of deviation. In the example of the percentage confidence level value above, the confidence level threshold can be 75% ± 2%, allowing the generated confidence level value to deviate by up to 2%. For example, it must fall below 73% to be outside the confidence level threshold. The threshold logic system 358 compares the generated confidence level value with the confidence level threshold, and when it determines that the generated confidence level value does not meet the threshold, the confidence system 230 can generate various action signals. For example, an action signal for automatically controlling the spraying system 102 to switch between target material application and spreading application. In another example, the confidence system 230 can automatically provide definitive instructions (such as alarms, displays, suggestions) to the operator or user on the interface. Additionally, it should be noted that the confidence level threshold can be dynamically adjusted by the confidence system 230 or the operator or user throughout the operation of the machinery.

[0093] Additionally, confidence level threshold values ​​can be generated based on a variety of considerations. These include manufacturer recommendations, supplier recommendations, service provider recommendations, metric priorities selected by the operator or user, and many other factors. For example, in the example of metric priorities, the operator or user can input the desired volume of material to be used throughout the field, and the threshold logic system 358 can determine the confidence level threshold for the entire field to optimize the volume of material used.

[0094] As shown in the figure, the confidence determination system 230 may further include a display generator 354. The display generator 354 can generate any number of displays, suggestions, or other indications (e.g., alarms) (these displays, suggestions, or other indications can be provided to the operator or user on an interface mechanism via an action signal generator 356), such as action signals for a control interface, such as an operator interface 260 or user interface 268 displaying the generated displays, suggestions, or other indications, examples of which are shown below. Figure 6 As described herein. The displays, suggestions, or other indications generated by the display generator 354 may be based on a determined confidence level or a generated confidence level value. For example, the display generator 354 may generate one or more current operation indicators indicating one or more desired tasks or operations being performed or to be performed by machinery; one or more suggestion indicators, such as one or more suggestion indicators indicating a suggestion to change the operation of mobile machinery; confidence level value indicators indicating one or more confidence levels; confidence level value threshold indicators indicating one or more confidence level thresholds; characteristic indicators indicating one or more characteristics (such as environmental characteristics, mechanical characteristics, or sensor characteristics); confidence problem indicators indicating one or more confidence problems; one or more actuable elements; one or more graphical displays; one or more image or video displays, such as video feeds; and various other items. In some examples, the displays generated by the display generator 354 may include multiple different display elements, including any combination of the display elements described herein.

[0095] like Figure 4 As shown, the confidence determination system 230 may further include a machine learning logic system 359. The machine learning logic system 359 may include a machine learning model, which may include (multiple) 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, LSTM and recurrent neural networks (RNNS), convolutional neural networks (CNNs), MCMC, random forests, reinforcement learning, or reward-based machine learning, etc.

[0096] The machine learning logic system 359 can improve the determination of confidence levels and the generation of confidence level values, such as by improving the identification of characteristics and conditions affecting the ability of a mobile machine to perform a desired task, and by learning the relationships between factors, conditions, or characteristics affecting the ability of the mobile machine 101 to perform a desired task or operation. The machine learning logic system 359 can also utilize closed-loop learning algorithms, such as one or more forms of supervised machine learning.

[0097] Figure 5 It is shown Figure 4 The flowchart shows an example of the operation of the confidence system 230. Figure 5 The operation shown is Figure 4 The system shown is an example of its operation in determining a confidence level in the ability of a mobile machine to perform a desired task and generating a confidence level value indicating the determined confidence level. It should be understood that this operation can be performed at any time or point in the entire operation of the mobile machine, or even if the operation of the mobile machine is not currently being performed. Furthermore, although the operation will be described based on a spraying system 102 performing agricultural spraying operations on a field, it should be understood that other machines performing various other mechanical operations with a confidence system 230 can also be used.

[0098] The initial assumption is that sprayer 102 is operational, as indicated by box 402. For example, operator(s) 262 or remote user(s) 270 may provide initial mechanical settings for the operation of spraying system 102, such as material application operations (e.g., broadcast application, targeted material application, etc.) and various other mechanical settings. The operator or user may manually input these settings based on their prior experience and knowledge. Initial settings may also be performed automatically by spraying system 102 itself. In another example, prior operating settings (e.g., settings from the previous year) or estimated settings may be downloaded from data storage devices(s). Initial mechanical settings may be input in various other ways, including but not limited to via touchscreen or some other interface mechanism (e.g., input mechanism).

[0099] Processing takes place at box 404, where the data acquisition logic system 352 of the confidence system 230 acquires various data, such as data related to spraying operations performed by the spraying system 102 on an agricultural surface. In one example, the data acquisition logic system acquires data generated by sensors such as sensor 210 or sensor 304 (as indicated in box 405), data obtained from data storage devices such as data storage device 208 or data storage device 302 (as indicated in box 406), or data obtained from other sources (as indicated in box 407). Other sources may include external sources (such as external weather stations) and data input by the operator or user. The data acquired from the sensors at box 405 may include sensor data indicating various characteristics of the environment of the machinery (such as characteristics of the field), data indicating various characteristics of the machinery (such as operating characteristics or machine settings), data indicating various characteristics of the sensors, and various other data (e.g., characteristics of the agricultural surface). For example, in the scenario of a spraying operation, sensor data may indicate characteristics related to weeds on the agricultural surface, such as type, quantity, density, location, etc. This is just an example; various other sensor data can be accessed at box 405.

[0100] Data obtained from the data storage devices(s) at box 406 may include data input by the operator or user, historical data, stored sensor data, environmental data, system data, and various other data, including but not limited to data input by the operator or user, historical data, stored sensor data, environmental data, system data, and various other data. Figure 3 The data described in the text.

[0101] Once the data is accessed (or otherwise obtained) at box 404, processing takes place at box 408, where confidence system 230 determines a confidence level regarding the ability of spraying system 102 to perform a target substance application operation, in which the substance is applied to the location of detected weeds in the field, and generates a confidence level value indicating the determined confidence level. The determination of the confidence level is based on the data accessed (or otherwise obtained) at box 404.

[0102] In one example, once the confidence level determination and confidence level value generation are completed at box 408, processing takes place at box 410, where action signal generator 356 generates one or more action signals. In one example, the action signals can be used to control the operation of one or more machines (such as controlling one or more controllable subsystems 202 of agricultural spraying system 102, or controllable subsystem 308 of vehicle 300 (as indicated in box 412)) to provide displays, suggestions, or other indications (e.g., alarms) on an interface (such as operator interface 260 or user interface 268 (as indicated in box 414)) or otherwise (as indicated in box 416). For example, control signals can be generated and provided to controllable subsystem 202 of spraying system 102. For example, control signals can be provided to spraying subsystem 214 to control one or more operating characteristics or mechanical settings of the spraying subsystem, thereby switching between target material application and spread material application, such as actuating or deactivating one or more nozzles 112. In another example, displays, suggestions, or other instructions may be provided to the interface to be presented to an operator or user (such as to operator 262 on operator interface 260 or to remote user 270 on user interface 268), including displays generated by display generator 354. Examples include displays indicating confidence level values, suggestions for changing the operating characteristics or mechanical settings of spraying system 102 (such as suggestions for switching between target material application and spread material application), and various other instructions.

[0103] In another example, once the confidence level has been determined and the confidence level value generated at box 408, the process continues at box 420, where the confidence logic system 358 compares the confidence level value with a threshold confidence level value. The threshold confidence level value can be set by an operator or user, can be automatically set by the confidence system 230, or can be set in other ways. The process proceeds to box 422, where, based on the comparison, it is determined whether the generated confidence level value meets the confidence level threshold. If, at box 422, it is determined that the generated confidence level value does not meet the confidence level threshold, the process continues at box 410, where the action signal generator 356 generates one or more action signals.

[0104] If at box 422 it is determined that the generated confidence level value does indeed meet the confidence level threshold, then processing continues at box 430, where it is determined whether the operation is complete. Alternatively, if at box 422 it is determined that the generated confidence level value does indeed meet the confidence level threshold, then processing takes place at box 410, where action signal generator 356 generates one or more action signals, such as action signals that provide the generated confidence level value, the confidence level threshold, or both on the interface.

