Path planning system and path planning method for autonomously driving agricultural machinery

Abstract

This route-planning system is for a farm machine that automatically travels in and out of fields, and comprises: a storage device that stores a map of an area including a plurality of farm fields and roads around the plurality of farm fields; and a processing device that generates routes for the farm machine on the map. The map includes attribute information indicating at least one of the following: whether each road is a farm road, whether each road is a road along a particular feature, and whether each road is a road where satellite signals from GNSS satellites can normally be received. When the processing device generates a route to a field or a route from the field to another location, the processing device generates, as a route for the farm machine, at least one of the following on the basis of the attribute information: a route prioritizing farm roads, a route prioritizing roads along the particular feature, and a route prioritizing roads where the satellite signals can normally be received.

Description

[Technical Field]

[0001] The present disclosure relates to a path planning system and a path planning method for an autonomously driven agricultural machine. [Background technology]

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

[0003] Patent Documents 1 and 2 disclose examples of a system in which an unmanned work vehicle automatically travels between two farm fields separated by a road. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-073602 [Patent Document 2] Patent Publication No. 2021-029218 Summary of the Invention [Problem to be solved by the invention]

[0005] The present disclosure provides a system and method for generating suitable routes for autonomously driving agricultural machines. [Means for solving the problem]

[0006] A path planning system according to an exemplary embodiment of the present disclosure is a path planning system for an agricultural machine that automatically travels within and outside a field. The path planning system includes a storage device that stores a map of an area including multiple fields and roads surrounding the multiple fields, and a processing device that generates a route for the agricultural machine on the map. The map includes attribute information that indicates at least one of whether each road is a farm road, whether each road runs along specific features, and whether each road can successfully receive satellite signals from GNSS satellites. When generating a route to a field or a route from the field to another location, the processing device generates at least one of a route that prioritizes farm roads, a route that prioritizes roads that run along the specific features, and a route that can successfully receive satellite signals, based on the attribute information, as the route for the agricultural machine.

[0007] A general or specific aspect 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. An apparatus may be composed of multiple devices. When an apparatus is composed of two or more devices, the two or more devices may be located in a single device or may be located separately in two or more separate devices. [Effects of the Invention]

[0008] According to an embodiment of the present disclosure, it is possible to generate a suitable route for an autonomously traveling agricultural machine. [Brief explanation of the drawings]

[0009] [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. [Figure 2] 1 is a side view schematically showing an example of a work vehicle and an implement coupled to the work vehicle. FIG. [Figure 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 that performs positioning using RTK-GNSS. [Figure 5] 3A and 3B are diagrams illustrating an example of an operation terminal and an operation switch group provided inside a cabin. [Figure 6] FIG. 2 is a block diagram illustrating an example of the hardware configuration of a management device and a terminal device. [Figure 7] FIG. 1 is a diagram schematically illustrating an example of a work vehicle that automatically travels along a target route in a farm field. [Figure 8] 10 is a flowchart illustrating an example of the operation of steering control 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. 10 is a diagram showing an example of a work vehicle at a position shifted to the right from the target route P. [Figure 9C] FIG. 10 is a diagram showing an example of a work vehicle at a position shifted to the left from a target route P. [Figure 9D] 10 is a diagram showing an example of a work vehicle facing in a direction inclined with respect to a target route P. FIG. [Figure 10] FIG. 1 is a diagram schematically 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. 10 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 13] FIG. 10 is a diagram illustrating an example of a GUI displayed on a display device. [Figure 14] 14 is a flowchart showing a route generation process in the example of FIG. 13. [Figure 15] FIG. 10 is a diagram showing another example of a GUI displayed on the display device. [Figure 16] FIG. 2 is a diagram showing an example of a map of an area in which a work vehicle travels. [Figure 17]FIG. 10 is a diagram showing an example of a route generated when the "farm road priority" mode is selected. [Figure 18] FIG. 10 is a diagram showing an example of a route generated when the "waterway priority" mode is selected. [Figure 19] FIG. 10 is a diagram showing another example of a map of an area in which a work vehicle travels. [Figure 20] FIG. 10 is a diagram showing an example of a route generated when the "GNSS-prioritized" mode is selected. [Figure 21] FIG. 1 is a diagram schematically illustrating an example of a situation in which a work vehicle is traveling near a row of trees. [Figure 22A] FIG. 4 is a diagram illustrating an example of the reception strength of a satellite signal. [Figure 22B] FIG. 10 is a diagram showing another example of the reception strength of satellite signals. [Figure 23] FIG. 10 is a diagram illustrating an example of a route generated by the management device when the "time priority" mode is selected. [Figure 24] FIG. 1 is a diagram illustrating an example of a global path. [Figure 25] FIG. 10 is a diagram illustrating an example of a table showing the correspondence between waiting locations and farm fields. [Figure 26] FIG. 10 is a diagram showing an example of a global route generated in a certain work day. [Figure 27] FIG. 10 is a diagram illustrating an example of a global path and a local path generated in an environment where obstacles are present. [Figure 28] 1 is a flowchart illustrating a method for path planning and cruise control. DETAILED DESCRIPTION OF THE INVENTION

