Patent Application
20240180059
The present disclosure relates generally to agricultural implements and, more particularly, to monitoring the performance of an agricultural implement during an agricultural operation within a field.
It is well known that, to attain the best agricultural performance from a field, a farmer must cultivate the soil, typically through a tillage operation. Tillage implements typically include a plurality of ground engaging tools configured to engage the soil as the implement is moved across the field. Such ground engaging tool(s) loosen and/or otherwise agitate the soil to a certain depth in the field to prepare the field for subsequent agricultural operations, such as planting operations.
When performing a tillage operation, it is desirable to create a level and uniform layer of tilled soil across the field to form a proper seedbed in subsequent planting operations. Depending on the season, different surface finishes may be desired. For instance, rougher surfaces with more and/or larger clods may be desired when tilling before wintering a field, as the surface will become smoother over winter and be ready for spring planting, whereas a smoother field may crust over during wintering, which requires another tillage pass before spring planting to break up the crust. However, the soil type or texture, the amount and distribution of crop residue, the moisture content, and/or the like may vary across a field, which requires an operator to constantly monitor the surface finish created during passes with the implement during the agricultural operation, and make frequent adjustments to the implement to maintain the proper surface finish. Further, it may be difficult for an operator to see the field directly behind the implement if the implement is creating dust. If the proper surface finish is not maintained, additional passes in the field may be required, which increases costs and time, and may even reduce the yield of the next planting within the field.
Accordingly, a system and method for monitoring the performance of an agricultural implement during an agricultural operation with the agricultural implement would be welcomed in the technology.
Aspects and advantages of the invention will be set forth in part in the following description, or may be obvious from the description, or may be learned through practice of the invention.
In one aspect, the present subject matter is directed to an agricultural system for monitoring the performance of an agricultural implement. The agricultural system may include an agricultural implement having at least one ground engaging tool, where the at least one ground engaging tool may be configured to engage a field during an agricultural operation performed by the agricultural implement within the field. The system may further include one or more Light Detection and Ranging (LIDAR) sensors having a field of view directed toward a portion of the field worked by the agricultural implement during the agricultural operation, where the one or more LIDAR sensors may be configured to generate first light at a first output frequency and second light at a second output frequency, the first output frequency being different than the second output frequency, and where the one or more LIDAR sensors may be configured to generate first data indicative of reflection of the first light off the portion of the field and second data indicative of reflection of the second light off the portion of the field. Additionally, the system may include a computing system communicatively coupled to the one or more LIDAR sensors. The computing system may be configured to receive the first data generated by the one or more LIDAR sensors, receive the second data generated by the one or more LIDAR sensors, and determine a surface feature parameter of the portion of the field based at least in part on the first data and the second data.
In another aspect, the present subject matter is directed to a method for monitoring the performance of an agricultural implement, with the agricultural implement having at least one ground engaging tool configured to engage a field during an agricultural operation within the field. The method may include controlling, with a computing system, one or more Light Detection and Ranging (LIDAR) sensors to generate first light at a first output frequency and second light at a second output frequency, with the one or more LIDAR sensors having a field of view directed towards a portion of the field worked by the agricultural implement during the agricultural operation. The method may further include receiving, with the computing system, first data generated by the one or more LIDAR sensors, where the first data may be indicative of reflection of the first light off of the portion of the field. Moreover, the method may include receiving, with the computing system, second data generated by the one or more LIDAR sensors, where the second data may be indicative of reflection of the second light off of the portion of the field. Additionally, the method may include determining, with the computing system, a surface feature parameter of the portion of the field based at least in part on the first data and the second data.
These and other features, aspects and advantages of the present invention will become better understood with reference to the following description and appended claims. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.
A full and enabling disclosure of the present invention, including the best mode thereof, directed to one of ordinary skill in the art, is set forth in the specification, which makes reference to the appended figures, in which:
Repeat use of reference characters in the present specification and drawings is intended to represent the same or analogous features or elements of the present technology.