[0105] If at box 430 it is determined that the operation has not yet completed, processing proceeds at box 404, where data can be accessed or otherwise obtained. If at box 430 it is determined that the operation has completed, processing ends.

[0106] Figure 6 This is a block diagram illustrating an example of an interface display that can be generated and provided by the confidence system 230, such as providing it to operator 262 on operator interface 262 or to remote user 270 on user interface 268. Figure 6 As shown, the interface display 450 includes a confidence level indicator 452, a confidence level threshold indicator 454, actuable elements 456 and 458, a current operation indicator 460, a suggestion indicator 462, a confidence level problem indicator, an environmental characteristic indicator 464, a mechanical characteristic indicator 466, a sensor characteristic indicator 468, a graph display 470, a video feed 472, an actuable element 473, and may also include other items 474. The confidence level indicator 452 itself includes a confidence level value indicator 453, which is illustratively shown as a percentage, although this is not mandatory. The confidence level threshold indicator 454 itself includes a confidence level value threshold indicator 455, which is illustratively shown as a percentage, although this is not mandatory, although generally confidence level values ​​and confidence level value thresholds will correspond to each other, as they will generally be represented similarly. The graph display 470 (which may include a confidence graph generated by the confidence graph generator 357) itself may include a mechanical indicator 474, a travel path indicator 476, a expected travel path indicator 478, a confidence level indicator 480, and a compass pointer 482. It should be noted that the graph display 470 may also include more or fewer items.

[0107] Confidence level indicator 452 displays the confidence level value generated by confidence system 230, as indicated by confidence level value indicator 453. Although illustratively shown as a percentage, it should be noted that confidence level values ​​can be represented in various ways, such as numbers, percentages (e.g., 0% to 100%) or scalar values, grayscale or scaled values ​​(e.g., AF, "high, medium, low", 1-10, etc.), suggestions (e.g., "change operation", "cannot be detected", "slow", etc.), and various other representations. For example, the form of representation can be selected by the operator or user based on operator or user preferences or otherwise customized. Additionally, confidence level indicator 452 displays a real-time or near-real-time confidence level value, and confidence level value indicator 453 can change dynamically throughout the operation of mobile machinery 101.

[0108] Confidence level threshold indicator 454 displays the confidence level threshold, as indicated by confidence level value threshold indicator 455. Although illustratively shown as a percentage, it should be noted that confidence level value thresholds can be represented in various ways, such as numbers, percentages (e.g., 0% to 100%) or scalar values, grayscale or scaled values ​​(e.g., AF, "High, Medium, Low", 1-10, etc.), suggestions (e.g., "Change Operation", "Cannot Detect", "Slow", etc.), and various other representations, although in general, confidence level values ​​and confidence level thresholds will be represented similarly. Confidence level values ​​are set by the confidence system 230 or by an operator or user, although confidence level value thresholds can be set in various other ways.

[0109] Figure 6 The interface display is also shown to include actuable elements 456 and 458, which can be actuated by an operator or user to adjust the confidence level threshold. Although in other examples, the confidence level threshold indication 454 itself can be actuated by an operator or user, such that the actuation surface is a numeric keypad or keypad or other input element to allow adjustment of the confidence level threshold.

[0110] The interface display 450 may also include a current operation instruction 460 and a suggestion instruction 462. The current operation instruction 460 displays an instruction on the currently desired task or operation of the mobile machinery 101, such as an instruction that the sprayer 102 is about to perform or is currently performing target spraying application. The suggestion instruction 462 displays a suggested instruction based on a confidence level (or a comparison of a confidence level value and a confidence level threshold). For example, the suggestion instruction 462 may include an instruction to switch to a broadcast spraying application. In some examples, the suggestion instruction 462 may be an actuable mechanism that can be actuated by an operator or user to, for example, implement the suggestion. For example, switching the mobile machinery 101 between current and suggested operations, such as switching the sprayer 102 between target application and broadcast application by actuating or deactivating one or more of the nozzles 112.

[0111] As shown in the figure, the interface display 450 also includes a confidence level issue indicator 463. The confidence level issue indicator 463 displays indications of one or more issues that adversely affect the confidence level, such as one or more characteristics that adversely affect the confidence level as determined by the confidence level issue logic system 362. Figure 6 As shown, the confidence problem indicator 463 can display a representation of the confidence problem, such as a word. Examples include "machine speed too high," "calibrate sensor," "sensor signal strength too low," and "rain." It should be noted that confidence problems can be represented in various ways, including, for example, numerical representations, symbols, lights, tactile or auditory outputs.

[0112] It should be noted that the current operation instruction 460 may include a list of currently desired tasks or operations (such as tasks or operations of separate controllable subsystems) of the mobile machinery 101, and the confidence system 230 may determine a corresponding confidence level and generate a corresponding confidence level value for each of the desired tasks or operations in the list, which may be displayed as part of the confidence level instruction 452. Similarly, each specific confidence level value may have a corresponding confidence level value threshold, which may be set in various ways, such as automatically set by the confidence system 230 or set by the operator or user. Each specific confidence level value threshold may be displayed as part of the confidence level threshold instruction 454. Furthermore, the confidence system 230 may display individual recommendations corresponding to each of the specific confidence levels, each of which may be displayed as part of the recommendation instruction 462, such as an ordered list of recommendations. Additionally, the confidence system 230 can display individual confidence questions corresponding to each of a particular confidence level, each of which can be displayed as part of the confidence question indication 463, such as an ordered list of confidence questions.

[0113] Figure 6 The interface display 450 is also shown to include various characteristic indicators, including environmental characteristic indicator 464, mechanical characteristic indicator 466, and sensor characteristic indicator 468. Environmental characteristic indicator 464 may include indications of various characteristics of the environment in which the mobile machinery 101 is operating, such as weather characteristics, field characteristics, and any number of other characteristics of the environment in which the mobile machinery 101 is operating. As shown, as some examples, environmental characteristic indicator 464 indicates current wind direction and speed, soil moisture, and current average weed height, although environmental characteristic indicator 464 may include any other number of indications of the characteristics of the environment in which the mobile machinery 101 is operating.

[0114] Mechanical characteristic indicator 466 may include indications of various characteristics of the mobile machinery 101, such as operating characteristics and mechanical settings, as well as any number of other mechanical characteristics. As shown, as examples, mechanical characteristic indicator 466 indicates the current speed of the mobile machinery 101, the current boom height, such as the current height of the boom above the surface of the field, although mechanical characteristic indicator 466 may include any number of other mechanical characteristic indications.

[0115] Sensor characteristic indication 468 may include indications of various characteristics of sensors of the mobile machinery 101 or vehicle 300. As shown, as examples, sensor characteristic indication 468 indicates the current signal strength of a sensor (such as position sensor 238), the current shutter speed setting (such as the shutter speed setting of sensing sensors 128, 556, or 609), and the current resolution setting (such as the resolution setting of sensing sensors 128, 556, or 609), although sensor characteristic indication 468 may include any number of other indications of sensor characteristics.

[0116] As shown, the interface display 450 may also include a graph display 470. The graph display 470 (which may include a confidence graph generated by the confidence graph generator 357) includes a machine indicator 476, a travel path indicator 478, a expected travel path indicator 480, a confidence level indicator 482, and a compass pointer 484. The machine indicator 476 provides a representation of the heading and position of the mobile machinery 101 on the agricultural surface (such as a field) on which it is operating. For example, as shown in the graph display 470, the mobile machinery 101 is in the southwest corner of the field and is currently moving north.

[0117] The travel path indicator 478 provides a representation of the path that the mobile machinery 101 has traveled along the field so far, while the expected travel path indicator 480 provides a representation of the expected route (such as a route commanded by the operator or user, or a route generated by the control system 204). Figure 6 As shown, the travel path indicator 478 is represented by a solid line, while the expected travel path indicator 480 is represented by a dashed line, in order to provide the operator or user with an observable difference between the two, although this is not mandatory. The travel path indicator 478 and the expected travel path indicator 480 can be represented in any number of ways and can be distinguished in any number of ways, such as different colors, different line designs, and various other stylistic differences. In some examples, in the case where the mobile machinery 101 deviates from the commanded or recommended route, this deviation can be indicated by simultaneously displaying both the travel path indicator 478 and the expected travel path indicator 480 in the area of ​​the field where the mobile machinery 101 has deviated from the commanded or recommended route.