[0010] (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 cultivators, vegetable transplanters, mowers, seed sowing machines, fertilizer applicators, and agricultural mobile robots. Not only can a work vehicle such as a tractor function alone as an "agricultural machinery," but the entire work vehicle and an implement attached to or towed by the work vehicle can also function as a single "agricultural machinery." Agricultural machinery performs agricultural work on the ground in a field, such as plowing, sowing, pest control, fertilizing, planting crops, or harvesting. These agricultural works are sometimes referred to as "ground work" or simply "work." Traveling while performing agricultural work by a vehicle-type agricultural machine is sometimes referred to as "work travel."

[0011] "Autonomous driving" refers to controlling the movement of an agricultural machine through the action of a control device, without manual operation by a driver. Agricultural machines that perform autonomous driving are sometimes called "autonomous agricultural machines" or "robotic agricultural machines." During autonomous driving, not only the movement of the agricultural machine but also the agricultural work operations (e.g., the operation of the implement) may be automatically controlled. When the agricultural machine is a vehicle-type machine, the movement of the agricultural machine through autonomous driving is referred to as "autonomous driving." The control device may control at least one of the following operations required for the movement of the agricultural machine: steering, adjusting the movement speed, and starting and stopping the movement. When controlling a work vehicle equipped with implements, the control device may control operations such as raising and lowering the implement, starting and stopping the operation of the implement, etc. Autonomous driving movement may include not only movement of the agricultural machine toward a destination along a predetermined route, but also movement of the agricultural machine following a tracking target. An autonomously driving agricultural machine may move partially based on user instructions. Furthermore, an autonomously driving agricultural machine may operate in a manual driving mode, in addition to an autonomous driving mode, in which the agricultural machine moves through manual operation by the driver. Steering an agricultural machine by the action of a control device, without manual operation, is called "automatic steering." Part or all of the control device may be external to the agricultural machine. Control signals, commands, data, and the like may be communicated 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 within a field or outside a field (e.g., on a road). During autonomous movement, the machine may detect obstacles and take action to avoid them.

[0012] A "work plan" is data that schedules one or more agricultural tasks to be performed by an agricultural machine. The work plan may include, for example, information indicating the order of agricultural tasks to be performed by the agricultural machine and the field on which each task will be performed. The work plan may also include information on the scheduled date and time for each task. A work plan that includes information on the scheduled date and time for each task is particularly referred to as a "work schedule" or simply a "schedule." The work schedule may include information on the scheduled start and / or end times for each task performed on each work day. The work plan or work schedule may include information for each task, such as the content of the task, the implements to be used, and / or the type and amount of agricultural materials to be used. Here, "agricultural materials" refers to materials used in agricultural tasks performed by an agricultural machine. Agricultural materials may also be simply referred to as "materials." Agricultural materials may include materials consumed in agricultural tasks, 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 task, or a processing device installed 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 the agricultural work of multiple agricultural machines. In this case, the management device may create a work plan that includes information about each agricultural work to be 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 and perform the scheduled agricultural work in accordance with the work plan.

