Patent Description:
Soil surface roughness generally relates to the planarity or smoothness of the soil within a field and is typically impacted by uneven soil profiles, soil clumps, crop residue, and foreign objects within the field (e.g., rocks). For various reasons, soil surface roughness is an important field characteristic to consider when performing a ground-engaging operation, such as a tillage operation, a planting operation, a fertilizing operation, and/or the like. For example, the soil surface roughness can impact the environmental quality of the soil, including erosion resistance and moisture content. In addition, the soil surface roughness can affect the seed-bed quality. As such, the ability to monitor and/or adjust the soil surface roughness within a field can be very important to maintaining a healthy, productive field, particularly when it comes to performing various ground-engaging operations.

In this regard, vision-based systems have been developed that attempt to estimate the soil surface roughness from images captured of the field. However, such vision-based systems suffer from various drawbacks or disadvantages, particularly with reference to the accuracy of the soil roughness estimates due to inaccurate or infrequent calibration of the vision-based systems. Further, calibrating such vision-based systems is often time consuming.

Accordingly, a system and method for determining field surface conditions with improved accuracy using vision-based data would be welcomed in the technology.

In one aspect, the present subject matter is directed to a system for determining field surface conditions, in accordance with the appended claims. The system includes a frame member and a ground engaging tool coupled to the frame member, with the ground engaging tool being configured to engage soil within a field as an agricultural implement is moved across the field. The system further includes a vision sensor having a field of view directed towards a portion of a surface of the field, where the vision sensor is configured to capture vision-based data indicative of a field surface condition of the field. The system also includes a secondary sensor coupled to the ground engaging tool, with the secondary sensor being configured to capture secondary data indicative of the field surface condition. Additionally, the system includes a controller communicatively coupled to the vision sensor and the secondary sensor. The controller is configured to determine an initial surface condition as a function of the vision-based data and to correct the initial surface condition based at least in part on the secondary data received from the secondary sensor.

In another aspect, the present subject matter is directed to a method for determining field surface conditions in accordance with the appended claims. The method includes receiving, with one or more computing devices, vision-based data indicative of a field surface condition of a field. The method further includes receiving, with the one or more computing devices, secondary data indicative of the field surface condition from a secondary sensor coupled to a ground engaging tool of an agricultural implement being moved across the field. The method also includes determining, with the one or more computing devices, a correction factor associated with the field surface condition based at least in part on the secondary data. Moreover, the method includes determining, with the one or more computing devices, a surface condition based at least in part on the vision-based data and the correction factor. Additionally, the method includes adjusting, with the one or more computing devices, an operation of one or more components of the agricultural implement based at least in part on the determined surface condition.

In general, the present subject matter is directed to systems and methods for determining field surface conditions during the performance of an agricultural operation within a field. In particular, the present subject matter is directed to a system according to claim <NUM> and a method according to claim <NUM> for correcting initial field surface conditions determined from vision-based data using correction factors derived, at least in part, from non-vision-based data generated from a secondary source or sensor (i.e., "secondary data") to provide more accurate estimates of field surface conditions. In several embodiments, the field surface condition monitored or determined using the disclosed systems and methods may include, but are not limited to, surface roughness (e.g., a number of ridges, undulations, etc. measured in an area), clod sizes, etc., which are indicators of the overall field surface condition of the field.

In particular, a computing system may obtain vision-based data of the field from a vision sensor coupled to an agricultural implement and secondary data from a non-vision-based or secondary sensor coupled to a ground engaging tool of the implement that is configured to ride along or roll on top of the surface of the field. In several embodiments, the secondary sensor may generally be configured to detect movement of the associated ground engaging tool as it rides along or rolls on top of the surface, with the movement being indicative of the field surface condition. The vision-based data derived from the vision sensor may be analyzed by the computing system to determine a vision-based surface condition of the field. The secondary data may similarly be separately analyzed to determine a secondary surface condition of the field. In one embodiment, the computing system may compare the surface conditions determined from the analysis of the vision-based data and the secondary data to determine a correction factor, which may be subsequently used to correct the initial vision-based surface condition. Additionally, in some embodiments, the operation of one or more components of the implement and/or the work vehicle may be adjusted based at least in part on the corrected surface condition, such as when the corrected surface condition falls outside an acceptable range.