[0118] Figure 6The diagram also shows that display 470 includes a confidence level indicator 482, which is illustratively shown as a marker placed at various locations along the travel path of the mobile machinery 101 to indicate the confidence level value at various locations throughout the work area. In some examples, the confidence level indicator 482 indicates areas where the confidence level value of the field does not meet a confidence level threshold. In other examples, the confidence level indicator 482 may indicate areas where the operation of the mobile machinery 101 in the field is switched, such as areas where the operation of the sprayer 102 in the field is switched from target material application operation to spread material application operation. In this way, areas of the field can be stored and referenced later, such as when analyzing yield values ​​of different areas of the field. These are merely examples, and indicator 482 may indicate various characteristics or conditions. Display 470 also includes a compass pointer 484 to indicate the setting of fields and items on display 470 or fields relative to north, south, east, and west.

[0119] As shown, the interface display 450 may also include a video feed 472. In one example, the video feed 472 shows a real-time or near-real-time video feed of an area of ​​the field surrounding the mobile machinery 101 (such as the area in front of the mobile machinery 101 in the field). In some examples, the video feed 472 may be generated based on signals received from sensing sensors 128, 565, or 609. In other examples, the video feed 472 may be a dynamic still frame display showing, for example, a recent image captured by the sensing sensors, or an image corresponding to a confidence level value indication 454 currently displayed on the interface display 450. As shown, the video feed 472 may display images or videos depicting crops 486 and weeds 488 in the field. In some examples, the interface display 450 may include an actuable mechanism 473 that can be actuated by an operator or user to adjust various settings of the sensing sensors that generate the video feed 472. For example, zoom, resolution, shutter speed, flash, and various other settings. Figure 6 As shown, the actuable element 473 can be actuated by an operator or user to adjust the viewpoint of the sensing sensor that generates the video feed 472, the adjustment of which can be represented accordingly by the image displayed on the video feed 472. As shown, the actuable element 473 is actuable to adjust the viewpoint of the sensing sensor to "up," "down," "left," or "right," although the viewpoint of the sensing sensor can be adjusted in various other directions. Actuation of the actuable element 473 by the user or operator can result in the generation of one or more control signals by the control system 204, such as control signals provided to the actuator corresponding to the sensing sensor that generates the video feed 472 to adjust the position or orientation of the sensing sensor 472, thereby adjusting the viewpoint of the sensing sensor.

[0120] The interface display 450 may include any number of other items (as indicated in 474), such as various other display elements, indicators, and actuable mechanisms.

[0121] Although Figure 6 The diagram illustrates the specific placement of the display elements; however, it should be understood that the display elements can be arranged in any number and manner. Additionally, although... Figure 6 Specific display elements are shown, but it should be noted that more or fewer elements can be displayed on interface display 450 or any number of other interface displays. Furthermore, although... Figure 6 Various display elements of a certain size are shown, but it should be understood that display elements can be of any size, and in some examples, the size of the display elements can be adjusted by the operator or user. Furthermore, it should be understood that various display elements can be stylized in various ways, such as various fonts, various colors, and any other number of stylizations.

[0122] As discussed earlier, while some of the examples described herein are in the context of specific machinery (e.g., spraying system 102), it should be understood that various systems and methods are applicable and can be used in combination with any number of machines. Figures 7 to 10 Examples are shown of other machines to which the various systems and methods described herein may be applied, including machinery 101. Figures 7 to 10 Some other machines are shown, but it should be noted that this is not an exhaustive list of machines to which the various systems and methods described herein are applicable. It should be noted that although... Figures 7 to 10 The examples in this paper are set in scenarios involving specific agricultural machinery (such as combine harvesters, planters, or tillage equipment). However, it should be noted that the various systems and methods described herein are applicable to and can be used in conjunction with any number of machines, including any number of agricultural, forestry, construction, or lawn management machines. Additionally, although... Figures 7 to 10 The examples in this paper are set in scenarios involving specific sensors or sensor systems and specific control devices; however, it will be noted that the various systems and methods described herein are applicable to any number of sensors or sensor systems and any number of control devices and can be used in conjunction with them. Furthermore, although... Figures 7 to 10 The examples described herein are set in scenarios involving specific operations, such as harvesting or planting. However, it should be understood that the systems and methods described herein are applicable to and can be used in combination with any number of operations performed by any number of different types of machinery. Furthermore, it should be understood that the confidence system 230 (of control system 204) is applicable to and can be used in combination with any number of different types of machinery performing any number of multiple operations.

[0123] Figure 7 The machine 101 shown includes an agricultural harvester 501 (in Figure 7 The example shown is a combine harvester, although various other harvesters are also envisioned. Figure 7 As can be seen from the illustration, the agricultural harvester 501 illustratively includes an operator's cab 503, which may have various different interface mechanisms for controlling the agricultural harvester 501 or displaying various information. The operator's cab 503 may include operator interface mechanisms that allow the operator to control and manipulate the agricultural harvester 501. The operator interface mechanisms in the operator's cab 503 can be any of a variety of different types of mechanisms. For example, they may include input mechanisms such as a steering wheel, control lever, joystick, button, pedal, switch, etc. Furthermore, the operator's cab 503 may include one or more operator interface display devices (such as one or more monitors), or mobile devices supported within the operator's cab 503. In this case, the operator interface mechanisms may also include user-actuable elements displayed on the display devices, such as icons, links, buttons, etc. The operator interface mechanisms may include one or more microphones, providing voice recognition on the agricultural harvester 501. They may also include audio interface mechanisms (e.g., speakers), one or more tactile interface mechanisms, or a variety of other operator interface mechanisms. The operator interface mechanisms may also include other output mechanisms, such as dials, gauges, instrument outputs, lights, audible or visual alarms, or tactile outputs, etc.

[0124] The agricultural harvester 501 includes a set of front-end equipment forming a cutting platform 502, which includes a header 504 having a cutter (generally indicated as 506). It may also include a feed chamber 508, a feed accelerator 509, and a thresher (generally indicated as 511). The thresher 511 schematically includes a threshing drum 512 and a set of concave plates 114. Further, the agricultural harvester 501 may include a separator 516, which includes a separator drum. The agricultural harvester 501 may include a cleaning subsystem (or cleaning chamber) 518, which itself may include a cleaning fan 520, a chaff screen 522, and a sieve 524. The material handling subsystem in the agricultural harvester 501 may include (in addition to the feed chamber 508 and feed accelerator 509) a discharge threshing drum 526, a tailings elevator 528, a clean grain elevator 530 (which moves the clean grain into the clean grain tank 532), and an unloading auger conveyor 534 and nozzles 536. The harvester 501 may also include a residue subsystem 538, which may include a shredder 540 and a spreader 542. The harvester 501 may also have a propulsion subsystem including an engine (or other power source) driving ground engagement elements 544 (such as wheels, tracks, etc.). It should be noted that the harvester 501 may also have more than one of any of the subsystems mentioned above (e.g., left and right cleaning chambers, separators, etc.).

[0125] like Figure 7 As shown, the header 504 has a main frame 507 and an attachment frame 510. The header 504 is attached to the feed chamber 508 via an attachment mechanism on the attachment frame 510, which cooperates with an attachment mechanism on the feed chamber 508. The main frame 507 supports the cutter 506 and the reel 505 and is movable relative to the attachment frame 510, such as by an actuator (not shown). Additionally, the attachment frame 510 is movable by operation of the actuator 549 to controllably adjust the position of the front-end assembly 102 relative to the harvester 101 on a surface (such as field 110) in the direction indicated by arrow 546, and thus controllably adjust the position of the header 504 above the surface. In one example, the main frame 507 and the attachment frame 510 can be raised and lowered together to set the height of the cutter 506 above the surface on which the harvester 501 travels. In another example, the main frame 507 may tilt relative to the attachment frame 510 to adjust the tilt angle of the crop on the mating surface of the cutter 506. Furthermore, in one example, the main frame 507 may rotate or otherwise move relative to the attachment frame 510 to improve ground following performance. The movement of the main frame 507 and the attachment frame 510 may be driven by actuators (such as hydraulic, pneumatic, mechanical, electromechanical, or electric actuators, and various other actuators) based on operator input or automatic input (such as control signals).

