Route generation system, agricultural machine, and route generation method

Abstract

To provide a route generation system capable of efficiently generating a route of an automatically driven agricultural machine, an agricultural machine equipped with such a route generation system, and a route generation method.SOLUTION: A route generation system includes: a storage device for storing map data for an agricultural machine to execute automatic driving, which includes position information on points that the agricultural machine has travelled, and data on a slip ratio of the agricultural machine related to the position information; and a processing device for generating a route for the agricultural machine to execute automatic driving on the basis of the data on the slip ratio included in the map data.SELECTED DRAWING: Figure 16B

Description

[Technical field]

[0001] The present disclosure relates to a route generation system for an autonomously driven agricultural machine, an agricultural machine equipped with such a route generation system, and a route generation method. [Background technology]

[0002] Research and development is being conducted on the automation of agricultural machinery. For example, work vehicles such as tractors, combines, and rice transplanters that automatically travel in fields using positioning systems such as GNSS (Global Navigation Satellite System) have been put to practical use. Research and development is also being conducted on work vehicles that automatically travel not only in fields but also outside of fields. Patent Document 1 discloses a system that automatically travels an unmanned work vehicle between two fields separated from each other by a road. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-029218 Summary of the Invention [Problem to be solved by the invention]

[0004] There is a need to efficiently generate routes for autonomous agricultural machinery.

[0005] The present disclosure provides a route generation system for an autonomously driving agricultural machine, an agricultural machine equipped with such a route generation system, and a route generation method. [Means for solving the problem]

[0006] A route generation system according to one aspect of the present disclosure includes a storage device that stores map data for an agricultural machine to perform automatic driving, the map data including position information of points where the agricultural machine has traveled and slip rate data of the agricultural machine associated with the position information, and a processing device that generates a route for the agricultural machine to perform automatic driving based on the slip rate data included in the map data.

[0007] A route generation method according to one aspect of the present disclosure includes storing map data for an agricultural machine to perform autonomous driving, the map data including location information of points where the agricultural machine has traveled and slip rate data of the agricultural machine associated with the location information, and generating a route for the agricultural machine to perform autonomous driving based on the slip rate data included in the map data.

[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, there is provided a route generation system capable of efficiently generating a route for an autonomously driving agricultural machine, an agricultural machine equipped with such a route generation system, and a route generation method. [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 diagram of an 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] FIG. 13 is a diagram illustrating an example of a setting screen displayed on the terminal device. [Figure 12] FIG. 10 is a diagram showing an example of a farm work schedule created by the management device. [Figure 13A] FIG. 4 is a diagram showing an example of the reception strength of a satellite signal. [Figure 13B] FIG. 11 is a diagram showing another example of the reception strength of satellite signals. [Figure 14] FIG. 2 is a diagram showing an example of a map of an area in which a work vehicle travels. [Figure 15A]FIG. 4 is a diagram showing an example of a GUI displayed on a display device. [Figure 15B] FIG. 13 is a diagram showing an example of a route that is generated when a "slip ratio priority" mode is selected. [Figure 15C] FIG. 13 is a diagram showing an example of a route that is generated when a "distance priority" mode is selected. [Figure 16A] 10 is a flowchart illustrating an example of a procedure for the processing device to generate a route. [Figure 16B] 10 is a flowchart illustrating an example of a procedure executed by the processing device. [Figure 17] FIG. 1 is a diagram showing an example of global and local paths generated in an environment where obstacles are present; [Figure 18] 1 is a flowchart illustrating a method for path planning and cruise control. 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 whole as one "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 while performing agricultural work by a vehicle-type agricultural machine may be 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 required for the movement of the agricultural machine, adjustment of the moving speed, and starting and stopping of the movement. 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] "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.

[0016] "Feature" means something that exists on the ground. Examples of features include waterways, grass, trees, roads, fields, ditches, rivers, bridges, forests, mountains, rocks, buildings, railroad tracks, etc. Things that do not exist in the real world, such as borders, place names, building names, field names, and line names, are not included in the "feature" in this disclosure.

[0017] "GNSS satellite" means an artificial satellite in a global navigation satellite system (GNSS). GNSS is a general term for satellite positioning systems such as GPS (Global Positioning System), QZSS (Quasi-Zenith Satellite System), GLONASS, Galileo, and BeiDou. GNSS satellite is a satellite in these positioning systems. A signal transmitted from a GNSS satellite is called a "satellite signal". A "GNSS receiver" is a device that receives radio waves transmitted from multiple satellites in the GNSS and performs positioning based on the signal superimposed on the radio waves. "GNSS data" is data output from a GNSS receiver. The GNSS data may be generated in a predetermined format such as the NMEA-0183 format. The GNSS data may include, for example, information indicating the reception status of satellite signals received from individual satellites. For example, the GNSS data may include an identification number, an elevation angle, an azimuth angle, and a value indicating the reception strength of each satellite from which a satellite signal is received. The reception strength is a numerical value indicating the strength of a received satellite signal. The reception strength may be expressed by a value such as a carrier to noise density ratio (C / N0). The GNSS data may include position information of the GNSS receiver or the agricultural machine calculated based on the received multiple satellite signals. The position information may be represented by, for example, latitude, longitude, and height above mean sea level. The GNSS data may further include information indicating the reliability of the position information.

[0018] "Satellite signals can be normally received" means that satellite signals can be stably received without a significant decrease in the reliability of positioning. When satellite signals cannot be normally received, this is sometimes expressed as "satellite signal reception interference". "Satellite signal reception interference" is a state in which the reliability of positioning is reduced compared to normal due to deterioration of the satellite signal reception conditions. Reception interference can occur, for example, when the number of detected satellites is small (e.g., 3 or less), when the reception strength of each satellite signal is low, or when multipath occurs. Whether or not reception interference occurs can be determined based on, for example, information about the satellites included in the GNSS data. For example, the presence or absence of reception interference can be determined based on the reception strength value for each satellite included in the GNSS data, or the DOP (Dilution of Precision) value indicating the satellite arrangement status.

[0019] 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".

[0020] 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 on 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 on the local path is shorter than the length of the link between the waypoints on 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 that 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.

[0021] A "storage location" is a location provided for storing an agricultural machine. The storage location may be, for example, a location managed by a user of the agricultural machine, or a location jointly operated by multiple users. The storage location may be, for example, a location reserved for storing the agricultural machine, such as a warehouse, barn, or parking lot at the home or business of a user (such as a farmer). The location of the storage location may be registered in advance and recorded in a storage device.

[0022] A "waiting place" is a place provided for the agricultural machine to wait while not performing agricultural work. One or more waiting places may be provided in the environment in which the agricultural machine performs automatic driving. The above-mentioned storage place is an example of a waiting place. The waiting place may be a place jointly managed or used by multiple users. The waiting place may be, for example, a warehouse, a garage, a barn, a parking lot, or other facility. The waiting place may be a warehouse, a barn, a garage, or a parking lot at the home or business of a farmer different from the user of the agricultural machine. A plurality of waiting places may be scattered in the environment in which the agricultural machine moves. Work such as replacement or maintenance of parts or implements of the agricultural machine, or replenishing materials may be performed in the waiting place. In that case, parts, tools, or materials required for those works may be placed in the waiting place.

[0023] (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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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).

[0030] The work vehicle 100 is equipped with devices used for positioning or self-location 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 generated by the management device 600. 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 that can avoid obstacles along the target route based on data output from a sensing device such as a camera or a LiDAR sensor. Within a farm field, the work vehicle 100 may travel 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.