Reference now will be made in detail to embodiments of the invention, one or more examples of which are illustrated in the drawings. Each example is provided by way of explanation of the invention, not limitation of the invention. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the scope or spirit of the invention. For instance, features illustrated or described as part of one embodiment can be used with another embodiment to yield still a further embodiment. Thus, it is intended that the present invention covers such modifications and variations as come within the scope of the appended claims and their equivalents.
In general, the present subject matter is directed to systems and methods for monitoring the performance of an agricultural implement during an agricultural operation with the agricultural implement. Specifically, the disclosed system may include an agricultural implement having at least one ground engaging tool (e.g., a shank, a disc blade, a leveling blade, a tine, a basket assembly, and/or the like) configured to engage and work a field during the agricultural operation. In accordance with aspects of the present subject matter, the system may further include one or more light detection and ranging (LIDAR) sensors having a field of view directed to a portion of the field worked by the implement (e.g., directed aft of the implement, directed towards a previous swath, and/or the like). The LIDAR sensor(s) may be multi-frequency LIDAR sensors configured to generate light at multiple frequencies, such as first light at a first frequency and second light at a second frequency, where the first and second frequencies interact differently with different materials. For instance, the first light at the first frequency may be reflected by clods, crop residue, and/or the like, whereas the second light at the second frequency may be reflected by clods, but not the crop residue and/or the like. A computing system of the disclosed system may be configured to receive first data generated by the LIDAR sensor(s) indicative of reflection of the first light off the portion of the worked area of the field and second data generated by the LIDAR sensor(s) indicative of reflection of the second light off the portion of the worked area, then determine a surface feature parameter of a surface of the portion of the field based at least in part on the first data and the second data, which in turn may be indicative of the performance of the implement.
For instance, the first data may indicate a surface profile of the field (created by clods, crop residue, soil, rocks, etc.), whereas the second data indicates at least one type of surface feature (e.g., clods, crop residue, soil, rocks, etc.) on the surface of the field. For example, the first data may indicate a surface profile of the surface of the field, whereas the second data may have voids indicating where crop residue is on the field. In such instance, subtracting the voids determined from the second data from the first data, for example, may indicate the location of clods. Thus, the computing system may be configured to determine surface feature parameters such as the surface roughness of the surface profile of the field, a levelness of the surface profile of the field, coverage and/or distribution of crop residue on the surface of the field, and/or a size and/or distribution of clods on the surface of the field based at least in part on the first data and the second data.
Referring now to the drawings,
In general, the implement 10 may be configured to be towed across a field in a direction of travel (e.g., as indicated by arrow 14) by the work vehicle 12. As shown, the implement 10 may be configured as a tillage implement, and the work vehicle 12 may be configured as an agricultural tractor. However, in other embodiments, the implement 10 may be configured as any other suitable type of implement, such as a seed-planting implement, a fertilizer-dispensing implement, and/or the like. Similarly, the work vehicle 12 may be configured as any other suitable type of vehicle, such as an agricultural harvester, a self-propelled sprayer, and/or the like.
As shown in
As shown in
In several embodiments, one or more ground engaging tools may be coupled to and/or supported by the frame 28. In such embodiments, the ground engaging tool(s) may, for example, include one or more ground-penetrating tools. More particularly, in certain embodiments, the ground engaging tools may include one or more disk blades 46 and/or one or more shanks 50 supported relative to the frame 28. In one embodiment, each disk blade 46 and/or shank 50 may be individually supported relative to the frame 28. Alternatively, one or more groups or sections of the ground engaging tools may be ganged together to form one or more ganged tool assemblies, such as the disk gang assemblies 44 shown in
As illustrated in
It should be appreciated that, in addition to the shanks 50 and the disk blades 46, the implement frame 28 may be configured to support any other suitable ground engaging tools. For instance, in the illustrated embodiment, the frame 28 is also configured to support a plurality of leveling blades 52 and rolling (or crumbler) basket assemblies 54.