[0126] In operation, and as an overview, the height of the header 504 is set, and the harvester 501 moves schematically across the field in the direction indicated by arrow 546. As the header moves, the header 504 engages the crop to be harvested and picks it up toward the cutter 506. After the crop is cut, it can be engaged by the reel 505, which moves the crop to the feed system (such as a feed rail). The feed system moves the crop to the center of the header 504 and then toward the feed accelerator 509 via the intermediate feed system in the feed chamber 508, which accelerates the crop into the thresher 511. The crop is then threshed by the drum 512, which rotates the crop against the concave plate 514. The threshed crop is moved by the separator drum in the separator 516, where some of the residue is moved toward the residue subsystem by the discharge threshing drum 526. It can be chopped by the residue shredder 540 and spread on the field by the spreader 542. In other implementations, the residue is simply left in the pile instead of being chopped up and scattered.

[0127] The grain falls into the cleaning chamber (or cleaning subsystem) 518. A husk sieve 522 separates some of the larger pieces from the grain, and a sieve 524 separates some of the finer pieces from the clean grain. The clean grain falls onto a screw conveyor in a clean grain elevator 530, which moves the clean grain upwards and stores it in a clean grain tank 532. Residue can be removed from the cleaning chamber 518 by an airflow generated by a cleaning fan 520. This residue can also be moved rearwards in the harvester 501 towards a residue handling subsystem 538.

[0128] Tailings can be transferred back to thresher 510 via tailings elevator 528, where they can be re-threshed. Alternatively, tailings can be transferred to a separate re-threshing mechanism (also using tailings elevator or another conveyor), where they are also re-threshed.

[0129] Figure 7It is also shown that, in one example, harvester 501 may include various sensors 580, some of which are schematically illustrated. For example, harvester 501 may include one or more ground speed sensors 547, one or more separator loss sensors 548, a grain cleaning camera 550, one or more grain cleaning chamber loss sensors 552, and one or more sensing sensors 556 (such as cameras and image processing systems). Ground speed sensor 547 schematically senses the travel speed of harvester 501 on the ground. This can be achieved by sensing the rotational speed of ground engagement element 544, drive shaft, axle, or various other components. Travel speed may also be sensed by a positioning system, such as a global positioning system (GPS), dead reckoning system, LORAN system, or various other systems or sensors that provide an indication of travel speed. Sensing sensor 556 is schematically mounted to the front, side, or rear of harvester 501 (relative to the direction of travel 546) and senses the field (and its characteristics) in front of, to the side, or behind the harvester (relative to the direction of travel) and generates sensor signals (e.g., images) indicating these characteristics. For example, sensing sensor 556 can generate sensor signals indicating the characteristics of vegetation in the field in front of or around combine harvester 501. In some examples, the viewpoint of sensor 556 can be adjusted, for example, such that sensor 556 is positioned with a viewing angle of up to 360 degrees around harvester 501. Although in Figure 7 The sensor 556 is shown at a specific location on the harvester 501, but it should be noted that the sensor 556 can be mounted at different locations on the harvester 501, and is not limited to these locations. Figure 7 The depiction shown is shown in the figure. Additionally, although only a single sensing sensor 556 is shown, it should be noted that multiple sensing systems installed at any number of locations within the harvester 501 can be used.

[0130] The grain chamber loss sensor 552 schematically provides output signals indicating the amount of grain loss on the right and left sides of the grain chamber 518. In one example, sensor 552 is an impact sensor that counts grain impacts per unit time (or per unit distance traveled) to provide an indication of grain loss in the grain chamber. The impact sensors for the left and right sides of the grain chamber can provide individual signals, or combined or aggregated signals. It should be noted that sensor 552 may also include a single sensor, rather than separate sensors for each grain chamber.

[0131] Separator loss sensor 548 provides signals indicating grain loss in the left and right separators. Sensors associated with the left and right separators can provide signals of separated grain loss or signals of combined or aggregated loss. This can also be achieved using various different types of sensors. It should be noted that separator loss sensor 548 may also include only a single sensor, rather than separate left and right sensors.

[0132] It should be understood, and as will be discussed further herein, that sensor 580 may include Figure 7 Various other sensors not schematically shown. For example, they may include a residue setting sensor configured to sense whether the harvester 501 is configured to shred residue, drop it into a pile, etc. They may include a cleaning chamber fan speed sensor configured near the fan 520 to sense the fan speed. They may include a threshing gap sensor sensing the gap between the drum 512 and the concave plate 514. They may include a threshing drum speed sensor sensing the drum speed of the drum 512. They may include a screening gap sensor sensing the size of the openings in the screening machine 522. They may include a sieve gap sensor sensing the size of the openings in the sieve 524. They may include a moisture sensor for material other than grain (MOG), configured to sense the moisture level of the material other than grain passing through the harvester 501. They may include mechanical setting sensors configured to sense various configuration settings on the harvester 501. They may also include mechanical orientation sensors, which may be any of various different types of sensors sensing the orientation of the harvester 501 or its components. These may include crop attribute sensors that can sense various types of crop attributes, such as crop type, crop moisture, and other crop properties. They may also be configured to sense crop characteristics as the crop is processed by the harvester 501. For example, they can sense the feed rate of the grain as it travels through the net grain elevator 520. They can sense the mass flow rate of the grain through the elevator 530 or provide additional output signals indicating other sensed variables. These may also include soil property sensors that can sense various types of soil properties, including but not limited to soil type, soil compaction, soil moisture, and soil structure.

[0133] Additional examples of sensor types could include, but are not limited to, various position sensors that can generate sensor signals indicating the position of harvester 501 in the field on which harvester 501 is traveling, or the position of various components of harvester 501 (such as header 504) relative to, for example, the field on which harvester 501 is traveling, or relative to other components of harvester 501. These are merely examples.

[0134] like Figure 7 As shown, the harvester 501 may also include a control system 204. The control system 204 may be on the harvester 501, or elsewhere, or distributed in different locations (e.g., remote computing system 266).

[0135] Figure 8 An example of machinery 101 including an agricultural planter 601 is shown. The planter 601 schematically includes a toolbar 602 as part of a frame 604. Figure 8 Multiple row units 606 are also shown mounted on a toolbar 602. The planter 601 can be towed behind another machine 605 (such as a tractor), which may have ground-engaging elements (e.g., wheels or tracks) driven by a propulsion system to drive the movement of the towing machine 605 and, consequently, the movement of the planter 601. It will also be noted that the towing vehicle 605 may include an operator's cab, which may have various operator interface mechanisms for controlling the mechanical planter 601 (and the towing vehicle 605).

[0136] like Figure 8 As shown, the planter 601 may also include a control system 204 and one or more sensors 607. The control system 204 may be on the tractor 605 or the planter 601, or elsewhere, or distributed in different locations (e.g., a remote computing system 266). The sensors 607 may include any number of sensors configured to detect any number of characteristics. The sensors 607 may be on the tractor 605 or the planter 601. Figure 8 In the example shown, sensor 607 may include one or more sensing sensors 609 (such as cameras and image processing systems). Sensing sensors 609 are mounted to the front, side, or rear of planter 601 (relative to the direction of travel 628) and schematically sense the field (and its characteristics) in front of, to the side, or rear of the planter (relative to the direction of travel), generating sensor signals (such as images) indicative of these characteristics. In some examples, the viewpoint of sensing sensor 609 may be adjusted, for example, such that sensor 609 is positioned with a viewing angle of up to 360 degrees around planter 601.

