Farm road identification system, control system and agricultural machinery

Abstract

This agricultural road identification system is for an agricultural machine that drives autonomously, said agricultural road identification system comprising at least one sensing device and a processing device. The at least one sensing device acquires first sensing data by sensing the ground surface on which the agricultural machine travels and acquires second sensing data by sensing the surrounding environment of the agricultural machine. The processing device acquires first information that relates to a transverse profile of the ground surface on the basis of the first sensing data, acquires second information that relates to the surrounding environment on the basis of the second sensing data, and determines whether or not a road on the ground surface is an agricultural road on the basis of the first information and the second information.

Description

[Technical field]

[0001] The present disclosure relates to a farm road identification system for an autonomously driven agricultural machine, a control system including such a farm road identification system, and an agricultural machine including such a control system. [Background technology]

[0002] Research and development is underway to automate agricultural machinery. For example, tractors, combine harvesters, rice transplanters, and other work vehicles that use positioning systems such as the Global Navigation Satellite System (GNSS) to travel autonomously within fields have been put to practical use. Research and development is also underway for work vehicles that can travel autonomously not only within fields but also outside of fields.

[0003] For example, Patent Document 1 discloses a system that automatically drives an unmanned work vehicle between two farm fields separated by a road. Patent Document 1 also discloses a system that stores data on farm roads connecting multiple farm fields and determines whether the farm roads are passable. Patent Document 2 discloses a control device that increases the driving force transmitted to the rear wheels of a four-wheel drive vehicle to a predetermined level or more when a certain condition is met, such as the road on which the four-wheel drive vehicle is traveling being a farm road. The control device of Patent Document 2 determines whether the road on which the vehicle is traveling is a farm road by obtaining information on the type of road stored in an information server of an intelligent road traffic system. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-029218 [Patent Document 2] Patent Publication No. 2021-130401 Summary of the Invention [Problem to be solved by the invention]

[0005] When an agricultural machine is driven autonomously, it is required to be able to distinguish whether the road on which it is traveling is a farm road or not in a variety of environments.

[0006] The present disclosure provides a system that can identify, in a variety of environments, whether a road on which an autonomously driven agricultural machine is about to travel is a farm road or not. [Means for solving the problem]

[0007] A farm road identification system according to one embodiment of the present disclosure is a farm road identification system for autonomous agricultural machinery, and includes at least one sensing device that senses the ground on which the agricultural machine travels to obtain first sensing data and senses the environment surrounding the agricultural machine to obtain second sensing data, and a processing device that obtains first information regarding a cross-sectional profile of the ground based on the first sensing data, obtains second information regarding the surrounding environment based on the second sensing data, and identifies whether a road on the ground is a farm road based on the first information and the second information.

[0008] The general or specific aspects of the present disclosure may be realized by an apparatus, a system, a method, an integrated circuit, a computer program, or a computer-readable non-transitory storage medium, or any combination thereof. The computer-readable storage medium may include a volatile storage medium or a non-volatile storage medium. The apparatus may be composed of multiple devices. When the apparatus is composed of two or more devices, the two or more devices may be arranged in one device or may be arranged separately in two or more separate devices. Effect of the Invention

[0009] According to an embodiment of the present disclosure, a system for autonomous agricultural machinery is provided that is capable of identifying whether the road on which the agricultural machine is about to travel is a farm road or not in a variety of environments. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram for explaining an overview of an agricultural management system according to an exemplary embodiment of the present disclosure. [Diagram 2] FIG. 1 is a side view showing a schematic example of a work vehicle and an implement coupled to the work vehicle. [Diagram 3] FIG. 2 is a block diagram showing an example of the configuration of a work vehicle and an implement. [Figure 4] FIG. 1 is a conceptual diagram showing an example of a work vehicle performing positioning using RTK-GNSS. [Diagram 5] 4 is a diagram showing an example of an operation terminal and an operation switch group provided inside the cabin. FIG. [Figure 6] 2 is a block diagram illustrating an example of a hardware configuration of a management device and a terminal device. [Figure 7] 1 is a diagram illustrating an example of a work vehicle that automatically travels along a target route in a farm field; [Figure 8] 4 is a flowchart showing an example of a steering control operation during automatic driving. [Figure 9A] 1 is a diagram showing an example of a work vehicle traveling along a target route P. FIG. [Figure 9B] FIG. 13 is a diagram showing an example of a work vehicle in a position shifted to the right from a target route P. [Figure 9C] FIG. 13 is a diagram showing an example of a work vehicle in a position shifted to the left from a target route P. [Figure 9D] 1 is a diagram showing an example of a work vehicle facing in an inclined direction with respect to a target route P. FIG. [Figure 10] FIG. 1 is a diagram illustrating an example of a situation in which a plurality of work vehicles are automatically traveling on roads inside and outside a farm field. [Figure 11] 1 is a flowchart showing an example of a method for path planning and driving control using a farm road identification system. [Figure 12] 13 is a flowchart showing an example of a method for identifying whether a road is a farm road or not. [Figure 13A] FIG. 2 is a diagram showing a monochrome image corresponding to an example of an image captured by a camera of a work vehicle. [Figure 13B] FIG. 2 is a diagram showing a monochrome image corresponding to an example of an image captured by a camera of a work vehicle. [Figure 13C] 1 is a plan view showing a schematic example of a work vehicle automatically traveling outside a farm field while using a farm road identification system; FIG. [Figure 13D] 1 is a plan view showing a schematic example of a work vehicle automatically traveling outside a farm field while using a farm road identification system; FIG. [Figure 13E] 1 is a plan view showing a schematic example of a work vehicle automatically traveling outside a farm field while using a farm road identification system; FIG. [Figure 13F] 13 is a flowchart showing an example of a method for identifying whether a road is a farm road or not. [Figure 14] FIG. 1 is a diagram showing an example of global and local paths generated in an environment where obstacles are present; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] (Definition of terms) In this disclosure, "agricultural machinery" refers to machinery used for agricultural purposes. Examples of agricultural machinery include tractors, harvesters, rice transplanters, riding management machines, vegetable transplanters, mowers, sowing machines, fertilizer applicators, and agricultural mobile robots. Not only may a work vehicle such as a tractor function as an "agricultural machinery" by itself, but also may a work vehicle and an implement attached to or towed by the work vehicle function as a single "agricultural machinery". Agricultural machinery performs agricultural work such as plowing, sowing, pest control, fertilization, planting crops, or harvesting on the ground in a field. These agricultural works are sometimes referred to as "ground work" or simply "work". Traveling of a vehicle-type agricultural machine while performing agricultural work is sometimes referred to as "work travel".

[0012] "Autonomous driving" means that the movement of the agricultural machine is controlled by the action of a control device, not by manual operation by the driver. An agricultural machine that performs automatic driving may be called an "automatic driving agricultural machine" or a "robot agricultural machine". During automatic driving, not only the movement of the agricultural machine but also the operation of agricultural work (for example, the operation of the working machine) may be automatically controlled. When the agricultural machine is a vehicle-type machine, the traveling of the agricultural machine by automatic driving is called "automatic driving". The control device may control at least one of steering, adjustment of the moving speed, and starting and stopping of the movement required for the movement of the agricultural machine. When controlling a work vehicle equipped with a working machine, the control device may control operations such as raising and lowering the working machine, starting and stopping the operation of the working machine. The movement by automatic driving may include not only the movement of the agricultural machine toward the destination along a predetermined route, but also the movement of the agricultural machine following a tracking target. An agricultural machine that performs automatic driving may move partially based on the instruction of a user. In addition, an agricultural machine that performs automatic driving may operate in a manual driving mode in which the agricultural machine moves by manual operation of the driver, in addition to the automatic driving mode. Steering an agricultural machine by the action of a control device, rather than manually, is called "automatic steering." A part or all of the control device may be external to the agricultural machine. Communication of control signals, commands, data, etc. may take place between the agricultural machine and a control device external to the agricultural machine. An agricultural machine that performs automatic driving may move autonomously while sensing the surrounding environment, without a human being being involved in controlling the movement of the agricultural machine. An agricultural machine capable of autonomous movement can travel unmanned in a field or outside the field (e.g., a road). During autonomous movement, the agricultural machine may detect obstacles and perform obstacle avoidance operations.

[0013] A "work plan" is data that determines a schedule for one or more agricultural works to be performed by an agricultural machine. The work plan may include, for example, information indicating the order of agricultural works to be performed by the agricultural machine and the field on which each agricultural work is to be performed. The work plan may include information on the day and time on which each agricultural work is scheduled to be performed. A work plan including information on the day and time on which each agricultural work is scheduled to be performed is particularly referred to as a "work schedule" or simply as a "schedule." The work schedule may include information on the scheduled start time and / or scheduled end time of each agricultural work performed on each work day. The work plan or work schedule may include information on the content of the work, the implement to be used, and / or the type and amount of agricultural materials to be used for each agricultural work. Here, "agricultural materials" refers to materials used in agricultural work performed by an agricultural machine. Agricultural materials may be simply referred to as "materials." Agricultural materials may include materials consumed by agricultural work, such as pesticides, fertilizers, seeds, or seedlings. The work plan may be created by a processing device that communicates with the agricultural machine to manage the agricultural work, or a processing device mounted on the agricultural machine. The processing device can create a work plan based on information input by a user (such as a farm manager or farm worker) by operating a terminal device, for example. In this specification, a processing device that communicates with agricultural machines and manages agricultural work is referred to as a "management device." The management device may manage agricultural work of multiple agricultural machines. In that case, the management device may create a work plan including information on each agricultural work performed by each of the multiple agricultural machines. The work plan can be downloaded by each agricultural machine and stored in a storage device. Each agricultural machine can automatically head to a field to perform the scheduled agricultural work according to the work plan, and perform the agricultural work.

[0014] An "environmental map" is data that expresses the positions or areas of objects that exist in the environment in which the agricultural machine moves using a specified coordinate system. An environmental map may be simply referred to as a "map" or "map data". The coordinate system that defines the environmental map may be, for example, a world coordinate system such as a geographic coordinate system fixed relative to the Earth. The environmental map may include information other than the positions of objects that exist in the environment (for example, attribute information and other information). The environmental map includes maps of various formats, such as a point cloud map or a grid map. Data of a local map or a partial map that is generated or processed in the process of constructing the environmental map is also referred to as a "map" or "map data".

[0015] A "global path" refers to data on a path connecting a starting point to a destination point when an agricultural machine moves automatically, which is generated by a processing device that performs path planning. Generating a global path is called global path planning or global path design. In the following description, the global path is also called a "target path" or simply a "path". The global path may be defined, for example, by the coordinate values ​​of multiple points through which the agricultural machine must pass. A point through which the agricultural machine must pass is called a "waypoint", and a line segment connecting adjacent waypoints is called a "link".

[0016] A "local path" means a local path that can avoid obstacles and is generated sequentially when the agricultural machine moves automatically along the global path. The generation of a local path is called local path planning or local path design. The local path is generated sequentially based on data acquired by one or more sensing devices equipped in the agricultural machine while the agricultural machine is moving. The local path may be defined by a plurality of waypoints along a part of the global path. However, if an obstacle exists near the global path, a waypoint may be set to bypass the obstacle. The length of the link between the waypoints in the local path is shorter than the length of the link between the waypoints in the global path. The device that generates the local path may be the same as or different from the device that generates the global path. For example, a management device that manages farm work by the agricultural machine may generate the global path, and a control device mounted on the agricultural machine may generate the local path. In this case, the combination of the management device and the control device functions as a "processing device" that performs path planning. The agricultural machine's controller may function as a processor for both global and local path planning.

[0017] "Farm road" means a road that is used mainly for agricultural purposes. Farm roads are not limited to roads paved with asphalt, but also include unpaved roads covered with dirt or gravel. Farm roads include roads (including private roads) that are exclusively passable by vehicle-type agricultural machinery (e.g., work vehicles such as tractors) and roads that are also passable by general vehicles (passenger cars, trucks, buses, etc.). Work vehicles may automatically travel on general roads in addition to farm roads. General roads are roads that have been developed for the traffic of general vehicles.

[0018] (Embodiment) Hereinafter, an embodiment of the present disclosure will be described. However, more detailed explanation than necessary may be omitted. For example, detailed explanation of already well-known matters and overlapping explanation of substantially the same configuration may be omitted. This is to avoid the following explanation becoming unnecessarily redundant and to facilitate understanding by those skilled in the art. Note that the inventor provides the attached drawings and the following explanation so that those skilled in the art can fully understand the present disclosure, and does not intend to limit the subject matter described in the claims by them. In the following description, components having the same or similar functions are given the same reference numerals.