Referring now to the drawings, <FIG> and <FIG> illustrate differing perspective views of one embodiment of an agricultural machine in accordance with aspects of the present subject matter. Specifically, <FIG> illustrates a perspective view of the agricultural machine including a work vehicle <NUM> and an associated agricultural implement <NUM>. Additionally, <FIG> illustrates a perspective view of the agricultural machine, particularly illustrating various components of the implement <NUM>.

In the illustrated embodiment, the agricultural machine corresponds to the combination of the work vehicle <NUM> and the associated agricultural implement <NUM>. As shown in <FIG> and <FIG>, the vehicle <NUM> corresponds to an agricultural tractor configured to tow the implement <NUM>, namely a tillage implement (e.g., a cultivator), across a field in a direction of travel (e.g., as indicated by arrow <NUM> in <FIG>). However, in other embodiments, the agricultural machine may correspond to any other suitable combination of work vehicle (e.g., an agricultural harvester, a self-propelled sprayer, and/or the like) and agricultural implement (e.g., such as a seeder, fertilizer, sprayer (a towable sprayer or a spray boom of a self-propelled sprayer), mowers, and/or the like). In addition, it should be appreciated that, as used herein, the term "agricultural machine" may refer not only to combinations of agricultural implements and vehicles, but also to individual agricultural implements and/or vehicles.

As shown in <FIG>, the vehicle <NUM> may include a frame or chassis <NUM> configured to support or couple to a plurality of components. For example, a pair of front track assemblies <NUM> (only one of which is shown) and a pair of rear track assemblies <NUM> may be coupled to the frame <NUM>. The track assemblies <NUM>, <NUM> may, in turn, be configured to support the vehicle <NUM> relative to the ground and move the vehicle <NUM> in the direction of travel <NUM> across the field. Furthermore, an operator's cab <NUM> may be supported by a portion of the frame <NUM> and may house various input devices (e.g., a user interface <NUM> shown in <FIG>) for permitting an operator to control the operation of one or more components of the vehicle <NUM> and/or the implement <NUM>. However, in other embodiments, the vehicle <NUM> may include wheels (not shown) in place of the front and/or rear track assemblies <NUM>, <NUM>. Furthermore, the vehicle <NUM> may include one or more devices for adjusting the speed at which the vehicle <NUM> and implement <NUM> move across the field in the direction of travel <NUM>. Specifically, in several embodiments, the vehicle <NUM> may include an engine <NUM> and a transmission <NUM> mounted on the frame <NUM>.

As shown in <FIG> and <FIG>, the implement <NUM> may include an implement frame <NUM>. More specifically, the frame <NUM> may extend along a longitudinal direction <NUM> between a forward end <NUM> and an aft end <NUM>. The frame <NUM> may also extend along a lateral direction <NUM> between a first side <NUM> and a second side <NUM>. In this respect, the frame <NUM> generally includes a plurality of structural frame members <NUM>, such as beams, bars, and/or the like, configured to support or couple to a plurality of components. Furthermore, a hitch assembly <NUM> may be connected to the frame <NUM> and configured to couple the implement <NUM> to the vehicle <NUM>. Additionally, a plurality of wheel assemblies may be coupled to the frame <NUM>, such as a set of centrally located wheels <NUM> and a set of front pivoting wheels <NUM>, to facilitate towing the implement <NUM> in the direction of travel <NUM>.

In several embodiments, the frame <NUM> may support a cultivator <NUM>, which may be configured to till or otherwise break the soil over which the implement <NUM> travels to create a seedbed. In this respect, the cultivator <NUM> may include a plurality of ground engaging shanks <NUM>, which are pulled through the soil as the implement <NUM> moves across the field in the direction of travel <NUM>. In one embodiment, the ground engaging shanks <NUM> may be configured to be pivotably mounted to the frame <NUM> in a manner that permits the penetration depths of the ground engaging shanks <NUM> to be adjusted.

Moreover, as shown in <FIG> and <FIG>, the implement <NUM> may also include one or more harrows <NUM>. Specifically, in several embodiments, each harrow <NUM> may include a plurality of ground engaging tines <NUM> configured to engage to the surface of the soil within the field in a manner that levels or otherwise flattens any windrows or ridges in the soil created by the cultivator <NUM>. As such, the ground engaging tines <NUM> may be configured to be pulled through the soil as the implement <NUM> moves across the field in the direction of travel <NUM>. It should be appreciated that the implement <NUM> may include any suitable number of harrows <NUM>.