[0137] Although Figure 8The image shows the sensor 609 at a specific location (mounted on toolbar 602), but it should be noted that the sensor 609 can be mounted at different locations on the planter 601 or the tractor 605, and is not limited to these locations. Figure 8 The depiction shown is shown in the figure. Additionally, although only a single sensing sensor 609 is shown, it should be noted that multiple sensing sensors can be used and can be installed in any number of locations within the planter 601 or the traction vehicle 605.

[0138] Figure 9 This is a side view showing an example of the output unit 606 in more detail. Figure 9 Each row unit 606 is shown schematically having a frame 608. The frame 608 is schematically connected to the toolbar 602 via a linkage generally shown as 610. The linkage 610 is schematically mounted to the toolbar 602 such that it can move up and down (relative to the toolbar 602).

[0139] Row unit 606 also schematically includes a seed hopper 612 for storing seeds. Seeds are supplied from hopper 612 to seed metering system 614, which meters the seeds and supplies the metered seeds to seed delivery system 616, which delivers the seeds from seed metering system 614 to furrows or furrows generated by row unit. In one example, seed metering system 614 uses a rotatable component (such as a disc or concave rotating component) and a pressure differential to hold the seeds on the disc and move them from the seed pool (supplied by hopper 612) to seed delivery system 616. Other types of metering devices may also be used.

[0140] The row unit 606 may also include a row cleaner 618, a furrow opener 620, a set of guide wheels 622, and a set of gathering wheels 624. It may also include an auxiliary hopper for supplying additional materials, such as fertilizer or other chemicals.

[0141] In operation, as row unit 606 moves in the direction generally indicated by arrow 628, row cleaner 618 typically cleans the row in front of furrow opener 620 to remove plant debris from previous growing seasons, and furrow opener 620 digs furrows in the soil. Gauge wheel 622 schematically controls the depth of the furrows, and seeds are metered by seed metering system 614 and delivered to the furrows by seed delivery system 616. Closing wheel 624 closes the furrows over the seeds. A downforce generator 631 may also be provided to apply downforce in a controlled manner to maintain the desired contact between the row unit and the soil.

[0142] Figure 10An example of agricultural machinery 101 including agricultural tillage machinery 649 is shown. Tillage machinery 649 may include tillage implements 650 and a tractor 651. Tillage implements 650 may include any number of tillage implements, but are schematically shown as a field tiller. Tillage implements 650 may include multiple sections, or it may include only a single section. Implements 650 may include a hitch assembly 656 at its front end 652 for attachment to the tractor 651 (e.g., a tractor). Implements 659 may include a main frame 658 attached to the hitch assembly 656. Implements 650 may also include one or more sub-frames. For example, in Figure 10 In the middle, the first subframe 660 is positioned toward the front end 652 of the machine 650, while the second subframe 662 is positioned toward the rear end 654 of the machine 650.

[0143] The frame may be supported by one or more wheels 664, 668. In this embodiment, one or more front wheels 668 support the implement 650 at its front end 652, and one or more rear wheels 664 support the rear end 654 of the implement 650. Furthermore, a first working tool 684 (shown as a disc assembly) may be connected to a first subframe 660, a second working tool 686 (shown as a ripper outrigger with sweepers) may be connected to the main frame 658, and a third working tool 688 (shown as a rake) may be connected to a second subframe 662. In other examples, the implement 650 may include more or fewer tools connected at different locations, as well as other types of tools.

[0144] like Figure 10 As shown, the agricultural tillage machinery 649 may also include a control system 204 and one or more sensors 670. The control system 204 may be on the tractor 651 or the tillage implement 650, or elsewhere, or distributed in different locations (e.g., a remote computing system 266). The sensors 670 may include any number of sensors configured to detect any number of characteristics. The sensors 670 may be on the tractor 651 or on the tillage implement 650. Figure 10In the example shown, sensor 670 may include one or more sensing sensors 659 (such as cameras and image processing systems) and sensors 672 (shown as 672-1 to 672-3). The first sensor 672-1 is connected to the first subframe 610 and configured to detect the distance between the first subframe 610 and the underlying surface. Similarly, the second sensor 672-2 is connected to the main frame 658 and configured to detect the distance between the main frame 658 and the underlying surface. Further, the third sensor 672-3 is connected to the second subframe 662 and configured to detect the distance between the second subframe 662 and the underlying surface. In some cases, the subframe may be connected to and below the main frame. Therefore, the distance between the first working tool 684 and the underlying surface of the subframe may differ from the distance between the second working tool 686 and the underlying surface. The same applies to the third working tool 688. In other examples, alternatively, or in addition to sensor 672, implement 650 may include other types of sensors (such as potentiometers) configured to generate sensor signals indicating the position of the work tool or frame relative to the ground, or other sensors configured to detect the position of wheels 664 or 668 (which may be actuable) relative to one or more of the frame. Sensor 672 may be any of a number of suitable sensors, including but not limited to ultrasonic sensors, radar sensors, lidar sensors, optical sensors, or other sensors.

[0145] The one or more sensing sensors 659 (such as cameras and image processing systems) can be mounted on implement 650 and / or towing vehicle 651, and schematically sense the field (and its characteristics) in front of, to the side of, or behind (relative to the direction of travel 646) of implement 650 and / or towing vehicle 651, and generate sensor signals, such as images, indicating these characteristics. In some examples, the viewpoint of the one or more sensing sensors 659 can be adjusted, for example, such that the sensor 659 is positioned with a viewing angle of up to 360 degrees around implement 650. Although in Figure 10 The specific location is shown, but it should be noted that the sensing sensor 659 can be mounted in different locations on the implement 650 or on the tractor 651 that pulls the implement 650, and is not limited to these locations. Figure 10 The depiction shown is shown in the figure. Furthermore, although only a single sensing sensor 659 is shown, it should be noted that multiple sensing sensors can be used and can be installed in any number of locations within the implement 650 and / or the tractor vehicle 651.

[0146] In operation, and as a general overview, as the tillage implement 650 moves in the direction generally indicated by arrow 646, one or more working tools (such as working tools 684, 686, and 688) on the tillage implement 650 engage with the field and can be set to an engagement depth within the field such that the working tools penetrate the field. The field is tilled, for example, by digging, stirring, turning, and leveling the soil, pulling the working tools across and / or through the field.

[0147] The current discussion has already mentioned processors and servers. In one embodiment, processors and servers include computer processors with associated memory and timing circuitry (not shown separately). They are functional parts of the system or device to which they belong and are actuated by and facilitate the function of other components or items in these systems.

[0148] Furthermore, numerous user interface displays have been discussed. They can take various forms and have a wide variety of user-actuable input mechanisms. For example, user-actuable input mechanisms can be text boxes, checkboxes, icons, links, drop-down menus, search boxes, etc. They can also be actuated in various ways. For example, they can be actuated using click devices (such as trackballs or mice). 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. In addition, if the screen on which they are displayed is a touch-sensitive screen, they can be actuated using touch gestures. Moreover, if the device displaying them has a voice recognition component, they can be actuated using voice commands.

[0149] Many data storage devices are also discussed. It is worth noting that they can each be divided into multiple data storage devices. For the system accessing them, all data storage devices can be local, all data storage devices can be remote, or some data storage devices can be local while others are remote. This paper considers all of these configurations.

[0150] Furthermore, the accompanying diagram shows multiple boxes, with each box representing a function. It should be noted that fewer boxes can be used, thus allowing the function to be performed by fewer components. Moreover, more boxes can be used with functions distributed across more components.

[0151] It should be noted that the above discussion has described various different systems, components, and / or logic. It should be understood that such systems, components, and / or logic can be constituted by hardware items (such as processors and associated memory, or other processing units, some of which will be described below) that perform the functions associated with those systems, components, and / or logic. Furthermore, systems, components, and / or logic can be constituted by software loaded into memory and subsequently executed by a processor, server, or other computing unit, as described below. Systems, components, and / or logic can also be constituted by different combinations of hardware, software, firmware, etc., some examples of which are described below. These are merely some examples of different structures that can be used to form the systems, components, and / or logic described above. Other structures may also be used.

[0152] It should also be noted that the confidence score can also be output to the cloud.