[0019] The following embodiments are illustrative, and the technology of the present disclosure is not limited to the following embodiments. For example, the numerical values, shapes, materials, steps, order of steps, layout of the display screen, and the like shown in the following embodiments are merely examples, and various modifications are possible as long as no technical contradiction occurs. In addition, one aspect can be combined with another aspect as long as no technical contradiction occurs.

[0020] Hereinafter, an embodiment in which the technology of the present disclosure is applied to a work vehicle such as a tractor, which is an example of an agricultural machine, will be mainly described. The technology of the present disclosure is not limited to work vehicles such as tractors, but can also be applied to other types of agricultural machines.

[0021] FIG. 1 is a diagram for explaining an overview of an agricultural management system according to an exemplary embodiment of the present disclosure. The agricultural management system shown in FIG. 1 includes a work vehicle 100, a terminal device 400, and a management device 600. The terminal device 400 is a computer used by a user who remotely monitors the work vehicle 100. The management device 600 is a computer managed by a business operator who operates the agricultural management system. The work vehicle 100, the terminal device 400, and the management device 600 can communicate with each other via a network 80. Although one work vehicle 100 is illustrated in FIG. 1, the agricultural management system may include multiple work vehicles or other agricultural machines.

[0022] The work vehicle 100 in this embodiment is a tractor. The work vehicle 100 can be equipped with an implement at either the rear or the front, or both. The work vehicle 100 can travel within a field while performing agricultural work according to the type of implement. The work vehicle 100 may also travel within or outside a field without an implement attached.

[0023] The work vehicle 100 has an automatic driving function. That is, the work vehicle 100 can travel by the action of a control device, not manually. The control device in this embodiment is provided inside the work vehicle 100, and can control both the speed and steering of the work vehicle 100. The work vehicle 100 can travel automatically not only in a field, but also outside the field (for example, on a road).

[0024] The work vehicle 100 is equipped with devices used for positioning or self-position estimation, such as a GNSS receiver and a LiDAR sensor. The control device of the work vehicle 100 automatically drives the work vehicle 100 based on the position of the work vehicle 100 and information on the target route. In addition to controlling the driving of the work vehicle 100, the control device also controls the operation of the implement. This allows the work vehicle 100 to perform agricultural work using the implement while automatically driving in the field. Furthermore, the work vehicle 100 can automatically drive along a road outside the field (e.g., a farm road or a general road) along a target route. When the work vehicle 100 automatically drives along a road outside the field, it drives while generating a local route along the target route that can avoid obstacles based on data output from a sensing device such as a camera or a LiDAR sensor. The work vehicle 100 can also detect a farm road based on data output from the sensing device and drive while generating a local route on the farm road. This allows the work vehicle 100 to automatically travel appropriately on the farm road even if the global route is not set correctly on the farm road. The work vehicle 100 may travel in the field while generating a local route as described above, or may travel along a target route without generating a local route and stop if an obstacle is detected.

[0025] The management device 600 is a computer that manages agricultural work by the work vehicle 100. The management device 600 can be, for example, a server computer that centrally manages information about a field on the cloud and supports agriculture by utilizing data on the cloud. The management device 600, for example, creates a work plan for the work vehicle 100 and performs global path planning for the work vehicle 100 according to the work plan. The management device 600 generates a global path (target path) in a different manner for inside the field and outside the field. The management device 600 generates a target path in the field based on information about the field. For example, the management device 600 can generate a target path in the field based on various information such as the outline of the field registered in advance, the area of ​​the field, the position of the entrance and exit of the field, the width of the work vehicle 100, the width of the implement, the content of the work, the type of crop being cultivated, the growing area of ​​the crop, the growing condition of the crop, or the spacing between the rows of crops or ridges. The management device 600 generates a target route in the field based on information input by the user using the terminal device 400 or another device, for example. The management device 600 generates a route in the field so as to cover, for example, the entire work area where the work is performed. On the other hand, the management device 600 generates a target route outside the field according to a work plan or a user's instruction. For example, the management device 600 can generate a target route outside the field based on various information such as the order of farm work indicated by the work plan, the position of the field where each farm work is performed, the position of the entrance and exit of the field, the scheduled start time and scheduled end time of each farm work, road surface conditions, weather conditions, or traffic conditions. The management device 600 may generate a target route based on information indicating a route or a waypoint specified by the user by operating the terminal device 400, regardless of the work plan. The management device 600 may further generate and edit an environmental map based on data collected by the work vehicle 100 or other moving bodies using a sensing device such as a LiDAR sensor. The management device 600 transmits the generated work plan, target route, and environmental map data to the work vehicle 100. The work vehicle 100 automatically moves and performs farm work based on this data.

[0026] It should be noted that the global route design and the generation (or editing) of the environmental map may be performed by other devices, not limited to the management device 600. For example, a control device of the work vehicle 100 may perform the global route design or the generation or editing of the environmental map.

[0027] The terminal device 400 is a computer used by a user located away from the work vehicle 100. The terminal device 400 shown in FIG. 1 is a laptop computer, but is not limited thereto. The terminal device 400 may be a stationary computer such as a desktop PC (personal computer), or may be a mobile terminal such as a smartphone or a tablet computer. The terminal device 400 may be used to remotely monitor the work vehicle 100 or remotely operate the work vehicle 100. For example, the terminal device 400 can display on a display an image captured by one or more cameras (imaging devices) equipped on the work vehicle 100. The user can view the image, check the situation around the work vehicle 100, and send an instruction to stop or start the work vehicle 100. The terminal device 400 can also display on a display a setting screen for the user to input information required to create a work plan for the work vehicle 100 (for example, a schedule for each farm work). When the user inputs the required information on the setting screen and performs a transmission operation, the terminal device 400 transmits the input information to the management device 600. The management device 600 creates a work plan based on the information. The terminal device 400 may further include a function of displaying a setting screen on the display for the user to input information required for setting a target route.

[0028] The configuration and operation of the system in this embodiment will be described in more detail below.

[0029] [1. Configuration] 2 is a side view that shows a schematic example of the work vehicle 100 and an implement 300 coupled to the work vehicle 100. The work vehicle 100 in this embodiment can operate in both a manual driving mode and an automatic driving mode. In the automatic driving mode, the work vehicle 100 can travel unmanned. The work vehicle 100 can be automatically driven both inside and outside a field.

[0030] As shown in Fig. 2, the work vehicle 100 includes a vehicle body 101, a prime mover (engine) 102, and a transmission 103. The vehicle body 101 is provided with wheels 104 with tires, and a cabin 105. The wheels 104 include a pair of front wheels 104F and a pair of rear wheels 104R. A driver's seat 107, a steering device 106, an operation terminal 200, and a group of switches for operation are provided inside the cabin 105. When the work vehicle 100 travels for work in a field, one or both of the front wheels 104F and the rear wheels 104R may be replaced with (multiple) wheels (crawlers) equipped with tracks instead of tires.

[0031] The work vehicle 100 is equipped with a plurality of sensing devices that sense the surroundings of the work vehicle 100. In the example of Fig. 2, the sensing devices include a plurality of cameras 120, a LiDAR sensor 140, and a plurality of obstacle sensors 130.

[0032] The cameras 120 may be installed, for example, on the front, rear, left and right sides of the work vehicle 100. The cameras 120 capture images of the environment around the work vehicle 100 and generate image data. The images captured by the cameras 120 may be transmitted to a terminal device 400 for remote monitoring. The images may be used to monitor the work vehicle 100 during unmanned driving. The cameras 120 may also be used to generate images for recognizing surrounding objects or obstacles, white lines, signs, or indications when the work vehicle 100 travels on roads outside of fields (farm roads or general roads).

[0033] The LiDAR sensor 140 in the example of FIG. 2 is disposed at the lower front part of the vehicle body 101. The LiDAR sensor 140 may be disposed at another position. The LiDAR sensor 140 repeatedly outputs sensor data indicating the distance and direction to each measurement point of an object present in the surrounding environment, or the two-dimensional or three-dimensional coordinate value of each measurement point, while the work vehicle 100 is mainly traveling outside the field. The sensor data output from the LiDAR sensor 140 is processed by a control device of the work vehicle 100. The control device can estimate the self-position of the work vehicle 100 by matching the sensor data with an environmental map. The control device can further detect objects such as obstacles present in the vicinity of the work vehicle 100 based on the sensor data, and generate a local route along which the work vehicle 100 should actually proceed, along the global route. The control device can also generate or edit an environmental map, for example, by using an algorithm such as SLAM (Simultaneous Localization and Mapping). The work vehicle 100 may be equipped with multiple LiDAR sensors positioned at different locations and with different orientations.

[0034] The obstacle sensors 130 shown in FIG. 2 are provided at the front and rear of the cabin 105. The obstacle sensors 130 may be arranged at other locations. For example, one or more obstacle sensors 130 may be provided at any positions on the sides, front, and rear of the vehicle body 101. The obstacle sensor 130 may include, for example, a laser scanner or an ultrasonic sonar. The obstacle sensor 130 is used to detect surrounding obstacles during autonomous driving and to stop or detour the work vehicle 100. A LiDAR sensor 140 may be used as one of the obstacle sensors 130.

[0035] The work vehicle 100 further includes a GNSS unit 110. The GNSS unit 110 includes a GNSS receiver. The GNSS receiver may include an antenna for receiving signals from GNSS satellites and a processor for calculating the position of the work vehicle 100 based on the signals received by the antenna. The GNSS unit 110 receives satellite signals transmitted from a plurality of GNSS satellites and performs positioning based on the satellite signals. GNSS is a general term for satellite positioning systems such as GPS (Global Positioning System), QZSS (Quasi-Zenith Satellite System, e.g., Michibiki), GLONASS, Galileo, and BeiDou. The GNSS unit 110 in this embodiment is provided on the top of the cabin 105, but may be provided in another position.

[0036] The GNSS unit 110 may include an inertial measurement unit (IMU). Signals from the IMU may be used to supplement the position data. The IMU may measure the tilt and minute movements of the work vehicle 100. By using data acquired by the IMU to supplement the position data based on satellite signals, the performance of positioning may be improved.

[0037] The control device of the work vehicle 100 may use sensing data acquired by sensing devices such as the camera 120 or LiDAR sensor 140 for positioning, in addition to the positioning results by the GNSS unit 110. When features that function as feature points exist in the environment in which the work vehicle 100 travels, such as farm roads, forest roads, general roads, or orchards, the position and orientation of the work vehicle 100 can be estimated with high accuracy based on the data acquired by the camera 120 or LiDAR sensor 140 and an environmental map stored in advance in a storage device. The position of the work vehicle 100 can be identified with higher accuracy by correcting or complementing the position data based on satellite signals using the data acquired by the camera 120 or LiDAR sensor 140.

[0038] The prime mover 102 may be, for example, a diesel engine. An electric motor may be used instead of a diesel engine. The transmission 103 can change the propulsive force and travel speed of the work vehicle 100 by changing gears. The transmission 103 can also switch the work vehicle 100 between forward and reverse.

[0039] The steering device 106 includes a steering wheel, a steering shaft connected to the steering wheel, and a power steering device that assists steering by the steering wheel. The front wheels 104F are steered wheels, and the traveling direction of the work vehicle 100 can be changed by changing the turning angle (also referred to as the "steering angle"). The steering angle of the front wheels 104F can be changed by operating the steering wheel. The power steering device includes a hydraulic device or an electric motor that supplies an auxiliary force for changing the steering angle of the front wheels 104F. When automatic steering is performed, the steering angle is automatically adjusted by the force of the hydraulic device or the electric motor under the control of a control device arranged in the work vehicle 100.

[0040] A coupling device 108 is provided at the rear of the vehicle body 101. The coupling device 108 includes, for example, a three-point support device (also referred to as a "three-point link" or "three-point hitch"), a PTO (Power Take Off) shaft, a universal joint, and a communication cable. The coupling device 108 can attach and detach the implement 300 to and from the work vehicle 100. The coupling device 108 can change the position or attitude of the implement 300 by raising and lowering the three-point link using, for example, a hydraulic device. In addition, power can be sent from the work vehicle 100 to the implement 300 via the universal joint. The work vehicle 100 can make the implement 300 perform a predetermined task while pulling the implement 300. The coupling device may be provided at the front of the vehicle body 101. In that case, the implement can be connected to the front of the work vehicle 100.

[0041] 2 is a rotary tiller, the implement 300 is not limited to a rotary tiller. For example, any implement, such as a seeder, a spreader, a transplanter, a mower, a rake, a baler, a harvester, a sprayer, or a harrow, can be connected to the work vehicle 100 and used.

[0042] 2 is capable of manned operation, but may be capable of only unmanned operation. In that case, components necessary only for manned operation, such as the cabin 105, steering device 106, and driver's seat 107, may not be provided in the work vehicle 100. The unmanned work vehicle 100 can travel autonomously or by remote control by a user.