[0031] 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 farm fields on the cloud and supports agriculture by utilizing data on the cloud. The management device 600 can, for example, create a work plan for the work vehicle 100 and generate a target route for the work vehicle 100 according to the work plan. Alternatively, the management device 600 may generate a target route for the work vehicle 100 in response to an operation by a user using the terminal device 400. Hereinafter, unless otherwise specified, the target route (i.e., global route) for the work vehicle 100 generated by the management device 600 will be simply referred to as a "route."

[0032] The management device 600 includes a storage device and a processing device. The storage device stores map data for the work vehicle 100 to perform automatic driving. The map data includes position information of points where the work vehicle 100 has traveled, and slip ratio data of the work vehicle 100 associated with the position information. The processing device generates a route along which the work vehicle 100 will perform automatic driving, based on the slip ratio data included in the map data. Through such processing, a route along which the work vehicle 100 will perform automatic driving can be efficiently created, as will be described in detail later.

[0033] The management device 600 generates a target route in the field using different methods for the inside and outside of the field. The management device 600 generates a target route in the field based on information about the field. For example, the management device 600 can generate a target route 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 to be cultivated, the growing area of ​​the crop, the growing condition of the crop, or the spacing of the crop rows 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 in the work plan, the location of the field where each farm work is performed, the location of the entrance and exit of the field, the scheduled start and end times of each farm work, attribute information of each road recorded on the map, road surface conditions, weather conditions, traffic conditions, etc. The management device 600 may generate a target route based on information indicating a route or waypoints specified by a user operating the terminal device 400, regardless of the work plan.

[0034] 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 the data.

[0035] 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.

[0036] 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 that information. The terminal device 400 can also be used to register one or more fields where the work vehicle 100 performs agricultural work, a storage location for the work vehicle 100, and one or more waiting locations where the work vehicle 100 temporarily waits. The terminal device 400 may further include a function to display on the display a setting screen for the user to input information required to set a target route.

[0037] The configuration and operation of the system in this embodiment will be described in more detail below.

[0038] [1. Configuration] 2 is a side view that shows a schematic example of a work vehicle 100 and a work 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.

[0039] 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 a plurality of wheels (crawlers) equipped with tracks instead of tires.

[0040] The work vehicle 100 is equipped with at least one sensing device that senses the environment around the work vehicle 100. In the example shown in Fig. 2, the work vehicle 100 is equipped with multiple sensing devices. The sensing devices include multiple cameras 120, a LiDAR sensor 140, and multiple obstacle sensors 130.

[0041] 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).

[0042] 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. For example, the LiDAR sensor 140 may be disposed at the upper part of the cabin 105. The LiDAR sensor 140 may be a 3D-LiDAR sensor, but may also be a 2D-LiDAR sensor. The LiDAR sensor 140 senses the environment around the work vehicle 100 and outputs sensing data. While the work vehicle 100 is traveling, 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. The sensor data output from the LiDAR sensor 140 is processed by a control device of the work vehicle 100. The control device can perform self-location estimation 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 around the work vehicle 100 based on the sensor data. The control device may also generate or compile an environmental map using algorithms such as Simultaneous Localization and Mapping (SLAM). The work vehicle 100 may be equipped with multiple LiDAR sensors arranged in different positions and with different orientations.

[0043] 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.

[0044] 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.

[0045] 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.

[0046] 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.

[0047] 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.

[0048] 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.

[0049] 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 working implement 300 to and from the work vehicle 100. The coupling device 108 can change the position or attitude of the working 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 working implement 300 via the universal joint. The work vehicle 100 can make the working implement 300 perform a predetermined task while pulling the working implement 300. The coupling device may be provided at the front of the vehicle body 101. In that case, an implement can be connected to the front of the work vehicle 100.

[0050] 2 is a rotary tiller, but the working machine 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.

[0051] 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.

[0052] 3 is a block diagram showing an example configuration of the work vehicle 100 and the work machine 300. The work vehicle 100 and the work machine 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.

[0053] 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 work machine 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.

[0054] 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, an identification number of each satellite from which the satellite signal is received, an elevation angle, an azimuth angle, and a value indicating reception strength. The reception strength may be expressed, for example, by a value such as a carrier-to-noise power density ratio (C / N0). The GNSS data may also include position information of the work vehicle 100 calculated based on the received plurality of satellite signals, and information indicating the reliability of the position information. The position information may be represented, for example, by latitude, longitude, height from mean sea level, and the like. The reliability of the position information may be represented, for example, by a DOP value indicating the satellite arrangement status.

[0055] 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.

[0056] 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.

[0057] 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.

[0058] 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.

[0059] 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.

[0060] 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.

[0061] 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.

[0062] 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.

[0063] The drive device 240 includes various devices necessary for the travel of the work vehicle 100 and the driving of the work implement 300, such as the prime mover 102, the transmission 103, the steering device 106, and the coupling device 108 described above. 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.

[0064] 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.

[0065] 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 roads in the surrounding areas. The environmental map and the target route may be generated by a processing device (processor) in the management device 600. Note that the control device 180 may have 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 the data of the work plan received by the communication device 190 from the management device 600 .

[0066] 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.

[0067] The storage device 170 also stores computer programs that cause each ECU in the control device 180 to execute various operations, which will be described later. 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.

[0068] 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 creation.

[0069] 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 .

[0070] 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 .

[0071] The ECU 183 controls the operation of the three-point link, the PTO shaft, and the like included in the coupling device 108 in order to cause the work machine 300 to perform a desired operation. The ECU 183 also generates a signal for controlling the operation of the work machine 300, and transmits the signal from the communication device 190 to the work machine 300.

[0072] 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.

[0073] The ECU 185 sequentially generates local paths capable of avoiding obstacles while the work vehicle 100 is traveling along the target path. While the work vehicle 100 is traveling, the ECU 185 recognizes obstacles present around the work vehicle 100 based on data output from the camera 120, the obstacle sensor 130, and the LiDAR sensor 140. The ECU 185 generates local paths so as to avoid the recognized obstacles.

[0074] The ECU 185 may have a function of performing global route design instead of the management device 600. In this 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 starting point of the movement of the work vehicle 100 to the destination point. The ECU 185 can create, for example, a route that can reach the destination in the shortest time as a target route based on an environmental map including road information stored in the storage device 170. Alternatively, the ECU 185 may generate, as a target route, a route that prioritizes a specific type of road (for example, a road along a specific feature such as a farm road or a waterway, or a road that can receive a satellite signal from a GNSS satellite well, etc.) based on attribute information of each road included in the environmental map.

[0075] 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-location estimation and the 2D map used for global route planning are both referred to as "environment maps." ECU 186 can also edit the map by adding various attribute information related to features (e.g., waterways, rivers, grass, trees, etc.) recognized based on data output from camera 120 or LiDAR sensor 140, road types (e.g., whether or not they are farm roads), road surface conditions, or road passability, etc.

[0076] 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.

[0077] 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.

[0078] The communication device 190 is a device including a circuit for communicating with the work machine 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 work machine 300. This allows the work machine 300 to perform a desired operation and to acquire information from the work machine 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 located near the work vehicle 100. Communication may be performed between such a mobile terminal in accordance with any wireless communication standard, such as cellular mobile communication such as Wi-Fi (registered trademark), 3G, 4G, or 5G, or Bluetooth (registered trademark).

[0079] 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 work 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 work 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.

[0080] 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 work machine 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 be provided with the operation switch group 210.

[0081] The drive device 340 in the work machine 300 shown in Fig. 3 performs operations necessary for the work machine 300 to perform a predetermined task. The drive device 340 includes devices according to the application of the work machine 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 work machine 300 can also be transmitted from the communication device 390 to the work vehicle 100.

[0082] 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.

