Determination system and determination method

Abstract

To judge the quality of the shape of a formed material formed in a field by a working device.SOLUTION: The determination system S includes the arithmetic processing unit 20c that determines the shape of the formed object based on the matching process between the template image and the cross-sectional image of the terrain including the formed object formed in the field by the working device 2.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a system and method for determining the shape of a molded product molded in a field. [Background technology]

[0002] The agricultural vehicle disclosed in Patent Document 1 includes a direction specifying unit that specifies the direction of the ridges, and a travel control unit that controls the vehicle to travel in the direction of the ridges specified by the direction specifying unit. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2021-153567 Summary of the Invention [Problem to be solved by the invention]

[0004] The agricultural work vehicle of Patent Document 1 can identify the direction of formations (for example, ridges) formed in a field, but cannot determine whether the shape of the formations (for example, ridges) is good or bad.

[0005] The present invention has been made to solve the problems of the conventional technology, and aims to provide an evaluation system and evaluation method that can determine whether the shape of a molded product formed in a field by a work device is good or bad. [Means for solving the problem]

[0006] A determination system according to one aspect of the present invention includes a calculation processing unit that determines the shape of a formed object formed in a field by a working implement based on a matching process between a cross-sectional image of a terrain including the formed object and a template image.

[0007] In a determination method according to one aspect of the present invention, a calculation processing unit determines the shape of a formed object formed in a field by a working implement based on a matching process between a cross-sectional image of a terrain including the formed object and a template image. [Effects of the Invention]

[0008] According to the present invention, it is possible to determine whether the shape of a molded product molded in a field by a work device is good or bad. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is an overall view showing an example of a determination system. [Figure 2] FIG. 2 is a schematic side view showing the working machine. [Figure 3] FIG. 2 is a schematic plan view showing the working machine. [Figure 4] FIG. 2 is a rear perspective view of the position changing device. [Figure 5] FIG. 3 is a diagram illustrating an example of a sensing range of a sensing device provided in a work machine. [Figure 6] FIG. 10 is a diagram illustrating a worked area. [Figure 7] FIG. 2 is a diagram illustrating a planned driving route. [Figure 8A] FIG. 10 is a diagram showing an example of acquiring a cross-sectional image of the terrain from point cloud data sensed from behind by a work machine performing ridge-making work. [Figure 8B] 10A and 10B are diagrams illustrating an example of a matching process between a cross-sectional image and a template image. [Figure 8C] FIG. 10 is a diagram showing an example of an estimation result of an abnormality location by matching processing. [Figure 9A] FIG. 1 is a diagram showing point cloud data (terrain image) showing a terrain including kamaboko-shaped ridges. [Figure 9B] 9B is a diagram showing an example of a cross-sectional image obtained by cutting the point cloud data in FIG. 9A at the thick line portion. FIG. [Figure 9C] FIG. 10 is a diagram showing an example of a kamaboko-shaped template image. [Figure 9D]10A and 10B are diagrams showing an example of a matching relationship and a contour difference image when the evaluation result of the ridge is OK. [Figure 9E] 10A and 10B are diagrams showing an example of a matching relationship and a contour difference image when the evaluation result of the ridge is NG. [Figure 10A] FIG. 1 is a diagram showing point cloud data (terrain image) showing a terrain including trapezoidal ridges. [Figure 10B] 10B is a diagram showing an example of a cross-sectional image obtained by cutting the point cloud data in FIG. 10A at the thick line portion. FIG. [Figure 10C] FIG. 10 is a diagram illustrating an example of a trapezoidal template image. [Figure 10D] 10A and 10B are diagrams showing an example of a matching relationship and a contour difference image when the evaluation result of the ridge is OK. [Figure 10E] 10A and 10B are diagrams showing an example of a matching relationship and a contour difference image when the evaluation result of the ridge is NG. [Figure 11] FIG. 10 is a diagram showing the relationship between all point cloud data obtained by the second sensing device and a region of interest. [Figure 12A] FIG. 10 is a diagram showing that the region of interest moves as the tractor moves, and showing the superposition of two regions of interest where the tractor is in a different position. [Figure 12B] FIG. 10 is a diagram illustrating an example of point cloud data when regions of interest are not superimposed. [Figure 12C] FIG. 10 is a diagram illustrating an example of point cloud data when regions of interest are superimposed. [Figure 13] 10A and 10B are diagrams for explaining how a comparison position is specified by scanning a template image with respect to a cross-sectional image. [Figure 14] 10 is a flowchart for changing the traveling state of the traveling vehicle body based on the evaluation results when ground work is performed by the ridge-forming device. [Figure 15] 10A and 10B are diagrams illustrating the difference between determining the shape of a single ridge by visual inspection and by automatic detection, based on a series of difference images. [Figure 16A] FIG. 10 is a diagram showing point cloud data (topographical image) showing kamaboko-shaped ridges. [Figure 16B]FIG. 16B is a diagram showing an example of a shape defect location in the point cloud data (topographical image) shown in FIG. 16A. [Figure 16C] 10A and 10B are diagrams illustrating an example of a matching relationship between a cross-sectional image of a shape-defective portion of a ridge and a template image. [Figure 17A] FIG. 10 is a diagram showing point cloud data (topographical image) showing trapezoidal ridges. [Figure 17B] 17B is a diagram showing an example of a shape defect location in the point cloud data (topographical image) shown in FIG. 17A. FIG. [Figure 17C] 10A and 10B are diagrams illustrating an example of a matching relationship between a cross-sectional image of a shape-defective portion of a ridge and a template image. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0011] FIG. 1 is an overall view showing an example of a determination system S in this embodiment. The determination system S is a device that determines the shape of a molded object M (e.g., a ridge M1) in a field H1. In this embodiment, a work machine 1 is equipped with the determination system S. Note that a server 50, which will be described later, may be equipped with part of the determination system S (e.g., a position estimation unit 20a, an automatic driving control unit 20b, and / or an arithmetic processing unit 20c). The determination system S may also be configured by the work machine 1 and the server 50 working together.

[0012] First, we will explain the work machine 1. The work machine 1 is a vehicle that can perform work while traveling, and in this embodiment is a tractor to which a work device 2 (implement) can be attached to a traveling body 3 (machine body). Note that the work machine 1 is not limited to a tractor, and can be any vehicle that can perform work while traveling. For example, the work machine 1 may be an agricultural machine such as a combine harvester or rice transplanter, or a construction machine such as a compact track loader or backhoe.

[0013] Fig. 2 is a schematic side view of the work machine 1. Fig. 3 is a schematic plan view of the work machine 1. In the description of this embodiment, the direction toward which an operator seated in the driver's seat 10 of the work machine 1 faces (the left side in Figs. 2 and 3) is referred to as the front, and the opposite direction (the right side in Figs. 2 and 3) is referred to as the rear. The left side of the operator (the front side in Fig. 2, the bottom side in Fig. 3) is referred to as the left side, and the right side of the operator (the back side in Fig. 2, the top side in Fig. 3) is referred to as the right side. In addition, the horizontal direction perpendicular to the front-to-rear direction is referred to as the width direction.

[0014] As shown in Figures 2 and 3, the work machine 1 is equipped with a traveling body 3 having a traveling device 7, a prime mover 4, and a transmission 5. The traveling device 7 is driven to provide propulsion force to the traveling body 3. The traveling device 7 is a wheeled traveling device 7 in which the front wheels 7F and the rear wheels 7R are configured as tires. The front wheels 7F and the rear wheels 7R are each provided as a pair, spaced apart in the width direction. As another example, a traveling device 7 in which the front wheels 7F and / or the rear wheels 7R are configured as crawlers may be used. The traveling body 3 is capable of traveling forward and backward by being driven by the traveling device 7.

[0015] A prime mover 4 is built into the front of the traveling vehicle body 3. The prime mover 4 is configured as, for example, a diesel engine. As another example, the prime mover 4 may be configured as another internal combustion engine such as a gasoline engine, an electric motor, or the like.

[0016] The transmission 5 changes the speed of the power output by the prime mover 4 by switching between gear positions, making it possible to switch the propulsive force of the traveling device 7 and change the switching state of the traveling device 7 (switching the traveling device 7 to forward or reverse). The transmission 5 also transmits the power of the prime mover 4 to the PTO shaft 6. The PTO shaft 6 is an output shaft that is connected to the working device 2 and drives the working device 2.

[0017] A protection mechanism 9 for protecting the driver's seat 10 is provided on the upper part of the traveling vehicle body 3. The protection mechanism 9 is, for example, a cabin 9A that surrounds the periphery of the driver's seat 10. The driver's seat 10 is provided inside the cabin 9A. Note that the protection mechanism 9 is not limited to the cabin 9A, and may be a canopy or a rope erected behind the driver's seat 10.

[0018] The working implement 2 is attached to the traveling body 3. In the tractor of this embodiment, the working implement 2 is detachably attached to the traveling body 3. Specifically, a coupling device 8 to which the working implement 2 can be detachably attached is provided at the front and / or rear of the traveling body 3. In the example shown in Figures 2 and 3, the coupling device 8 is provided at the rear of the traveling body 3. Therefore, the working machine 1 can couple the working implement 2 to the coupling device 8 and tow the coupled working implement 2 by driving the traveling device 7.

[0019] 2 and 3, a position changing device 8A configured with a three-point link mechanism is shown as an example of the coupling device 8. This position changing device 8A is a lifting device that changes the relative position between the traveling body 3 and the working device 2 by raising and lowering the working device 2 relative to the traveling body 3. Below, the position changing device 8A configured with a three-point link mechanism will be described in detail.

[0020] 4 is a perspective view of the position changing device 8A as seen from the rear. The position changing device 8A has a lift arm 8a, a lower link 8b, a top link 8c, a lift rod 8d, and a lift cylinder 8e.

[0021] The front end of the lift arm 8a is supported at the upper rear part of the case (transmission case) that houses the transmission 5 so that it can swing upward or downward. The lift arm 8a swings (lifts and lowers) when driven by a lift cylinder 8e. The lift cylinder 8e is composed of a hydraulic cylinder. As shown in FIG. 1, the lift cylinder 8e is connected to a hydraulic pump via a control valve 34. The control valve 34 is an electromagnetic valve or the like, and extends and retracts the lift cylinder 8e.