[0043] 3 is a block diagram showing an example configuration of the work vehicle 100 and the implement 300. The work vehicle 100 and the implement 300 can communicate with each other via a communication cable included in the coupling device 108. The work vehicle 100 can communicate with the terminal device 400 and the management device 600 via the network 80.

[0044] The work vehicle 100 in the example of FIG. 3 includes a GNSS unit 110, a camera 120, an obstacle sensor 130, a LiDAR sensor 140, and an operation terminal 200, as well as a sensor group 150 for detecting the operating state of the work vehicle 100, a control system 160, a communication device 190, an operation switch group 210, a buzzer 220, and a drive device 240. These components are connected to each other so as to be able to communicate with each other via a bus. The GNSS unit 110 includes a GNSS receiver 111, an RTK receiver 112, an inertial measurement unit (IMU) 115, and a processing circuit 116. The sensor group 150 includes a steering wheel sensor 152, a turning angle sensor 154, and an axle sensor 156. The control system 160 includes a storage device 170 and a control device 180. The control device 180 includes a plurality of electronic control units (ECUs) 181 to 186. The implement 300 includes a drive unit 340, a control unit 380, and a communication unit 390. Note that Fig. 3 shows components that are relatively highly related to the operation of the autonomous driving by the work vehicle 100, and does not show other components.

[0045] The GNSS receiver 111 in the GNSS unit 110 receives satellite signals transmitted from a plurality of GNSS satellites and generates GNSS data based on the satellite signals. The GNSS data is generated in a predetermined format, such as the NMEA-0183 format. The GNSS data may include, for example, values ​​indicating the identification number, elevation angle, azimuth angle, and reception strength of each satellite from which the satellite signal is received.

[0046] The GNSS unit 110 shown in FIG. 3 performs positioning of the work vehicle 100 using RTK (Real Time Kinematic)-GNSS. FIG. 4 is a conceptual diagram showing an example of a work vehicle 100 performing positioning by RTK-GNSS. In positioning by RTK-GNSS, in addition to satellite signals transmitted from multiple GNSS satellites 50, correction signals transmitted from a reference station 60 are used. The reference station 60 may be installed near the field where the work vehicle 100 performs work travel (for example, within 10 km from the work vehicle 100). The reference station 60 generates a correction signal, for example, in an RTCM format, based on the satellite signals received from the multiple GNSS satellites 50, and transmits it to the GNSS unit 110. The RTK receiver 112 includes an antenna and a modem, and receives the correction signal transmitted from the reference station 60. The processing circuit 116 of the GNSS unit 110 corrects the positioning result by the GNSS receiver 111 based on the correction signal. By using RTK-GNSS, it is possible to perform positioning with an accuracy of, for example, a few centimeters. Position information including latitude, longitude, and altitude information is acquired by highly accurate positioning using RTK-GNSS. The GNSS unit 110 calculates the position of the work vehicle 100 at a frequency of, for example, about 1 to 10 times per second.

[0047] The positioning method is not limited to RTK-GNSS, and any positioning method (such as interferometric positioning or relative positioning) that can obtain position information with the required accuracy can be used. For example, positioning may be performed using a Virtual Reference Station (VRS) or a Differential Global Positioning System (DGPS). If position information with the required accuracy can be obtained without using a correction signal transmitted from the reference station 60, the position information may be generated without using a correction signal. In that case, the GNSS unit 110 does not need to be equipped with the RTK receiver 112.

[0048] Even when RTK-GNSS is used, in places where a correction signal from the reference station 60 cannot be obtained (for example, on a road far from a field), the position of the work vehicle 100 is estimated by other methods without relying on a signal from the RTK receiver 112. For example, the position of the work vehicle 100 can be estimated by matching data output from the LiDAR sensor 140 and / or the camera 120 with a highly accurate environmental map.

[0049] The GNSS unit 110 in this embodiment further includes an IMU 115. The IMU 115 may include a three-axis acceleration sensor and a three-axis gyroscope. The IMU 115 may include an orientation sensor such as a three-axis geomagnetic sensor. The IMU 115 functions as a motion sensor and can output signals indicating various quantities such as the acceleration, speed, displacement, and attitude of the work vehicle 100. The processing circuit 116 can estimate the position and orientation of the work vehicle 100 with higher accuracy based on the signal output from the IMU 115 in addition to the satellite signal and the correction signal. The signal output from the IMU 115 can be used to correct or complement the position calculated based on the satellite signal and the correction signal. The IMU 115 outputs signals at a higher frequency than the GNSS receiver 111. Using the high-frequency signal, the processing circuit 116 can measure the position and orientation of the work vehicle 100 at a higher frequency (for example, 10 Hz or more). Instead of the IMU 115, a three-axis acceleration sensor and a three-axis gyroscope may be provided separately. The IMU 115 may be provided as a device separate from the GNSS unit 110.

[0050] The camera 120 is an imaging device that captures the environment around the work vehicle 100. The camera 120 includes an image sensor, such as a charge coupled device (CCD) or a complementary metal oxide semiconductor (CMOS). The camera 120 may also include an optical system including one or more lenses, and a signal processing circuit. The camera 120 captures the environment around the work vehicle 100 while the work vehicle 100 is traveling, and generates image (e.g., video) data. The camera 120 can capture video at a frame rate of, for example, 3 frames per second (fps) or more. The images generated by the camera 120 can be used, for example, when a remote observer uses the terminal device 400 to check the environment around the work vehicle 100. The images generated by the camera 120 may be used for positioning or obstacle detection. As shown in FIG. 2, multiple cameras 120 may be provided at different positions on the work vehicle 100, or a single camera may be provided. A visible camera for generating a visible light image and an infrared camera for generating an infrared image may be provided separately. Both a visible camera and an infrared camera may be provided as cameras for generating images for monitoring. The infrared camera may also be used to detect obstacles at night.

[0051] The obstacle sensor 130 detects objects present around the work vehicle 100. The obstacle sensor 130 may include, for example, a laser scanner or an ultrasonic sonar. When an object is present closer than a predetermined distance from the obstacle sensor 130, the obstacle sensor 130 outputs a signal indicating the presence of an obstacle. A plurality of obstacle sensors 130 may be provided at different positions of the work vehicle 100. For example, a plurality of laser scanners and a plurality of ultrasonic sonars may be disposed at different positions of the work vehicle 100. By providing such a large number of obstacle sensors 130, blind spots in monitoring obstacles around the work vehicle 100 can be reduced.

[0052] The steering wheel sensor 152 measures the rotation angle of the steering wheel of the work vehicle 100. The turning angle sensor 154 measures the turning angle of the front wheels 104F which are steered wheels. The measurement values ​​by the steering wheel sensor 152 and the turning angle sensor 154 are used for steering control by the control device 180.

[0053] The axle sensor 156 measures the rotational speed of the axle connected to the wheels 104, i.e., the number of rotations per unit time. The axle sensor 156 may be a sensor that uses, for example, a magnetoresistive element (MR), a Hall element, or an electromagnetic pickup. The axle sensor 156 outputs, for example, a numerical value indicating the number of rotations per minute (unit: rpm) of the axle. The axle sensor 156 is used to measure the speed of the work vehicle 100.

[0054] The drive device 240 includes various devices necessary for the travel of the work vehicle 100 and the driving of the implement 300, such as the above-mentioned prime mover 102, the transmission 103, the steering device 106, and the coupling device 108. The prime mover 102 may include an internal combustion engine such as a diesel engine. The drive device 240 may include an electric motor for traction instead of or in addition to the internal combustion engine.

[0055] The buzzer 220 is an audio output device that emits a warning sound to notify of an abnormality. For example, the buzzer 220 emits a warning sound when an obstacle is detected during automatic driving. The buzzer 220 is controlled by the control device 180.

[0056] The storage device 170 includes one or more storage media such as a flash memory or a magnetic disk. The storage device 170 stores various data generated by the GNSS unit 110, the camera 120, the obstacle sensor 130, the LiDAR sensor 140, the sensor group 150, and the control device 180. The data stored in the storage device 170 may include map data (environmental map) of the environment in which the work vehicle 100 travels, and data of a global route (target route) for automatic driving. The environmental map includes information on multiple farm fields in which the work vehicle 100 performs farm work and the roads in the surrounding areas. The environmental map and the target route may be generated by a processor in the management device 600. Note that the control device 180 in this embodiment has a function of generating or editing the environmental map and the target route. The control device 180 can edit the environmental map and the target route acquired from the management device 600 according to the travel environment of the work vehicle 100. The storage device 170 also stores data on the work plan received by the communication device 190 from the management device 600. The work plan includes information regarding a plurality of farm works to be performed by the work vehicle 100 over a plurality of work days. The work plan may be, for example, work schedule data including information on the scheduled time of each farm work to be performed by the work vehicle 100 on each work day. The storage device 170 also stores computer programs that cause each ECU in the control device 180 to execute various operations described below. Such computer programs may be provided to the work vehicle 100 via a storage medium (e.g., a semiconductor memory or an optical disk) or an electric communication line (e.g., the Internet). Such computer programs may be sold as commercial software.

[0057] The control device 180 includes a plurality of ECUs, such as an ECU 181 for speed control, an ECU 182 for steering control, an ECU 183 for implement control, an ECU 184 for automatic driving control, an ECU 185 for route generation, and an ECU 186 for map generation.

[0058] The ECU 181 controls the speed of the work vehicle 100 by controlling the prime mover 102 , the transmission 103 , and the brakes, all of which are included in the drive device 240 .

[0059] The ECU 182 controls the steering of the work vehicle 100 by controlling the hydraulic device or electric motor included in the steering device 106 based on the measurement values ​​of the steering wheel sensor 152 .

[0060] The ECU 183 controls the operation of the three-point link and the PTO shaft included in the coupling device 108, etc., in order to cause the implement 300 to perform a desired operation. The ECU 183 also generates a signal that controls the operation of the implement 300, and transmits the signal from the communication device 190 to the implement 300.

[0061] The ECU 184 performs calculations and control to realize autonomous driving based on data output from the GNSS unit 110, the camera 120, the obstacle sensor 130, the LiDAR sensor 140, and the sensor group 150. For example, the ECU 184 identifies the position of the work vehicle 100 based on data output from at least one of the GNSS unit 110, the camera 120, and the LiDAR sensor 140. In a farm field, the ECU 184 may determine the position of the work vehicle 100 based only on data output from the GNSS unit 110. The ECU 184 may estimate or correct the position of the work vehicle 100 based on data acquired by the camera 120 or the LiDAR sensor 140. By using the data acquired by the camera 120 or the LiDAR sensor 140, the accuracy of positioning can be further improved. Outside the farm field, the ECU 184 estimates the position of the work vehicle 100 using data output from the LiDAR sensor 140 or the camera 120. For example, the ECU 184 may estimate the position of the work vehicle 100 by matching data output from the LiDAR sensor 140 or the camera 120 with an environmental map. During autonomous driving, the ECU 184 performs calculations necessary for the work vehicle 100 to travel along a target path or a local path based on the estimated position of the work vehicle 100. The ECU 184 sends a speed change command to the ECU 181 and a steering angle change command to the ECU 182. In response to the speed change command, the ECU 181 changes the speed of the work vehicle 100 by controlling the prime mover 102, the transmission 103, or the brakes. In response to the steering angle change command, the ECU 182 changes the steering angle by controlling the steering device 106.

[0062] The ECU 185 sequentially generates local routes that can avoid obstacles while the work vehicle 100 is traveling along the target route. For example, the ECU 185 recognizes farm roads and obstacles around the work vehicle 100 based on data output from the camera 120, the obstacle sensor 130, and the LiDAR sensor 140 while the work vehicle 100 is traveling. The ECU 185 generates local routes on the farm roads so as to avoid the recognized obstacles. The ECU 185 may have a function of designing a global route instead of the management device 600. In that case, the ECU 185 determines the destination of the work vehicle 100 based on the work plan stored in the storage device 170, and determines a target route from the start point of the movement of the work vehicle 100 to the destination point. The ECU 185 can create a target route that can reach the destination in the shortest time, for example, based on an environmental map including road information stored in the storage device 170.

[0063] The ECU 186 generates or edits a map of the environment in which the work vehicle 100 travels. In this embodiment, an environmental map generated by an external device such as the management device 600 is transmitted to the work vehicle 100 and recorded in the storage device 170, but the ECU 186 can also generate or edit the environmental map instead. Hereinafter, an operation in which the ECU 186 generates an environmental map will be described. The environmental map can be generated based on sensor data output from the LiDAR sensor 140. When generating the environmental map, the ECU 186 sequentially generates three-dimensional point cloud data based on the sensor data output from the LiDAR sensor 140 while the work vehicle 100 is traveling. The ECU 186 can generate the environmental map by connecting the point cloud data sequentially generated using an algorithm such as SLAM. The environmental map generated in this manner is a highly accurate three-dimensional map and can be used for self-location estimation by the ECU 184. A two-dimensional map used for global route planning can be generated based on this three-dimensional map. In this specification, the 3D map used for self-localization and the 2D map used for global route planning are both referred to as “environment maps.” The ECU 186 can also edit the map by adding various attribute information related to structures, road surface conditions, road passability, etc., recognized based on data output from the camera 120 or the LiDAR sensor 140.