Further, in one embodiment, the implement <NUM> may include one or more baskets or rotary firming wheels <NUM>. In general, the basket(s) <NUM> may be configured to reduce the number of clods in the soil and/or firm the soil over which the implement <NUM> travels. Each basket <NUM> may form part of a basket assembly, including one or more basket frame members that rotatably couples the basket <NUM> to a portion of the implement <NUM>. For example, as shown, each basket <NUM> may be configured to be pivotably coupled to one of the harrows <NUM>. Alternatively, the basket(s) <NUM> may be configured to be pivotably coupled to the frame <NUM> or any other suitable location of the implement <NUM>. It should be appreciated that the implement <NUM> may include any suitable number of baskets <NUM>.

Additionally, the implement <NUM> may also include any number of suitable actuators (e.g., hydraulic cylinders) for adjusting the relative positioning, penetration depth, and/or down force associated with the various ground engaging tools of the implement <NUM> (e.g., ground engaging tools <NUM>, <NUM>, <NUM>). For instance, the implement <NUM> may include one or more first actuators <NUM> (<FIG>) coupled to the frame <NUM> for raising or lowering the frame <NUM> relative to the ground, thereby allowing the penetration depth and/or the down pressure of the shanks <NUM> and ground engaging tines <NUM> to be adjusted. Similarly, the implement <NUM> may include one or more second actuators <NUM> (<FIG>) coupled to the baskets <NUM> to allow the baskets <NUM> to be moved relative to the frame <NUM> such that the down pressure on the baskets <NUM> is adjustable.

In accordance with aspects of the present subject matter, one or more sensors, such as one or more vision sensor(s) <NUM>, may be provided in operative association with the implement <NUM>. For instance, <FIG> and <FIG> illustrate examples of various locations for mounting one or more vision sensor(s) <NUM> for capturing images of the field or other similar image-like data. Specifically, as shown in <FIG> and <FIG>, a first vision sensor 104A may be provided at a first location on the implement <NUM>, a second vision sensor 104B may be provided at a second location on the implement <NUM>, and a third vision sensor 104C may be provided at a third location on the implement <NUM>. Each of the first, second, and third vision sensors 104A, 104B, 104C is positioned at the aft end <NUM> of the implement <NUM>. Each vision sensor <NUM> has a field of view <NUM> directed at least partially downwardly towards the field surface. For instance, each of the first, second, and third vision sensors 104A, 104B, 104C has a respective field of view 106A, 106B, 106C generally directed towards the field surface. More particularly, in the illustrated embodiment, the field of view 106A, 106B, 106C of each of the vision sensors 104A, 104B, 104C is directed rearwardly of the implement <NUM>, particularly rearwardly of the baskets <NUM> along the direction of travel <NUM>. As such, the vision sensors 104A, 104B, 104C may be configured to capture data (e.g., vision-based data) indicative of one or more surface conditions of the field surface after the ground working operations of the implement <NUM>. Such data may then be used to determine field surface conditions, such as soil roughness, residue coverage, and/or clod sizes, after such ground working operations.

It should be appreciated that, while only three vision sensors <NUM> are illustrated as being associated with the implement <NUM>, any suitable number of vision sensors <NUM> may instead be associated with the implement <NUM>. It should further be appreciated that, while the vision sensors <NUM> associated with the implement <NUM> (i.e., the vision sensors 104A, 104B, 104C) are shown as only being positioned at the aft end of the implement <NUM>, the vision sensors <NUM> may be positioned elsewhere on the implement <NUM>, such as adj acent to any of the other ground engaging tools, such as the shanks <NUM> or the tines <NUM>, such as vision sensors <NUM>(<NUM>), <NUM>(<NUM>) shown in <FIG>.