[0083] 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 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 further generate or edit an environmental map. The environmental map may be distributed from a computer external to the management device 600.

[0084] 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.

[0085] 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.

[0086] 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.

[0087] The RAM 680 provides a working area for temporarily loading, at boot time, the control programs 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.

[0088] 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.

[0089] 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.

[0090] [2. Operation] Next, the operations of the work vehicle 100, the terminal device 400, and the management device 600 will be described.

[0091] [2-1. Automatic driving operation] First, an example of the operation of the 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 work 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 may perform an operation such as stopping the traveling, issuing a warning sound from the buzzer 220, and transmitting a warning signal to the terminal device 400. In the field, the positioning of the work vehicle 100 is mainly performed based on the 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 using data acquired by the camera 120 or the LiDAR sensor 140. Outside the field, when an obstacle is detected, the work vehicle 100, for example, avoids the obstacle or stops there. Outside the field, the position of the work vehicle 100 can be 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.

[0092] An example of the operation of the work vehicle 100 when it travels autonomously within a farm field will now be described.

[0093] FIG. 7 is a diagram showing a schematic 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 work 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. Although each main route P1 shown in FIG. 7 is a straight route, each main route P1 may include a curved portion. The main path P1 may be automatically generated, for example, by a user performing an operation of specifying two points (points A and B in FIG. 7) near the edge of the field while viewing a map of the field displayed on the operation terminal 200 or the terminal device 400. In this case, multiple main paths P1 are set parallel to a line segment connecting point A and point B specified by the user, and a target path in the field is generated by connecting the main paths P1 with a turning path P2. The dashed line in FIG. 7 represents the working width of the working machine 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 working machine 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 route can be created so as to cover, for example, the entire work area 72 in a farm 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 route as shown in Fig. 7. Note that the target route shown in Fig. 7 is merely an example, and the method of determining the target route is arbitrary.

[0094] Next, an example of control by the control device 180 during automatic operation in a farm field will be described.

[0095] 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.

[0096] 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.

[0097] Hereinafter, an example of steering control by the control device 180 will be described more specifically with reference to FIGS. 9A to 9D.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] 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 that brings the work vehicle 100 closer to the target path P can be made smooth.

[0104] If an obstacle is detected by one or more obstacle sensors 130 while traveling, the control device 180 may, for example, stop the work vehicle 100. At this time, the buzzer 220 may be caused to emit a warning sound or a warning signal may be sent to the terminal device 400. If it is possible to avoid the obstacle, the control device 180 may generate a local route that can avoid the obstacle, and control the drive device 240 so that the work vehicle 100 travels along that route.

[0105] 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.

[0106] 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 multiple 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 multiple 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 work 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.

[0107] [2-2. Creating a work plan] The work vehicle 100 in this embodiment moves between fields and automatically performs agricultural work in each field according to the work plan and target route created by the management device 600. The work plan includes information on one or more agricultural works to be performed by the work vehicle 100. For example, the work plan includes one or more agricultural works to be performed by the work vehicle 100 and information on the field on which each agricultural work is performed. The work plan may include multiple agricultural works to be performed by the work vehicle 100 over multiple work days and information on the field on which each agricultural work is performed. More specifically, the work plan may be a database including information on a work schedule indicating which agricultural machine will perform which agricultural work in which field at what time for each work day. Hereinafter, the work plan will be referred to as a work plan. An example in which the data of such a work schedule is described below. The work plan can be created by the processor 660 of the management device 600 based on information input by the user using the terminal device 400. An example of a method for creating a work schedule will be described below.

[0108] Fig. 11 is a diagram showing an example of a setting screen 760 displayed on the display device 430 of the terminal device 400. In response to a user's operation using the input device 420, the processor 460 of the terminal device 400 starts up application software for creating a schedule, and causes the display device 430 to display a setting screen 760 as shown in Fig. 11. The user can input information required for creating a work schedule on this setting screen 760.

[0109] 11 shows an example of a setting screen 760 when tilling with fertilizer application is performed as agricultural work in a rice field. The setting screen 760 is not limited to the one shown in the figure and can be changed as appropriate. The setting screen 760 in the example of FIG. 11 includes a date setting section 762, a crop plan selection section 763, a field selection section 764, an operation selection section 765, a worker selection section 766, a time setting section 767, a machine selection section 768, a fertilizer selection section 769, and an application amount setting section 770.

[0110] The date setting section 762 displays the date input by the input device 420. The input date is set as the date on which the farm work will be carried out.

[0111] The cultivation plan selection unit 763 displays a list of names of cultivation plans created in advance. The user can select a desired cultivation plan from the list. A cultivation plan is created in advance for each type and variety of crop, and is recorded in the storage device 650 of the management device 600. A cultivation plan is a plan for which crop is to be cultivated (i.e. planted) in which field. A cultivation plan is made by a manager who manages multiple fields before planting crops in the fields. In the example of FIG. 11, a cultivation plan for the rice variety "Koshihibuki" is selected. In this case, the contents set on the setting screen 760 are associated with the cultivation plan for "Koshihibuki".

[0112] The fields in the map are displayed in the field selection section 764. The user can select any field from the displayed fields. In the example of FIG. 11, the portion showing "Field A" is selected. In this case, the selected "Field A" is set as the field where farm work will be performed.

[0113] The work selection section 765 displays a plurality of farm works necessary for cultivating the selected crop. The user can select one farm work from among the plurality of farm works. In the example of FIG. 11, "plowing" is selected from among the plurality of farm works. In this case, the selected "plowing" is set as the farm work to be performed.

[0114] The worker selection section 766 displays workers registered in advance. The user can select one or more workers from the multiple workers displayed. In the example of FIG. 11, "Worker B, Worker C" are selected from the multiple workers. In this case, the selected "Worker B, Worker C" are set as the workers in charge of performing or managing the agricultural work. In this embodiment, since the agricultural machine performs the agricultural work automatically, the workers do not actually perform the agricultural work, but may simply remotely monitor the agricultural work performed by the agricultural machine.

[0115] The time setting section 767 displays the work time input from the input device 420. The work time is specified by a start time and an end time. The input work time is set as the scheduled time for carrying out the farm work.

[0116] The machine selection section 768 is a section for setting the agricultural machine to be used in the agricultural work. For example, the machine selection section 768 includes a type of agricultural machine registered in advance by the management device 600. The model number or type of the implement and the type or model of the available implement may be displayed. The user can select a specific machine from the displayed machines. In the example of FIG. 11, an implement with the model number "NW4511" is selected. In this case, the implement is set as the machine to be used in the farm work.

[0117] The fertilizer selection section 769 displays the names of multiple fertilizers that have been registered in advance by the management device 600. The user can select a specific fertilizer from the multiple fertilizers displayed. The selected fertilizer is set as the fertilizer to be used in the farm work.

[0118] A numerical value input from the input device 420 is displayed in the spray amount setting section 770. The input numerical value is set as the spray amount.

[0119] When the crop plan, farm field, farm work, worker, work time, fertilizer, and application amount are entered on the setting screen 760 and "Register" is selected, the communication device 490 of the terminal device 400 transmits the entered information to the management device 600. The processor 660 of the management device 600 stores the received information in the storage device 650. The processor 660 creates a schedule of farm work to be performed by each agricultural machine based on the received information, and stores the schedule in the storage device 650.

[0120] The information on agricultural work managed by the management device 600 is not limited to the above. For example, the type and amount of pesticide to be used in the field may be set on the setting screen 760. Information on agricultural work other than the agricultural work shown in FIG. 11 may be set.