[0153] The current discussion has already mentioned processors and servers. In one embodiment, processors and servers include computer processors with associated memory and timing circuitry (not shown separately). They are functional parts of the system or device to which they belong and are actuated by and facilitate the function of other components or items in these systems.

[0154] Furthermore, numerous user interface displays have been discussed. They can take various forms and have a wide variety of user-actuable input mechanisms. For example, user-actuable input mechanisms can be text boxes, checkboxes, icons, links, drop-down menus, search boxes, etc. They can also be actuated in various ways. For example, they can be actuated using click devices (such as trackballs or mice). 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. In addition, if the screen on which they are displayed is a touch-sensitive screen, they can be actuated using touch gestures. Moreover, if the device displaying them has a voice recognition component, they can be actuated using voice commands.

[0155] Many data storage devices are also discussed. It is worth noting that they can each be divided into multiple data storage devices. For the system accessing them, all data storage devices can be local, all data storage devices can be remote, or some data storage devices can be local while others are remote. This paper considers all of these configurations.

[0156] Furthermore, the accompanying diagram shows multiple boxes, with each box representing a function. It should be noted that fewer boxes can be used, thus allowing the function to be performed by fewer components. Moreover, more boxes can be used with functions distributed across more components.

[0157] It should be noted that the above discussion has described various different systems, components, and / or logic. It should be understood that such systems, components, and / or logic can be constituted by hardware items (such as processors and associated memory, or other processing units, some of which will be described below) that perform the functions associated with those systems, components, and / or logic. Furthermore, systems, components, and / or logic can be constituted by software loaded into memory and subsequently executed by a processor, server, or other computing unit, as described below. Systems, components, and / or logic can also be constituted by different combinations of hardware, software, firmware, etc., some examples of which are described below. These are merely some examples of different structures that can be used to form the systems, components, and / or logic described above. Other structures may also be used.

[0158] It should also be noted that the confidence score can also be output to the cloud.

[0159] Figure 11 yes Figure 2 The machine 101 shown here communicates with components in the remote server architecture 700. 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 delivering the services. In various example embodiments, the remote server can deliver services over a wide area network (WAN), such as the Internet, using appropriate protocols. For example, remote servers can deliver applications over a WAN, and they can be accessed via a web browser or any other computing component. Figure 2 The software or components shown, along with the corresponding data, can be stored on servers at remote locations. Computing resources in a remote server environment can be consolidated at a remote data center location, or they can be distributed. Remote server infrastructure can deliver services through a shared data center, even if they appear as a single access point to the user. Therefore, the components and functions described herein can be provided from remote servers at remote locations using a remote server architecture. Alternatively, they can be provided from conventional servers, or they can be installed directly or otherwise on client devices.

[0160] exist Figure 11 In the example embodiments shown, some items are similar to Figure 2 The items shown in the diagram are similarly numbered. Figure 11Specifically, the control system 204 can be located at a remote server location 702. Thus, machinery 101 (e.g., spraying system 102, harvester 501, planter 601, tillage machinery 649, etc.), (multiple) operators 262, or (multiple) remote users 270 access these systems through the remote server location 702.

[0161] Figure 11 Another embodiment of the remote server architecture is also described. Figure 11 It is also possible to imagine that... Figure 2 Some components are located at a remote server location 702, while others are not. As an example, data storage device 704 (which includes third-party systems) can be located at a location separate from location 702 and accessed via a remote server at location 702. Regardless of their location, they can be directly accessed via a network (WAN or LAN) by machine 101 and / or (multiple) operators 262 and one or more remote users 270 (via user equipment 706). They can be hosted at a remote site, provided as a service, or accessed by a connection service residing at a remote location. Furthermore, data can be stored in virtually any location and accessed intermittently by interested parties or forwarded to interested parties. For example, a physical carrier can be used instead of an electromagnetic carrier, or a physical carrier can be used in addition to an electromagnetic carrier. In such an example embodiment, in cases of poor or nonexistent cell coverage, another mobile machine (such as a fuel vehicle) can have an automatic information collection system. When the machine approaches the fuel vehicle to refuel, the system automatically collects information from the mobile machine using any type of dedicated wireless connection. When a fuel vehicle arrives at a location with cellular (or other) wireless coverage, the collected information can be forwarded to the main network. For example, a fuel vehicle might enter a covered location while traveling on other types of fuel or at a main fuel storage location. This paper considers all of these architectures. Furthermore, information can be stored on the machinery until it enters a covered location. The machinery itself can then send the information to the main network.

[0162] It should also be noted that, Figure 2 The components or parts thereof can be placed on a variety of different devices. Some of these devices include servers, desktop computers, laptop computers, tablet computers, or other mobile devices such as PDAs, mobile phones, smartphones, multimedia players, personal digital assistants, etc.

[0163] Figure 12This is a simplified block diagram of a schematic example embodiment of a handheld or mobile computing device 16 that can be used as a user's or customer's handheld device 16, which can be deployed in this system (or as part thereof). For example, the mobile device can be deployed in the operating room of machine 101 for use in generating, processing, or displaying confidence values ​​and various other information. Figures 13 to 14 Examples are handheld or mobile devices.

[0164] Figure 12 A general block diagram of the components of client device 16, which can operate... Figure 2 The device 16 includes some components shown, interacts with them, or both. 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 is provided for automatically receiving information (e.g., by scanning). Examples of communication link 13 include those allowing communication via one or more communication protocols, such as wireless services for providing cellular access to a network, and protocols for providing local wireless connectivity to a network.

[0165] In other embodiments, the application can receive data on a removable Secure Digital (SD) card connected to interface 15. Interface 15 and communication link 13 are connected along bus 19 to processor 17 (which can also be implemented from...). Figure 2 The bus communicates with (multiple) processors 232, 274 or 310, and is also connected to memory 21 and input / output (I / O) components 23, as well as clock 25 and positioning system 27.

[0166] In one embodiment, I / O components 23 are provided to facilitate input and output operations. The I / O components 23 in various embodiments of device 16 may include input components (such as buttons, touch sensors, optical sensors, microphones, touchscreens, proximity sensors, accelerometers, orientation sensors) and output components (such as display devices, speaker and / or printer ports). Other I / O components 23 may also be used.

[0167] Clock 25 schematically includes a real-time clock component that outputs the time and date. Schematically, it may also provide timing functions for processor 17.

[0168] Positioning system 27 schematically includes a component that outputs the current geographic location of device 16. This may include, for example, a Global Positioning System (GPS) receiver, a LoRAN system, a dead reckoning system, a cellular triangulation system, or other positioning systems. It may also include, for example, mapping or navigation software that generates desired maps, navigation routes, and other geographic functions.

[0169] Memory 21 stores operating system 29, network settings 31, applications 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 actuated by other components to facilitate their functions.

[0170] Figure 13 An embodiment of a tablet computer 800 is shown, in which device 16 is illustrated. Figure 13 In the diagram, computer 800 is shown as having a user interface display screen 802. Screen 802 can be a touchscreen or a pen-enabled interface that receives input from a pen or stylus. It can also use a virtual keyboard on the screen. Of course, it can also be attached to a keyboard or other user input device, for example, via a suitable attachment structure (such as a wireless link or USB port). Computer 800 can also schematically receive voice input.

[0171] Figure 14 Similar to Figure 13 In addition to device 16, which is a smartphone 71, the smartphone 71 has a touch-sensitive display 73 that displays 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, smartphones 71 are built on a mobile operating system and offer more advanced computing power and connectivity than feature phones.

[0172] Note that other forms of device 16 are possible.

[0173] Figure 15 It is one of the deployable ones Figure 2 An embodiment of a computing environment, including components or portions thereof. Reference Figure 15 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 232, 274, or 310), a system memory 930, and a system bus 921 that connects 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 2 The described memory and program can be deployed in Figure 15 In the corresponding part.