Moreover, it should be appreciated that the vision sensors <NUM> may correspond to any suitable sensing devices configured to detect or capture image or image-like data indicative of the field surface conditions of the field. For example, the vision sensors <NUM> may correspond to any suitable device(s) configured to capture images or other image-like data of the field that allow characteristics of the soil surface such as surface roughness, clod sizes, or other soil features to be detected. For instance, in several embodiments, the vision sensor(s) may correspond to any suitable camera(s), such as single-spectrum camera or a multi-spectrum camera configured to capture images, for example, in the visible light range and/or infrared spectral range. Additionally, in a particular embodiment, the camera(s) may correspond to a single lens camera configured to capture two-dimensional images or a stereo camera(s) having two or more lenses with a separate image sensor for each lens to allow the camera(s) to capture stereographic or three-dimensional images. Alternatively, the vision sensor(s) <NUM> may correspond to any other suitable image capture device(s) and/or other vision sensor(s) capable of capturing "images" or other image-like data of the field. For example, the vision sensor(s) <NUM> may correspond to or include radio detection and ranging (RADAR) sensors and/or light detection and ranging (LIDAR) sensors.

In addition to the vision sensors <NUM>, one or more secondary sensor(s) <NUM> may be provided in operative association with the implement <NUM>, particularly the ground engaging tools of the implement <NUM> that ride along or roll on top of the field surface, in order to calibrate the results of the vision-based data. For example, one or more secondary sensors 108A may be mounted or positioned on one or more of the tines <NUM> and/or one or more secondary sensors 108B may be mounted on or positioned relative to one or more of the baskets <NUM>, such as on a member(s) supporting the basket(s). In general, such secondary sensor(s) 108A, 108B may also be configured to detect the movement of the associated ground engaging tool(s) as it rides or rolls along the surface, thereby providing an indication of the surface condition of the field. It should be appreciated that, while only two secondary sensor(s) <NUM> are illustrated as being associated with the implement <NUM>, any suitable number of secondary sensor(s) <NUM> may instead be associated with the implement <NUM>.

The secondary sensor(s) <NUM> may correspond to any suitable sensing devices configured to detect or capture data indicative of the movement of the associated ground surface engaging tool. For example, the secondary sensor(s) <NUM> may correspond to any suitable device(s) configured to collect tool movement data that allows the surface roughness and/or other soil surface characteristics to be detected. For instance, in several embodiments, the secondary sensor(s) <NUM> may correspond to or include one or more accelerometers, rotation sensors, load sensor(s), and/or the like. The accelerometer(s) may be used to detect the acceleration or movement of the associated ground surface engaging tool (e.g., as the tine(s) <NUM> deflect and/or as the basket(s) <NUM> move up and down along the field surface). Similarly, the rotation sensor(s) may be used to detect the angular position of the associated ground surface engaging tool (e.g., as the basket(s) <NUM> rotate about their attachment point to the frame <NUM>). Further, the load sensor(s) may be used to detect load(s) (e.g., stress or strain) on the associated ground surface engaging tool (e.g., as the tine(s) <NUM> bend or flex).

In general, as will be described in greater detail below, such displacement or movement-related parameters associated with the surface engaging tools (e.g., the acceleration or movement of the tine(s) <NUM> and/or basket(s) <NUM>, the angular movement or pivoting of the basket(s) <NUM>, and/or the load(s) on the tine(s) <NUM>) may be indicative of or otherwise associated with surface conditions of the field, such as surface roughness. Specifically, as the surface engaging tools are moved across the soil surface, the tools are displaced by the roughness of or variations in the soil surface within the field. Thus, as the magnitude of the displacement of the surface engaging tools increases, it may be inferred that the soil surface is rougher and/or has larger clods. Additionally, the frequency of such displacement may also be used to assess if there are patterns in the surface characteristics, which may indicate that the implement frame <NUM> is not properly leveled.

It should be appreciated that the configuration of the vehicle <NUM> and the implement <NUM> described above and shown in <FIG> and <FIG> are provided only to place the present subject matter in an exemplary field of use. Thus, it should be readily apparent that the present subject matter may be readily adaptable to any manner of machine configuration.

Referring now to <FIG>, a schematic view of one embodiment of a system <NUM> for determining surface conditions of a field is illustrated in accordance with aspects of the present subject matter. In general, the system <NUM> will be described with reference to the vehicle <NUM> and the implement <NUM> described above with reference to <FIG> and <FIG>. However, it should be appreciated by those of ordinary skill in the art that the disclosed system <NUM> may generally be utilized with agricultural machines having any other suitable machine configuration. Additionally, it should be appreciated that, for purposes of illustration, communicative links or electrical couplings of the system <NUM> shown in <FIG> are indicated by dashed lines.