[0013] An "environmental map" is data that represents the positions or areas of objects 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. An environmental map may also include information other than the positions of objects in the environment (e.g., attribute information and other information). Environmental maps include maps in various formats, such as point cloud maps or grid maps. Data for local or partial maps that are generated or processed in the process of constructing an environmental map are also referred to as a "map" or "map data."

[0014] "Farm road" means a road that is primarily used 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 (for example, 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.

[0015] "Feature" means something that exists on the ground. Examples of features include waterways, grass, trees, roads, fields, ditches, rivers, bridges, forests, mountains, rocks, buildings, and railroad tracks. Things that do not exist in the real world, such as boundaries, place names, building names, field names, and road names, are not included in the "feature" in this disclosure.

[0016] "GNSS satellite" refers to an artificial satellite in the 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 satellites are satellites in these positioning systems. Signals transmitted from GNSS satellites are called "satellite signals." A "GNSS receiver" is a device that receives radio waves transmitted from multiple GNSS satellites and performs positioning based on signals superimposed on the radio waves. "GNSS data" is data output from a GNSS receiver. GNSS data may be generated in a predetermined format, such as the NMEA-0183 format. GNSS data may include, for example, information indicating the reception status of satellite signals received from individual satellites. For example, GNSS data may include the identification number, elevation angle, azimuth angle, and values ​​indicating reception strength of each satellite from which a satellite signal is received. Reception strength is a numerical value indicating the strength of the received satellite signal. The reception strength may be expressed as a value such as the carrier-to-noise power density ratio (C / N0). The GNSS data may include position information of the GNSS receiver or agricultural machine calculated based on multiple received satellite signals. The position information may be expressed 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.

[0017] "Satellite signals can be received normally" means that satellite signals can be received stably enough that the reliability of positioning is not significantly reduced. The inability to receive satellite signals normally is sometimes referred to as "satellite signal reception interference." "Satellite signal reception interference" refers to a state in which the reliability of positioning is reduced compared to normal due to poor satellite signal reception. Reception interference can occur, for example, when the number of detected satellites is small (e.g., three or fewer), when the reception strength of each satellite signal is low, or when multipath interference occurs. Whether reception interference is occurring can be determined, for example, based on satellite-related information contained in GNSS data. For example, the presence or absence of reception interference can be determined based on the reception strength value for each satellite contained in the GNSS data or the DOP (Dilution of Precision) value, which indicates the satellite positioning status.

[0018] A "global path" refers to data on a path connecting a starting point to a destination point when an agricultural machine moves automatically, 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." A global path can 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."

[0019] A "local path" refers to a local path that can avoid obstacles and is generated sequentially when an agricultural machine automatically moves along a global path. Generating a local path is called local path planning or local path design. A 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. A local path may be defined by multiple waypoints along a portion of the global path. However, if an obstacle exists near the global path, waypoints may be set to bypass the obstacle. The length of the link between waypoints on a local path is shorter than the length of the link between 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 installed on the agricultural machine may generate the local path. In this case, the combination of the management device and the control device functions as a "processing device" that performs path planning. The agricultural machine's controller may function as a processor for both global and local path planning.

[0020] A "storage location" is a location provided for storing agricultural machinery. A storage location may be, for example, a location managed by a user of the agricultural machinery, or a location jointly operated by multiple users. A storage location may be, for example, a location set aside for storing agricultural machinery, 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.