[0174] Computer 910 typically includes a variety of computer-readable media. Computer-readable media can be any available medium accessible to computer 910, and includes volatile and non-volatile media, removable and non-removable media. By way of example and not limitation, computer-readable media can include computer storage media and communication media. Computer storage media is distinct from, and does not include, modulated data signals or carrier waves. It includes hardware storage media, including volatile and non-volatile, removable and non-removable media implemented in any method or technology, for storing 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 technologies, CD-ROM, digital versatile disk (DVD) or other optical disc storage devices, magnetic tape, magnetic tape, disk storage devices or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to computer 910. Communication media can implement computer-readable instructions, data structures, program modules, or other data in a transmission mechanism, and includes any information delivery medium. The term "modulated data signal" refers to a signal that has one or more of its characteristics set or changed in a manner that encodes information in the signal.

[0175] System memory 930 includes computer storage media in the form of volatile and / or non-volatile memory, such as read-only memory (ROM) 931 and random access memory (RAM) 932. The basic input / output system 933 (BIOS) (which contains basic routines such as those that help transfer information between components within computer 910 during startup) is typically stored in ROM 931. RAM 932 typically contains data and / or program modules that are readily accessible to and / or currently being operated by the processing unit 920. This is by way of example and not limitation. Figure 15 The operating system 934, application program 935, other program modules 936, and program data 937 are shown.

[0176] Computer 910 may also include other removable / non-removable volatile / non-volatile computer storage media. This is just one example. Figure 15A hard disk drive 941, an optical disk drive 955, and a non-volatile optical disk drive 956 are shown that read from or write to a non-removable, non-volatile magnetic medium. The hard disk drive 941 is typically connected to the system bus 921 via a non-removable memory interface (such as interface 940), and the hard disk drive 951 and the optical disk drive 955 are typically connected to the system bus 921 via a removable memory interface (such as interface 950).

[0177] Alternatively or additionally, the functions described herein may be performed at least in part by one or more hardware logic components. For example, but not limited to, illustrative types of hardware logic components that may be used include field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip systems (SOCs), complex programmable logic devices (CPLDs), and the like.

[0178] The above discussion and Figure 15 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 15 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.

[0179] 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, 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.

[0180] Computer 910 operates in a networked environment using a logical connection (such as a local area network (LAN) or a wide area network (WAN)) to one or more remote computers (such as remote computer 980).

[0181] 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 over WAN 973 (such as the Internet). In a networking environment, program modules may be stored in a remote memory storage device. Figure 15 For example, it is shown that remote application 985 can reside on remote computer 980.

[0182] It should also be noted that the different embodiments described herein can be combined in different ways. That is, portions of one or more embodiments can be combined with portions of one or more other embodiments. All of this is considered herein.

[0183] Example 1 is a mobile agricultural machine, comprising:

[0184] A sensor that detects a characteristic and generates a sensor signal indicating the characteristic;

[0185] A data storage device access logic system accesses a data storage device, the data storage device having stored data indicating characteristics that can affect the ability of the mobile agricultural machinery to perform operations;

[0186] A confidence level system configured to receive the stored data and generate a confidence level value based on the stored data, the confidence level value indicating the confidence level in the mobile agricultural machinery's ability to perform the operation; and

[0187] An action signal generator is configured to generate action signals for controlling the actions of the mobile agricultural machinery based on the confidence level value.

[0188] Example 2 is a mobile agricultural machine according to claim 1, wherein the action signal controls an operator-accessible interface mechanism of the mobile agricultural machine to display an indication of the confidence level value.

[0189] Example 3 is a mobile agricultural machine based on any or all of the previous examples, wherein the display includes instructions for suggesting changes to the operation of the mobile agricultural machine.

[0190] Example 4 is a mobile agricultural machine according to any or all of the previous examples, wherein the characteristic is the geographic location of weeds in the environment in which the mobile agricultural machine is operating.

[0191] Example 5 is a mobile agricultural machine according to any or all of the previous examples, wherein the mobile agricultural machine includes a mobile agricultural spraying system and the operation is a target material application operation, wherein the recommendation suggests changing the operation of the mobile agricultural spraying system from target material application to broadcast material application.

[0192] Example 6 is a mobile agricultural machine according to any or all of the previous examples, wherein the mobile agricultural machine further includes:

[0193] A threshold logic system that compares the confidence level value with a confidence level threshold indicating the desired confidence level value.

[0194] Example 7 is a mobile agricultural machine based on any or all of the previous examples, wherein the motion signal generator generates the motion signal based on a comparison of the confidence level value with the confidence level value threshold.

[0195] Example 8 is a mobile agricultural machine according to any or all of the previous examples, wherein the mobile agricultural machine includes a mobile agricultural spraying system that applies a substance to a surface in the environment in which the mobile agricultural spraying system performs the operation, and the characteristic includes the geographical location of weeds in the environment.

[0196] Example 9 is a mobile agricultural sprayer according to any or all of the previous examples, wherein the operation includes a target material application operation, in which the mobile agricultural spraying system applies a material to the geographic location of the weeds in the environment, and the action signal controls the spraying subsystem of the mobile agricultural spraying system to change the operation of the mobile agricultural spraying system from the target material application operation to a broadcast material application operation.

[0197] Example 10 is a mobile agricultural machine according to any or all of the previous examples, wherein the action signal actuates one or more nozzles of the spraying subsystem.

[0198] Example 11 is a mobile agricultural machine according to any or all of the previous examples, wherein the characteristic capable of affecting the ability of the mobile agricultural machine to perform the operation includes one or more sensor characteristics capable of affecting the ability of the sensor to accurately detect the characteristic.

[0199] Example 12 is a mobile agricultural machine according to any or all of the previous examples, wherein the mobile agricultural machine includes mobile agricultural planting machinery.

[0200] Example 13 is a mobile agricultural machine according to any or all of the previous examples, wherein the mobile agricultural machine includes a mobile agricultural harvester.

[0201] Example 14 is a mobile agricultural machine according to any or all of the previous examples, wherein the mobile agricultural machine includes mobile agricultural tillage machinery.

[0202] Example 15 is a method for controlling mobile agricultural machinery, the method comprising:

[0203] Obtain data indicating characteristics that can affect the ability of the mobile agricultural machinery to perform operations;

[0204] Based on the obtained data, a confidence level value is generated to indicate the confidence level of the mobile agricultural machinery's ability to perform the operation; and

[0205] Action signals are generated based on the confidence level value to control the movement of the mobile agricultural machinery.

[0206] Example 16 is a method according to any or all of the previous examples, wherein generating motion signals to control the mobile agricultural machinery includes a control interface to generate a display indicating a confidence level value.

[0207] Example 17 is based on the method of any or all of the previous examples, wherein generating the display includes displaying instructions for suggesting changes to the operation of the mobile agricultural machinery.

[0208] Example 18 is a method based on any or all of the previous examples, and also includes:

[0209] The receiving characteristic is an indication provided by sensor signals generated by a sensor, wherein the characteristic is the geographical location of weeds in the environment in which the mobile agricultural machinery performs the operation.

[0210] Example 19 is a method according to any or all of the previous examples, wherein the mobile agricultural machinery includes a mobile agricultural spraying system, and the operation is a target material application operation in which a material is applied by the agricultural spraying system to the geographic location of the weeds, wherein the recommendation suggests changing the operation of the mobile agricultural spraying system from the target material application operation to broadcast material application.

[0211] Example 20 is based on the method of any or all of the previous examples, and also includes:

[0212] The confidence level value is compared with the confidence level threshold that indicates the expected confidence level value;

[0213] The action signal is generated based on the comparison.

[0214] Example 21 is a method according to any or all of the previous examples, wherein the mobile agricultural machinery includes a mobile agricultural spraying system that applies herbicides to a surface in the environment in which the mobile agricultural spraying system performs the operation, and the characteristic includes the geographical location of weeds on the surface.

[0215] Example 22 is a method according to any or all of the previous examples, wherein the operation includes a target substance application operation in which the mobile agricultural spraying system applies a herbicide to the geographic location of the weeds on the surface of the environment, and the action signal controls the spraying subsystem of the mobile agricultural spraying system to change the operation of the mobile agricultural spraying system from the target substance application operation to the sowing substance application operation.