As shown in <FIG>, the system <NUM> may include a controller <NUM> and various other components configured to be communicatively coupled to and/or controlled by the controller <NUM>, such as one or more sensors configured to capture data associated with the surface conditions of a field (e.g., vision sensor(s) <NUM>, secondary sensor(s) <NUM>), a user interface (e.g., user interface <NUM>), various components of the implement <NUM> (e.g., implement actuators <NUM>, <NUM>), and/or various components of the work vehicle <NUM> (e.g., vehicle drive component(s), such as the engine <NUM> and/or transmission <NUM> of the vehicle <NUM>). The user interface <NUM> described herein may include, without limitation, any combination of input and/or output devices that allow an operator to provide operator inputs to the controller <NUM> and/or that allow the controller <NUM> 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. For instance, as shown in <FIG>, the user interface <NUM> may include an electronic display 13A for displaying information to the operator and/or for receiving inputs from the operator.

In general, the controller <NUM> may correspond to any suitable processor-based device(s), such as a computing device or any combination of computing devices. Thus, as shown in <FIG>, the controller <NUM> may generally include one or more processor(s) <NUM> and associated memory devices <NUM> configured to perform a variety of computer-implemented functions (e.g., performing the methods, steps, algorithms, calculations and the like disclosed herein). As used herein, the term "processor" refers not only to integrated circuits referred to in the art as being included in a computer, but also refers to a controller, a microcontroller, a microcomputer, a programmable logic controller (PLC), an application specific integrated circuit, and other programmable circuits. Additionally, the memory <NUM> may generally comprise memory element(s) including, but not limited to, computer readable medium (e.g., random access memory (RAM)), computer readable nonvolatile medium (e.g., a flash memory), a floppy disk, a compact disc-read only memory (CD-ROM), a magneto-optical disk (MOD), a digital versatile disc (DVD) and/or other suitable memory elements. Such memory <NUM> may generally be configured to store information accessible to the processor(s) <NUM>, including data <NUM> that can be retrieved, manipulated, created and/or stored by the processor(s) <NUM> and instructions <NUM> that can be executed by the processor(s) <NUM>.

It should be appreciated that the controller <NUM> may correspond to an existing controller for the vehicle <NUM> or the implement <NUM> or may correspond to a separate processing device. For instance, in one embodiment, the controller <NUM> may form all or part of a separate plug-in module that may be installed in operative association with the vehicle <NUM> or the implement <NUM> to allow for the disclosed system and method to be implemented without requiring additional software to be uploaded onto existing control devices of the vehicle <NUM> or the implement <NUM>.

In several embodiments, the data <NUM> may be stored in one or more databases. For example, the memory <NUM> may include a vision database <NUM> for storing vision-based data received from the vision sensor(s) <NUM>. For example, the vision sensors <NUM> may be configured to continuously or periodically capture images of the field or other image-like data associated with the surface conditions of the field as an operation is being performed with the field. In such an embodiment, the data transmitted to the controller <NUM> from the vision sensor(s) <NUM> may be stored within the vision database <NUM> for subsequent processing and/or analysis. It should be appreciated that, as used herein, the terms vision-based data or image-like data may include any suitable type of data received from the vision sensor(s) <NUM> that allows for the field surface conditions of a field to be analyzed by an operator, including photographs or other images, RADAR data, LIDAR data, and/or other image-related data (e.g., scan data and/or the like).

Further, as shown in <FIG>, the memory <NUM> may include a secondary database <NUM>. The secondary database <NUM> may be configured to store secondary data received from the non-vision-based or secondary sensor(s) <NUM>. For example, the secondary sensor(s) <NUM> may be configured to continuously or periodically monitor movement of the associated surface engaging tool (e.g., tine(s) <NUM>, basket(s) <NUM>, etc.) as an operation is being performed within the field. In such an embodiment, the data transmitted to the controller <NUM> from the secondary sensor(s) <NUM> may be stored within the secondary database <NUM> for subsequent processing and/or analysis. It should be appreciated that, as used herein, the term secondary data may include any suitable type of non-vision-based data received from the secondary sensor(s) <NUM> that allows for the determination of surface conditions of a field, including acceleration data, rotational data, load data, and/or the like.