[0064] Through the operation of these ECUs, the control device 180 realizes autonomous driving. During autonomous driving, the control device 180 controls the drive device 240 based on the measured or estimated position of the work vehicle 100 and the target route. In this way, the control device 180 can cause the work vehicle 100 to travel along the target route.

[0065] The multiple ECUs included in the control device 180 can communicate with each other according to a vehicle bus standard such as CAN (Controller Area Network). A faster communication method such as in-vehicle Ethernet (registered trademark) may be used instead of CAN. In FIG. 3, each of the ECUs 181 to 186 is shown as an individual block, but the functions of each of these may be realized by multiple ECUs. An in-vehicle computer that integrates at least some of the functions of the ECUs 181 to 186 may be provided. The control device 180 may include ECUs other than the ECUs 181 to 186, and any number of ECUs may be provided depending on the functions. Each ECU includes a processing circuit including one or more processors.

[0066] The communication device 190 is a device including a circuit for communicating with the implement 300, the terminal device 400, and the management device 600. The communication device 190 includes a circuit for transmitting and receiving signals conforming to the ISOBUS standard such as ISOBUS-TIM between the communication device 390 of the implement 300. This allows the implement 300 to perform a desired operation and to obtain information from the implement 300. The communication device 190 may further include an antenna and a communication circuit for transmitting and receiving signals between the communication devices of the terminal device 400 and the management device 600 via the network 80. The network 80 may include, for example, a cellular mobile communication network such as 3G, 4G, or 5G, and the Internet. The communication device 190 may have a function for communicating with a mobile terminal used by a supervisor near the work vehicle 100. Communication between such mobile terminals may be performed in accordance with any wireless communication standard, such as Wi-Fi (registered trademark), cellular mobile communication such as 3G, 4G or 5G, or Bluetooth (registered trademark).

[0067] The operation terminal 200 is a terminal through which a user performs operations related to the traveling of the work vehicle 100 and the operation of the implement 300, and is also referred to as a virtual terminal (VT). The operation terminal 200 may include a display device such as a touch screen, and / or one or more buttons. The display device may be, for example, a display such as a liquid crystal or an organic light-emitting diode (OLED). By operating the operation terminal 200, a user can perform various operations such as switching the automatic driving mode on / off, recording or editing an environmental map, setting a target route, and switching the implement 300 on / off. At least some of these operations can also be realized by operating the operation switch group 210. The operation terminal 200 may be configured to be removable from the work vehicle 100. A user at a location away from the work vehicle 100 may operate the detached operation terminal 200 to control the operation of the work vehicle 100. The user may control the operation of the work vehicle 100 by operating a computer on which necessary application software is installed, such as a terminal device 400, instead of the operation terminal 200.

[0068] 5 is a diagram showing an example of the operation terminal 200 and the operation switch group 210 provided inside the cabin 105. Inside the cabin 105, the operation switch group 210 including a plurality of switches that can be operated by a user is arranged. The operation switch group 210 may include, for example, a switch for selecting a gear stage of the main transmission or the sub-transmission, a switch for switching between an automatic driving mode and a manual driving mode, a switch for switching between forward and reverse, and a switch for raising and lowering the implement 300. Note that in the case where the work vehicle 100 only performs unmanned driving and does not have a function of manned driving, the work vehicle 100 does not need to have the operation switch group 210.

[0069] The drive device 340 in the implement 300 shown in Fig. 3 performs operations necessary for the implement 300 to perform a predetermined task. The drive device 340 includes devices according to the application of the implement 300, such as a hydraulic device, an electric motor, or a pump. The control device 380 controls the operation of the drive device 340. The control device 380 causes the drive device 340 to perform various operations in response to signals transmitted from the work vehicle 100 via the communication device 390. In addition, a signal according to the state of the implement 300 can also be transmitted from the communication device 390 to the work vehicle 100.

[0070] Next, the configurations of the management device 600 and the terminal device 400 will be described with reference to Fig. 6. Fig. 6 is a block diagram illustrating a schematic hardware configuration of the management device 600 and the terminal device 400.

[0071] The management device 600 includes a storage device 650, a processor 660, a ROM (Read Only Memory) 670, a RAM (Random Access Memory) 680, and a communication device 690. These components are connected to each other via a bus so that they can communicate with each other. The management device 600 can function as a cloud server that manages the schedule of farm work in a field performed by the work vehicle 100 and supports agriculture by utilizing the data it manages. A user can input information required for creating a work plan using the terminal device 400 and upload the information of the work plan to the management device 600 via the network 80. The management device 600 can create a schedule of farm work, that is, a work plan, based on the information. The management device 600 can also generate or edit an environmental map and perform global route planning for the work vehicle 100. The environmental map may be distributed from a computer external to the management device 600.

[0072] The communication device 690 is a communication module for communicating with the work vehicle 100 and the terminal device 400 via the network 80. The communication device 690 can perform wired communication conforming to a communication standard such as IEEE1394 (registered trademark) or Ethernet (registered trademark). The communication device 690 may perform wireless communication conforming to the Bluetooth (registered trademark) standard or the Wi-Fi standard, or cellular mobile communication such as 3G, 4G, or 5G.

[0073] The processor 660 may be, for example, a semiconductor integrated circuit including a central processing unit (CPU). The processor 660 may be realized by a microprocessor or a microcontroller. Alternatively, the processor 660 may be realized by a field programmable gate array (FPGA) equipped with a CPU, a graphics processing unit (GPU), an application specific integrated circuit (ASIC), an application specific standard product (ASSP), or a combination of two or more circuits selected from these circuits. The processor 660 sequentially executes a computer program stored in the ROM 670, which describes a group of instructions for executing at least one process, to realize a desired process.

[0074] The ROM 670 is, for example, a writable memory (e.g., PROM), a rewritable memory (e.g., flash memory), or a read-only memory. The ROM 670 stores a program that controls the operation of the processor 660. The ROM 670 does not need to be a single storage medium, and may be a collection of multiple storage media. A part of the collection of multiple storage media may be a removable memory.

[0075] The RAM 680 provides a working area for temporarily loading, at boot time, the control program stored in the ROM 670. The RAM 680 does not have to be a single storage medium, and may be a collection of multiple storage media.

[0076] The storage device 650 mainly functions as a database storage. The storage device 650 may be, for example, a magnetic storage device or a semiconductor storage device. An example of a magnetic storage device is a hard disk drive (HDD). An example of a semiconductor storage device is a solid state drive (SSD). The storage device 650 may be a device independent of the management device 600. For example, the storage device 650 may be a storage device connected to the management device 600 via the network 80, such as a cloud storage.

[0077] The terminal device 400 includes an input device 420, a display device 430, a storage device 450, a processor 460, a ROM 470, a RAM 480, and a communication device 490. These components are connected to each other via a bus so as to be able to communicate with each other. The input device 420 is a device for converting instructions from a user into data and inputting the data to a computer. The input device 420 may be, for example, a keyboard, a mouse, or a touch panel. The display device 430 may be, for example, a liquid crystal display or an organic EL display. The processor 460, the ROM 470, the RAM 480, the storage device 450, and the communication device 490 are described in the hardware configuration example of the management device 600, and the description thereof will be omitted.

[0078] [2. Operation] Next, the operations of the work vehicle 100, the terminal device 400, and the management device 600 will be described.

[0079] [2-1. Automatic driving operation] First, an example of the operation of automatic driving by the work vehicle 100 will be described. The work vehicle 100 in this embodiment can automatically travel both inside and outside the field. In the field, the work vehicle 100 drives the implement 300 while traveling along a preset target route to perform a predetermined agricultural work. When the obstacle sensor 130 detects an obstacle while traveling in the field, the work vehicle 100 stops traveling, emits a warning sound from the buzzer 220, and transmits a warning signal to the terminal device 400. In the field, the positioning of the work vehicle 100 is mainly performed based on data output from the GNSS unit 110. On the other hand, outside the field, the work vehicle 100 automatically travels along a target route set on a farm road or a general road outside the field. While traveling outside the field, the work vehicle 100 travels while performing local route planning based on data acquired by the camera 120 or the LiDAR sensor 140. For example, while traveling outside the field, the work vehicle 100 can detect a farm road based on data acquired by the camera 120 or the LiDAR sensor 140 and travel while generating a local route on the farm road. When an obstacle is detected outside the field, the work vehicle 100 avoids the obstacle or stops on the spot. Outside the field, the position of the work vehicle 100 is estimated based on the positioning data output from the GNSS unit 110 as well as the data output from the LiDAR sensor 140 or the camera 120.

[0080] The following first describes the operation of the work vehicle 100 when it travels automatically within a farm field. The operation of the work vehicle 100 when it travels automatically outside a farm field, and the processing of global route design and local route design outside a farm field will be described later.

[0081] FIG. 7 is a diagram showing an example of a work vehicle 100 that automatically travels along a target route in a field. In this example, the field includes a work area 72 in which the work vehicle 100 performs work using the implement 300, and a headland 74 located near the outer periphery of the field. Which area of ​​the field on the map corresponds to the work area 72 or the headland 74 can be set in advance by the user. The target route in this example includes multiple parallel main routes P1 and multiple turning routes P2 that connect the multiple main routes P1. The main route P1 is located within the work area 72, and the turning route P2 is located within the headland 74. Each main route P1 shown in FIG. 7 is a straight route, but each main route P1 may include a curved portion. The dashed line in FIG. 7 represents the working width of the implement 300. The working width is set in advance and recorded in the storage device 170. The working width may be set and recorded by the user operating the operation terminal 200 or the terminal device 400. Alternatively, the working width may be automatically recognized and recorded when the implement 300 is connected to the work vehicle 100. The interval between the multiple main paths P1 may be set according to the working width. The target path may be created based on the user's operation before the automatic driving is started. The target path may be created so as to cover, for example, the entire working area 72 in the field. The work vehicle 100 automatically travels back and forth from the start point of the work to the end point of the work along the target path as shown in FIG. 7. Note that the target path shown in FIG. 7 is merely an example, and the method of determining the target path is arbitrary.

[0082] Next, an example of control by the control device 180 during automatic operation in a farm field will be described.

[0083] FIG. 8 is a flowchart showing an example of the operation of steering control during automatic driving executed by the control device 180. The control device 180 performs automatic steering by executing the operations of steps S121 to S125 shown in FIG. 8 while the work vehicle 100 is traveling. The speed is maintained at a preset speed, for example. The control device 180 acquires data indicating the position of the work vehicle 100 generated by the GNSS unit 110 while the work vehicle 100 is traveling (step S121). Next, the control device 180 calculates the deviation between the position of the work vehicle 100 and the target route (step S122). The deviation represents the distance between the position of the work vehicle 100 at that time and the target route. The control device 180 determines whether the deviation of the calculated position exceeds a preset threshold value (step S123). If the deviation exceeds the threshold value, the control device 180 changes the steering angle by changing the control parameters of the steering device included in the drive device 240 so that the deviation becomes smaller. If the deviation does not exceed the threshold in step S123, the operation of step S124 is omitted. In the following step S125, the control device 180 determines whether or not a command to end the operation has been received. The command to end the operation may be issued, for example, when a user remotely instructs the automatic driving to be stopped or when the work vehicle 100 reaches the destination. If the command to end the operation has not been issued, the process returns to step S121, and the same operation is executed based on the newly measured position of the work vehicle 100. The control device 180 repeats the operations of steps S121 to S125 until a command to end the operation is issued. The above operations are executed by the ECUs 182 and 184 in the control device 180.

[0084] 8, the control device 180 controls the driving device 240 based only on the deviation between the position of the work vehicle 100 identified by the GNSS unit 110 and the target route, but the control may also take into consideration the azimuth deviation. For example, when the azimuth deviation, which is the angular difference between the orientation of the work vehicle 100 identified by the GNSS unit 110 and the direction of the target route, exceeds a preset threshold, the control device 180 may change a control parameter (e.g., steering angle) of the steering device of the driving device 240 in accordance with the deviation.

[0085] Hereinafter, an example of steering control by the control device 180 will be described more specifically with reference to FIGS. 9A to 9D.