[0022] The front end of lower link 8b is supported on the rear lower part of transmission 5 so as to be swingable upward or downward. The front end of top link 8c is supported on the rear part of transmission 5 above lower link 8b so as to be swingable upward or downward. Lift rod 8d connects lift arm 8a and lower link 8b. The rear part of lower link 8b and the rear part of top link 8c are formed in a hook shape.

[0023] When the lift cylinder 8e is driven (extends and retracts), the lift arm 8a moves up and down, and the lower link 8b connected to the lift arm 8a via the lift rod 8d also moves up and down, causing the working device 2 to swing (lift and lower) upward or downward with the front part of the lower link 8b as a fulcrum.

[0024] In the above explanation, the position changing device 8A configured as a three-point link mechanism has been described as an example of the coupling device 8, but the coupling device 8 may be any device that is at least capable of coupling the working device 2 to the traveling body 3. For example, the coupling device 8 may be configured as a swing drawbar or the like that couples the working device 2 to the traveling body 3 without changing the relative positions of the working device 2 and the traveling body 3.

[0025] The work device 2 is a device that performs work on a work field H (e.g., a field H1) or a work object in the work field H (e.g., crops planted in the field H1, etc.). The work device 2 is a tillage device that performs tillage work, a ridge forming device that forms ridges, a furrow cutting device that cuts furrows, a harvesting device that harvests crops, a reaping device that cuts grass etc., a spreading device that spreads grass etc., a grass collecting device that collects grass etc., a shaping device that shapes grass etc., a fertilizer spreading device that spreads fertilizer, a pesticide spreading device that sprays pesticides, a separating device that separates crops, etc. In this embodiment, the work device 2 is a ridge forming device that forms ridges in the field H1.

[0026] Although the above description is of a case where the work machine 1 is a tractor and the work implement 2 is coupled to the coupling device 8, the work implement 2 is not limited to an implement coupled to the traveling body 3 by the coupling device 8. For example, the work implement 2 may be a front loader attached to the front of the traveling body 3.

[0027] Furthermore, the working device 2 may be any device that is provided on the working machine 1 and performs work at the work site H, and does not have to be a device that can be attached to and detached from the traveling body 3 like an implement. For example, if the working machine 1 is a combine harvester, the working device 2 includes a harvesting device that harvests crops. If the working machine 1 is a rice transplanter, the working device 2 includes a planting device that plants seedlings. If the working machine 1 is a backhoe or compact track loader, the working device 2 can be an attachment that can be attached to the position changing device 8A (such as an arm or boom).

[0028] 1, the work machine 1 is equipped with a steering device 11. The steering device 11 has a handle 11a (steering wheel), a steering shaft 11b (rotating shaft) that rotates in conjunction with the rotation of the handle 11a, and an assist mechanism 11c (power steering mechanism) that assists in steering the handle 11a.

[0029] The assist mechanism 11c includes a control valve 35 and a steering cylinder 32. The control valve 35 is, for example, a three-position switching valve that can be switched by moving a spool or the like. The control valve 35 can also be switched by steering the steering shaft 11b. The steering cylinder 32 is connected to an arm 36 (knuckle arm) that changes the direction of the front wheels 7F. Therefore, by rotating the steering wheel 11a, the switching position and opening degree of the control valve 35 are switched in response to the operation, and the steering cylinder 32 extends or retracts to the left or right depending on the switching position and opening degree of the control valve 35, making it possible to change the steering direction of the front wheels 7F.

[0030] The above-described steering device 11 is an example and is not limited to the above-described configuration. For example, if the traveling device 7 can change the rudder angle by differentiating the propulsive force in one direction and the propulsive force in the other direction in the width direction, the traveling device 7 may also be configured to function as the steering device 11.

[0031] As shown in FIG. 1, the work implement 1 includes a control device 20 and a storage device 21. The control device 20 includes one or more processors. The control device 20 is a controller for the work implement 1 and performs various controls related to the work implement 1. The control device 20 is communicably connected to each device and apparatus mounted on the work implement 1 via an in-vehicle network such as CAN, ISOBUS, LIN, or FlexRay. For example, the control device 20 performs control processing (operations) of the work implement 2, prime mover 4, transmission 5, position change device 8A, steering device 11, etc., based on a signal (operation signal) input from an operation device.

[0032] The control device 20 includes one or more memories, various analog circuits, various digital circuits, etc. The one or more memories store (memorize) software programs and various data to be executed by one or more processors. The control device 20 can read software programs from one or more memories using one or more processors and execute various processes based on the software programs. Note that the control device 20 may also be able to execute various processes based on predetermined logic circuits using one or more processors.

[0033] The processor may be, for example, a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a field programmable gate array (FPGA), or an application specific integrated circuit (ASIC).

[0034] The control device 20 may execute various processes by having multiple physically separated processors cooperate with each other, and the configuration is not limited to the configuration described above. In such a case, the multiple processors are mounted on one or more computers that are physically separated from the work machine 1, and these processors are connected to each other so as to be able to communicate with each other via a network such as an in-vehicle network, a LAN, a WAN, or the Internet.

[0035] In addition, the software program may be stored in a storage device 21 (non-volatile memory such as HDD, SSD, CD-ROM, DVD-ROM, etc.) communicatively connected to the control device 20, or in an external server 50 connected via the network, and installed from there into the memory.

[0036] As shown in FIG. 1, the work machine 1 is equipped with one or more sensing devices 25. The sensing devices 25 sense the surroundings of the work machine 1. Specifically, the sensing devices 25 perform sensing by measuring the distance to the environment (surrounding objects) surrounding the work machine 1. The sensing devices 25 are distance measurement sensors that measure the distance to at least a portion of the surroundings of the work machine 1. The sensing devices 25 can measure the distance to at least a portion of the surroundings of the work machine 1 and detect point cloud data of the environment surrounding the work machine 1.

[0037] The sensing device 25 is connected to the control device 20 via wire or wireless communication so as to be able to communicate with the control device 20, and outputs sensing results to the control device 20. The sensing device 25 includes an optical distance measuring sensor, a signal processing circuit, etc. The optical distance measuring sensor of the sensing device 25 can be, for example, a LiDAR (Light Detection And Ranging).

[0038] A LIDAR (laser sensor) emits pulsed measurement light (laser light) millions of times per second from a light source such as a laser diode, and reflects the measurement light with a rotating mirror to scan horizontally or vertically and project it over a predetermined detection range (sensing range, e.g., 360°). The LIDAR then receives the measurement light reflected by an object with a light-receiving element. A signal processing circuit detects the distance to the object based on the time between when the LIDAR emits the measurement light and when it receives the reflected light (ToF (Time of Flight) method).

[0039] In addition to LIDAR, a ToF camera can be exemplified as the optical distance measuring sensor of the sensing device 25. In the above example, the sensing device 25 has an optical distance measuring sensor, but instead of the optical distance measuring sensor, an acoustic distance measuring sensor (for example, an airborne ultrasonic sensor such as a sonar) may be used.

[0040] FIG. 5 is a diagram showing an example of a sensing range Es of a sensing device 25 provided on the work machine 1. One or more sensing devices 25 are provided on the work machine 1, and the sensing range Es is sensed by the one or more sensing devices 25. The sensing range Es includes at least the worked area Ea where the work machine 1 (work machine 2) has performed work. The sensing device 25 also senses a position estimation range Eb, which is a range necessary to estimate the position of the work machine 1 on which the sensing device 25 is provided. An example of the position estimation range Eb is the range in the direction of travel of the work machine 1.

[0041] Note that Figure 5 is merely for the purpose of explaining the sensing range Es, and the sensing range Es, worked area Ea, and position estimation range Eb are not limited to the examples shown in Figure 5. The distance that the sensing device 25 can sense also varies depending on the distance measuring sensor adopted as the sensing device 25.

[0042] The work implement 1 performs work while traveling. For this reason, a work execution range Ea1, which is the area in which the work implement 1 can perform work (the area in which the work implement 2 of the work implement 1 performs work at a predetermined position), moves as the work implement 1 travels. The work execution range Ea1 is the range in which the work implement 2 performs work at a predetermined position, in other words, at a predetermined time, when the work implement 1 performs work while traveling. In other words, the work execution range Ea1 means the range in which the work implement 1 at a predetermined position (time) acts on an object (the field H1, crops planted in the field H1, weeds in the field H1, etc.).

[0043] Therefore, as the work implement 1 moves, the range to which the work execution range Ea1 moves can be said to be formed as a worked area Ea in the work site H. Furthermore, the work execution range Ea1 corresponding to the current position of the work implement 1 is included as part of the worked area Ea. In other words, the work execution range Ea1 does not mean the entire range in which the work implement 1 performs a series of tasks in the work site H (field H1).

[0044] In the example shown in FIG. 5, for convenience of explanation, the work execution range Ea1 is shown as a substantially rectangular range in a plan view, but this is not limited thereto. The work execution range Ea1 varies depending on the type of work implement 2 and the work content, and may be substantially circular or irregularly shaped. The work execution range Ea1 also varies depending on the work target (the location where work is performed) of the work implement 2. That is, when the work implement 2 performs work on the ground of the field H1, such as with a tilling implement, ridge-making implement, or harvesting implement, the work execution range Ea1 is the ground of the field H1, and therefore the worked area Ea is the part of the ground of the field H1 where the work implement 2 has performed work. Furthermore, when the work implement 2 performs work on areas other than the ground of the field H1, such as with a fruit harvesting implement, the work execution range Ea1 is fruit trees and the like other than the ground, and therefore the worked area Ea is the part of these work targets where the work implement 2 has performed work. In this embodiment, the working device 2 is a ridge-forming device, and therefore the worked area Ea includes the ridges M1 formed by the ridge-forming device.