In several embodiments, the instructions <NUM> stored within the memory <NUM> of the controller <NUM> may be executed by the processor(s) <NUM> to implement a calibration module <NUM>. The calibration module <NUM> may generally be configured to calibrate or correct the initial field surface conditions determined from the vision-based data received from the vision sensor(s) <NUM> based on the secondary data received from the secondary sensor(s) <NUM>. For example, as discussed above with reference to <FIG> and <FIG>, the controller <NUM> may be configured to analyze the vision-based data to determine a vision-based surface condition corresponding to a characteristic of the field surface, such as surface roughness or clod size. For instance, the controller <NUM> may be configured to execute one or more image processing techniques to automatically identify the surface roughness of the field and characterize such surface roughness with a given numerical value, grade, and/or indicator. The controller <NUM> may similarly be configured to analyze the secondary data to determine a secondary surface condition corresponding to the characteristic of the field surface. For instance, the controller <NUM> may be configured to correlate the movement of the associated surface engaging tools detected based on the secondary data generated by the secondary sensor(s) to a surface roughness of the field.

It should be appreciated that the correlation between the movement of the ground engaging tools and the surface roughness of the field may be pre-determined from experimental data. For instance, in one embodiment, one or more data collection trials may be performed in which the implement <NUM> is moved across different portions of a field, with each portion representing a set or known surface roughness. The movement of the ground engaging tools may be monitored by the controller <NUM> based on the secondary data detected by the secondary sensor(s) <NUM> as the implement <NUM> is moved across the different portions of the field. The controller <NUM> may then be configured to generate a correlation between the movement of the ground engaging tools and the surface roughness across a range of surface roughnesses based on the monitored secondary data.

Moreover, in several embodiments, the calibration module <NUM> may be configured to determine a correction value or factor for adjusting or correcting the initial surface condition determined as a function of the vision-based data using the surface condition derived from the secondary data. For instance, the controller <NUM> may be configured to determine an error value or differential between the surface conditions determined based on vision-based data and the surface condition determined based on the secondary data. In one embodiment, the error or differential value may be used directly as the correction factor for subsequently adjusting the initial surface condition, or subsequent surface conditions, deriving from the vision-based data. Alternatively, in some embodiments, the controller <NUM> may derive the correction factor at least in part from the error or differential value, e.g., using one or more suitable data-analysis algorithms. The controller <NUM> may then correct or adjust the initial vision-based surface condition by applying the correction factor thereto, thereby allowing the initial vision-derived data to be corrected or calibrated based on the secondary data derived from the secondary sensor(s). For instance, the controller <NUM> may add or subtract the correction factor from the initial vision-based surface condition to determine a corrected surface condition. Given the established correlation between the secondary data and the monitored surface condition, the corrected surface condition will generally provide a more accurate representation of the surface conditions present within the field.

It should be appreciated that the calibration module <NUM> may perform the correction procedure described above as frequently as necessary to ensure that the field surface condition determined from the vision-based data is more accurate throughout a tillage operation. For instance, the calibration module <NUM> may perform the disclosed correction procedure continuously, periodically, or only as requested by the operator of the implement <NUM>.

Further, as shown in <FIG>, the controller <NUM> may also include a communications interface <NUM> to provide a means for the controller <NUM> to communicate with any of the various other system components described herein. For instance, one or more communicative links or interfaces (e.g., one or more data buses) may be provided between the communications interface <NUM> and the vision sensor(s) <NUM> to allow images or other vision-based data transmitted from the vision sensor(s) <NUM> to be received by the controller <NUM>. Similarly, one or more communicative links or interfaces (e.g., one or more data buses) may be provided between the communications interface <NUM> and the secondary sensor(s) <NUM> to allow data transmitted from the secondary sensor(s) <NUM> to be received by the controller <NUM>. Additionally, one or more communicative links or interfaces (e.g., one or more data buses) may be provided between the communications interface <NUM> and the user interface <NUM> to allow operator inputs to be received by the controller <NUM> and to allow the controller <NUM> to control the operation of one or more components of the user interface <NUM> (e.g., the display 13A when presenting surface condition data to the operator).

Additionally, as shown in <FIG>, one or more communicative links or interfaces (e.g., one or more data buses) may be provided between the communications interface <NUM> and the implement actuator(s) <NUM>, <NUM>, the vehicle drive component(s) <NUM>, <NUM>, and/or the like to allow the controller <NUM> to control the operation of such system components. For example, the instructions <NUM> stored within the memory <NUM> of the controller <NUM> may also be executed by the processor(s) <NUM> to implement a control module <NUM>. In general, the control module <NUM> may be configured to adjust the operation of the implement <NUM> by controlling one or more components of the implement <NUM> or the work vehicle <NUM>. Specifically, in several embodiments, the controller <NUM> may be configured to receive an input indicating that the monitored surface condition differs from a target or desired value or range.