[0086] FIG. 9A is a diagram showing an example of the work vehicle 100 traveling along the target route P. FIG. 9B is a diagram showing an example of the work vehicle 100 in a position shifted to the right from the target route P. FIG. 9C is a diagram showing an example of the work vehicle 100 in a position shifted to the left from the target route P. FIG. 9D is a diagram showing an example of the work vehicle 100 facing in an inclined direction with respect to the target route P. In these figures, the pose indicating the position and orientation of the work vehicle 100 measured by the GNSS unit 110 is expressed as r(x, y, θ). (x, y) are coordinates representing the position of the reference point of the work vehicle 100 in the XY coordinate system, which is a two-dimensional coordinate system fixed to the earth. In the examples shown in FIGS. 9A to 9D, the reference point of the work vehicle 100 is at the position where the GNSS antenna on the cabin is installed, but the position of the reference point is arbitrary. θ is an angle representing the measured orientation of the work vehicle 100. In the illustrated example, the target route P is parallel to the Y axis, but generally the target route P is not necessarily parallel to the Y axis.

[0087] As shown in FIG. 9A, if the position and orientation of the work vehicle 100 do not deviate from the target route P, the control device 180 maintains the steering angle and speed of the work vehicle 100 without changing them.

[0088] 9B, when the position of the work vehicle 100 has shifted to the right from the target route P, the control device 180 changes the steering angle so that the travel direction of the work vehicle 100 tilts to the left and approaches the route P. At this time, the speed may be changed in addition to the steering angle. The magnitude of the steering angle may be adjusted according to the magnitude of the position deviation Δx, for example.

[0089] 9C, when the position of the work vehicle 100 has shifted to the left from the target route P, the control device 180 changes the steering angle so that the travel direction of the work vehicle 100 tilts to the right and approaches the route P. In this case, the speed may also be changed in addition to the steering angle. The amount of change in the steering angle may be adjusted according to the magnitude of the position deviation Δx, for example.

[0090] As shown in FIG. 9D, when the position of the work vehicle 100 is not far from the target route P but the orientation is different from the direction of the target route P, the control device 180 changes the steering angle so that the azimuth deviation Δθ becomes smaller. In this case, the speed may also be changed in addition to the steering angle. The magnitude of the steering angle may be adjusted, for example, according to the magnitudes of the position deviation Δx and the azimuth deviation Δθ. For example, the smaller the absolute value of the position deviation Δx, the larger the amount of change in the steering angle according to the azimuth deviation Δθ may be. When the absolute value of the position deviation Δx is large, the steering angle is changed significantly to return to the route P, so that the absolute value of the azimuth deviation Δθ inevitably becomes large. Conversely, when the absolute value of the position deviation Δx is small, it is necessary to bring the azimuth deviation Δθ closer to zero. For this reason, it is appropriate to relatively increase the weight of the azimuth deviation Δθ (i.e., the control gain) for determining the steering angle.

[0091] Control techniques such as PID control or MPC control (model predictive control) can be applied to the steering control and speed control of the work vehicle 100. By applying these control techniques, the control for moving the work vehicle 100 closer to the target path P can be made smooth.

[0092] If an obstacle is detected by one or more obstacle sensors 130 while traveling, the control device 180 stops the work vehicle 100. At this time, the control device 180 may cause the buzzer 220 to emit an alarm or send an alarm signal to the terminal device 400. If it is possible to avoid the obstacle, the control device 180 may control the drive device 240 to avoid the obstacle.

[0093] The work vehicle 100 in this embodiment is capable of autonomous driving not only in a field but also outside the field. Outside the field, the control device 180 can detect objects (e.g., other vehicles or pedestrians) that exist at a position relatively far from the work vehicle 100 based on data output from the camera 120 or the LiDAR sensor 140. The control device 180 can realize autonomous driving on roads outside the field by generating a local route to avoid the detected object and performing speed control and steering control along the local route.

[0094] In this way, the work vehicle 100 in this embodiment can automatically travel inside and outside the field without a human driver. FIG. 10 is a diagram showing an example of a situation in which a plurality of work vehicles 100 are automatically traveling inside the field 70 and on the road 76 outside the field 70. The storage device 170 records an environmental map and a target route of an area including a plurality of fields and roads around them. The environmental map and the target route can be generated by the management device 600 or the ECU 185. When the work vehicle 100 travels on a road, the work vehicle 100 travels along the target route while sensing the surroundings using sensing devices such as the camera 120 and the LiDAR sensor 140 with the implement 300 raised. During travel, the control device 180 sequentially generates local routes and causes the work vehicle 100 to travel along the local routes. This allows the work vehicle 100 to travel automatically while avoiding obstacles. The target route may be changed during travel depending on the situation.

[0095] [2-2. Identifying whether it is a farm road or not] The sensing device of the work vehicle 100 and the control device 180 of the work vehicle 100 in this embodiment work together to function as a farm road identification system for the work vehicle 100. The farm road identification system can identify whether or not the road on which the work vehicle 100 is about to travel is a farm road. The farm road identification system is mainly used while the work vehicle 100 is traveling automatically outside the field. The farm road identification system can execute an operation of identifying whether or not the road is a farm road and generating a local route along the farm road. The farm road identification system may identify farm roads while the work vehicle 100 is manually traveling outside the field and collect data on the position and width of the farm road. The collected data may be used for generating a map including detailed information on the farm roads.

[0096] In the example of FIG. 2, the sensing device of the work vehicle 100 includes, for example, a plurality of cameras 120, a LiDAR sensor 140, and a plurality of obstacle sensors 130. Without being limited thereto, the sensing device of the work vehicle 100 may include at least one of the camera 120, the obstacle sensor 130, and the LiDAR sensor 140. At least one of the sensing devices possessed by the work vehicle 100 can be used as a sensing device in the farm road identification system. Note that, although an example in which a sensing device provided in the work vehicle 100 is used as a sensing device possessed by the farm road identification system will be described here, this is not limiting. For example, a sensing device possessed by another moving body such as an agricultural machine other than the work vehicle 100 or a drone (unmanned aerial vehicle: UAV) may be used as a sensing device in the farm road identification system.

[0097] The sensing device senses the ground on which the work vehicle 100 runs (for example, the ground located in the traveling direction of the work vehicle 100) to obtain sensing data related to the ground. This sensing data may be referred to as "first sensing data". The sensing device also senses the environment around the work vehicle 100 to obtain sensing data related to the surrounding environment including features other than the ground. This sensing data may be referred to as "second sensing data". The first sensing data and the second sensing data may be obtained by the same sensing device or by different sensing devices. For example, the first sensing data may be obtained by the camera 120 and the second sensing data may be obtained by the LiDAR sensor 140, or vice versa. Alternatively, one or both of the first sensing data and the second sensing data may be obtained using both the camera 120 and the LiDAR sensor 140. The first sensing data obtained by the camera 120 may include image data of the ground on which the work vehicle 100 runs. The first sensing data acquired by the LiDAR sensor 140 may include point cloud data of the ground on which the work vehicle 100 travels. Similarly, the second sensing data acquired by sensing with the camera 120 may include image data of the environment around the work vehicle 100. The second sensing data acquired by sensing with the LiDAR sensor 140 may include point cloud data of the environment around the work vehicle 100.

[0098] The control device 180 of the work vehicle 100 functions as a processing device that identifies whether or not the road on which the work vehicle 100 is traveling is a farm road based on the first sensing data and the second sensing data. Here, an example in which the control device 180 functions as a processing device of the farm road identification system will be described, but a part or all of the processing executed by the control device 180 in the farm road identification system may be executed by another device. Such another device may be any of the management device 600 (processor 660), the terminal device 400 (processor 460), and the operation terminal 200. For example, when a part of the processing executed by the control device 180 is executed by the processor 660 of the management device 600, the combination of the control device 180 and the management device 600 functions as a processing device of the farm road identification system. Here, an example in which the ECU 185 for route generation possessed by the control device 180 functions as a processing device of the farm road identification system will be described, but the farm road identification processing may be executed by another ECU possessed by the control device 180. In addition to the ECUs 181 to 186, the control device 180 may further have an ECU for identifying whether or not the road is a farm road.

[0099] The control device 180 acquires information relating to a transverse profile of the ground on which the work vehicle 100 travels, based on the first sensing data. The control device 180 also acquires information relating to the environment around the work vehicle 100, based on the second sensing data. The information relating to the transverse profile of the ground on which the work vehicle 100 travels is sometimes referred to as "first information," and the information relating to the environment around the work vehicle 100 is sometimes referred to as "second information."

[0100] The transverse profile of the ground on which the work vehicle 100 travels refers to the shape of the ground (i.e., the ground surface) in a direction intersecting the direction in which the work vehicle 100 travels (hereinafter also referred to as the "transverse direction"). The transverse profile can be acquired, for example, as a graph in which the horizontal axis represents the position on the scanning line in the transverse direction and the vertical axis represents the distance (i.e., height or depth) of the ground relative to a reference plane, or as table data including information of such a graph. The "reference plane" is, for example, a horizontal plane, but may be an inclined plane when the ground is inclined as a whole. If the sensing device has a ranging capability, the distance from the reference plane to the ground can be calculated based on the position information of the sensing device and information acquired by measuring the distance from the sensing device to the ground on the scanning line. Examples of sensing devices having such ranging capability include a depth camera, a LiDAR sensor, and a laser interferometer. Also, if the sensing device is a camera without a ranging function, the height or depth of the ground on the scanning line may be estimated from an image acquired by the camera using image processing technology. When determining the transverse profile, the control device 180 may, for example, use the IMU 115 of the work vehicle 100 to measure (or estimate) the inclination angle of the work vehicle 100 or the inclination angle of the sensing device, and obtain the transverse profile by correcting the first sensing data using the inclination angle. The control device 180 may generate a signal (also referred to as a transverse profile signal) including first information indicating the transverse profile, for example, at regular intervals or each time the work vehicle 100 travels a certain distance, and record it in the storage device 170. A distance (also referred to as a repetition interval) corresponding to the interval in the longitudinal direction (corresponding to the direction in which the work vehicle 100 travels) between two successive records of the transverse profile signal, i.e., the interval between the scanning lines, may be set to any value within a range of, for example, 1 cm to 50 cm.

[0101] It should be noted that the transverse profile does not necessarily have to contain information about the exact height or depth of the ground surface relative to the reference surface, but may contain information that roughly indicates the size of the irregularities, e.g. "rough areas with large irregularities", "rough areas with small irregularities", "almost flat areas", etc., depending on the size of the irregularities.

[0102] The transverse profile may also include information on the transverse gradient, i.e., the gradient of the ground in a direction intersecting the direction in which the work vehicle 100 travels. The transverse gradient is, for example, a value obtained by dividing the difference in ground height between the right and left ends of the road by the width of the road. Each scan line may be divided into a plurality of regions, and a value obtained by dividing the difference in ground height between both ends of each region by the width of each region may be determined as the partial transverse gradient. The control device 180 may detect the width (i.e., the transverse length) of the drivable region of the road on which the work vehicle 100 is to travel based on the first sensing data. Using the region of each scan line that corresponds to the drivable region, a value obtained by dividing the difference in ground height between both ends of the region by the width of the drivable region may be determined as the transverse gradient of the drivable region.

[0103] The information (first information) regarding the transverse profile of the ground surface on which the work vehicle 100 travels may include data on a scan line in a direction other than the transverse direction. In this disclosure, as long as the information includes a profile of the ground surface (ground surface) in the transverse direction, the information is referred to as the first information.

[0104] The control device 180 may, for example, acquire a cross-sectional profile of the ground every time the work vehicle 100 travels a predetermined distance (e.g., one meter or more). In this case, the control device 180 may cause the sensing device to acquire the first sensing data every time the work vehicle 100 travels the predetermined distance.

[0105] The control device 180 may further obtain, in addition to the transverse profile of the ground, a longitudinal profile of the ground, i.e., the shape of the ground in the direction along which the work vehicle 100 is traveling, based on the first sensing data.

[0106] The information (second information) on the environment around the work vehicle 100 is information on the environment that may include features other than the ground around the work vehicle 100. The second information is, for example, information on objects present around the work vehicle 100 (including, for example, the position and type of the object). For example, the control device 180 can obtain the second information by recognizing one or more objects present around the work vehicle 100 based on the second sensing data. The control device 180 may further identify the type of the recognized object. The control device 180 may use machine learning to recognize the object and identify the type of the object. For example, the control device 180 may use an identification technique such as semantic segmentation using a convolutional neural network (CNN) to identify the type of the object from the second sensing data such as image data. The identification algorithm is not limited to a specific one, and any algorithm can be used.

[0107] The control device 180 identifies whether or not a road on the ground on which the work vehicle 100 runs is a farm road based on information on the cross-sectional profile of the ground on which the work vehicle 100 runs and information on the environment around the work vehicle 100. The control device 180 identifies whether or not a road on the ground on which the work vehicle 100 runs is a farm road, for example, by determining whether or not the information on the cross-sectional profile of the ground on which the work vehicle 100 runs and the information on the environment around the work vehicle 100 satisfy one or more conditions. The determination conditions are determined in advance, and may be recorded, for example, in the storage device 170 of the work vehicle 100, the storage device 650 of the management device 600, or the storage device 450 of the terminal device 400. The determination conditions may be set by the user. Specific examples of the determination conditions will be described later.