Moreover, in several embodiments, the implement 10 may include a plurality of actuators configured to adjust the positions of the implement 10 and/or various ground engaging tools coupled thereto. For example, in some embodiments, the implement 10 may include a plurality of disk gang actuators 60 (one is shown in
Further, in some embodiments, the implement 10 may include a plurality of shank frame actuator(s) 62 (
In the illustrated embodiment, each actuator 60, 62, 64 corresponds to a fluid-driven actuator, such as a hydraulic or pneumatic cylinder. However, it should be appreciated that each actuator 60, 62, 64 may correspond to any other suitable type of actuator, such as an electric linear actuator. It should additionally be appreciated that the implement 10 may include any other suitable actuators for adjusting the position and/or orientation of the ground-engaging tools of the implement 10 relative to the ground and/or implement frame 28.
In accordance with aspects of the present subject matter, the implement 10 and/or the work vehicle 12 may be equipped with one or more sensors for monitoring the performance of the implement 10 during an agricultural operation (e.g., a tillage operation) performed with the implement 10. For instance, one or more LIDAR sensors 100 may be supported on the implement 10 and/or the work vehicle 12, with the LIDAR sensor(s) 100 being configured to generate data indicative of one or more surface feature parameters of the surface of the field worked by the implement 10, where each of the surface feature parameter(s), in turn, is indicative of the performance of the implement 10. For example, the LIDAR sensor(s) 100 are supported on the implement 10 and/or the work vehicle 12 such that the LIDAR sensor(s) 100 are spaced apart from and above a surface of the field during an agricultural operation with the implement 10 while having a field of view generally directed towards a portion of the field. In some embodiments, the field of view of each of the LIDAR sensor(s) 100 is directed towards a portion of the field that has already been worked by the implement 10 during the current agricultural operation. For instance, the field of view of the LIDAR sensor(s) 100 may be directed aft of the implement 10 relative to the direction of travel 14 along a current swath being worked by the implement 10 and/or towards another swath (e.g., a directly adjacent swath to the current swath) within the field that was previously worked by the implement 10 during the current agricultural operation. In some instances, the LIDAR sensor(s) 100 may be positioned proximate a rear end of the implement 10 relative to the direction of travel 14. However, it should be appreciated that the LIDAR sensor(s) 100 may instead, or additionally, be positioned at any other suitable location for generating data indicative of the performance of the implement 10. In some embodiments, the LIDAR sensor(s) 100 is a three-dimensional (3D) LIDAR sensor(s). However, in other embodiments, the LIDAR sensor(s) 100 is a two-dimensional (2D) LIDAR sensor(s).
In accordance with aspects of the present subject matter, the LIDAR sensor(s) 100 are configured to output multiple frequencies of light and detect the reflectance of the multiple frequencies off of the field. For instance, in some embodiments, each of the LIDAR sensor(s) 100 is a multi-frequency LIDAR sensor(s) configured to output multiple frequencies of light simultaneously. For instance, each LIDAR sensor 100 may output or generate first light at a first output frequency, second light at a second output frequency, third light at a third output frequency, and so on, simultaneously, where the output frequencies are different from each other (e.g., the first output frequency is different from the second output frequency, the second output frequency is different from the third output frequency, the first output frequency is different from the third output frequency, etc.). Each of the output frequencies of light may interact differently with different materials. For instance, certain output frequencies of light (e.g., the first light at the first output frequency) may reflect off of some surface feature types (e.g., crop residue, clods, rocks, etc. on the surface of the field and sometimes the surface of the field itself), whereas other output frequencies of light (e.g., the second light at the second output frequency) may reflect off only some of the same surface feature types (e.g., clods, rocks, etc. on the surface of the field and sometimes the surface of the field itself), but be absorbed or not reflected by others of the surface feature types (e.g., the crop residue on the surface of the field).
Thus, as will be described below in greater detail, the different frequencies of the LIDAR sensor(s) 100 may be used to identify different surface features (e.g., surface profile, residue, clods, and/or the like) of the field already worked by the implement 10, which may, in turn, be used to determine at least one surface feature parameter (e.g., surface roughness, surface levelness, crop residue coverage, crop residue distribution, clod sizes, clod distribution, and/or the like) where the surface feature parameter(s) may be used to determine the performance of the implement 10.