[0045] 6 is a diagram illustrating the completed work area Ea. Here, regardless of the arrangement of the work device 2 relative to the work machine 1, when the work machine 1 performs work while traveling in a predetermined direction of travel, the work machine 1 moves away from the location where work has already been performed as it travels in the direction of travel. Therefore, when the work machine 1 performs work at a predetermined first position P1 and then moves from the first position P1 in the direction of travel, the sensing device 25 attached to the work machine 1 moves away from the work execution range Ea1 at the first position P1.

[0046] At this time, as viewed from the sensing device 25, the work machine 1 and / or work device 2 passes through at least a portion of the work execution range Ea1 (t=1) at the first position P1, and at a predetermined second position P2 on the traveling direction side of the first position P1, at least a portion of the work execution range Ea1 (t=1) appears from the work machine 1 and / or work device 2. The example shown in FIG. 6 shows a state in which, when the work machine 1 moves to the second position P2 on the traveling direction side (front side), the work execution range Ea1 (t=1) appears behind the work device 2 as viewed from the sensing device 25. For this reason, it is preferable that one or more sensing devices 25 be able to sense a range that includes the opposite side of the traveling direction as the sensing range Es.

[0047] 5 shows a case where the work implement 2 is attached to the rear of the traveling body 3 and the sensing device 25 senses the area behind the work machine 1 and the work implement 2, but the range of the sensing range Es that includes the side opposite the direction of travel is not limited to the rear of the work implement 1 and the work implement 2. For example, if the work implement 2 is attached offset in the width direction from the traveling body 3, in other words, if the work execution range Ea1 is offset in the width direction from the traveling body 3, the range of the sensing range Es that includes the side opposite the direction of travel will include the work execution range Ea1 that is offset in the width direction from the traveling body 3.

[0048] In this embodiment, the direction of travel of the work implement 1 is either forward or backward. Therefore, the sensing device 25 can sense an area around the work implement 1 that includes at least the front and rear of the work implement 1. In the example shown in FIGS. 2 and 3, two sensing devices 25 are provided on the work implement 1, one sensing device 25 (first sensing device 25a) senses the front, and the other sensing device 25 (second sensing device 25b) senses the rear. For example, the first sensing device 25a is provided in the front part of the roof 9a of the cabin 9A. The second sensing device 25b is provided in the rear part of the roof 9a.

[0049] The first sensing device 25a masks an area for detecting devices and equipment, such as the cabin 9A including the roof 9a, provided on the work machine 1. For this reason, the first sensing device 25a senses a range (for example, 180°) substantially in front of the work machine 1, and detects point cloud data of the sensing range Es.

[0050] The second sensing device 25b masks the area in which to detect devices and equipment provided on the work implement 1, such as the cabin 9A including the roof 9a. At this time, the second sensing device 25b may acquire the position of the work implement 2 connected to the position change device 8A and mask the area in which to detect the work implement 2. For this reason, the second sensing device 25b senses a range (for example, 180°) approximately behind the work implement 1 and detects point cloud data of the sensing range Es.

[0051] With the above configuration, in this embodiment, the first sensing device 25a and the second sensing device 25b can perform sensing of approximately 360° around the work machine 1. Note that one or more sensing devices 25 may be provided on the work machine 1, and it is sufficient that the surroundings of the work machine 1 can be sensed by one or more sensing devices 25. The sensing range Es is not limited to approximately 360° around the work machine 1, and the mounting position of the sensing device 25 is not limited to the above-mentioned position. In FIG. 5, the sensing range Es may include blind spots and is approximately 360° around the work machine 1, but is not limited to this. Note that in this embodiment, the work machine 2 is a ridge-forming device. Therefore, the sensing range Es is sufficient as long as it is a range in which at least the molded object M (e.g., ridge M1) can be detected. Here, the sensing range Es is the range on the side of the work implement 1 where the work tool 2 is placed, and is, for example, approximately 180° behind the periphery of the work implement 1, but it may also be 90° or the like and is not limited to these numerical values. The second sensing device 25b acquires point cloud data that indicates at least the topography of the periphery of the work implement 2. Furthermore, the second sensing device 25b acquires point cloud data that indicates the topography of the field H1 including the ridges M1 formed by the work implement 2 (ridge-forming device).

[0052] As shown in FIG. 1, the work implement 1 is equipped with an imaging device 26. The imaging device 26 may be a CCD camera equipped with a CCD (Charge Coupled Device) image sensor, a CMOS camera equipped with a CMOS (Complementary Metal Oxide Semiconductor) image sensor, or the like. The imaging device 26 is provided at the rear of the roof 9a. The imaging device 26 captures an image behind the work implement 1, and the captured image includes ridges M1 formed in the field H1 by the work implement 2 (ridge-forming device). The second sensing device 25b and the imaging device 26 are arranged adjacent to each other vertically or horizontally at the rear of the roof 9a. Therefore, the point cloud data of the sensing range Es captured by the second sensing device 25b and the captured image captured by the imaging device 26 are from approximately the same measurement point (viewpoint).

[0053] Furthermore, when a rope is provided as the protection mechanism 9, a single sensing device 25 may be provided on top of the rope. Alternatively, a sensing device 25 may be provided on mounting structures extending outward in the width direction of the traveling body 3 at the front and rear of the traveling body 3, with a pair of sensing devices 25 at each of the front and rear of the traveling body 3, positioned at a distance outward in the width direction from the traveling body 3. Furthermore, one or more sensing devices 25 may be provided on the working device 2 that is detachable from the traveling body 3. Furthermore, the second sensing device 25b and the imaging device 26 are arranged adjacent to each other vertically or horizontally above the rope.

[0054] As shown in Fig. 1, the determination system S for the work machine 1 includes a position estimation unit 20a that estimates the position of the work machine 1 based on the sensing results of the sensing device 25. The position estimation unit 20a is, for example, a software program implemented in the control device 20. As another example, if the work machine 1 is connected to an information processing device such as an external server 50 so that it can communicate directly or indirectly with the work machine 1, the position estimation unit 20a may be provided in the server 50 or the like external to the work machine 1. In the following explanation, an example will be described in which the position estimation unit 20a is provided in the control device 20 (work machine 1), and detailed explanations of other examples will be omitted.

[0055] The position estimation unit 20a estimates the position of the work machine 1 based on the sensing results of the sensing device 25 and environmental map information. The position estimation unit 20a estimates the position based on the sensing results of the sensing device 25 (ranging signals obtained from the ranging sensor), environmental map information, and a SLAM (Simultaneous Localization and Mapping) algorithm.

[0056] The environmental map information is map information that shows objects in the environment around the work field H, including the work field H where the work machine 1 performs work, and is generated from point cloud data. Taking an example where the work field H is a field H1 and the environmental map information shows the environment around the field H1, including the field H1, the environmental map information shows the ground around the field H1, the crops planted in the field H1, the ridges M1 formed in the field H1, the ridges around the field H1, the fences around the field H1, the weeds on the ground around the field H1, the barns around the field H1, etc. as a three-dimensional point cloud. The environmental map information is generated in advance based on the sensing results of the sensing device 25 and stored in the storage device 21. Note that the environmental map information stored in the storage device 21 may be generated based on the sensing results of the sensing device 25 of another work machine 1, etc.

[0057] In estimating the position of the work machine 1, the position estimation unit 20a acquires point cloud data (detected point cloud data) from the sensing results of the sensing device 25 of the work machine 1 and aligns (matches) the acquired detected point cloud data with the point cloud data of the environmental map information, thereby estimating the position of the work machine 1. The position estimation unit 20a estimates a predetermined position of the work machine 1 as the position estimation of the work machine 1.

[0058] Furthermore, the position estimation unit 20a may estimate (position estimate) the position (estimated position EP) of the work machine 1 (traveling body 3) based on its own position detected by a position detection device 27 attached to the work machine 1 using a satellite positioning system (positioning satellite) such as D-GPS, GPS, GLONASS, Beidou, Galileo, or Michibiki, that is, the position (e.g., latitude, longitude) of the GPS antenna. In this case, the own position (e.g., latitude, longitude) detected by the position detection device 27 may be used, and the sensing results of the sensing device 25 and environmental map information may not be used.

[0059] 1, the control device 20 has an automatic driving control unit 20b. The automatic driving control unit 20b is composed of electric and electronic circuits, a CPU, and programs stored in a memory, which are provided in the control device 20.

[0060] The automatic driving control unit 20b controls the automatic driving of the work machine 1 (hereinafter referred to as automatic driving control). The automatic driving control unit 20b can execute line-type automatic driving control and / or autonomous-type automatic driving control. To explain automatic driving using line-type automatic driving control as an example, the automatic driving control unit 20b controls the devices and apparatuses provided in the work machine 1 based on the estimated position EP and a predefined planned driving route L so that the traveling vehicle body 3 travels along the planned driving route L. For example, as automatic driving control, the automatic driving control unit 20b controls the steering angle and driving speed (vehicle speed) of the traveling vehicle body 3.

[0061] The planned travel route L may be stored in advance in the storage device 21, or may be created (defined) based on an estimated position EP estimated by the position estimation unit 20a when the work machine 1 actually travels. The planned travel route L may also be created based on information input via an input interface.

[0062] The input interface is, for example, a display device 15 that is provided in the work machine 1 and that allows input operations. The display device 15 has, in addition to a display screen that displays an image, for example, a touchpad or hardware switches. The input interface is sufficient as long as it allows at least the input operation of information and the input information can be acquired by the control device 20, and may be an operable terminal such as a smartphone that is communicatively connected to the control device 20. The input interface may also be a communication device that can communicate with an external server 50 or the like, and the communication device may receive the planned travel route L managed by the external server 50 or the like.

[0063] During automatic driving control, the automatic driving control unit 20b controls the steering angle so that the positional deviation between the estimated position EP and the planned traveling route L is less than a threshold value. In other words, when the positional deviation between the estimated position EP and the planned traveling route L is less than the threshold value, the automatic driving control unit 20b controls the control valve 35 of the steering device 11 to maintain the steering angle. On the other hand, when the positional deviation between the estimated position EP and the planned traveling route L is equal to or greater than the threshold value, the automatic driving control unit 20b controls the control valve 35 of the steering device 11 to change the steering angle in a direction that reduces the positional deviation.