[0108] The farm road identification system in this embodiment can identify whether the road on which the agricultural machine is about to travel is a farm road or not based on sensing data of the ground on which the agricultural machine travels and sensing data of the environment around the agricultural machine, so that it can identify whether the road on which the agricultural machine is about to travel is a farm road or not in various environments. For example, even if information on the road type of the road cannot be obtained from an environmental map or an intelligent road traffic system, it can identify whether the road is a farm road or not using sensing data of the ground on which the agricultural machine travels and the environment around the agricultural machine. Since it is possible to identify whether the road is a farm road or not in various environments, the traveling of the autonomously driven agricultural machine can be performed more smoothly. "Identifying whether the road is a farm road or not" means, in other words, for example, determining whether the road is a road that should be recognized as being different from a general road. A general road is a road maintained for the traffic of general vehicles.

[0109] As already mentioned, a "farm road" refers to a road that is mainly used for agricultural purposes. Farm roads can be broadly divided into intra-field farm roads and main farm roads. Intra-field farm roads are farm roads that are mainly used for agricultural production activities, and include, for example, farm roads used for travel to and from fields, transporting agricultural materials to fields, harvesting agricultural products, pest control work, transporting agricultural products from fields, and the like. Intra-field farm roads include, for example, roads connecting fields to fields, roads connecting fields to settlements, and roads connecting fields to agricultural facilities (for example, collection and shipping centers, fruit sorting centers, rice centers, country elevators, compost centers, and the like). Main farm roads are main farm roads in rural areas, and are mainly used for the distribution of agricultural products and agricultural materials. Main farm roads include, for example, roads used for the purpose of transporting agricultural products to markets and consumer areas. An example of a main farm road is a road that connects an agricultural facility with a general road.

[0110] However, the criteria for identifying a farm road by the farm road identification system according to the embodiment of the present disclosure can be adjusted as appropriate. In other words, it is not necessary to identify all of the above-mentioned "farm roads" as farm roads. For example, it is preferable to be able to distinguish and recognize farm roads that are not well maintained compared to general roads, such as unpaved farm roads or narrow farm roads, from general roads.

[0111] Furthermore, the farm road identification system in this embodiment has the advantage of being able to adjust the criteria for identifying a road as a farm road depending on the type of agricultural machine (including the type of implement if the agricultural machine is equipped with an implement). Alternatively, the farm road identification system may be able to adjust the criteria for identifying a road as a farm road depending on the characteristics of the agricultural machine or implement (e.g., width, height, weight, horsepower, etc.).

[0112] The farm road identification system of this embodiment uses the external characteristics of the farm road, specifically, identifies whether or not it is a farm road based on information about the cross-sectional profile of the ground on which the agricultural machine runs and information about the environment around the agricultural machine, so the criteria for identifying a farm road can be adjusted appropriately according to needs. The farm road identification system may be configured so that the user can change the criteria for identifying a farm road by operating the operation terminal 200 or the terminal device 400.

[0113] The farm road identification system in this embodiment may be configured to perform an operation of identifying a farm road when designing a local route, for example. The control device 180 may perform local route design and identification of whether or not the road is a farm road in parallel, or may identify whether or not the road is a farm road before designing a local route. When the control device 180 determines that the road on which the work vehicle 100 is to travel is a farm road, it may set a local route for the work vehicle 100 based on sensing data of the ground on which the work vehicle 100 travels and sensing data of the environment around the work vehicle 100. For example, when the control device 180 determines that the road on which the work vehicle 100 is to travel is a farm road, it may set a waypoint at an appropriate position on the farm road (for example, near the center in the transverse direction) to set a local route. When the control device 180 determines that the road on which the work vehicle 100 is to travel is a farm road, it may detect a drivable area of ​​the road on which the work vehicle 100 is to travel (for example, the width of the area in the transverse direction) based on sensing data of the ground on which the work vehicle 100 travels and / or a transverse profile of the ground. The drivable area can be set by, for example, avoiding obstacles on the road. In addition to obstacles, the drivable area may be set by excluding areas where it is preferable for the work vehicle 100 to avoid driving, such as large unevenness or steps, mud, etc. The control device 180 may detect ruts (i.e., traces of wheels) formed on the ground based on sensing data of the ground on which the work vehicle 100 drives. The ruts are formed on the ground, for example, as recesses (depressions) extending along the direction in which the road extends. When the control device 180 detects ruts, it may set a local route along the ruts. When two ruts are detected on the ground, the control device 180 may compare the distance between the ruts with the distance between the two front wheels 104F, and set a local route so that the front wheels 104F drive on the ruts if the difference between these distances is negligibly small, and so that the front wheels 104F drive while avoiding the ruts if the difference between the distances is large.

[0114] When the control device 180 determines that the road on which the work vehicle 100 is to travel is a farm road, it may detect at least one characteristic point of a field entrance / exit, a ditch, and an agricultural facility from the sensing data of the environment around the work vehicle 100, and use the characteristic point to set a landmark on the route of the work vehicle 100. The set landmark may be used for self-location estimation.

[0115] The control device 180 may reflect information indicating the result of identifying whether or not a road is a farm road on the map. For example, the control device 180 may add attribute information indicating that a specific road on an existing map is a farm road to the map. The control device 180 may also correct the position and width of the farm road on the existing map based on the identified position and width information of the farm road if the position and width of the farm road on the existing map are inaccurate.

[0116] The control device 180 may further use information (sometimes referred to as third information) on the degree of vibration of the work vehicle 100 to identify whether or not the road is a farm road. For example, the control device 180 may acquire information on the degree of vibration of the work vehicle 100 (for example, frequency (frequency) characteristics of the vibration waveform of the work vehicle 100, vibration acceleration, etc.) based on a signal output from a sensor (for example, an acceleration sensor possessed by the work vehicle 100) that detects the vibration of the work vehicle 100. The control device 180 may acquire a vibration waveform from, for example, an acceleration sensor of the work vehicle 100, and perform filtering to remove components other than those caused by unevenness of the ground (for example, acceleration of the work vehicle 100, etc.). By performing such filtering, the vibration waveform can be used to evaluate the unevenness of the ground. Machine learning may be used for filtering.

[0117] When the control device 180 determines that the road on the ground on which the work vehicle 100 travels is a farm road, the control device 180 may further determine whether or not the work vehicle 100 can travel on the road based on the width and / or length of the work vehicle 100. The work vehicle 100 illustrated here is a tractor to which an implement can be attached. When the work vehicle 100 is attached with an implement, the control device 180 can determine whether or not the work vehicle 100 can travel on the road based on the width and / or length of the attached implement. The width and length of the work vehicle 100 are recorded, for example, in the storage device 170 of the work vehicle 100. The width and length of the implement attached to the work vehicle 100 are also recorded, for example, in the storage device 170 of the work vehicle 100. The implement may be automatically recognized and recorded when it is connected to the work vehicle 100.

[0118] The control device 180 can change the control method of the work vehicle 100 based on the result of identifying whether the road on the ground on which the work vehicle 100 is traveling is a farm road or not. For example, the control device 180 may control the drive device 240 using a different method when the road on which the work vehicle 100 is to travel is identified as a farm road and when it is identified as not a farm road. For example, the control device 180 may reduce the speed of the work vehicle 100 when the road on which the work vehicle 100 is to travel is identified as a farm road compared to when it is identified as not a farm road.

[0119] When the control device 180 determines that the work vehicle 100 cannot travel on that road, it stops the travel of the work vehicle 100. When the control device 180 determines that the work vehicle 100 cannot travel on that road, it may notify a computer remotely monitoring the work vehicle 100 that the work vehicle 100 cannot travel on that road. For example, the control device 180 may send a signal to the terminal device 400 to notify a user remotely monitoring the work vehicle 100. The user can remotely operate the work vehicle 100 via the terminal device 400, for example.

[0120] Fig. 11 is a flowchart showing an example of the operation of route planning and driving control using the farm road identification system in this embodiment. In the example of Fig. 11, identification of whether or not a road is a farm road is performed before local route design.

[0121] In the example shown in FIG. 11, the management device 600 first acquires a map and a work plan from the storage device 650 (step S141). Next, the management device 600 performs global route design for the work vehicle 100 based on the map and the work plan by the above-mentioned method (step S142). The global route design may be performed at any timing before the work vehicle 100 starts traveling. The global route design may be performed immediately before the work vehicle 100 starts traveling, or may be performed on or before the day before the work vehicle 100 starts traveling. In addition, the global route may be generated based on information (e.g., starting point, destination point, waypoint, etc.) input by the user using the terminal device 400. The management device 600 transmits data indicating the generated global route to the work vehicle 100. After that, the management device 600 issues a travel instruction to the work vehicle 100 at a predetermined timing. In response to this, the control device 180 of the work vehicle 100 controls the drive device 240 to start traveling of the work vehicle 100 (step S143). As a result, the work vehicle 100 starts traveling. The timing of the start of traveling can be set to an appropriate timing that allows the work vehicle 100 to reach the farm field by the scheduled start time of the first farm work on each work day indicated by the work plan, for example. While the work vehicle 100 is traveling, the ECU 185 of the control device 180 identifies whether the road on which the work vehicle 100 is traveling is a farm road or not (step S144). When it is determined that the road is a farm road, the ECU 185 of the control device 180 determines whether the road is drivable or not (step S145). When it is determined that the road is drivable, the ECU 185 of the control device 180 performs local route design to avoid collision with an obstacle by a method described later (step S146). When it is determined that the road is not a farm road as a result of identifying whether the road is a farm road or not (step S144), local route design (step S146) may be performed without determining whether the road is drivable or not (step S145). If no obstacle is detected, ECU 185 generates a local path that is approximately parallel to the global path, and if an obstacle is detected, ECU 185 generates a local path that can avoid the obstacle. Next, ECU 184 determines whether or not to end the traveling of work vehicle 100 (step S147).For example, if a local route that can avoid the obstacle cannot be generated, or if the work vehicle 100 has arrived at the destination, the ECU 184 stops the work vehicle 100 (step S148). If it is determined that traveling is not possible, the ECU 184 also stops the work vehicle 100 (step S148). If no obstacle is detected, or if a local route that can avoid the obstacle can be generated, the process returns to step S143, and thereafter, the operations of steps S143 to S148 are repeated until it is determined in step S148 that traveling is to be ended.

[0122] While the work vehicle 100 is traveling, the control device 180 may, at a predetermined timing, identify whether the road on which the work vehicle 100 is about to travel is a farm road. For example, the control device 180 may acquire a vibration waveform from an acceleration sensor of the work vehicle 100, perform filtering to remove components caused by factors other than the unevenness of the ground (e.g., the acceleration of the work vehicle 100, etc.), and evaluate the degree of vibration (such as the frequency characteristics of the vibration) from the obtained vibration waveform. The control device 180 may determine whether an index value indicating the degree of vibration is greater than a predetermined value, and may use the degree of vibration being greater than the predetermined value as a trigger to identify whether the road on which the work vehicle 100 is about to travel is a farm road.

[0123] The application example of the farm road identification system is not limited to the example in Fig. 11. For example, the work plan does not have to be used in setting a global route. The farm road identification system can also be used to create a map including information on whether or not a road is a farm road.

[0124] FIG. 12 is a flowchart showing an example of a method for identifying whether or not a road is a farm road. In this example, when information (first information) on the cross-sectional profile of the ground on which the work vehicle 100 travels satisfies at least one first condition, and information (second information) on the environment around the work vehicle 100 satisfies at least one second condition, the control device 180 determines that the road on which the work vehicle 100 is about to travel is a farm road. The control device 180 acquires the first information and the second information (step S151). The control device 180 determines whether or not the first information satisfies the first condition (step S152). When it is determined that the first information satisfies the first condition, the control device 180 determines whether or not the second information satisfies the second condition (step S153). When it is determined that the second information satisfies the second condition, it determines that the road is a farm road (step S154). When it is determined that the first information does not satisfy the first condition and when it is determined that the second information does not satisfy the second condition, the control device 180 determines that the road is not a farm road (step S155).

[0125] 12, for example, the control device 180 may acquire the second information only when it is determined that the first information satisfies the first condition. The order of determining whether the first information satisfies the first condition (step S152) and determining whether the second information satisfies the second condition (step S153) may be reversed.

[0126] (Specific examples of conditions for determining whether a road is a farm road or not) Specific examples of the determination conditions for whether or not a road is a farm road will be described with reference to Figures 13A and 13B. Figures 13A and 13B are diagrams showing monochrome images corresponding to example images captured by the camera 120 of the work vehicle 100. These diagrams show examples of images including the ground on which the work vehicle 100 travels and the environment around the work vehicle 100. The control device 180 can identify a farm road according to, for example, the determination conditions shown below. The determination conditions shown below can also be used in combination.