It should be appreciated that multiple, single-frequency LIDAR sensors may be used instead of a multi-frequency LIDAR sensor 100, where each single-frequency LIDAR sensor is configured to generate light at a different frequency from another single-frequency LIDAR sensor. For instance, a single multi-frequency LIDAR sensor may weigh less than, require fewer input ports to a computing system than, and cost less than multiple single-frequency LIDAR sensors. It further should be appreciated that the configuration of the implement 10 described above and shown in
Referring now to
In several embodiments, the system 200 may include a computing system 202 and various other components configured to be communicatively coupled to and/or controlled by the computing system 202, such as LIDAR sensor(s) (e.g., the LIDAR sensor(s) 100 configured to generate data indicative of the performance of the implement 10), actuator(s) of the implement 10 (e.g., the implement actuator(s) 60, 62, 64), drive device(s) of the vehicle 12 (e.g., the engine 24, the transmission 26, etc.), and/or a user interface(s) (e.g., user interface(s) 120). The user interface(s) 120 described herein may include, without limitation, any combination of input and/or output devices that allow an operator to provide operator inputs to the computing system 202 and/or that allow the computing system 202 to provide feedback to the operator, such as a keyboard, keypad, pointing device, buttons, knobs, touch sensitive screen, mobile device, audio input device, audio output device, and/or the like. Additionally, the computing system 202 may be communicatively coupled to one or more position sensors 122 configured to generate data indicative of the location of the implement 10 and/or the vehicle 12, such as a satellite navigation positioning device (e.g., a GPS system, a Galileo positioning system, a Global Navigation satellite system (GLONASS), a BeiDou Satellite Navigation and Positioning system, a dead reckoning device, and/or the like).
In general, the computing system 202 may correspond to any suitable processor-based device(s), such as a computing device or any combination of computing devices. Thus, as shown in
It should be appreciated that the computing system 202 may correspond to an existing computing device for the implement 10 or the vehicle 12 or may correspond to a separate processing device. For instance, in one embodiment, the computing system 202 may form all or part of a separate plug-in module that may be installed in operative association with the implement 10 or the vehicle 12 to allow for the disclosed system and method to be implemented without requiring additional software to be uploaded onto existing control devices of the implement 10 or the vehicle 12.
In several embodiments, the data 208 may be stored in one or more databases. For example, the memory 206 may include a sensor database 212 for storing data generated by the sensors 100, 122. For instance, the LIDAR sensor(s) 100 may be configured to continuously or periodically generate data associated with a portion of the field, such as during the performance of the agricultural operation with the implement 10. The data from the LIDAR sensor(s) 100 may be taken with reference to the position of the implement 10 and/or the vehicle 12 within the field based on the position data from the position sensor(s) 122. The data transmitted to the computing system 202 from the sensors 100, 122 may be stored within the sensor database 212 for subsequent processing and/or analysis. It should be appreciated that, as used herein, the term “sensor data 212” may include any suitable type of data received from the sensors 100, 122 that allows for the performance of the implement to be determined. For instance, the data generated by the LIDAR sensor(s) 100 may include reflectance data (e.g., as a point-cloud), and/or any other suitable type of data, and the data generated by the position sensor(s) 122 may include GPS coordinates, and/or any other suitable type of data.
Moreover, in some embodiments, the memory 206 may also include a soil type database 214 for storing field data indicative of the different soil types across a field. The field data stored in the soil type database 214 may include, for example, a soil type map indicating the soil type (e.g., established composition of silt, loam, clay, sand, etc., and/or texture) at each location within a field. The field data stored in the soil type database 214 may be generated and stored in the soil type database 214 before the performance of the agricultural operation with the agricultural implement 10. Soil type maps may be, for example, SSURGO maps, and/or any other suitable type of soil map. However, it should be appreciated that the field data may be stored in any other suitable format other than a soil type map, such as a lookup table, and/or the like.