[0064] Further, regarding the automatic driving control when the work implement 1 works in the field H1, the automatic driving control unit 20b performs automatic driving control, for example, so that the work implement 1 travels back and forth between one end and the other end of the work field H (field H1). Fig. 7 is a diagram illustrating a planned travel route L. As shown in Fig. 7, the planned travel route L in the field H1 includes a straight section L1 that travels from one end of the field H1 to the other, and a turning section L2 that connects one straight section L1 with the other straight section L1.

[0065] The automatic driving control unit 20b may control the work device 2, the position change device 8A, etc., depending on the position of the work implement 1 on the planned travel route L, etc., and control the work performed by the work device 2. The automatic driving control unit 20b can control the execution and stopping of work by the work device 2. The automatic driving control unit 20b can control the drive of the position change device 8A (lifting device) and the PTO shaft 6, and switch between a working state in which the work device 2 performs work and a non-working state in which the work device 2 does not perform work.

[0066] Taking the example of the working device 2 being a tilling device or a ridge-making device that is towed by the working machine 1 and performs work while in contact with or embedded in the ground, the automatic driving control unit 20b can use the position change device 8A to lower the working device 2 to the ground to switch it to a working state, or use the position change device 8A to raise the working device 2 from the ground to switch it to a non-working state.

[0067] Furthermore, when the working device 2 is a working device 2 that is driven by power transmitted from the PTO shaft 6 or by a built-in actuator (e.g., an electric actuator), such as a rotary tiller or a molding device, the automatic driving control unit 20b can switch between a working state and a non-working state by controlling these power sources (PTO shaft 6, actuator, etc.).

[0068] For example, the automatic driving control unit 20b switches to the working state when the estimated position EP is located on the straight section L1, and switches to the non-working state when the estimated position EP is located on the turning section L2.

[0069] The automatic driving control unit 20b may switch between the working state and the non-working state according to the areas defined in the field map, regardless of the position of the estimated position EP on the planned travel route L. For example, the area where work is performed (working area Ha) is defined as the area inside the headland of the field H1. Furthermore, the area where work is not performed (non-working area Hb) is defined as the headland, entrances and exits of the field H1, and places where work has already been performed. Note that the above-mentioned working area Ha and non-working area Hb are merely examples, and the working area Ha may, for example, include the headland.

[0070] In the above-described embodiment, automatic driving has been explained using line-type automatic driving control as an example, but in autonomous automatic driving control, the automatic driving control unit 20b controls each device and apparatus provided in the work machine 1 to perform work within the field H1 based on the estimated position and sensing results, regardless of the planned driving route L.

[0071] The work machine 1 may also employ a display device 15 that displays the current position of the work machine 1 on a field map based on the estimated position EP estimated by the position estimation unit 20a and a field map showing the field H1. The display device 15 may be a display placed near the driver's seat 10 of the work machine 1, or may be a mobile terminal carried by the worker or a manager's terminal that monitors the work of the work machine 1. Examples of mobile terminals and manager's terminals include terminals such as smartphones (multi-function mobile phones), tablets, and PDAs, as well as fixed computers such as personal computers.

[0072] The work machine 1 has a communication device 29. The communication device 29 is a communication module that performs either direct communication or indirect communication with the server 50, and can perform wireless communication using, for example, the IEEE802.11 series of communication standards, such as Wi-Fi (Wireless Fidelity, registered trademark), BLE (Bluetooth (registered trademark) Low Energy), LPWA (Low Power, Wide Area), and LPWAN (Low-Power Wide-Area Network). The communication device 29 can also perform wireless communication using, for example, a mobile phone communication network or a data communication network.

[0073] The server 50 has a communication device 51 and a storage device 52. Similar to the communication device 29, the communication device 51 is a communication module that performs either direct communication or indirect communication with the work machine 1. The communication device 51 can perform wireless communication via, for example, a mobile phone communication network or a data communication network. The storage device 52 is, for example, a hard disk drive (HDD) or a solid state drive (SSD).

[0074] As shown in FIG. 1, the determination system S of the work implement 1 includes a calculation processing unit 20c. FIG. 8A is a diagram showing an example of acquiring a cross-sectional image G of the terrain from point cloud data rearward sensed by the work implement 1 during ridge-forming work. FIG. 8B is a diagram showing an example of matching processing between the cross-sectional image G and a template image TP. The calculation processing unit 20c determines the shape of the formed object M (e.g., ridge M1) formed in the field H1 by the work implement 2 based on matching processing between the cross-sectional image G of the terrain including the formed object M (e.g., ridge M1) and the template image TP. For example, the control device 20 functions as the calculation processing unit 20c when a processor of the control device 20 executes a determination program. The calculation processing unit 20c is, for example, a software program implemented in the control device 20. Furthermore, when the work implement 1 is directly or indirectly connected to an external server 50 or the like so as to be able to communicate with the external server 50 or the like, the calculation processing unit 20c may be provided in the external server 50 or the like. In the following description, a case where the arithmetic processing unit 20c is provided in the control device 20 (work machine 1) will be described as an example, and detailed descriptions of other examples will be omitted.

[0075] FIG. 8A is a diagram showing an example in which a cross-sectional image G of the terrain is acquired from point cloud data sensed rearward by a work machine 1 performing ridge-forming work. As shown in FIG. 8A, the calculation processing unit 20c acquires a terrain image C showing the terrain including a formed object M, and generates a cross-sectional image G from the terrain image C. The formed object M is, for example, a ridge M1, and has an elongated shape in a plan view. As shown in FIG. 8A, the cross-sectional image G is an image obtained by cutting the terrain image C along a plane (including a substantially vertical plane) perpendicular to the elongated direction of the formed object M (for example, the ridge M1). In FIG. 8A, the formed object M is a ridge M1 having a kamaboko shape (semi-cylindrical shape), but it may also have a shape other than a kamaboko shape, such as a trapezoid.

[0076] Specifically, as shown in FIG. 8A, the second sensing device 25b (sensing device 25) acquires point cloud data showing the terrain around the working device 2 (e.g., a ridge-forming device) as a terrain image C. FIG. 9A is a diagram showing point cloud data PD (terrain image C) showing the terrain including the kamaboko-shaped ridges M1. As shown in FIG. 9A, the second sensing device 25b acquires point cloud data PD showing the terrain image C showing the terrain (e.g., terrain including the kamaboko-shaped ridges M1) around the working device 2 (e.g., a ridge-forming device). The calculation processing unit 20c generates a cross-sectional image G (see FIG. 9B) from the point cloud data PD (see FIG. 9A) of the terrain including the ridges M1.

[0077] In FIG. 9A, the cut portions of the point cloud data PD are indicated by thick lines (lines perpendicular to the longitudinal direction of the ridges M1). FIG. 9B is a diagram showing an example of a cross-sectional image G obtained by cutting the point cloud data PD in FIG. 9A at the thick line portions. As shown in FIG. 9B, the cross-sectional image G at the thick line portions in FIG. 9A is an image showing a cross section of the kamaboko-shaped ridges M1 thinly sliced. For example, the thickness of the cross-sectional image G (the thickness of the thick line in FIG. 9A) is, for example, 10 cm, and the width (the approximate length of the thick line in FIG. 9A) is, for example, 2 m, but is not limited to this.

[0078] Note that the imaging device 26 may capture an image of the ground work state while the ground work is being performed. For example, the imaging device 26 may capture an image of the terrain (i.e., the terrain including the ridge M1) around the work implement 2 (e.g., the ridge-forming implement).

[0079] Here, the case of a trapezoidal ridge M1 will be explained using Figure 10. Figure 10A is a diagram showing point cloud data PD (terrain image C) indicating a terrain including a trapezoidal ridge M1. In the case shown in Figure 10A, the second sensing device 25b acquires point cloud data PD indicating a terrain image C showing the terrain (e.g., terrain including a trapezoidal ridge M1) around the working device 2 (e.g., a ridge-forming device). The calculation processing unit 20c generates a cross-sectional image G (see Figure 10B) from the point cloud data PD (see Figure 10A) of the terrain including the ridge M1.

[0080] In FIG. 10A, the cut portions of the point cloud data PD are indicated by thick lines (lines perpendicular to the longitudinal direction of the ridges M1). FIG. 10B is a diagram showing an example of a cross-sectional image G obtained by cutting the point cloud data PD in FIG. 10A at the thick line portions. As shown in FIG. 10B, the cross-sectional image G of the thick line portions in FIG. 10A is an image showing a cross section of the trapezoidal ridges M1 that have been thinly sliced. The generation of the cross-sectional image G from the point cloud data PD by the calculation processing unit 20c will be described later.

[0081] Next, the template image TP shown in Fig. 8B etc. will be described. The template image TP is an estimated image showing the shape of a molded object M (e.g., ridge M1) that is estimated to be molded by the working device 2. The calculation processing unit 20c sets the template image TP in accordance with the working device 2. Specifically, the calculation processing unit 20c sets the template image TP in accordance with at least one of the type (e.g., model) of the working device 2 and setting information (information that determines at least one of the ridge height, ridge width, ridge shape, and ridge spacing).

[0082] For example, the calculation processing unit 20c may set a template image TP according to the type (e.g., model) of the operating device 2. If the operating device 2 is one of the first to nth models, a template image TP of the corresponding model is set. That is, a template image TP of a shape and size specified by the specifications (various dimensional data) of the first to nth models is set.

[0083] Furthermore, the calculation processing unit 20c may set a template image TP according to the setting information of the working device 2 (information that determines at least one of the ridge height, ridge width, ridge shape, and ridge spacing).

[0084] The storage device 21 stores in advance, as correspondence data, a template image TP corresponding to the type of the maintenance device 2, a template image TP corresponding to the setting information of the maintenance device 2, and a template image TP corresponding to the type and setting information of the maintenance device 2. The calculation processing unit 20c can call up and set the template image TP corresponding to at least one of the type (e.g., model) and setting information of the maintenance device 2 using the correspondence data in the storage device 21.