[0121] FIG. 12 is a diagram showing an example of a schedule of farm work (i.e., a work plan) created by the management device 600. The schedule in this example includes information indicating the date and time when the farm work is performed, the field, the work content, and the implement to be used for each registered agricultural machine. In addition to the information shown in FIG. 12, the schedule may also include other information according to the work content, such as the type of pesticide or the amount of pesticide to be sprayed. In accordance with such a schedule, the processor 660 of the management device 600 issues instructions for the farm work to the work vehicle 100. The schedule may be downloaded by the control device 180 of the work vehicle 100 and also stored in the storage device 170. In that case, the control device 180 may autonomously start operating in accordance with the schedule stored in the storage device 170.

[0122] In this embodiment, the work plan is created by the management device 600, but the work plan may be created by another device. For example, the processor 460 of the terminal device 400 or the control device 180 in the work vehicle 100 may have a function of generating or updating the work plan.

[0123] [2-3. Route generation for autonomous driving] The management device 600 according to this embodiment functions as a route generation system that generates a route for an agricultural machine (in this example, the work vehicle 100) to perform automatic driving.

[0124] The management device 600, which functions as a route generation system in this embodiment, has a memory device 650 that stores map data for the work vehicle 100 to perform automatic driving, including position information of points where the work vehicle 100 has traveled and slip rate data of the work vehicle 100 associated with the position information, and a processing device (processor) 660 that generates a route for the work vehicle 100 to perform automatic driving based on the slip rate data included in the map data.

[0125] The map data to which the route generation system according to this embodiment is applied is used for the work vehicle 100 to perform automatic driving. However, the position information of the points where the work vehicle 100 has traveled, which is added to the map data, can use both information acquired while the work vehicle 100 is traveling in automatic driving and information acquired while the work vehicle 100 is traveling in manual driving. "Map data for the agricultural machine to perform automatic driving" is data that expresses the positions or areas of objects (including features) that exist in the environment in which the agricultural machine performs automatic driving using a specified coordinate system, and may further include attribute information of the objects. The map data may be in various formats such as a point cloud map or a grid map, and is not limited to two-dimensional map data but may be three-dimensional map data.

[0126] The route generation system according to this embodiment is mainly used for generating a route along which the work vehicle 100 automatically travels outside a field. The route generated by the route generation system according to this embodiment may include, for example, a route along which the work vehicle 100 automatically travels outside a field, or a route along which the work vehicle 100 automatically travels on a farm road. The route generation system according to this embodiment may also be used for generating a route along which the work vehicle 100 automatically travels within a field.

[0127] The processing device 660 generates a route for the work vehicle 100 to perform automatic driving based on, for example, map data stored in the storage device 650. At this time, the processing device 660 can generate a route using slip rate data acquired when the work vehicle 100 traveled in the past, so that a suitable route for the work vehicle 100 can be efficiently generated. A specific example will be described later, but for example, a route can be generated by combining roads with low slip rates. For example, an agricultural machine that performs automatic driving has the opportunity to travel on roads such as farm roads that are not well maintained. According to the route generation system of this embodiment, a route can be generated based on slip rate data (traveling record) when the road is actually traveled, so that a more suitable route for the work vehicle 100 to perform automatic driving can be generated. Using the route generation system of this embodiment, the work vehicle 100 can travel efficiently by automatic driving.

[0128] The processing device 660 generates a route for the work vehicle 100 to perform autonomous driving by setting a plurality of waypoints, each of which includes position and speed information. Slip ratio information of the work vehicle 100 is associated with some or all of the plurality of waypoints. The processing device 660 may change the speed of each waypoint according to the value of the slip ratio data included in the map data. For example, the speed may be set to be lower as the slip ratio increases.

[0129] The processing device 660 can update (or correct) the slip ratio data included in the map data. That is, the processing device 660 may acquire data on the slip ratio of the work vehicle 100 while the work vehicle 100 is traveling in an automatic or manual driving mode, and add the acquired data on the slip ratio of the work vehicle 100 to the map data in association with the position information of the work vehicle 100. By updating the slip ratio data included in the map data, the accuracy of the map data can be maintained. For example, when the road surface condition of the road included in the map data changes significantly (for example, when an unpaved road is paved with asphalt), slip ratio data reflecting the change in the road surface condition can be included in the map data. The processing device 660 may update the slip ratio data included in the map data at predetermined intervals (periodically).

[0130] The processing device 660 may also acquire information on the surrounding environment when the slip ratio data is acquired, and store it in the map data. While the work vehicle 100 is traveling in an automatic or manual driving mode, the processing device 660 acquires information on the surrounding environment of the work vehicle 100 by using sensor data output from one or more sensing devices that sense the surrounding environment of the work vehicle 100, or data acquired by communicating with an external computer, and may add the information on the surrounding environment of the work vehicle 100 when the slip ratio data of the work vehicle 100 is acquired to the map data in association with the slip ratio of the work vehicle 100. Examples of the information on the surrounding environment of the work vehicle 100 include weather information, precipitation information, and information on the condition of the road surface (ground) on which the work vehicle 100 is traveling (e.g., the degree of muddiness) when the slip ratio data of the work vehicle 100 is acquired. When the work vehicle 100 automatically travels outside a field, the work vehicle 100 typically does not perform work (ground work), and therefore the load due to the work does not contribute to the slip ratio of the work vehicle 100. When the work vehicle 100 automatically travels outside a field, the main factor that determines the slip ratio of the work vehicle 100 is considered to be the condition of the ground (e.g., whether the ground is dry or wet, how muddy the ground is, whether the ground is paved or unpaved, how uneven the ground is, etc.). Therefore, it is preferable that the processing device 660 acquires information on the environment around the work vehicle 100 that may be related to the condition of the ground on which the work vehicle 100 travels. For example, the ground may be wet when it is raining or after it has rained, and the more the amount of precipitation, the greater the degree of muddiness. By the processing device 660 acquiring, for example, weather information or precipitation information along with the slip ratio data, it may be possible to effectively utilize the slip ratio data to generate a route.

[0131] The processing device 660 acquires information about the environment around the work vehicle 100, for example, based on sensor data obtained by sensing the environment around the work vehicle 100 using one or more sensing devices possessed by the work vehicle 100. In the example of Fig. 2, the sensing devices possessed by the work vehicle 100 include multiple cameras 120, a LiDAR sensor 140, and multiple obstacle sensors 130. The processing device 660 acquires information about the environment around the work vehicle 100, based on sensor data output from at least one of the sensing devices possessed by the work vehicle 100, for example, image data acquired by the camera 120, data output from the obstacle sensor 130 or the LiDAR sensor 140 (for example, point cloud data), etc.

[0132] Alternatively, the work vehicle 100 may travel while sensing the surrounding environment with one or more sensing devices possessed by other moving objects, such as agricultural machinery other than the work vehicle 100 or a drone (Unmanned Aerial Vehicle: UAV). The processing device 660 of the path generation system according to this embodiment may acquire information about the surrounding environment of the work vehicle 100 based on sensor data output from a sensing device possessed by other moving objects, such as agricultural machinery other than the work vehicle 100 or a drone.

[0133] In addition, the processing device 660 may obtain weather information (e.g., sunny / cloudy / rainy), precipitation information, temperature information, humidity information, etc., when the slip ratio data of the work vehicle 100 is obtained from a server computer that distributes weather information via a network such as the Internet.