The instructions 210 stored within the memory 206 of the computing system 202 may be executed by the processor(s) 204 to implement a performance module 218. In general, the performance module 218 may be configured to assess the sensor data 212 deriving from the sensors 100, 122 to determine the performance of the implement 10 during an agricultural operation with the implement 10 within a field. For instance, the performance module 218 may be configured to assess the sensor data 212 deriving from the sensors 100, 122 to determine one or more surface features (e.g., surface profile, residue, clod, and/or the like) and one or more parameters of such surface feature(s) (e.g., surface roughness, surface levelness, residue coverage, residue distribution, clod distribution, clod size, and/or the like) across the field, where the surface feature(s), particularly the parameter of the surface feature(s), is indicative of the performance of the implement 10.
For example, as indicated above, in one embodiment, first light generated by the LIDAR sensor(s) 100 at a first frequency (e.g., a shorter frequency) may be reflected by all of the surface features of the field within the field of view of the LIDAR sensor(s) 100. As such, the first data generated by the LIDAR sensor(s) 100 indicates the first light reflected and detected by LIDAR sensor(s) 100 and is indicative of the surface profile of the field, including any clods, residue, rocks, etc. on the surface of the field. Further, as indicated above, second light generated by the LIDAR sensor(s) 100 at a second frequency, different from the first frequency, (e.g., a longer frequency) may be reflected by only some of the surface features of the field within the field of view of the LIDAR sensor(s) 100. For instance, the second light may be absorbed by residue, but reflected by clods, rocks, and/or the like. As such, the second data generated by the LIDAR sensor(s) 100 indicates the second light reflected and detected by LIDAR sensor(s) 100 and is indicative of residue, which appears as voids as the second light is absorbed by the residue, and clods, rocks, and/or the like, which appears as the reflected light. It should be appreciated that the data corresponding to each frequency may be generated such that the data may be compared for a portion of the field. For instance, the first data and the second data may be generated simultaneously for the same portion of the field within the field of view of the sensor(s) 100 such that the first data and the second data may be directly compared.
The performance module 218 may be configured to determine surface feature parameter(s) of the surface feature(s) of the field from the first data and the second data. For instance, the performance module 218 may identify areas in the first data corresponding to the voids in the second data. For example, the performance module 218 may overlay the first data and the second data then determine surface feature(s) and surface feature parameter(s) based on the overlay. The voids from the second data overlaid onto the first data indicates the coverage (e.g., percentage of coverage) and the average size or thickness of the crop residue layer across the particular portion of the field within the field of view of the sensor(s) 100. Further, the difference in height between the surface profile from the first data and the surface profile from the second data at the void location indicates the size (e.g., height) and distribution of clods across the portion of the field within the field of view of the sensor(s) 100 from the areas that do not correspond to the residue. The performance module 218 may determine the overall surface roughness and/or surface levelness of the surface profile of the field based on the first data alone (e.g., including the crop residue and the clods), or may determine the roughness based on the overlay of the first data and the second data. The term “surface roughness” is intended to mean the texture of the surface profile whereas “surface levelness” is intended to mean the slope of the surface profile across a lateral width of the swath. It should be appreciated that, by using the first data and the second data together, a more dense point cloud may be generated than from the first data or the second data separately, which allows for better boundaries of residue and clods to be determined than can be determined from the first data or the second data separately, which improves determination of the different surface feature parameters. It should further be appreciated that the performance module 218 may identify the different surface features in any suitable order and/or may similarly identify the surface feature parameters in any suitable order.
It should additionally be appreciated that, in some embodiments, the performance module 218 may also be configured to control the LIDAR sensor(s) 100 to generate light at different frequencies and to generate the associated reflectance data. For instance, in some embodiments, the performance module 218 may determine the different frequencies at which the LIDAR sensor(s) 100 generate light simultaneously based at least in part on operator input(s) via the user interface(s) 120. For example, an operator may directly input the two or more frequencies for generating lights then the performance module 218 may control the LIDAR sensor(s) 100 according to such frequencies. However, in other instances, the control module 220 may use the data from the position sensor(s) 122 to determine the soil type from the soil type database 214 at the corresponding location within the field, then use known relationships between the soil type and reflectance properties (e.g., using look-up tables, suitable mathematical formulas, and/or algorithms which may also be stored in the soil type database 214 or otherwise accessible by the computing system 202) to determine the appropriate frequencies and either automatically control the LIDAR sensor(s) 100 according to such frequencies or suggest such frequencies to the operator via the user interface(s) 120.