In some embodiments, the controller <NUM> may be configured to automatically adjust the operation of the implement <NUM> based on the corrected surface condition determined using the vision-based data and as corrected based on the secondary date (e.g., using the correction factor). For example, in one embodiment, the controller <NUM> may be configured to compare the corrected surface condition to a predetermined threshold established for the monitored surface condition (e.g., a predetermined surface roughness threshold). In such an embodiment, the controller <NUM> may be configured to adjust the operation of the implement <NUM> when the corrected surface condition crosses the predetermined threshold, such as when a corrected surface roughness determined for the field exceeds a maximum surface roughness threshold. For instance, the controller <NUM> may extend or retract the frame actuator <NUM> in a manner that increases the aggressiveness of the tines <NUM> and/or extend or retract the basket actuators <NUM> in a manner that increases the down force applied to the baskets to reduce the surface roughness within the field. In another example, the operator may determine that the surface condition of the field is too smooth and may request that controller <NUM> execute appropriate control actions for increasing the roughness of the soil surface, such as by decreasing a down force applied to the tine(s) <NUM> and/or the basket(s) <NUM>.

Additionally or alternatively, the controller <NUM> may be configured to automatically adjust the operation of the vehicle <NUM> based on the corrected field surface condition. For example, as shown in <FIG>, the controller <NUM> may be configured to control an operation of one or more vehicle drive components, such as the engine <NUM> and/or the transmission <NUM> of the vehicle. In such embodiments, the controller <NUM> may be configured to control the operation of the vehicle drive component(s) <NUM>, <NUM> based on the corrected field surface condition, for example, to slow down the vehicle <NUM> and implement <NUM> and/or bring the vehicle <NUM> and implement <NUM> to a stop when it is determined that the field surface condition has cross a predetermined threshold and/or has fallen outside a target range.

Alternatively, in other embodiments, the controller <NUM> may be configured to receive a control action input from the operator associated with the selection of a specific control action for adjusting the operation of one or more of the components of the implement <NUM> or the vehicle <NUM> to improve the field surface conditions. For example, in one embodiment, an operator may determine that the corrected field surface condition is outside of desired tolerances and may instruct the controller <NUM> to execute a specific control action, such as the ones described above, to adjust the field surface conditions.

It should be appreciated that, depending on the type of controller being used, the above-described control actions may be executed directly by the controller <NUM> or indirectly via communications with a separate controller. For instance, when the controller <NUM> corresponds to an implement controller of the implement <NUM>, the controller <NUM> may be configured to execute the implement-related control actions directly while being configured to execute the vehicle-related control actions by transmitting suitable instructions or requests to a vehicle-based controller of the vehicle <NUM> towing the implement <NUM> (e.g., using an ISObus communications protocol). Similarly, when the controller <NUM> corresponds to a vehicle controller of the vehicle towing the implement <NUM>, the controller <NUM> may be configured to execute the vehicle-related control actions directly while being configured to execute the implement-related control actions by transmitting suitable instructions or requests to an implement-based controller of the implement <NUM> (e.g., using an ISObus communications protocol). In other embodiments, the controller <NUM> may be configured to execute both the implement-based control actions and the vehicle-based control actions directly or the controller <NUM> may be configured to execute both of such control action types indirectly via communications with a separate controller.

Referring now to <FIG> a flow diagram of one embodiment of a method <NUM> for determining field surface conditions is illustrated in accordance with aspects of the present subject matter. In general, the method <NUM> will be described herein with reference to the work vehicle <NUM> and the implement <NUM> shown in <FIG> and <FIG>, as well as the various system components shown in <FIG>. However, it should be appreciated that the disclosed method <NUM> may be implemented with work vehicles and/or implements having any other suitable configurations and/or within systems having any other suitable system configuration. In addition, although <FIG> depicts steps performed in a particular order for purposes of illustration and discussion, the methods discussed herein are not limited to any particular order or arrangement. One skilled in the art, using the disclosures provided herein, will appreciate that various steps of the method disclosed herein can be omitted, rearranged, combined, and/or adapted in various ways without deviating from the scope of the present disclosure.