[0134] The slip ratio of the work vehicle 100 may be calculated by a known method. For example, while the work vehicle 100 is traveling in an automatic or manual driving mode, the processing device 660 acquires information on the ground speed of the work vehicle 100 and the rotation speed of the drive wheels (wheels 104) of the work vehicle 100, and calculates the slip ratio of the work vehicle 100 based on the ground speed of the work vehicle 100 and the rotation speed of the drive wheels of the work vehicle 100. The axle sensor 156 of the work vehicle 100 measures the rotation speed of the axle connected to the wheels 104, that is, the number of rotations per unit time. The target speed of the work vehicle 100 is calculated based on the data output from the axle sensor 156. The processing device 660 calculates the ground speed of the work vehicle 100 based on, for example, GNSS data output from a GNSS receiver included in the work vehicle 100. If there is no slip between the drive wheels and the ground, the target speed and the ground speed will be equal, but if there is slip in the drive wheels, a discrepancy will occur between the target speed and the ground speed. The slip ratio is calculated based on the difference between the target speed and the ground speed. The greater the difference between the target speed and the ground speed, the greater the slip ratio. The slip ratio is typically expressed as the ratio of the difference between the target speed and the ground speed to the target speed (slip ratio = (target speed - ground speed) / target speed).

[0135] When the processing device 660 calculates the slip ratio based on the GNSS data output from the GNSS receiver of the work vehicle 100, the processing device 660 may acquire the reception strength of the satellite signal by the GNSS receiver of the work vehicle 100 as information on the surrounding environment when the slip ratio data was acquired, and may add the information to the map data in association with the slip ratio. The processing device 660 may determine whether the acquisition of the slip ratio data was performed in a situation where the satellite signal can be normally received, based on the reception strength of the satellite signal by the GNSS receiver. For example, when the reception strength of the satellite signal by the GNSS receiver is higher than a predetermined strength, the processing device 660 may determine that the acquisition of the slip ratio data was performed in a situation where the satellite signal can be normally received. The processing device 660 may add the slip ratio data to the map data only when it is determined that the acquisition of the slip ratio data was performed in a situation where the satellite signal can be normally received.

[0136] 13A and 13B are diagrams showing examples of the reception strength of satellite signals. FIG. 13B shows an example of the reception strength of each satellite signal in a situation where the satellite signal can be normally received. FIG. 13B shows an example of the reception strength of each satellite signal in a situation where the satellite signal cannot be normally received (i.e., reception interference may occur). In this example, satellite signals from 12 satellites are received, and the reception strength is expressed as a value of the carrier-to-noise power density ratio (C / N0). Note that this is only one example, and the number of satellites from which the satellite signal can be received and the expression of the reception strength depend on the system. As an example, the presence or absence of reception interference can be determined by whether or not the number of satellites whose reception strength exceeds a preset reference value is equal to or greater than a threshold value (e.g., 4). In FIG. 13A and FIG. 13B, an example of the reference value of the reception strength is shown by a broken line. When the threshold value is, for example, 4, in the example of FIG. 13A, the number of satellites whose reception strength exceeds the reference value is 5, which is equal to or greater than the threshold. Therefore, in such a case, it can be determined that the satellite signal can be normally received. On the other hand, in the example of FIG. 13B, the number of satellites whose reception strength exceeds the reference value is 1, which is less than the threshold. Therefore, in such a case, it can be determined that the situation is not normal reception. The above method is merely an example, and other methods may be used to determine whether each road is a road on which satellite signals can be normally received. For example, if the GNSS data includes a value indicating the reliability of positioning, it may be determined whether satellite signals can be normally received based on the reliability value.

[0137] Fig. 14 is a diagram showing an example of a map of an area in which the work vehicle 100 travels. Such a map may be displayed on the display device 430. This map is a two-dimensional digital map, and is generated by the management device 600 or another device. A map such as that shown in Fig. 14 may be created for the entire area in which the work vehicle 100 may travel. Note that although the map shown in Fig. 14 is a two-dimensional map, a three-dimensional map may also be used for route generation.

[0138] The map shown in FIG. 14 includes information on the positions (e.g., latitude and longitude) of each point on the multiple fields 70 in which the work vehicle 100 performs farm work, the surrounding roads 76, and features such as waterways 78. The map further includes attribute information indicating at least one of whether each road 76 is a farm road, whether each road 76 runs along a specific feature such as a waterway 78, and whether each road 76 is a road on which satellite signals from GNSS satellites can be normally received. In addition to these attribute information, for example, attribute information indicating the width of each road 76 at each point may be included in the map. The management device 600 can determine whether the work vehicle 100 can pass through the road 76 based on the width of each road 76 at each point. The map may include attribute information indicating whether each road 76 is a general road other than a farm road. Based on such attribute information, a route that avoids general roads can be generated.

[0139] In FIG. 14, an example of a starting point S and a destination point G of the automatic travel of the work vehicle 100 is indicated by a star. The starting point S and the destination point G may be set by, for example, a user. Alternatively, the management device 600 may set the starting point S and the destination point G according to a work schedule for each work day. The work schedule for each work day is generated in advance by the management device 600 and stored in the storage device 650, as described with reference to FIG. 12. In addition to the starting point S and the destination point G, one or more waypoints may be set. For each of the starting point S, the destination point G, and the waypoint, one or both of the scheduled arrival time and the scheduled departure time may be recorded.

[0140] The route generation system according to the present embodiment may have a plurality of modes for route generation. For example, the processing device 660 can generate a route in a first mode in which the work vehicle 100 performs automatic driving by preferentially combining roads on which the slip rate of the work vehicle 100 is smaller than a first threshold value, and in a second mode in which the work vehicle 100 performs automatic driving so as to minimize the travel time (travel time) or travel distance (travel distance) of the work vehicle 100. The first threshold value may be determined in advance, or may be set by the user each time. The user may select from a plurality of modes. The processing device 660 may generate a route in which the work vehicle 100 performs automatic driving in any mode selected by the user from a plurality of modes including the first mode and the second mode.

[0141] FIG. 15A is a diagram showing an example of a GUI displayed on the display device 430. In this example, a GUI is displayed in which the user can select one of three modes: "slip ratio priority", "time priority", and "mileage priority". In the example of FIG. 15A, "slip ratio priority" corresponds to the first mode, and "time priority" and "mileage priority" correspond to the second mode. Either "time priority" or "mileage priority" may be omitted. In addition, these other modes may be further included. FIG. 15A shows a state in which "slip ratio priority" is selected as an example. The processing device 660 automatically generates a route from the starting point to the destination point of the automatic traveling of the work vehicle 100. The starting point and the destination point may be set in advance by the user or may be set by the management device 600 according to a work plan created in advance. After the starting point and the destination point are set, the management device 600 generates a route from the starting point to the destination point at a predetermined timing before the automatic traveling starts.

[0142] FIG. 15B is a diagram showing an example of a route generated when the "slip ratio priority" mode is selected in the example map of FIG. 14. In the "slip ratio priority" mode (first mode), the processing device 660 generates a route 75A that combines roads with a slip ratio smaller than a first threshold as a route for the work vehicle 100 to travel from the starting point S to the destination point G by performing automatic driving. For example, the processing device 660 may select, as the route for the work vehicle 100, a route with the shortest travel distance or travel time (or a relatively short route) among the routes generated by combining roads with a slip ratio smaller than the first threshold among the roads between the starting point S and the destination point G. The processing device 660 may further refer to the work plan of the work vehicle 100 in selecting the route. In other words, a route that follows the schedule of farm work on that work day may be selected and determined as the route for the work vehicle 100. If a route from the starting point S to the destination point G cannot be generated by combining only roads whose slip ratios are smaller than the first threshold, the processing device 660 may generate a route for the work vehicle 100 by further combining roads whose slip ratios are equal to or greater than the first threshold but as small as possible.