Referring still to
The control action, in one embodiment, includes adjusting the operation of one or more components of the implement 10, such as adjusting the operation of one or more of the actuators 60, 62, 64 to adjust the penetration depth of the ground engaging tool(s) 46, 50, 52, 54 and/or adjust the operation of one or more of the drive device(s) 24, 26 to adjust a ground speed of the implement 10 and/or the vehicle 12 based on the monitored surface feature parameter(s) (e.g., surface roughness, surface levelness, residue coverage, residue size, clod distribution, clod size, etc.) to improve performance of the implement 10. In some embodiments, the control action may include controlling the operation of the user interface 120 to notify an operator of the performance (e.g., the monitored surface feature parameter(s)) and/or the like. Additionally, or alternatively, in some embodiments, the control action may include adjusting the operation of the implement 10 based on an input from an operator, e.g., via the user interface 120.
Additionally, as shown in
Referring now to
As shown in
Further, at (304), the method 300 may include receiving first data generated by the one or more LIDAR sensors indicative of reflection of the first light off of a portion of a field worked by an agricultural implement during an agricultural operation. For example, as described above, the computing system 202 may be configured to receive first data generated by the LIDAR sensor(s) 100 indicative of reflection of the first light off of a portion of a field worked by the agricultural implement 10 during an agricultural operation (the portion of the field being within the field of view of the sensor(s) 100).
Moreover, at (306), the method 300 may include receiving second data generated by the one or more LIDAR sensors indicative of reflection of the second light off of the portion of the field during the agricultural operation. Similarly, as described above, the computing system 202 may be configured to receive second data generated by the LIDAR sensor(s) 100 indicative of reflection of the second light off of the portion of the field worked by the agricultural implement 10 during the agricultural operation (the portion of the field being within the field of view of the sensor(s) 100).
Additionally, at (308), the method 300 may include determining a surface feature parameter of the portion of the field based at least in part on the first data and the second data. For example, as discussed above, the computing system 202 may be configured to determine a surface feature parameter of one or more surface features of the portion of the field, such as a surface roughness of the surface profile, a levelness of the surface profile, crop residue coverage, crop residue size, clod distribution, clod size, and/or the like, based at least in part on the first data and the second data, with the surface feature parameter being indicative of the performance of the implement 10.
It is to be understood that the steps of the method 300 are performed by the computing system 202 upon loading and executing software code or instructions which are tangibly stored on a tangible computer readable medium, such as on a magnetic medium, e.g., a computer hard drive, an optical medium, e.g., an optical disk, solid-state memory, e.g., flash memory, or other storage media known in the art. Thus, any of the functionality performed by the computing system 202 described herein, such as the method 300, is implemented in software code or instructions which are tangibly stored on a tangible computer readable medium. The computing system 202 loads the software code or instructions via a direct interface with the computer readable medium or via a wired and/or wireless network. Upon loading and executing such software code or instructions by the computing system 202, the computing system 202 may perform any of the functionality of the computing system 202 described herein, including any steps of the method 300 described herein.
The term “software code” or “code” used herein refers to any instructions or set of instructions that influence the operation of a computer or computing system. They may exist in a computer-executable form, such as machine code, which is the set of instructions and data directly executed by a computer's central processing unit or by a computing system, a human-understandable form, such as source code, which may be compiled in order to be executed by a computer's central processing unit or by a computing system, or an intermediate form, such as object code, which is produced by a compiler. As used herein, the term “software code” or “code” also includes any human-understandable computer instructions or set of instructions, e.g., a script, that may be executed on the fly with the aid of an interpreter executed by a computer's central processing unit or by a computing system.
This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they include structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal languages of the claims.