[0085] 9C is a diagram showing an example of a kamaboko-shaped template image TP. If the ridge shape of the setting information is the kamaboko shape shown in FIG. 9A, the calculation processing unit 20c sets a template image TP (see FIG. 9C) that matches the kamaboko shape of the working device 2 and has a size and dimensions according to at least one of the ridge height, ridge width, and ridge spacing of the setting information.

[0086] Fig. 10C is a diagram showing an example of a trapezoidal template image TP. If the ridge shape of the setting information is the trapezoid shape shown in Fig. 10A, the calculation processing unit 20c sets a template image TP (see Fig. 10C) that matches the trapezoid shape of the working device 2 and has a size and dimensions according to at least one of the ridge height, ridge width, and ridge spacing of the setting information.

[0087] In addition, if the user changes the setting information (information that determines at least one of the ridge height, ridge width, ridge shape, and ridge spacing), the calculation processing unit 20c may calculate and set a template image TP identified by the changed setting information.

[0088] As shown in FIG. 8A, the second sensing device 25b acquires point cloud data PD including the molded object M in the field H1. FIG. 11 is a diagram showing the relationship between all point cloud data acquired by the second sensing device 25b and a region of interest K. For all sensing ranges ES shown in FIG. 11, the amount of point cloud data is very large (e.g., 450,000 points / second), so processing all the point cloud data takes a long calculation time, raising concerns about impairing real-time performance. Therefore, in order to exclude unnecessary point cloud data, the calculation processing unit 20c sets a region of interest K in a range including the ridge M1 and extracts point cloud data PD for the region of interest K. As a result, the amount of point cloud data for the region of interest K is reduced to approximately 1 / 2 to 1 / 3 of the original amount of all the point cloud data, but it may be reduced further.

[0089] FIG. 12A shows the movement of the region of interest K as the tractor moves, and illustrates the superposition of two regions of interest K where the tractor is positioned at different locations. As shown on the left side of FIG. 12A, the position of the region of interest K moves as the work machine 1 moves (travels straight ahead). As shown on the right side of FIG. 12A, the region of interest K of the work machine 1 located at a certain time (region K2 shown by a solid line) partially overlaps with the region of interest K of the work machine 1 located, for example, 0.1 seconds earlier (region K1 shown by a dashed line) (the overlapping portion is indicated by hatching). FIG. 12B shows an example of point cloud data without the superposition of the region of interest K. In the point cloud data without the superposition of the region of interest K shown in FIG. 12B, i.e., the point cloud data of the region of interest K at the above-mentioned time or 0.1 seconds earlier, there are many horizontal streaks and the shape of the ridge M1 is blurred. FIG. 12C shows an example of point cloud data with the superposition of the region of interest K. In the point cloud data when the region of interest K is superimposed as shown in FIG. 12C, horizontal streaks are reduced and the shape of the ridge M1 appears.

[0090] Here, the generation of a cross-sectional image G from the point cloud data PD will be described. The calculation processing unit 20c acquires position information of the point cloud data PD based on position information from the position detection device 27 and distance measurement information from the second sensing device 25b (sensing device 25). Then, the calculation processing unit 20c associates the position information of the point cloud data PD with extracted point cloud data PD1 (point cloud data PD) extracted from a region of interest K of the point cloud data, and stores them in the storage device 21.

[0091] Then, the calculation processing unit 20c performs coordinate conversion of the extracted point cloud data PD1 (point cloud data PD) of the region of interest K from the coordinate system of the second sensing device 25b (sensing device 25) to the world coordinate system based on the position information for the extracted point cloud data PD1 (point cloud data PD) of multiple regions of interest K (e.g., regions K1 and K2 shown in FIG. 12A) that are located at different positions on the traveling vehicle body 3, thereby superimposing the extracted point cloud data PD1 (point cloud data PD) of multiple regions of interest K (e.g., regions K1 and K2 shown in FIG. 12A) on the world coordinate system. As a result, extracted point cloud data PD1 (point cloud data PD) for a predetermined length in the longitudinal direction of the ridge M1 (overlapping length of multiple regions of interest K) is constructed in the world coordinate system (point cloud reconstruction: point cloud voxel data). The calculation processing unit 20c generates a cross-sectional image G from slice point cloud data PD2 of a predetermined thickness (for example, 10 cm) on a plane perpendicular to the traveling direction of the traveling vehicle body 3, using the extracted point cloud data PD1 (point cloud data PD) superimposed in the world coordinate system. Note that this predetermined thickness may be a value other than, for example, 10 cm.

[0092] The arithmetic processing unit 20c performs spline interpolation on the slice point cloud data PD2. By performing spline interpolation, it is possible to curve the scattered points in the slice point cloud data PD2 that indicate the contours of the terrain (including the contours of the ridges M1). The arithmetic processing unit 20c then generates a cross-sectional image G from the slice point cloud data PD2 after spline interpolation. For example, the contour of the cross-sectional image G shown in FIG. 8B can be curved, resulting in a smooth contour. Note that the interpolation method is not limited to spline interpolation; for example, a smooth curve can also be created by performing linear interpolation, cubic interpolation, or nearest neighbor interpolation, and then applying a filter such as a Gaussian filter.

[0093] As shown in FIGS. 8B and 13, the calculation processing unit 20c determines the shape of the ridge M1 based on a matching process between a cross-sectional image G of the terrain including the ridge M1 and a template image TP.

[0094] FIG. 13 is a diagram illustrating how the comparison position Pcp is determined by scanning the template image TP with respect to the cross-sectional image G. As shown in FIG. 13, the calculation processing unit 20c superimposes the template image TP on the cross-sectional image G and moves it in a predetermined direction SD (scanning direction), setting the position Pn where the overlapping area between the cross-sectional portion of the molding M included in the cross-sectional image G and the template image TP is the largest as the comparison position Pcp. As shown in FIG. 13, the calculation processing unit 20c sequentially calculates the overlapping area at each position each time the template image TP is moved in the predetermined direction SD at a predetermined pitch from a start position Ps at the left end of the cross-sectional image G to an end position Pe at the right end, and stores the overlapping area in association with each position. Here, when the template image TP is at position Pn, the overlapping area between the cross-sectional portion of the molding M in the cross-sectional image G and the template image TP is the largest, so position Pn is set (determined) as the comparison position Pcp.

[0095] 13, the predetermined direction SD is set to only the horizontal direction, and the arithmetic processing unit 20c performs one-dimensional scanning (line scanning) of the template image TP, but this is not limiting. The predetermined direction SD may be set to both the horizontal and vertical directions, and the arithmetic processing unit 20c may perform two-dimensional scanning (planar scanning) of the template image TP.

[0096] 8B is a diagram showing an example of the matching process between the cross-sectional image G and the template image TP. As shown in FIG. 8B, the calculation processing unit 20c determines that the molding M has a molding abnormality when the difference D between the outline OL1 of the template image TP set at the comparison position Pcp and the outline OL2 of the cross-sectional portion of the molding M is equal to or greater than a threshold. FIG. 8C is a diagram showing an example of the estimation result of the abnormal portion by the matching process. The calculation processing unit 20c may generate an estimation result image RG by adding an abnormal area AL where the difference D is equal to or greater than a threshold to the point cloud data PD shown in FIG. 9A or an image captured by the imaging device 26, and display the estimation result image RG on the display device 15.

[0097] Figure 9D is a diagram showing an example of the matching relationship and the contour difference image F when the evaluation result of the ridge M1 is OK. Figure 9E is a diagram showing an example of the matching relationship and the contour difference image F when the evaluation result of the ridge M1 is NG. In Figures 8B and 9E, for example, there are one or more locations where the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molded product M is greater than or equal to a threshold, so the calculation processing unit 20c determines that the ridge formation has failed (abnormal formation of the ridge M1).

[0098] On the other hand, as shown in Figure 9D, if there is no location where the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molded product M is equal to or greater than the threshold value, the calculation processing unit 20c determines that there are no abnormalities in the formation of the ridge M1 for the portion of the ridge M1 that corresponds to the cross-sectional image G. In Figure 9D, the contour OL2 of the cross-sectional portion of the ridge M1 roughly matches the contour OL1 of the template image TP (to be precise, matches within less than the threshold value). Then, if the calculation processing unit 20c determines that there are no abnormalities in the formation of the ridge M1 for all cross-sectional images G of the ridge M1, for example, it determines that the ridge formation for the ridge M1 has been successful.

[0099] The calculation processing unit 20c generates a contour difference image F that shows the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molded object M (ridge M1), as shown in the lower part of FIG. 9D and the lower part of FIG. 9E. The contour difference image F is an image of the thickness portion of the cross-sectional image G viewed from above, and shows the difference D between the contour OL2 of the upper surface of the cross-sectional image G and the contour OL1 of the upper surface of the template image TP. The contour difference image F shown in FIG. 9D is an image that indicates that there is no molding abnormality in the ridge M1. On the other hand, the contour difference image F shown in FIG. 9E is an image that indicates that there is a molding abnormality in the ridge M1.

[0100] 9E, the arithmetic processing unit 20c indicates, as a specific aspect SG, a portion of the contour difference image F where the difference D is equal to or greater than a threshold. The threshold may include, for example, a first threshold and a second threshold that is greater than the first threshold. The arithmetic processing unit 20c does not indicate a specific aspect SG for a portion of the contour difference image F where the difference D is equal to or less than the first threshold, indicates a first specific aspect SG1 as a specific aspect SG for a portion of the contour difference image F where the difference D is greater than the first threshold and equal to or less than the second threshold, and indicates a second specific aspect SG2, different from the first specific aspect SG1, as a specific aspect SG for a portion of the contour difference image F where the difference D exceeds the second threshold.

[0101] For example, the first specific aspect SG1 indicates a shape abnormality (small abnormality) of the molded product M that is below a specified level, such as a small ridge collapse or small depression, but does not require redoing the ridge formation. On the other hand, the second specific aspect SG2 indicates a shape abnormality (large abnormality) of the molded product M that exceeds a specified level, such as a large ridge collapse or large depression, and requires redoing the ridge formation. For example, if the value is equal to or greater than the first threshold value and less than the second threshold value, a shape abnormality below a specified level is detected. If the value is equal to or greater than the second threshold value, a shape abnormality above a specified level is detected.