[0143] In this example, the road along the waterway 78 has a relatively high slip ratio, so the ratio of roads along the waterway 78 to the generated route 75A is low. In this way, in the "slip ratio priority" mode (first mode), the processing device 660 can generate a route that avoids roads with a relatively high slip ratio (for example, roads along waterways or roads along cliff edges) as much as possible.

[0144] Fig. 15C is a diagram showing an example of a route that is generated when the "distance priority" mode is selected in the example map of Fig. 14. In the "distance priority" mode (second mode), the processing device 660 generates route 75B that is the shortest distance traveled as a route for the work vehicle 100 to travel from the starting point S to the destination point G while performing autonomous driving.

[0145] In this example, the ratio of roads along the waterway 78 in the route 75B generated in the "travel distance priority" mode (second mode) is higher than the ratio of roads along the waterway 78 in the route 75A generated in the "slip ratio priority" mode (first mode). The user can select from a plurality of modes (modes for route generation) possessed by the processing device 660 to generate a route according to the weather, work plan, etc. when the work vehicle 100 performs automatic driving. Note that the processing device 660 may generate a route for the work vehicle 100 in any of a plurality of modes for route generation according to a predetermined algorithm without providing a mode selection function by the user. The plurality of modes possessed by the processing device 660 may further include a mode in which the user manually sets a route. When the "manual setting" mode is selected, the processing device 660, for example, displays a map of the area in which the work vehicle 100 travels on the display device 430 and allows the user to select a route.

[0146] When generating a route for the work vehicle 100 to perform automatic driving in the first mode or the second mode, the processing device 660 may notify the user that the generated route includes a road with a large slip ratio if the generated route includes a road with a large slip ratio greater than the second threshold. In response to the notification that the generated route includes a road with a large slip ratio, the user may, for example, select whether or not to approve the generated route. In response to the notification that the generated route includes a road with a large slip ratio, the user may select to travel part or all of the generated route by manual driving. The second threshold may be determined in advance or may be set by the user each time. The second threshold may be set, for example, independently of the above-mentioned first threshold, and may be greater than the first threshold or less than the first threshold.

[0147] An example of a method for setting the first threshold value will be described. The processing device 660 may change the first threshold value depending on the weather and the amount of precipitation. For example, the processing device 660 acquires information on the weather expected when the work vehicle 100 travels along the route from sensor data obtained by sensing the environment around the work vehicle 100 or data acquired by communicating with an external computer, and changes the first threshold value depending on the weather. For example, if the weather is rainy when the work vehicle 100 travels along the route, the first threshold value is set to be smaller than when it is sunny. Alternatively, the processing device 660 may acquire information on the amount of precipitation expected when the work vehicle 100 travels along the route from an external computer, and set the first threshold value to be smaller as the amount of precipitation increases.

[0148] The second threshold may be set according to the weather and the amount of precipitation, similar to the first threshold. For example, the processing device 660 acquires information on the weather expected when the work vehicle 100 travels along the route from sensor data sensing the environment around the work vehicle 100 or data acquired by communicating with an external computer, and changes the second threshold according to the weather. For example, if the weather is rainy when the work vehicle 100 travels along the route, the second threshold is set to be smaller than when it is sunny. Alternatively, the processing device 660 may acquire information on the amount of precipitation expected when the work vehicle 100 travels along the route from an external computer, and set the second threshold to be smaller as the amount of precipitation increases.

[0149] FIG. 16A is a flowchart showing an example of a procedure for the processing device 660 in the example of FIGS. 15A to 15C to generate a route.

[0150] In step S202, the processing device 660 determines the selected mode. For example, the user selects one of "slip ratio priority," "time priority," and "mileage priority" shown in FIG. 15A and presses "OK." If "slip ratio priority" is selected, the process proceeds to step S203. If "time priority" is selected, the process proceeds to step S204. If "mileage priority" is selected, the process proceeds to step S205.

[0151] In step S203, the processing device 660 generates a route for the work vehicle 100 to perform automatic driving by preferentially combining roads on which the slip ratio of the work vehicle 100 is smaller than a first threshold value. In step S204, the processing device 660 generates a route for the work vehicle 100 to perform automatic driving so that the travel time of the work vehicle 100 is the shortest. In step S205, the processing device 660 generates a route for the work vehicle 100 to perform automatic driving so that the travel distance of the work vehicle 100 is the shortest. After step S203, S204, or S205, the process proceeds to step S206.

[0152] In step S206, the processing device 660 determines whether the route generated in step S203, S204, or S205 includes a road with a slip ratio greater than the second threshold. If it is determined that the generated route includes a road with a slip ratio greater than the second threshold, the process proceeds to step S207. If it is determined that the generated route does not include a road with a slip ratio greater than the second threshold, the process proceeds to step S209.

[0153] In step S207, the processing device 660 notifies the user that the generated route includes a road with a large slip ratio. For example, the processing device 660 notifies the user by displaying the information on the display device 430.

[0154] In step S208, the processing device 660 determines whether the generated route is approved. The user can select whether to approve the generated route, for example, by using the display device 430. If the generated route is not approved by the user, the process returns to step S202.

[0155] If the generated route is approved by the user, in step S209, the processing device 660 transmits the generated route to the work vehicle 100 at a predetermined timing. The work vehicle 100 performs autonomous traveling according to the generated route and the previously acquired work schedule.

[0156] Fig. 16B is a flowchart showing an example of a procedure executed by the processing device 660 of the route generation system, and shows an example of a procedure when the processing device 660 updates the slip ratio data included in the map data. The processing device 660 may execute the procedure of the flowchart in Fig. 16B in parallel with the procedure when generating a route as exemplified in Fig. 16A.

[0157] In step S181, the processing device 660 acquires position information of the work vehicle 100 and data on the slip ratio of the work vehicle 100 while the work vehicle 100 is traveling in an automatic or manual driving mode.

[0158] In step S182, the processor 660 associates the slip ratio data of the work vehicle 100 acquired in step S181 with the position information of the work vehicle 100 and adds it to the map data.

[0159] In step S183, the processing device 660 determines whether or not information on the surrounding environment when the slip ratio data was acquired has also been acquired. If information on the surrounding environment when the slip ratio data was acquired has also been acquired, the process proceeds to step S184, where the processing device 660 adds the acquired information on the surrounding environment to the map data in association with the slip ratio of the work vehicle 100.

[0160] The processor 660 repeats steps S181 to S184 until a command to end the operation is issued (step S185).

[0161] Here, an example has been described in which the processing device 660 of the management device 600 functions as a processing device of the route generation system, but part or all of the processing executed by the processing device 660 of the management device 600 in the route generation system may be executed by another device. Such other device may be any of the terminal device 400 (processor 460), the control device 180 of the work vehicle 100, and the operation terminal 200. For example, when part of the processing executed by the processing device 660 of the management device 600 is executed by the control device 180, the combination of the management device 600 and the control device 180 functions as a processing device of the route generation system. In the example described, the storage device 650 of the management device 600 functions as a storage device that stores the travel history of the work vehicle 100, but the storage device 450 of the terminal device 400 and / or the storage device 170 of the work vehicle 100 may function as a storage device of the route generation system. The work vehicle 100 may be equipped with a route generation system, in which case the control device 180 and the storage device 170 of the work vehicle 100 function as a processing device and a storage device of the route generation system. The control device 180 of the work vehicle 100 may further include, in addition to the ECUs 181-186 illustrated, an ECU for performing some or all of the processing for controlling traveling.

[0162] [2-4. Local Route Planning] 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 second route 30B. The ECU 185 determines whether or not 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 are present, ECU 185 generates a local route substantially parallel to second route 30B. Information indicating the generated local route 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 route. 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.