[0127] The first condition includes, for example, a condition that reflects that ruts extending along the direction in which the road extends are formed on the ground on which the work vehicle 100 travels. For example, in the example of Fig. 13A and Fig. 13B, two ruts 24 extending along the direction in which the road extends are formed. The two ruts 24 extend approximately parallel to each other. A convex portion extending along the direction in which the road extends may be formed between the two ruts 24. Ruts may be formed on an unpaved farm road as in the example of Fig. 13A and Fig. 13B. Furthermore, grass may grow on or along the convex portion between the two ruts. Such ruts can be detected as one of the characteristics of a farm road and used as a condition for identifying whether or not the road is a farm road.

[0128] Specifically, the first condition includes, for example, a condition that a portion indicating a recess is included at a corresponding position of the consecutive transverse profiles. The first condition may include, for example, a condition that a portion indicating two recesses is included at a corresponding position of the consecutive transverse profiles. After such a recess is detected from the consecutive transverse profiles, the control device 180 may further determine whether the detected recess is classified as a wheel rut. For example, image data of the ground can be used to determine whether the recess is classified as a wheel rut.

[0129] The first condition may further include a condition that a convex portion is formed between two concave portions. The first condition may further include a condition that grass grows on or along the convex portion. Grass may be detected, for example, by detecting green pixels using RGB values ​​of color image data of the ground captured by the camera 120. The RGB color space may be converted to an HSV color space, and green pixels may be detected using the HSV color space. The HSV color space is a color space composed of three components: hue, saturation, and value. When detecting green pixels, the hue range may be set to, for example, a range of 30 to 90.

[0130] Another example of the first condition may include a condition that the gradient (inclination) of the ground in a direction intersecting the direction in which the road extends is greater than a predetermined value. For example, as in the example of FIG. 13B, when there is a forest 26 on one side of the road, the gradient of the road in a direction intersecting the direction in which the road extends may be large. The first condition may include, for example, a condition that the gradient of the cross-sectional profile of the ground is greater than a predetermined value.

[0131] The first condition may include a condition related to the roughness of the road. For example, IRI (International Roughness Index) is used as an evaluation index for the unevenness in the longitudinal direction of a paved road surface. Unpaved farm roads are considered to have larger unevenness in the longitudinal direction than general roads. The control device 180 may acquire a longitudinal profile of the road and obtain the IRI from the longitudinal profile to evaluate the degree of unevenness (roughness) of the road. The first condition may include a condition that the degree of unevenness of the road is greater than a predetermined value.

[0132] The second condition includes, for example, a condition that at least one of the groups consisting of a farm field, a ridge, a forest, and vegetation exists adjacent to the road on both sides or one side of the road. The existence of any of a farm field, a ridge, a forest, and vegetation adjacent to the road is detected as one of the characteristics of a farm road and used as one of the conditions for identifying whether it is a farm road or not. For example, in the example of FIG. 13A, a farm field 22 exists adjacent to the road on both sides, and in the example of FIG. 13B, a farm field 22 exists adjacent to the road on one side of the road. The control device 180 detects the road from sensing data acquired by sensing the environment around the work vehicle 100, for example, and recognizes objects existing adjacent to the road on both sides or one side of the road, and identifies the type of the recognized object.

[0133] 13C, 13D, and 13E are plan views that diagrammatically show an example of a state in which the work vehicle 100 automatically travels on a road 20 outside a farm field while using the farm road identification system in this embodiment.

[0134] As shown in FIG. 13C, in the section A1 of the road 20, two ruts 24 are formed extending along the direction in which the road 20 extends (in this example, the vertical direction in the figure), and there are farm fields 22 adjacent to the road 20 on both sides of the road 20. For example, the control device 180 distinguishes whether the road 20 is a farm road according to the method shown in the flowchart of FIG. 12. In the section A1 of the road 20, the first information satisfies the first condition, and the second information satisfies the second condition, so the control device 180 judges that the road 20 is a farm road. On the other hand, as shown in FIG. 13D, in the section A2 of the road 20, the ground on which the work vehicle 100 travels does not have any unevenness corresponding to the ruts, and there are farm fields 22 adjacent to the road 20 on both sides of the road 20. Therefore, in the section A2 of the road 20, the second information satisfies the second condition, but the first information does not satisfy the first condition, so the control device 180 judges that the road 20 is not a farm road.

[0135] The method of identifying whether or not a road is a farm road is not limited to the above-mentioned example. Another example of the method of identifying whether or not a road is a farm road will be described with reference to Fig. 13E and Fig. 13F. Fig. 13F is a flowchart showing another example of the method of identifying whether or not a road is a farm road. The differences from the flowchart in Fig. 12 will be mainly described.

[0136] For example, as shown in FIG. 13E, two ruts 24 extending along the direction of the road 20 are formed in the sections A10, A11, and A12 of the road 20 that are continuous with each other. In the sections A10 and A12 of the road 20, a farm field 22 exists adjacent to the road 20 on at least one side of the road 20, so the control device 180 determines that the road 20 is a farm road because the first information satisfies the first condition and the second information satisfies the second condition. On the other hand, in the section A11 following the section A10, there is no farm field, ridge, forest, or vegetation adjacent to the road 20 on either side of the road 20. Instead, a structure (building) 29 exists here. Therefore, in the section A11, the first information satisfies the first condition, but the second information does not satisfy the second condition. At this time, the control device 180 refers to the distance traveled by the work vehicle 100 since it last determined that the road 20 was a farm road in section A10, which precedes section A11 (step S153a), determines whether the referred distance is equal to or less than a predetermined distance (e.g., 100 m or less) (step S153b), and determines that the road 20 is a farm road if it is equal to or less than the predetermined distance. That is, when the state changes from one in which the first information satisfies the first condition and the second information satisfies the second condition to one in which the first information satisfies the first condition and the second information does not satisfy the second condition, the control device 180 determines that the road is a farm road if the distance traveled by the work vehicle 100 in a state in which the second information does not satisfy the second condition is equal to or less than a predetermined distance.

[0137] [2-3. Obstacle avoidance] Management device 600 generates a global route, and information about the generated global route is transmitted to work vehicle 100 and stored in storage device 170. ECU 184, which performs automatic driving control, controls ECUs 181 and 182 so that work vehicle 100 travels along the global route. As a result, work vehicle 100 starts traveling along the global route.

[0138] When the work vehicle 100 is traveling outside the field, an obstacle such as a pedestrian or another vehicle may be present on or near the global route. In order to prevent the work vehicle 100 from colliding with the obstacle, the ECU 185 in the control device 180 sequentially generates a local route that can avoid the obstacle while the work vehicle 100 is traveling. The ECU 185 generates the local route based on sensing data acquired by sensing devices (obstacle sensor 130, LiDAR sensor 140, camera 120, etc.) equipped on the work vehicle 100 while the work vehicle 100 is traveling. The local route is defined by a plurality of waypoints along a part of the global route. The ECU 185 determines whether an obstacle is present on or near the path of the work vehicle 100 based on the sensing data. If such an obstacle is present, the ECU 185 sets a plurality of waypoints to avoid the obstacle and generates a local route. If no obstacles exist, ECU 185 generates a local path that is approximately parallel to the global path. Information indicating the generated local path is sent to ECU 184 for automatic driving control. ECU 184 controls ECU 181 and ECU 182 so that work vehicle 100 travels along the local path. This allows work vehicle 100 to travel while avoiding obstacles. If there are traffic lights on the road on which work vehicle 100 travels, work vehicle 100 may recognize the traffic lights based on images captured by camera 120, for example, stop at a red light, and start at a green light.

[0139] FIG. 14 is a diagram showing an example of a global route and a local route generated in an environment where an obstacle exists. In FIG. 14, the global route 30 is illustrated by a dotted arrow, and the local route 32 generated sequentially during traveling is illustrated by a solid arrow. The global route 30 is defined by a plurality of waypoints 30p. The local route 32 is defined by a plurality of waypoints 32p set at intervals shorter than the waypoints 30p. Each waypoint has, for example, position and direction information. The management device 600 generates the global route 30 by setting the plurality of waypoints 30p at a plurality of locations including an intersection of the road 76. The intervals between the waypoints 30p may be relatively long, for example, several meters to several tens of meters. The ECU 185 generates the local route 32 by setting the plurality of waypoints 32p based on the sensing data output from the sensing device while the work vehicle 100 is traveling. The interval between the waypoints 32p in the local route 32 is shorter than the interval between the waypoints 30p in the global route 30. The interval between the waypoints 32p may be, for example, several tens of centimeters (cm) to several meters (m). The local route 32 is generated within a relatively small range (for example, a range of about several meters) starting from the position of the work vehicle 100. FIG. 14 illustrates a series of local routes 32 generated while the work vehicle 100 travels along a road 76 between fields 70 and turns left at an intersection. The ECU 185 repeats the operation of generating a local route from the position of the work vehicle 100 estimated by the ECU 184 to a point, for example, several meters ahead, while the work vehicle 100 is moving. The work vehicle 100 travels along the local routes that are generated successively.

[0140] In the example shown in FIG. 14, an obstacle 40 (e.g., a person) is present in front of the work vehicle 100. In FIG. 14, an example of a range sensed by a sensing device such as the camera 120, the obstacle sensor 130, or the LiDAR sensor 140 mounted on the work vehicle 100 is illustrated as a sector. In such a situation, the ECU 185 generates a local route 32 so as to avoid the obstacle 40 detected based on the sensing data. The ECU 185 determines whether there is a possibility that the work vehicle 100 will collide with the obstacle 40 based on, for example, the sensing data and the width of the work vehicle 100 (including the width of the implement if an implement is attached). If there is a possibility that the work vehicle 100 will collide with the obstacle 40, the ECU 185 sets a plurality of waypoints 32p so as to avoid the obstacle 40, and generates the local route 32. The ECU 185 may recognize not only the presence or absence of an obstacle 40 but also the state of the road surface (e.g., mud, depressions, etc.) based on the sensing data, and when a portion where traveling is difficult is detected, the local route 32 may be generated to avoid such a portion. The work vehicle 100 travels along the local route 32. When the obstacle 40 cannot be avoided no matter how the local route 32 is set, the control device 180 may stop the work vehicle 100. At this time, the control device 180 may send a warning signal to the terminal device 400 to alert the supervisor. After stopping, when it is recognized that the obstacle 40 has moved and there is no longer a risk of collision, the control device 180 may resume traveling of the work vehicle 100.

[0141] In the example of the flowchart in FIG. 11, once the global route is generated, it is not changed until the destination is reached. Not limited to this example, the global route may be corrected while the work vehicle 100 is traveling. For example, the ECU 185 may recognize at least one of the state of the road on which the work vehicle 100 is traveling, the state of the vegetation around the work vehicle 100, and the weather state based on sensing data acquired by a sensing device such as the camera 120 or the LiDAR sensor 140 while the work vehicle 100 is traveling, and may change the global route if the recognized state satisfies a predetermined condition. When the work vehicle 100 is traveling along the global route, some roads may be difficult to pass. For example, the road may be muddy due to heavy rain, the road surface may be subsided, or the road may be impassable due to an accident or other cause. Alternatively, the vegetation around the farm road may be longer than expected, or new buildings may be constructed, making it difficult to receive satellite signals from GNSS satellites. Taking such a situation into consideration, ECU 185 may detect roads that are difficult to travel on the basis of sensing data acquired while work vehicle 100 is traveling, and change the route to avoid such roads. Furthermore, when ECU 185 changes the route, it may store the changed route in storage device 170 and transmit information on the changed route to management device 600. In that case, management device 600 may adopt the changed route the next time a route to the same field is generated. This enables flexible route planning in response to changes in the traveling environment.

[0142] The farm road identification system in the above embodiment can also be attached to an agricultural machine that does not have that function. Such a system can be manufactured and sold independently of the agricultural machine. A computer program used in such a system can also be manufactured and sold independently of the agricultural machine. The computer program can be provided, for example, by being stored in a computer-readable non-transitory storage medium. The computer program can also be provided by downloading via a telecommunication line (for example, the Internet).

[0143] As described above, the present disclosure includes the farm road identification system, control system, and agricultural machine described in the following items.

[0144] [Item 1] A farm road identification system for an autonomous agricultural machine, comprising: Sensing a ground surface on which the agricultural machine travels to obtain first sensing data; at least one sensing device that senses an environment around the agricultural machine to obtain second sensing data; and obtaining first information regarding a transverse profile of the ground based on the first sensing data. Get acquiring second information about the surrounding environment based on the second sensing data; a processing device that identifies whether a road on the ground is a farm road or not based on the first information and the second information; A farm road identification system comprising:

[0145] According to the above-described farm road identification system, it is possible to identify whether the road on which an agricultural machine is about to travel is a farm road or not in a variety of environments.