[0102] Next, the case of a trapezoidal ridge M1 will be described. Fig. 10D is a diagram showing an example of the matching relationship and the contour difference image F when the evaluation result of the ridge M1 is OK. Fig. 10E is a diagram showing an example of the matching relationship and the contour difference image F when the evaluation result of the ridge M1 is NG. In Fig. 10E, there are one or more locations where the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molded product M is greater than or equal to the threshold, so the calculation processing unit 20c determines that the ridge formation has failed (the ridge M1 is abnormally formed).

[0103] On the other hand, as shown in Figure 10D, if there is no point where the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molded product M is equal to or greater than the threshold value, the calculation processing unit 20c determines that there are no abnormalities in the formation of the ridge M1 for the portion of the ridge M1 that corresponds to the cross-sectional image G. In Figure 10D, the contour OL2 of the cross-sectional portion of the ridge M1 roughly matches the contour OL1 of the template image TP (to be precise, matches within less than the threshold value). Then, if the calculation processing unit 20c determines that there are no abnormalities in the formation of the ridge M1 for all cross-sectional images G of the ridge M1, it determines that the ridge formation for the ridge M1 has been successful.

[0104] The calculation processing unit 20c generates a contour difference image F that shows the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molded object M (ridge M1), as shown in the lower part of FIG. 10D and the lower part of FIG. 10E. The contour difference image F is an image of the thickness portion of the cross-sectional image G viewed from above, and shows the difference D between the contour OL2 of the upper surface of the cross-sectional image G and the contour OL1 of the upper surface of the template image TP. The contour difference image F shown in FIG. 10D is an image that indicates that there is no molding abnormality in the ridge M1. On the other hand, the contour difference image F shown in FIG. 10E is an image that indicates that there is a molding abnormality in the ridge M1.

[0105] 10E, the arithmetic processing unit 20c indicates, as a specific aspect SG, a portion where the difference D in the contour difference image F is equal to or greater than a threshold. The arithmetic processing unit 20c does not indicate a specific aspect SG for a portion where the difference D is equal to or less than a first threshold, indicates a first specific aspect SG1 as a specific aspect SG for a portion where the difference D exceeds the first threshold and is equal to or less than a second threshold, and indicates a second specific aspect SG2, different from the first specific aspect SG1, as a specific aspect SG for a portion where the difference D exceeds the second threshold.

[0106] Under the control of the arithmetic processing unit 20c, the storage device 21 stores the contour difference images F in association with the position information of the contour difference images F. The arithmetic processing unit 20c may generate a series of difference images FA (see FIG. 15 ) in which the plurality of contour difference images F stored in the storage device 21 are arranged in order of their positions based on the position information of the contour difference images F. The storage device 21 may also store the speed of the traveling vehicle body 3, the position of the traveling vehicle body 3 acquired by the position detection device 27, the working state of the working device 2, and the contour difference images F in association with each other.

[0107] The control device 20 may transmit the series of differential images FA to the server 50 shown in Fig. 1. The storage device 52 of the server 50 stores the series of differential images FA. The control device 20 may also transmit the series of differential images FA to the server 50 in association with positional information of the molding M included in the series of differential images FA. The storage device 52 of the server 50 stores the series of differential images FA in association with positional information of the molding M included in the series of differential images FA.

[0108] Furthermore, the control device 20 may associate the contour difference image F with position information of the contour difference image F and transmit them to the server 50. The storage device 52 of the server 50 stores the contour difference image F and the position information of the contour difference image F in association with each other.

[0109] FIG. 15 is a diagram illustrating the difference between determining the shape of a single ridge M1 by visual inspection and automatic detection, based on a series of difference images FA. As shown in FIG. 15, when automatic detection is performed based on the series of difference images FA, areas indicating shape abnormalities such as ridge collapse (hatched areas in the series of difference images FA in FIG. 15) are properly detected. In other words, the shape abnormality of the ridge M1 is properly detected. In contrast, when performing visual inspection, areas indicating shape abnormalities such as ridge collapse (hatched areas in the series of difference images FA in FIG. 15) are overlooked, and areas that do not result in shape abnormalities (dotted areas in the series of difference images FA in FIG. 15) are determined to be abnormal (misjudged). These facts demonstrate that automatic detection is superior to visual inspection.

[0110] FIG. 16A is a diagram showing point cloud data PD (terrain image C) showing a kamaboko-shaped ridge M1. FIG. 16B is a diagram showing an example of a shape-defective area in the point cloud data PD (terrain image C) shown in FIG. 16A. FIG. 16C is a diagram showing an example of a matching relationship between a cross-sectional image G of the shape-defective area of ​​the ridge M1 and a template image TP. As shown in FIG. 16A, the second sensing device 25b acquires point cloud data PD showing a terrain including a formed product M (kamaboko-shaped ridge M1) formed by the working device 2 (e.g., a ridge-forming device). The calculation processing unit 20c generates a cross-sectional image G shown in FIG. 16C from the point cloud data PD (see FIG. 16A) of the terrain including the ridge M1.

[0111] As shown in FIG. 16C , the calculation processing unit 20c determines that the molding M has a molding abnormality when the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molding M is equal to or greater than a threshold. The calculation processing unit 20c may generate an abnormal area AL indicating the area determined to have a molding abnormality, and as shown in FIG. 16B , generate an estimation result image RG in which the abnormal area AL is attached to a corresponding position in the point cloud data PD, and display the estimation result image RG on the display device 15. Note that in the example of FIG. 16C , the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molding M is expressed as a vertical distance, but is not limited thereto, and the difference D may also be the diagonal or horizontal length between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molding M.

[0112] FIG. 17A is a diagram showing point cloud data PD (terrain image C) showing a trapezoidal ridge M1. FIG. 17B is a diagram showing an example of a shape-defective area in the point cloud data PD (terrain image C) shown in FIG. 17A. FIG. 17C is a diagram showing an example of a matching relationship between a cross-sectional image G of a shape-defective area of ​​the ridge M1 and a template image TP. As shown in FIG. 17A, the second sensing device 25b acquires point cloud data PD showing a terrain including a molded product M (trapezoidal ridge M1) formed by a working device 2 (e.g., a ridge-forming device). The calculation processing unit 20c generates a cross-sectional image G shown in FIG. 17C from the point cloud data PD (see FIG. 17A) of the terrain including the ridge M1.

[0113] As shown in FIG. 17C , the calculation processing unit 20c determines that the molding M has a molding abnormality when the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molding M is equal to or greater than a threshold. The calculation processing unit 20c may generate an abnormal area AL indicating the area determined to have a molding abnormality, and as shown in FIG. 17B , generate an estimation result image RG in which the abnormal area AL is attached to a corresponding position in the point cloud data PD, and display the estimation result image RG on the display device 15. Note that in the example of FIG. 17C , the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molding M is expressed as a vertical distance, but is not limited thereto, and the difference D may also be the diagonal or horizontal length between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molding M.

[0114] 14 is a flowchart for changing the traveling state of the traveling vehicle body 3 based on the evaluation results when ground work is performed with the ridge-making device. For ease of explanation, the ridge-making device will be described, but the same can be applied to other work devices 2.

[0115] 14, the automatic driving control unit 20b starts automatic driving based on an automatic driving instruction (S1). The automatic driving control unit 20b controls the transmission 5 and the like so that the vehicle speed of the work implement 1 becomes a vehicle speed set corresponding to the planned travel route L (e.g., the straight section L1) (S2). The automatic driving control unit 20b also controls the steering device 11 based on the vehicle body position estimated by the position estimator 20a and the planned travel route L (e.g., the straight section L1) (S3).

[0116] The automatic driving control unit 20b (control device 20) causes the work device 2 (ridge-forming device) to perform ridge formation work based on the ridge-forming instruction (S4). The ridge-forming instruction includes an instruction from the driver to start ridge formation or a preset instruction to start automatic ridge formation.

[0117] As shown in FIG. 8A, the second sensing device 25b (sensing device 25) acquires point cloud data PD indicating the ground work state while the ground work is being carried out (i.e., point cloud data PD of the terrain including ridge M1) (S5). The storage device 21 stores the point cloud data PD indicating the ground work state acquired by the second sensing device 25b (S6). Note that the imaging device 26 may also capture an image of the ground work state while the ground work is being carried out in S5. The storage device 21 may also store a ground work image, which is the captured ground work state, in S6.

[0118] The calculation processing unit 20c generates a cross-sectional image G (see Figures 9B and 10B) from the point cloud data PD stored in the storage device 21 (for example, the point cloud data PD of the terrain including the ridge M1 shown in Figures 9A and 10A) (S7).

[0119] The arithmetic processing unit 20c performs a matching process between the cross-sectional image G of the terrain including the formed object M (e.g., ridge M1) formed in the field H1 by the working device 2 and the template image TP (S8). That is, as shown in FIG. 8B, the cross-sectional image G is compared with the template image TP. In the case of a kamaboko-shaped ridge M1, the arithmetic processing unit 20c performs a matching process between the cross-sectional image G and the template image TP as shown in FIGS. 9D and 9E. In the case of a trapezoidal ridge M1, the arithmetic processing unit 20c performs a matching process between the cross-sectional image G and the template image TP as shown in FIGS. 10D and 10E.

[0120] The calculation processing unit 20c evaluates the shape of the molding M (e.g., ridge M1) based on the matching process between the cross-sectional image G and the template image TP (S9). For example, as shown in Figures 9D and 10D, if there is no location where the difference D between the outline OL1 of the template image TP and the outline OL2 of the cross-sectional portion of the molding M is equal to or greater than a threshold, the calculation processing unit 20c determines that there is no abnormality in the formation of the ridge M1 for the portion of the ridge M1 that corresponds to the cross-sectional image G, and evaluates the evaluation result as good (S9).