[0163] FIG. 17 is a diagram showing an example of a global route and a local route generated in an environment where an obstacle exists. In FIG. 17, 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 orientation 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. 17 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.

[0164] In the example shown in FIG. 17, an obstacle 40 (e.g., a person) is present in front of the work vehicle 100. In FIG. 17, 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.

[0165] Fig. 18 is a flowchart showing the operation of route planning and travel control in this embodiment. By executing the operations of steps S141 to S146 shown in Fig. 18, route planning can be performed and the automatic travel of the work vehicle 100 can be controlled.

[0166] In the example shown in FIG. 18, 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 using the method described above (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 one day or earlier before the work vehicle 100 starts traveling. The global route may also be generated based on information (e.g., starting point, destination point, waypoint, etc.) input by the user using the terminal device 400. As described above, when the management device 600 generates a route to a farm field or a route from the farm field to another location (for example, a storage location or waiting location of the work vehicle 100), the management device 600 generates at least one of a route that prioritizes farm roads, a route that prioritizes roads along specific features, and a route that prioritizes roads that can normally receive satellite signals as a route for the work vehicle 100 based on attribute information of each road on the map. The management device 600 transmits data indicating the generated global route to the work vehicle 100. Thereafter, 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 the travel of the work vehicle 100 (step S143). As a result, the work vehicle 100 starts traveling. The timing of the start of travel 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 agricultural work on each work day indicated by the work plan, for example. The ECU 185 of the control device 180 performs local route design using the above-mentioned method to avoid collision with an obstacle while the work vehicle 100 is traveling (step S144). If no obstacle is detected, the ECU 185 generates a local route that is approximately parallel to the global route. If an obstacle is detected, the ECU 185 generates a local route that can avoid the obstacle. Next, the ECU 184 determines whether or not to end the traveling of the work vehicle 100 (step S145). 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 S146).If no obstacle is detected, or if a local route that can avoid the obstacle has been generated, the process returns to step S143, and ECU 184 causes work vehicle 100 to travel along the generated local route. Thereafter, the operations of steps S143 to S145 are repeated until it is determined in step S145 that travel is to be ended.

[0167] Through the above operations, the work vehicle 100 can automatically travel along the generated route without colliding with any obstacles.

[0168] In the example of FIG. 18, 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.

[0169] As described above, the present disclosure includes the path generation system and agricultural machine described in the following items.

[0170] [Item 1] a storage device that stores map data for an agricultural machine to perform automatic driving, the map data including position information of a point where the agricultural machine has traveled and data on a slip rate of the agricultural machine associated with the position information; a processing device that generates a route for the agricultural machine to automatically drive on the basis of the slip ratio data included in the map data; A route generation system having the following features:

[0171] [Item 2] The processing device includes: Obtaining slip rate data of the agricultural machine while the agricultural machine is traveling; 2. A route generation system as described in item 1, which associates the acquired slip ratio data of the agricultural machine with position information of the agricultural machine and adds it to the map data.

[0172] [Item 3] The processing device includes: While the agricultural machine is traveling, information on the surrounding environment of the agricultural machine is acquired based on sensor data output from a sensing device that senses the surrounding environment of the agricultural machine or data acquired through communication with an external computer; 3. A route generation system as described in item 2, wherein information on the surrounding environment of the agricultural machine at the time when the slip rate data of the agricultural machine is acquired is associated with the slip rate of the agricultural machine and added to the map data.

[0173] [Item 4] 4. The route generation system according to item 3, wherein the information on the surrounding environment includes weather information, precipitation information, or information on the degree of muddiness of the road surface at the time when the slip rate data of the agricultural machine is acquired.

[0174] [Item 5] The processing device includes: While the agricultural machine is traveling, information on the ground speed of the agricultural machine and the rotational speed of the drive wheels of the agricultural machine is acquired; 5. A route generation system according to any one of items 1 to 4, which calculates a slip ratio of the agricultural machine based on the ground speed and the rotational speed of the agricultural machine.

[0175] [Item 6] The processing device includes: 6. A route generation system as described in item 5, which calculates the ground speed of the agricultural machine based on GNSS data output from a GNSS receiver possessed by the agricultural machine.

[0176] [Item 7] The processing device includes: a first mode in which the route is generated by preferentially combining roads on which a slip rate of the agricultural machine is smaller than a first threshold; a second mode of generating the route so as to minimize a travel time or a travel distance of the agricultural machine; 7. The route generation system according to any one of claims 1 to 6, wherein the route can be generated by

[0177] [Item 8] The processing device includes: 8. The route generation system according to item 7, wherein the route is generated in any one of a plurality of modes including the first mode and the second mode selected by a user.

[0178] [Item 9] The processing device includes: obtaining information on weather predicted when the agricultural machine travels along the route from sensor data obtained by sensing an environment around the agricultural machine or data obtained by communicating with an external computer; 9. The route generation system according to item 7 or 8, wherein the first threshold is changed depending on the weather.

[0179] [Item 10] The processing device includes: obtaining information on a predicted amount of precipitation when the agricultural machine travels along the route from an external computer; 10. The route generation system according to item 9, wherein the first threshold is set to a smaller value as the amount of precipitation increases.

[0180] [Item 11] A route generation system according to any one of items 7 to 10, wherein when generating the route in the first mode or the second mode, if the generated route includes a road with a slip rate greater than a second threshold, the system notifies the user that the route includes a road with a large slip rate.

[0181] [Item 12] The processing device includes: obtaining information on weather predicted when the agricultural machine travels along the route from sensor data obtained by sensing an environment around the agricultural machine or data obtained by communicating with an external computer; Item 12. The route generation system according to item 11, wherein the second threshold is changed depending on the weather.

[0182] [Item 13] The processing device includes: obtaining information on a predicted amount of precipitation when the agricultural machine travels along the route from an external computer; Item 13. The route generation system according to item 12, wherein the second threshold is set smaller as the amount of precipitation increases.

[0183] [Item 14] the processing unit generates the path defined by a plurality of waypoints, each waypoint including position and velocity information; 14. The route generation system according to any one of claims 1 to 13, wherein the speeds of the plurality of waypoints are changed depending on the value of the slip ratio data included in the map data.

[0184] [Item 15] 15. The route generation system according to any one of claims 1 to 14, wherein the route includes a route in which the agricultural machine travels outside a field.

[0185] [Item 16] 16. The route generation system according to any one of claims 1 to 15, wherein the route includes a route along which the agricultural machine travels on a farm road.

[0186] [Item 17] 17. An agricultural machine comprising a path generation system according to any one of items 1 to 16.