[0146] [Item 2] The farm road identification system described in item 1, wherein the processing device recognizes one or more objects present in the vicinity of the agricultural machine based on the second sensing data and acquires the second information including the recognition results.

[0147] According to the above configuration, it is possible to identify whether the road on which the agricultural machine is about to travel is a farm road or not, based on information about objects present around the agricultural machine.

[0148] [Item 3] The farm road identification system described in item 1 or 2, wherein the processing device determines that the road is a farm road when the first information satisfies a first condition and the second information satisfies a second condition.

[0149] [Item 4] the at least one sensing device includes a LiDAR sensor and / or a camera; The first sensing data includes point cloud data of the ground acquired by the LiDAR sensor and / or image data of the ground acquired by the camera, The farm road identification system according to any one of items 1 to 3, wherein the second sensing data includes point cloud data of the surrounding environment acquired by the LiDAR sensor and / or image data of the surrounding environment acquired by the camera.

[0150] [Item 5] A farm road identification system described in any one of items 1 to 4, wherein when the processing device determines that the road is a farm road, it determines whether the agricultural machine can travel on the road based on the width and / or length of the agricultural machine.

[0151] According to the above configuration, the autonomously driven agricultural machine can travel more smoothly. Furthermore, the farm road identification system having the above configuration can be applied to a variety of agricultural machines.

[0152] [Item 6] The agricultural machine is a tractor to which an implement can be attached, A farm road identification system as described in any one of items 1 to 5, wherein when the processing device determines that the road is a farm road and the tractor is equipped with an implement, the processing device determines whether the agricultural machine can travel on the road based on the width and / or length of the implement.

[0153] According to the above configuration, the traveling of the autonomous agricultural machine can be performed more smoothly. In addition, the farm road identification system having the above configuration can be applied to various agricultural machines (including implements attached to the agricultural machines).

[0154] [Item 7] A farm road identification system as described in item 5 or 6, wherein when the processing device determines that the agricultural machine cannot travel on the road, it notifies a monitoring computer of the agricultural machine that the agricultural machine cannot travel on the road.

[0155] According to the above configuration, the traveling and control of the agricultural machine can be performed in cooperation with the monitoring computer of the agricultural machine.

[0156] [Item 8] The farm road identification system described in Item 3, wherein the processing device determines that the second condition is satisfied when, based on the second sensing data, at least one selected from the group consisting of a farm field, a footpath, a forest, and vegetation is recognized adjacent to the road on both sides or one side of the road.

[0157] [Item 9] the at least one sensing device includes a LiDAR sensor and / or a camera; The second sensing data includes point cloud data of the surrounding environment acquired by the LiDAR sensor and / or image data of the surrounding environment acquired by the camera; The processing device detects the road from the second sensing data and detects at least one selected from the group consisting of farm fields, paddy fields, forests, and vegetation adjacent to the road and located on either side or both sides of the road.

[0158] [Item 10] The farm road identification system described in item 3, wherein the processing device determines that the first condition is satisfied when a rut formed on the ground and extending along the direction in which the road extends is detected based on the first information.

[0159] [Item 11] The farm road identification system described in item 3, wherein the processing device determines that the first condition is satisfied when it detects, based on the first information, that the cross-sectional profile of the ground has a convex portion in the center and that the convex portion extends along the direction in which the road extends.

[0160] [Item 12] Item 12. The farm road identification system according to item 11, wherein the processing device determines that the first condition is satisfied when grass is detected growing on or along the convex portion based on the first information.

[0161] [Item 13] the at least one sensing device includes a camera; the first sensing data includes color image data of the ground captured by the camera; Item 13. The farm road identification system according to item 12, wherein the processing device detects grass growing on or along the convex portion based on the RGB values ​​of the color image data of the ground.

[0162] [Item 14] 4. The farm road identification system according to item 3, wherein the processing device determines that the first condition is satisfied when a slope of the ground that is greater than a predetermined value is detected based on the first information.

[0163] [Item 15] The agricultural machine further includes a sensor for detecting vibrations of the agricultural machine. A farm road identification system described in any one of items 1 to 14, wherein the processing device acquires third information regarding the degree of vibration of the agricultural machine based on the signal output from the sensor, and further identifies whether the road is a farm road or not based on the third information.

[0164] [Item 16] The processing device determines whether an index value representing the degree of vibration of the agricultural machine is greater than a predetermined value, and when the index value is greater than the predetermined value, identifies whether the road is a farm road or not.

[0165] [Item 17] 17. The farm road identification system according to any one of claims 1 to 16, wherein the processing device evaluates the roughness of the ground based on the first sensing data, and further identifies whether the road is a farm road or not based on the roughness of the ground.

[0166] [Item 18] A farm road identification system described in any one of items 1 to 17, wherein when the processing device determines that the road is a farm road, it sets a route for the agricultural machine along the road based on the first sensing data and the second sensing data.

[0167] According to the above configuration, the efficiency of route design (route planning) for an autonomously driven agricultural machine can be improved.

[0168] [Item 19] Item 19. The farm road identification system according to item 18, wherein the processing device detects at least one feature point selected from the group consisting of a field entrance / exit, a ditch, and an agricultural facility from the second sensing data, and sets a landmark on a path of the agricultural machine using the at least one feature point.

[0169] According to the above configuration, the efficiency of route design (route planning) for an autonomously driven agricultural machine can be improved.

[0170] [Item 20] A farm road identification system according to any one of items 1 to 19, A control device for controlling the traveling of the agricultural machine; A control system comprising:

[0171] [Item 21] Item 21. The control system according to item 20, wherein the control device uses different control methods for the agricultural machine when the processing device determines that the road is a farm road and when the processing device determines that the road is not a farm road.

[0172] According to the above configuration, the autonomously driven agricultural machine can travel more smoothly on both general roads and farm roads.

[0173] [Item 22] 22. An agricultural machine comprising the control system according to item 20 or 21. [Industrial Applicability]

[0174] The technology of the present disclosure can be applied to a farm road identification system for agricultural machinery, such as a tractor, a harvester, a rice transplanter, a riding tiller, a vegetable transplanter, a grass cutter, a seeding machine, a fertilizer applicator, or an agricultural robot, etc. The farm road identification system according to the embodiment of the present disclosure is used, for example, while the agricultural machinery is autonomously traveling outside a field. [Explanation of symbols]

[0175] 20...road, 22...field, 24...rut, 26...forest, 30...global route, 32...local route, 40...obstacle, 50...GNSS satellite, 60...reference station, 70...field, 72...work area, 74...headland, 76...road, 80...network, 100...work vehicle, 101...vehicle body, 102...prime mover (engine), 103...transmission (transmission gear) transmission), 104 ··· wheels, 105 ··· cabin, 106 ··· steering gear, 107 ··· driver's seat, 108 ··· coupling device, 110 ··· positioning device (GNSS unit), 111 ··· GNSS receiver, 112 ··· RTK receiver, 115 ··· inertial measurement unit (IMU), 116 ··· processing circuit, 120 ··· camera, 130 ··· obstacle sensor, 140 ··· LiDAR sensor, 15 0....sensor group, 152...steering wheel sensor, 154...turning angle sensor, 156...axle sensor, 160...control system, 170...storage device, 180...control device, 181-186...ECU, 190...communication device, 200...operation terminal, 210...operation switch group, 220...buzzer, 240...drive device, 300...implement, 340... Drive device, 380, control device, 390, communication device, 400, terminal device, 420, input device, 430, display device, 450, storage device, 460, processor, 470, ROM, 480, RAM, 490, communication device, 600, management device, 650, storage device, 660, processor, 670, ROM, 680, RAM, 690, communication device

Claims

1. A farm road identification system for an autonomous agricultural machine, comprising: Sensing a ground surface on which the agricultural machine travels to obtain first sensing data; at least one sensing device that senses an environment around the agricultural machine to obtain second sensing data; obtaining first information regarding a transverse profile of the ground surface based on the first sensing data; acquiring second information about the surrounding environment based on the second sensing data; a processing device that identifies whether a road on the ground is a farm road or not based on the first information and the second information; A farm road identification system comprising:

2. The farm road identification system according to claim 1 , wherein the processing device recognizes one or more objects present in the vicinity of the agricultural machine based on the second sensing data, and acquires the second information including a result of the recognition.

3. The farm road identification system according to claim 1 , wherein the processing device determines that the road is a farm road when the first information satisfies a first condition and the second information satisfies a second condition.

4. the at least one sensing device includes a LiDAR sensor and / or a camera; The first sensing data includes point cloud data of the ground acquired by the LiDAR sensor and / or image data of the ground acquired by the camera, The farm road identification system according to any one of claims 1 to 3, wherein the second sensing data includes point cloud data of the surrounding environment acquired by the LiDAR sensor and / or image data of the surrounding environment acquired by the camera.

5. A farm road identification system according to any one of claims 1 to 3, wherein when the processing device determines that the road is a farm road, it determines whether the agricultural machine can travel on the road based on the width and / or length of the agricultural machine.

6. The agricultural machine is a tractor to which an implement can be attached, A farm road identification system as described in any one of claims 1 to 3, wherein when the processing device determines that the road is a farm road and the tractor is equipped with an implement, the processing device determines whether the agricultural machine can travel on the road based on the width and / or length of the implement.

7. 6. The farm road identification system according to claim 5, wherein when the processing device determines that the agricultural machine cannot travel on the road, the processing device notifies a monitoring computer of the agricultural machine that the agricultural machine cannot travel on the road.

8. The farm road identification system of claim 3, wherein the processing device determines that the second condition is satisfied when, based on the second sensing data, at least one selected from the group consisting of a farm field, a footpath, a forest, and vegetation is recognized adjacent to the road on both sides or one side of the road.

9. the at least one sensing device includes a LiDAR sensor and / or a camera; The second sensing data includes point cloud data of the surrounding environment acquired by the LiDAR sensor and / or image data of the surrounding environment acquired by the camera; The farm road identification system according to claim 8, wherein the processing device detects the road from the second sensing data and detects at least one selected from the group consisting of farm fields, paddy fields, forests, and vegetation adjacent to the road and located on either side or both sides of the road.

10. The farm road identification system according to claim 3 , wherein the processing device determines that the first condition is satisfied when a rut formed on the ground and extending along the direction in which the road extends is detected based on the first information.

11. The farm road identification system of claim 3, wherein the processing device determines that the first condition is satisfied when it detects, based on the first information, that the cross-sectional profile of the ground has a convex portion in the center and that the convex portion extends along the direction in which the road extends.

12. The farm road identification system according to claim 11 , wherein the processing device determines that the first condition is satisfied when it detects, based on the first information, that grass is growing on or along the convex portion.

13. the at least one sensing device includes a camera; the first sensing data includes color image data of the ground captured by the camera; The farm road identification system according to claim 12 , wherein the processing device detects grass growing on or along the convex portion based on RGB values ​​of the color image data of the ground.

14. The farm road identification system according to claim 3 , wherein the processing device determines that the first condition is satisfied when a slope of the ground that is greater than a predetermined value is detected based on the first information.

15. The agricultural machine further includes a sensor for detecting vibrations of the agricultural machine. A farm road identification system described in any one of claims 1 to 3 and 8 to 14, wherein the processing device obtains third information regarding the degree of vibration of the agricultural machine based on the signal output from the sensor, and further identifies whether the road is a farm road or not based on the third information.

16. The farm road identification system according to claim 15, wherein the processing device determines whether an index value representing the degree of vibration of the agricultural machine is greater than a predetermined value, and when the index value is greater than the predetermined value, identifies whether the road is a farm road or not.

17. The farm road identification system according to any one of claims 1 to 3 and 8 to 14, wherein the processing device evaluates the roughness of the ground based on the first sensing data, and identifies whether the road is a farm road or not further based on the roughness of the ground.

18. A farm road identification system described in any one of claims 1 to 3 and 8 to 14, wherein when the processing device determines that the road is a farm road, it sets a route for the agricultural machine along the road based on the first sensing data and the second sensing data.

19. The farm road identification system according to claim 18, wherein the processing device detects at least one feature point selected from the group consisting of an entrance / exit of a field, a ditch, and an agricultural facility from the second sensing data, and sets a landmark on a path of the agricultural machine using the at least one feature point.

20. A farm road identification system according to any one of claims 1 to 3 and 8 to 14; A control device for controlling the traveling of the agricultural machine; A control system comprising:

21. The control system according to claim 20 , wherein the control device uses a different control method for the agricultural machine when the processing device determines that the road is a farm road and when the processing device determines that the road is not a farm road.

22. An agricultural machine comprising a control system according to claim 20.

Images