[0216] Example 23 is a method according to any or all of the foregoing examples, wherein controlling the spraying subsystem of the mobile agricultural spraying subsystem to change the operation of the mobile agricultural spraying system from the target material application operation to the spreading material application includes actuating one or more nozzles mounted on the spray bar of the mobile agricultural spraying system.

[0217] Example 24 is a method according to any or all of the previous examples, wherein the characteristics that can affect the ability of the mobile agricultural machinery to perform the operation include sensor characteristics that can affect the ability of the sensor to accurately detect characteristics.

[0218] Example 25 is based on any or all of the methods of the previous examples, wherein the mobile agricultural machinery includes a mobile agricultural harvester.

[0219] Example 26 is a method according to any or all of the previous examples, wherein the mobile agricultural machinery includes mobile agricultural planting machinery.

[0220] Example 27 is a method according to any or all of the previous examples, wherein the mobile agricultural machinery includes mobile agricultural tillage machinery.

[0221] Example 28 is a mobile agricultural spraying system that applies a substance to a surface in an environment in which the mobile agricultural spraying system operates, the mobile agricultural spraying system comprising:

[0222] A sensing sensor is installed in the mobile agricultural spraying system. The sensing sensor detects the geographical location of weeds on the surface in front of the spray bar and generates a sensor signal indicating the geographical location of the weeds on the surface. The spray bar transports the material from the material source to multiple nozzles arranged along the spray bar.

[0223] A data storage access logic system configured to access data stored in a data storage device that indicates at least one characteristic capable of influencing the ability of the mobile agricultural spraying system to perform a target substance application operation, in which the mobile agricultural spraying system attempts to apply a substance only to the geographic location of the weeds; and

[0224] The control system includes:

[0225] A confidence level system configured to receive the sensor signals and stored data, and generate a confidence level value based on the sensor signals and stored data, the confidence level value indicating the confidence level of the mobile agricultural spraying system in its ability to perform the application of the target substance.

[0226] A threshold logic system, wherein the threshold logic system is configured to:

[0227] The confidence level value is compared with the confidence level threshold that indicates the expected confidence level value;

[0228] Generate a threshold output indicating the comparison; and

[0229] An action signal generator, which generates action signals for controlling the actions of the mobile agricultural spraying system based on the threshold output.

[0230] Example 29 is a mobile agricultural sprayer according to any or all of the previous examples, wherein the action signal controls an interface mechanism in the cab of the mobile agricultural sprayer to generate a display including an instruction to change the operation of the mobile agricultural spraying system from a target material application operation to a spread material application operation, in which the mobile agricultural spraying system attempts to apply a material evenly to the entire surface.

[0231] Example 30 is a mobile agricultural sprayer according to any or all of the previous examples, wherein the action signal automatically controls the spraying subsystem of the mobile agricultural sprayer to change the operation of the mobile agricultural spraying system from target material application operation to spread material application, wherein the action signal actuates one or more of a plurality of nozzles.

[0232] Example 31 is one or more of the machines, systems, or methods described herein.

[0233] Although the subject matter has been described in language specific to structural features and / or methodological actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are disclosed as examples of implementing the claims.

Claims

1. A mobile agricultural machine, comprising: A sensor that detects a characteristic and generates a sensor signal indicating the characteristic; A data storage device access logic system accesses a data storage device, the data storage device having stored data indicating characteristics that can affect the ability of the mobile agricultural machinery to perform operations, wherein the characteristic is the geographical location of weeds in the environment in which the mobile agricultural machinery is operating; A confidence level system configured to receive the stored data and generate a confidence level value based on the stored data, the confidence level value indicating the confidence level in the mobile agricultural machinery's ability to perform the operation; and An action signal generator is configured to generate action signals for controlling the actions of the mobile agricultural machinery based on the confidence level value. The action signal controls an operator-accessible interface mechanism of the mobile agricultural machinery to display an indication of the confidence level value. The display includes instructions for suggesting changes to the operation of the mobile agricultural machinery; and, The mobile agricultural machinery includes a mobile agricultural spraying system, and the operation is a target substance application operation. The recommendation suggests changing the operation of the mobile agricultural spraying system from target substance application to broadcasting substance application.

2. The mobile agricultural machinery according to claim 1, wherein, The mobile agricultural machinery also includes: A threshold logic system that compares the confidence level value with a confidence level threshold indicating the desired confidence level value.

3. The mobile agricultural machinery according to claim 2, wherein, The motion signal generator generates the motion signal based on a comparison between the confidence level value and the confidence level threshold value.

4. The mobile agricultural machinery according to claim 3, wherein, The mobile agricultural machinery includes a mobile agricultural spraying system that applies materials to surfaces in the environment in which the mobile agricultural spraying system performs the operation, and the characteristics include the geographical location of weeds in the environment.

5. The mobile agricultural machinery according to claim 4, wherein, The operation includes a target substance application operation, in which the mobile agricultural spraying system applies a substance to the geographical location of the weeds in the environment, and the action signal controls the spraying subsystem of the mobile agricultural spraying system to change the operation of the mobile agricultural spraying system from the target substance application operation to a broadcasting substance application operation.

6. The mobile agricultural machinery according to claim 5, wherein, The action signal actuates one or more nozzles of the spraying subsystem.

7. The mobile agricultural machinery according to any one of the preceding claims, wherein, The characteristics that can affect the ability of the mobile agricultural machinery to perform the operation include one or more sensor characteristics that can affect the ability of the sensor to accurately detect the characteristic.

8. The mobile agricultural machinery according to any one of the preceding claims, wherein, The mobile agricultural machinery includes mobile agricultural planting machinery.

9. The mobile agricultural machinery according to any one of the preceding claims, wherein, The mobile agricultural machinery includes mobile agricultural harvesters.

10. The mobile agricultural machinery according to any one of the preceding claims, wherein, The mobile agricultural machinery includes mobile agricultural tillage machinery.

11. A method for controlling mobile agricultural machinery, the method comprising: Obtain data indicating characteristics that can affect the ability of the mobile agricultural machinery to perform operations; Based on the obtained data, a confidence level value is generated to indicate the confidence level of the mobile agricultural machinery's ability to perform the operation; An action signal is generated based on the confidence level value to control the action of the mobile agricultural machinery. The action signal for generating the action signal to control the action of the mobile agricultural machinery includes a control interface for generating a display indicating the confidence level value. The generated display includes instructions that display suggestions for changing the operation of the mobile agricultural machinery; The method further includes receiving an indication of characteristics provided by a sensor signal generated by a sensor, wherein the characteristics are the geographical location of weeds in the environment in which the mobile agricultural machinery is operating; The mobile agricultural machinery includes a mobile agricultural spraying system, and the operation is a target substance application operation in which the substance is applied by the agricultural spraying system to the geographical location of the weeds. The recommendation suggests changing the operation of the mobile agricultural spraying system from the target substance application operation to the broadcasting application of the substance.

12. A mobile agricultural spraying system that applies a substance to a surface in an environment in which the mobile agricultural spraying system operates, the mobile agricultural spraying system comprising: A sensing sensor is installed in the mobile agricultural spraying system. The sensing sensor detects the geographical location of weeds on the surface in front of the spray bar and generates a sensor signal indicating the geographical location of the weeds on the surface. The spray bar transports the material from the material source to multiple nozzles arranged along the spray bar. A data storage access logic system configured to access data stored in a data storage device that indicates at least one characteristic capable of influencing the ability of the mobile agricultural spraying system to perform a target substance application operation in which the mobile agricultural spraying system attempts to apply the substance only to the geographic location of the weeds. as well as The control system includes: A confidence level system configured to receive the sensor signals and stored data, and generate a confidence level value based on the sensor signals and stored data, the confidence level value indicating the confidence level of the mobile agricultural spraying system in its ability to perform the application of the target substance. A threshold logic system, wherein the threshold logic system is configured to: The confidence level value is compared with the confidence level threshold that indicates the expected confidence level value; Generate a threshold output indicating the comparison; and An action signal generator generates action signals for controlling the actions of the mobile agricultural spraying system based on the threshold output; and The confidence system is configured to generate action signals to control the mobile agricultural spraying system to switch between target spraying and broadcast spraying.

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