[0187] [Item 18] storing map data for an agricultural machine to perform automatic driving, the map data including position information of a point where the agricultural machine has traveled and data on a slip rate of the agricultural machine associated with the position information; generating a route along which the agricultural machine will automatically drive based on the slip ratio data included in the map data; and A route generation method comprising: [Industrial Applicability]

[0188] The technology disclosed herein can be applied to a route generation system that generates a route for autonomous driving of agricultural machinery such as a tractor, a harvester, a rice transplanter, a riding tiller, a vegetable transplanter, a grass cutter, a seed sower, a fertilizer applicator, or an agricultural robot, as well as an agricultural machine equipped with such a route generation system and a route generation method. [Explanation of symbols]

[0189] 40 obstacle, 50 GNSS satellite, 60 reference station, 70 field, 71 entrance / exit, 72 work area, 74 headland, 76 road, 80 network, 100 work vehicle, 101 vehicle body, 102 engine, 103 transmission, 104 wheel, 105 cabin, 106 Steering system, 107, driver's seat, 108, coupling device, 110, positioning device, 111, GNSS receiver, 112, RTK receiver, 115, inertial measurement unit (IMU), 116, processing circuit, 120, camera, 130, obstacle sensor, 140, LiDAR sensor, 150, sensor group, 152, steering wheel sensor, 154 156···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 switches, 220···Buzzer, 240···Drive device, 300···Work machine (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, 660...processor (processing device), 670...storage device, 670...ROM, 680...RAM, 690...communication device

Claims

1. a storage device that stores map data for an agricultural machine to perform automatic driving, the map data including position information of a point where the agricultural machine has traveled and data on a slip rate of the agricultural machine associated with the position information; a processing device that generates a route for the agricultural machine to automatically drive on the basis of the slip ratio data included in the map data; having The processing device includes: Obtaining slip rate data of the agricultural machine while the agricultural machine is traveling; The obtained slip ratio data of the agricultural machine is associated with position information of the agricultural machine and added to the map data; While the agricultural machine is traveling, information on the surrounding environment of the agricultural machine is acquired based on sensor data output from a sensing device that senses the surrounding environment of the agricultural machine or data acquired through communication with an external computer; A route generation system that adds information about the surrounding environment of the agricultural machine at the time when the data on the slip rate of the agricultural machine is acquired to the map data in association with the slip rate of the agricultural machine.

2. The route generation system according to claim 1 , wherein the information on the surrounding environment includes information on the weather, the amount of precipitation, or the degree of muddiness of the road surface at the time when the data on the slip ratio of the agricultural machine was acquired.

3. The processing device includes: a first mode in which the route is generated by preferentially combining roads on which a slip rate of the agricultural machine is smaller than a first threshold; a second mode of generating the route so as to minimize a travel time or a travel distance of the agricultural machine; The route generation system according to claim 1 , wherein the route can be generated by

4. a storage device that stores map data for an agricultural machine to perform automatic driving, the map data including position information of a point where the agricultural machine has traveled and data on a slip rate of the agricultural machine associated with the position information; a processing device that generates a route for the agricultural machine to automatically drive on the basis of the slip ratio data included in the map data; having The processing device includes: a first mode in which the route is generated by preferentially combining roads on which a slip rate of the agricultural machine is smaller than a first threshold; a second mode of generating the route so as to minimize a travel time or a travel distance of the agricultural machine; A route generation system capable of generating the route.

5. The processing device includes: The route generation system according to claim 3 or 4, wherein the route is generated in any one of a plurality of modes including the first mode and the second mode, the mode being selected by a user.

6. The processing device includes: The weather forecast information for when the agricultural machine travels along the route is sent to the surroundings of the agricultural machine. The information is acquired from sensor data that senses the surrounding environment or from data obtained by communicating with an external computer. The route generation system according to claim 3 or 4, wherein the first threshold value is changed depending on the weather.

7. The processing device includes: obtaining information on a predicted amount of precipitation when the agricultural machine travels along the route from an external computer; The route generation system according to claim 6 , wherein the first threshold is set to be smaller as the amount of precipitation increases.

8. The processing device includes:

5. The route generation system of claim 3 or 4, wherein when generating the route in the first mode or the second mode, if the generated route includes a road with a slip ratio greater than a second threshold, the system notifies the user that the route includes a road with a large slip ratio.

9. The processing device includes: obtaining information on weather predicted when the agricultural machine travels along the route from sensor data obtained by sensing an environment around the agricultural machine or data obtained by communicating with an external computer; The route generation system according to claim 8 , wherein the second threshold is changed depending on the weather.

10. The processing device includes: obtaining information on a predicted amount of precipitation when the agricultural machine travels along the route from an external computer; The route generation system according to claim 9 , wherein the second threshold is set to be smaller as the amount of precipitation increases.

11. a storage device that stores map data for an agricultural machine to perform automatic driving, the map data including position information of a point where the agricultural machine has traveled and data on a slip rate of the agricultural machine associated with the position information; a processing device that generates a route for the agricultural machine to automatically drive on the basis of the slip ratio data included in the map data; having A route generation system, wherein the route includes a route in which the agricultural machine travels outside of a field.

12. The processing device includes: Obtaining slip rate data of the agricultural machine while the agricultural machine is traveling; 12. The route generation system according to claim 4 or 11, wherein the acquired data on the slip ratio of the agricultural machine is associated with position information of the agricultural machine and added to the map data.

13. The processing device includes: While the agricultural machine is traveling, information on the surrounding environment of the agricultural machine is acquired based on sensor data output from a sensing device that senses the surrounding environment of the agricultural machine or data acquired through communication with an external computer; The route generation system according to claim 12 , wherein information on the surrounding environment of the agricultural machine when the data on the slip ratio of the agricultural machine is acquired is associated with the slip ratio of the agricultural machine and added to the map data.

14. The route generation system according to claim 13 , wherein the information on the surrounding environment includes information on the weather, the amount of precipitation, or the degree of muddiness of the road surface at the time when the data on the slip ratio of the agricultural machine was acquired.

15. The processing device includes: While the agricultural machine is traveling, information on the ground speed of the agricultural machine and the rotational speed of the drive wheels of the agricultural machine is acquired; The route generation system according to claim 1 , further comprising: a slip ratio of the agricultural machine calculated based on the ground speed and the rotational speed of the agricultural machine.

16. The processing device includes: The route generation system according to claim 15, wherein the ground speed of the agricultural machine is calculated based on GNSS data output from a GNSS receiver included in the agricultural machine.

17. the processing unit generates the path defined by a plurality of waypoints, each waypoint including position and velocity information; 12. The route generation system according to claim 1, wherein the speeds of the plurality of waypoints are changed in accordance with values ​​of the slip ratio data included in the map data.

18. The route generation system according to claim 3 or 4, wherein the route includes a route along which the agricultural machine travels outside a farm field.

19. The route generation system according to claim 1 , wherein the route includes a route along which the agricultural machine travels on a farm road.

20. An agricultural machine comprising a path generation system according to any one of claims 1 to 4 and 11.

21. storing map data for an agricultural machine to perform automatic driving, the map data including position information of a point where the agricultural machine has traveled and data on a slip rate of the agricultural machine associated with the position information; generating a route along which the agricultural machine will automatically drive based on the slip ratio data included in the map data; Obtaining slip ratio data of the agricultural machine while the agricultural machine is traveling; adding the acquired slip ratio data of the agricultural machine to the map data in association with position information of the agricultural machine; acquiring information on the surrounding environment of the agricultural machine from sensor data output from a sensing device that senses the surrounding environment of the agricultural machine while the agricultural machine is traveling or from data obtained by communicating with an external computer; adding information on the surrounding environment of the agricultural machine at the time when the data on the slip ratio of the agricultural machine was acquired to the map data in association with the slip ratio of the agricultural machine; A route generation method comprising:

22. storing map data for an agricultural machine to perform automatic driving, the map data including position information of a point where the agricultural machine has traveled and data on a slip rate of the agricultural machine associated with the position information; generating a route along which the agricultural machine will automatically drive based on the slip ratio data included in the map data; and Including, generating said pathway, a first mode in which the route is generated by preferentially combining roads on which a slip rate of the agricultural machine is smaller than a first threshold; a second mode of generating the route so as to minimize a travel time or a travel distance of the agricultural machine; A route generation method that can be performed by

23. storing map data for an agricultural machine to perform automatic driving, the map data including position information of a point where the agricultural machine has traveled and data on a slip rate of the agricultural machine associated with the position information; generating a route along which the agricultural machine will automatically drive based on the slip ratio data included in the map data; and Including, A route generation method, wherein the route includes a route in which the agricultural machine travels outside a field.

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