[0121] On the other hand, as shown in Figures 9E and 10E, if there is at least one location where the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molding M is greater than or equal to a threshold value, the calculation processing unit 20c determines that there is an abnormality in the formation of the ridge M1 for the portion of the ridge M1 that corresponds to the cross-sectional image G, and evaluates that the evaluation result is not good (S9).

[0122] If the evaluation result is bad (S10, Yes), the difference D between the outline OL1 of the template image TP and the outline OL2 of the cross-section of the molded object M is equal to or greater than a threshold value, which may mean that the work implement 2 (ridge-forming implement) is not plowing to a sufficient depth. If the evaluation result is bad (S10, Yes), the control device 60 changes the driving state, etc. (S11: driving change process). In the driving change process, the control device 60 determines a change in the driving state based on the operating information (motor rotation speed, vehicle speed, accelerator operation amount, load factor of the motor 4) of the traveling vehicle body 3 stored in the storage device 21 and the evaluation result. The control device 60, for example, uses a simulation model, an evaluation function, etc. to determine the motor rotation speed, vehicle speed, accelerator operation amount, and load factor of the motor 4 such that the difference D is less than the threshold value (i.e., the difference D is small). In the driving change process (S11), when the prime mover rotation speed, vehicle speed, accelerator operation amount, and load factor of the prime mover 4 are determined so that the difference D becomes less than the threshold value (i.e., the difference D becomes small), the vehicle speed (set vehicle speed) set corresponding to the planned driving route L (e.g., the straight section L1) is increased or decreased, or the prime mover rotation speed is increased or decreased, depending on the determined results.

[0123] The control device 60 may change the work state instead of or in addition to changing the traveling state in S11 (S11: work change process). In the work change process, the control device 60 determines a change in the work state based on the operation information of the work device 2 stored in the storage device 21 (working height position of the work device 2, PTO (Power take-off) rotation speed (rotation speed of the PTO shaft 6), rotation speed of the tiller tines, and load factor of the prime mover 4) and the evaluation results. For example, the control device 60 uses a simulation model, an evaluation function, or the like to determine the working height position of the work device 2, the rotation speed of the PTO shaft 6, the rotation speed of the tiller tines, and the load factor of the prime mover 4 such that the difference D becomes less than a threshold value (i.e., the difference D becomes small). In the work change process (S11), the working height position of the work implement 2, the rotation speed of the PTO shaft 6, the rotation speed of the tiller tines, and the load factor of the prime mover 4 are determined so that the difference D becomes less than the threshold value (i.e., the difference D becomes small), and then, in response to the determined results, for example, the work implement 2 set in accordance with the planned travel route L (e.g., the straight section L1) is raised or lowered, or the prime mover rotation speed is increased or decreased.

[0124] After S11, or if the evaluation result is good (S10, No), the control device 20 determines whether the work is complete (S12), and if the work is not complete (S12, No), the process returns to S5. The control device 20 (arithmetic processing unit 20c) continues the process of evaluating the next cross-sectional image G (S5 to S10). On the other hand, if the work is complete (S12, Yes), the control device 20 ends this process.

[0125] 14 illustrates the case of automatic driving, but manual driving is also possible. The work machine 1 may be equipped with an alarm device 28 that notifies the driver when the evaluation result of the molded product M (e.g., ridge M1) is not good during manual driving. The alarm device 28 is, for example, a speaker, buzzer, or the like that outputs an alarm sound (audio guidance, warning sound, etc.) indicating that the evaluation result is not good. The alarm device 28 may also be the display device 15. For example, the display device 15 may display an alarm that notifies the driver that the evaluation result is not good, instead of or in addition to outputting an alarm sound using a speaker, buzzer, etc. In other words, the alarm device 28 warns the driver during manual driving. The driver can take measures such as reducing vehicle speed or lowering the work implement 2 (lowering the working height of the work implement 2).

[0126] In the determination system S of this embodiment, the shape of the molding M is determined using a sensing device 25 (lidar) rather than a camera. For example, a method using stereo matching with a camera (passive stereo from camera images) has difficulty determining the shape of a molding M with a texture with few distinctive features. In contrast, the sensing device 25 (lidar) can measure even textures with few distinctive features. Therefore, the determination system S can acquire three-dimensional information more accurately than a method using stereo matching with a camera. However, this does not mean that a camera is not used or cannot be used at all in a flow that changes the traveling state of the traveling vehicle body 3 based on the evaluation results when ground work is performed with a ridge-making device; a camera may be used depending on the situation, processing content, etc.

[0127] Next, the determination system S of this embodiment determines the shape of the molded product M using a template image TP estimated from the working device 2 (ridge-forming device: molding machine). For example, in a conventional method of determining the shape of the molded product M based on an ideal ground surface condition that is actually measured, it is necessary to actually measure the ground surface condition once to obtain the ideal ground surface condition. Furthermore, creating neat, straight ridges to obtain the ideal ground surface condition is technically difficult, even for an experienced driver. In contrast, the determination system S uses a template image TP. In other words, the template image TP can be estimated from the shape of the working device 2 (ridge-forming device: molding machine). Therefore, the determination system S does not need to measure and obtain the ideal ground surface condition.

[0128] Furthermore, in the conventional method, since the ideal ground surface state is compared with the measured ground surface state, it is subject to the influence of left-right positional misalignment, which can result in low judgment accuracy. In the conventional method, it is difficult to determine the difference between the ideal ground surface state and the target ground surface state. In contrast, the template image TP of the judgment system S has the advantage of being unaffected by left-right positional misalignment and having high judgment accuracy. Compared to conventional judgment methods, the judgment system S has the advantage of requiring less load to apply and being less susceptible to misalignment.

[0129] The main characteristic features and effects of the determination system S and the determination method in the above-described embodiments are as follows.

[0130] (Item A1) A judgment system S having an arithmetic processing unit 20c that judges the shape of a molded object M based on a matching process between a cross-sectional image G of the terrain including the molded object M formed in a field H1 by a work device 2 and a template image TP.

[0131] According to this configuration, the degree of match between the cross-sectional shape of the molded product M shown in the cross-sectional image G and the template image TP can be determined by a matching process between the cross-sectional shape of the molded product M and the template image TP. Therefore, it is possible to determine whether the shape of the molded product M molded in the field H1 by the working device 2 is good or bad.

[0132] (Item A2) The determination system S according to item A1, wherein the calculation processing unit 20c acquires a topographical image C showing a topography including the molding M, and generates the cross-sectional image G from the topographical image C.

[0133] According to this configuration, a cross-sectional image G is generated from a terrain image C showing the terrain including the molded object M formed in the field H1 by the work implement 2. The cross-sectional image G shows the outline of the molded object M, allowing the shape of the molded object M to be accurately determined.

[0134] (Item A3) A determination system S described in Item A1 or A2, wherein the molding M has a long shape when viewed in a plane, and the cross-sectional image G is an image of the topographical image C cut along a plane perpendicular to the long direction of the molding M.

[0135] According to this configuration, the cross-sectional image G is a cross-sectional image of the elongated molding M, which is a plane perpendicular to its longitudinal direction, so that a cross-sectional image G showing the cross section of the terrain including the molding M can be obtained, and the cross-sectional shape of the molding M can be accurately determined.

[0136] (Item A4) A judgment system S described in any one of items A1 to A3, wherein the calculation processing unit 20c overlays the template image TP on the cross-sectional image G and sets the position where the overlapping area between the cross-sectional portion of the molding M included in the cross-sectional image G and the template image TP is the largest as the comparison position Pcp.

[0137] According to this configuration, the cross-sectional portion of the molding M included in the cross-sectional image G can be properly matched with the template image TP, and the accuracy of determining the shape of the molding M can be improved.

[0138] (Item A5) The calculation processing unit 20c is a judgment system S described in item A4, which judges that the molding M has a molding abnormality when the difference D between the contour OL1 of the template image TP set at the comparison position Pcp and the contour OL2 of the cross-sectional portion of the molding M is greater than or equal to a threshold value.

[0139] This configuration makes it possible to find abnormalities in formation that are difficult to see or that are easily overlooked by the naked eye.

[0140] (Item A6) The determination system S according to item A5, wherein the calculation processing unit 20c generates a contour difference image F showing the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molding M.

[0141] According to this configuration, the contour difference image F shows the difference D between the contour OL1 of the template image TP and the contour OL2 of the cross-sectional portion of the molding M, so that the user can visually grasp the areas of the contour OL2 of the molding M where the difference D from the contour OL1 of the template image TP is large and the extent of that difference D.

[0142] (Item A7) The determination system S according to item A6, wherein the calculation processing unit 20c indicates a location where the difference D in the contour difference image F is equal to or greater than the threshold value in a specific manner SG.

[0143] According to this configuration, the portions of the contour difference image F where the difference D is equal to or greater than the threshold value are displayed in a specific manner SG, so that it is possible to clearly indicate the portions of the molding abnormality in the contour difference image F. It is possible to clearly notify the user of the portions of the molding abnormality in the contour difference image F.

[0144] (Item A8) The thresholds include a first threshold and a second threshold greater than the first threshold, and the calculation processing unit 20c does not show the specific aspect SG in the contour difference image F where the difference D is less than or equal to the first threshold, shows a first specific aspect SG1 as the specific aspect SG in the area where the difference D exceeds the first threshold and is less than or equal to the second threshold, and shows a second specific aspect SG2 different from the first specific aspect SG1 as the specific aspect SG in the area where the difference D exceeds the second threshold, in the judgment system S described in item A7.

[0145] According to this configuration, the portions of the contour difference image F where the difference D exceeds the first threshold and is equal to or smaller than the second threshold are displayed in the first specific manner SG1, and the portions of the contour difference image F where the difference D exceeds the second threshold are displayed in the second specific manner SG2, so that the portions of the molding abnormality in the contour difference image F can be clearly indicated in at least two stages. The portions of the molding abnormality in the molded object M can be more clearly notified to the user in the contour difference image F.