As shown in <FIG>, at (<NUM>), the method <NUM> may include receiving vision-based data indicative of a field surface condition of a field. For instance, as described above, the controller <NUM> may be configured to receive an input(s) from one or more sensors configured to provide an indication of the surface condition of the field, such as by receiving vision-based data from one or more vision sensors <NUM> provided in operative association with the implement <NUM> that is indicative of the surface roughness within the field.

The method <NUM>, at (<NUM>), may further include receiving secondary data indicative of the field surface condition from a secondary sensor coupled to a ground engaging tool of an agricultural implement being moved across the field. For instance, as described above, the controller <NUM> may be configured to receive an input(s) from one or more non-vision-based sensors configured to provide an indication of displacement or movement of an associated surface engaging tool, such as by receiving secondary data from one or more secondary sensors <NUM> provided in operative association with the tines <NUM> and/or baskets <NUM>.

Further, at (<NUM>), the method <NUM> may include determining a correction factor associated with the field surface condition based at least in part on the secondary data. For instance, as described above, the controller <NUM> may be configured to analyze the vision-based data to determine a vision-based surface condition and the secondary data to determine a secondary surface condition. The controller <NUM> may then compare the vision-based surface condition to the secondary surface condition to determine a correction factor, which may, for example, be equal to the error or differential between the surface condition derived from the vision-based and non-vision-based sensor data.

Moreover, at (<NUM>), the method <NUM> may include determining a surface condition based at least in part on the vision-based data and the correction factor. As indicated above, the initial vision-based surface condition generated from the vision-based data may be corrected based on the correction factor. For example, in one embodiment, the correction factor may be added to or subtracted from each initial vision-based surface condition to determine an actual or corrected surface condition for the field.

Additionally, at (<NUM>), the method <NUM> may include adjusting an operation of one or more components of the agricultural implement based at least in part on the determined surface condition. For instance, as described above, the controller <NUM> may be configured to adjust the operation of the implement <NUM> and/or the work vehicle <NUM> in response to an input indicating that the corrected surface condition is not within tolerances. The input may be received from an operator of the implement <NUM> or may be automatically generated by the controller <NUM> based on the comparison of the corrected surface condition to one or more predetermined thresholds and/or target ranges.

It is to be understood that, in several embodiments, the steps of the method <NUM> are performed by the controller <NUM> 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 disc, solid-state memory, e.g., flash memory, or other storage media known in the art. Thus, in several embodiments, any of the functionality performed by the controller <NUM> described herein, such as the method <NUM>, are implemented in software code or instructions which are tangibly stored on a tangible computer readable medium. The controller <NUM> 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 controller <NUM>, the controller <NUM> may perform any of the functionality of the controller <NUM> described herein, including any steps of the method <NUM> described herein.

Claim 1:
A system (<NUM>) for determining field surface conditions, the system (<NUM>) comprising a frame member (<NUM>), a ground engaging tool (<NUM>) coupled to the frame member (<NUM>), the ground engaging tool (<NUM>) being configured to engage soil within a field as an agricultural implement (<NUM>) is moved across the field, and a vision sensor (<NUM>) having a field of view (<NUM>) directed towards a portion of a surface of the field, the vision sensor (<NUM>) being configured to capture vision-based data indicative of a field surface condition of the field, the system (<NUM>) being characterized by:
a secondary sensor (<NUM>) coupled to the ground engaging tool (<NUM>), the secondary sensor (<NUM>) being configured to capture secondary data indicative of the field surface condition; and
a controller (<NUM>) communicatively coupled to the vision sensor (<NUM>) and the secondary sensor (<NUM>), the controller (<NUM>) being configured to determine an initial surface condition associated with the field surface condition as a function of the vision-based data and to adjust the initial surface condition based at least in part on the secondary data received from the secondary sensor (<NUM>)
wherein :
- the controller (<NUM>) is configured to adjust the initial surface condition by determining a correction factor based on the secondary data received from the secondary sensor (<NUM>) and by applying the correction factor to the initial surface condition to determine a corrected surface condition,
- the secondary sensor (<NUM>) is provided in operative association with the ground-engaging tool (<NUM>) such that the secondary sensor (<NUM>) detects a parameter indicative of movement of the ground-engaging tool (<NUM>) as the ground-engaging tool (<NUM>) rides along a surface of the field.