[0146] (Item A9) A judgment system S described in any one of items A6 to A8, which includes a storage device 21 that stores the contour difference images F in correspondence with positional information of the contour difference images F, and the calculation processing unit 20c generates a series of difference images FA in which the plurality of contour difference images F stored in the storage device 21 are arranged in the order of their positions based on the positional information of the contour difference images F.

[0147] According to this configuration, the series of differential images FA are a series of contour differential images F showing the molding M in a planar view, and therefore can show the distribution and extent of molding abnormalities throughout the molding M. This allows the user to visually grasp the distribution and extent of molding abnormalities throughout the molding M.

[0148] (Item A10) A judgment system S described in any one of items A6 to A9, comprising a work machine 1 having the work device 2, a traveling body 3 to which the work device 2 can be attached, and a position detection device 27 that acquires the position of the traveling body 3, wherein the memory device 21 stores the speed of the traveling body 3, the position of the traveling body 3 acquired by the position detection device 27, the work status of the work device 2, and the contour difference image F in association with each other.

[0149] With this configuration, the relationship between the contour difference image F, the vehicle speed, the vehicle body position, and the working state of the working implement 2 can be confirmed.

[0150] (Item A11) The determination system S according to any one of items A2 to A8, further comprising a sensing device 25 that acquires point cloud data PD that indicates the terrain around the work implement 2 as the terrain image C. According to this configuration, the sensing device 25 acquires point cloud data PD, so even if the textures of the field H1 and the molding M (such as the feel when touching the surface and the appearance) have few characteristics, it is possible to accurately acquire three-dimensional information, and therefore the shape of the molding M can be determined with high precision.

[0151] (Item A12) The determination system S according to item A11, wherein the calculation processing unit 20c generates the cross-sectional image G from the point cloud data PD.

[0152] According to this configuration, the shape of the molding M can be determined by comparing the cross-sectional image G generated from the point cloud data PD with the template image TP.

[0153] (Item A13) A determination system S described in Item A12, which is provided with a work machine 1 having the work device 2, a traveling body 3 to which the work device 2 can be attached, a position detection device 27 that acquires the position of the traveling body 3, and the sensing device 25, wherein the calculation processing unit 20c acquires position information of the point cloud data PD based on position information from the position detection device 27 and distance measurement information from the sensing device 25, converts the extracted point cloud data PD1 of a region of interest K from the coordinate system of the sensing device 25 to a world coordinate system based on the position information, performs this conversion on the extracted point cloud data PD1 of multiple regions of interest K that have different position information, and overlays the extracted point cloud data PD1 of the multiple regions of interest K in the world coordinate system.

[0154] According to this configuration, the point cloud data PD of regions of interest K at different positions can be properly aligned and superimposed, so that the point cloud data PD can be made denser at the superimposed locations, thereby improving the quality of the point cloud data PD.

[0155] (Item A14) The calculation processing unit 20c generates the cross-sectional image G from slice point cloud data PD2 of a predetermined thickness in a plane perpendicular to the direction of travel of the traveling vehicle body 3, using the extracted point cloud data PD1 superimposed in the world coordinate system as the judgment system S described in item A13.

[0156] According to this configuration, slice point cloud data PD2 corresponding to the distance that the traveling vehicle body 3 has traveled by a predetermined distance can be generated as cross-sectional images G sequentially.

[0157] (Item A15) The calculation processing unit 20c performs interpolation on the slice point cloud data PD2 to curve the points indicating the contour of the terrain, and generates the cross-sectional image G from the interpolated slice point cloud data PD2 in the judgment system S described in item A14.

[0158] According to this configuration, the scattered contours in the cross-sectional image G can be interpolated into curved contours, the contours of the cross-sectional portions of the molding M can be curved, and the difference between the contours of the template image TP and the contours of the cross-sectional portions of the molding M can be appropriately determined, thereby improving the accuracy of molding abnormalities.

[0159] (Item A16) The determination system S according to any one of Items A1 to A15, wherein the template image TP is an estimated image showing the shape of the molded product M that is estimated to be molded by the working device 2.

[0160] According to this configuration, the template image TP is an estimated image showing the shape of the molding M that is estimated to be formed by the working device 2, so there is no need to prepare an actual image showing the shape of the molding M formed by the working device 2, and the template image TP can be generated easily and without hassle.

[0161] (Item A17) The determination system S according to item A16, wherein the calculation processing unit 20c sets the template image TP according to the operation device 2.

[0162] According to this configuration, the template image TP is set according to the working device 2, so that molding abnormalities of the molded object M having different external shapes (at least one of shape and size) depending on the working device 2 can be appropriately determined.

[0163] (Item A18) The determination system S according to item A17, wherein the calculation processing unit 20c sets the template image TP according to at least one of the type of the working device 2 and setting information.

[0164] According to this configuration, the template image TP is set according to at least one of the type of working device 2 and the setting information (information that determines at least one of the ridge height, ridge width, ridge shape, and ridge spacing), so that molding abnormalities in the molded product M having different external shapes (at least one of the shape and size) can be appropriately determined depending on at least one of the type of working device 2 and the setting information.

[0165] (Item A19) A determination method in which the calculation processing unit 20c determines the shape of the molding M based on a matching process between a cross-sectional image G of the terrain including the molding M formed in the field H1 by the work device 2 and a template image TP.

[0166] According to this configuration, it is possible to determine whether the shape of the molded object M molded in the field H1 by the work implement 2 is good or bad.

[0167] Although the present invention has been described above, the embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0168] 1: Work equipment 2: Work equipment 3: Running vehicle 20: Control device 20c: arithmetic processing unit 21:Storage device 25: Sensing device 27: Position detection device C: Terrain image D: Difference F: Contour difference image FA: A series of differential images G: Cross-sectional image H1: Field K: Region of interest M: Molded object OL1: Contour OL2: Contour Pcp: Comparison position PD: Point cloud data PD1: Extracted point cloud data PD2: Slice point cloud data SG: Specific Aspects SG1: First specific embodiment SG2: Second specific embodiment TP: Template image S: Judgment system

Claims

1. A determination system including a calculation processing unit that determines the shape of a formed object formed in a field by a working implement based on a matching process between a cross-sectional image of a terrain including the formed object and a template image.

2. The determination system according to claim 1 , wherein the calculation processing unit acquires a topographical image showing a topography including the molding, and generates the cross-sectional image from the topographical image.

3. The molded product has an elongated shape in a plan view, The determination system according to claim 2 , wherein the cross-sectional image is an image obtained by cutting the topographical image along a plane perpendicular to the longitudinal direction of the object.

4. The determination system according to claim 3 , wherein the calculation processing unit overlays the template image on the cross-sectional image and sets the position where the overlapping area between the cross-sectional portion of the molding included in the cross-sectional image and the template image is the largest as the comparison position.

5. The judgment system described in claim 4, wherein the calculation processing unit judges that the molding has a molding abnormality when the difference between the contour of the template image set at the comparison position and the contour of the cross-sectional portion of the molding is greater than or equal to a threshold value.

6. The determination system according to claim 5 , wherein the arithmetic processing unit generates a contour difference image that indicates a difference between the contour of the template image and the contour of the cross-sectional portion of the molding.

7. The determination system according to claim 6 , wherein the calculation processing unit indicates, in a specific manner, a portion where the difference in the contour difference image is equal to or greater than the threshold value.

8. The threshold values ​​include a first threshold value and a second threshold value that is greater than the first threshold value, The determination system described in claim 7, wherein the calculation processing unit does not show the specific aspect in areas of the contour difference image where the difference is less than or equal to the first threshold, shows a first specific aspect as the specific aspect in areas where the difference exceeds the first threshold and is less than or equal to the second threshold, and shows a second specific aspect different from the first specific aspect as the specific aspect in areas where the difference exceeds the second threshold.

9. a storage device that stores the contour difference image and position information of the contour difference image in association with each other; The determination system according to any one of claims 6 to 8, wherein the calculation processing unit generates a series of difference images by arranging the plurality of contour difference images stored in the storage device in order of their positions based on position information of the contour difference images.

10. a work machine including the work device, a traveling vehicle body to which the work device can be attached, and a position detection device that acquires the position of the traveling vehicle body; 10. The determination system according to claim 9, wherein the storage device stores the speed of the traveling vehicle body, the position of the traveling vehicle body acquired by the position detection device, the working state of the working device, and the contour difference image in association with each other.

11. The determination system according to any one of claims 2 to 8, further comprising a sensing device that acquires point cloud data representing the terrain around the work implement as the terrain image.

12. The determination system according to claim 11 , wherein the arithmetic processing unit generates the cross-sectional image from the point cloud data.

13. a work machine including the work device, a traveling vehicle body to which the work device can be attached, a position detection device that acquires the position of the traveling vehicle body, and the sensing device; The determination system described in claim 12, wherein the calculation processing unit acquires position information of the point cloud data based on position information from the position detection device and ranging information from the sensing device, converts the extracted point cloud data of a region of interest from the coordinate system of the sensing device to a world coordinate system based on the position information, performs this conversion on the extracted point cloud data of multiple regions of interest that have different position information, and overlays the extracted point cloud data of the multiple regions of interest in the world coordinate system.

14. The determination system according to claim 13 , wherein the calculation processing unit generates the cross-sectional image from slice point cloud data of a predetermined thickness on a plane perpendicular to the traveling direction of the traveling vehicle body using the extracted point cloud data superimposed in the world coordinate system.

15. The determination system according to claim 14 , wherein the calculation processing unit performs interpolation on the slice point cloud data to curve the points indicating the contour of the terrain, and generates the cross-sectional image from the slice point cloud data after the interpolation.

16. The determination system according to claim 1 , wherein the template image is an estimated image showing the shape of the molded product that is estimated to be molded by the working device.

17. The determination system according to claim 16 , wherein the calculation processing unit sets the template image in accordance with the work device.

18. The determination system according to claim 17 , wherein the calculation processing unit sets the template image in accordance with at least one of the type of the work tool and setting information.

19. A determination method in which an arithmetic processing unit determines the shape of a formed object formed in a field by a working implement based on a matching process between a cross-sectional image of a terrain including the formed object and a template image.

Images