[0021] A "waiting location" is a location provided for an agricultural machine to wait while not performing agricultural work. One or more waiting locations may be provided in an environment in which the agricultural machine performs autonomous driving. The storage location described above is an example of a waiting location. A waiting location may be a location jointly managed or used by multiple users. A waiting location may be, for example, a warehouse, garage, barn, parking lot, or other facility. A waiting location may be a warehouse, barn, garage, or parking lot at the home or business of a farmer who is different from the user of the agricultural machine. Multiple waiting locations may be scattered throughout the environment in which the agricultural machine moves. Work such as replacement or maintenance of agricultural machine parts or implements, or replenishment of materials, may be performed in a waiting location. In this case, parts, tools, or materials required for those work may be stored in the waiting location.

[0022] (Embodiment) Hereinafter, embodiments of the present disclosure will be described. However, more detailed descriptions than necessary may be omitted. For example, detailed descriptions of well-known matters and redundant descriptions of substantially identical configurations may be omitted. This is to avoid unnecessary redundancy in the following description and to facilitate understanding by those skilled in the art. Note that the inventors provide the accompanying drawings and the following description to enable those skilled in the art to fully understand the present disclosure, and do not intend for them to limit the subject matter described in the claims. In the following description, components having the same or similar functions are designated by the same reference numerals.

[0023] The following embodiments are examples, and the technology of the present disclosure is not limited to the following embodiments. For example, the numerical values, shapes, materials, steps, step order, display screen layout, etc. shown in the following embodiments are merely examples, and various modifications are possible as long as no technical contradiction occurs. Furthermore, one aspect can be combined with another aspect as long as no technical contradiction occurs.

[0024] The following mainly describes 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 agricultural machinery. 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 machinery.

[0025] FIG. 1 is a diagram illustrating 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 to remotely monitor the work vehicle 100. The management device 600 is a computer managed by a business operator that 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 FIG. 1 illustrates one work vehicle 100, the agricultural management system may include multiple work vehicles or other agricultural machinery.

[0026] The work vehicle 100 in this embodiment is a tractor. The work vehicle 100 can be fitted 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.

[0027] The work vehicle 100 has an automatic driving function. That is, the work vehicle 100 can travel by the operation of a control device, without manual operation. 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 within a field, but also outside the field (for example, on a road).

[0028] 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 causes the work vehicle 100 to travel automatically 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 travel 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 traveling automatically within a field. Furthermore, the work vehicle 100 can automatically travel along roads outside the field (e.g., farm roads or public roads) along a target route. When traveling automatically along roads outside the field, the work vehicle 100 travels while generating a local route along the target route that can avoid obstacles based on data output from sensing devices such as a camera or LiDAR sensor. Within the 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.

[0029] The management device 600 is a computer that manages agricultural work performed by the work vehicle 100. The management device 600 may 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 may, for example, create a work plan for the work vehicle 100 and generate a target route for the work vehicle 100 in accordance with the work plan. Alternatively, the management device 600 may generate the target route for the work vehicle 100 in response to a user's operation 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."

[0030] The management device 600 includes a storage device and a processing device. The storage device stores a map of an area including multiple fields and roads surrounding the fields. The processing device generates a route for the work vehicle 100 on the map. The map includes attribute information indicating at least one of whether each road is a farm road, whether each road runs along a specific feature such as a waterway or river, and whether each road can successfully receive satellite signals from GNSS satellites. When generating a route to a field or a route from a field to another location, the processing device generates at least one of the following routes for the work vehicle 100 based on the attribute information: a route that prioritizes farm roads, a route that prioritizes roads that run along specific features, and a route that prioritizes successful satellite signal reception. Through this processing, a route suitable for autonomous driving of the work vehicle 100 can be generated, as will be described in detail later.

[0031] The management device 600 generates target routes within the field and outside the field using different methods. The management device 600 generates target routes within the field based on information about the field. For example, the management device 600 can generate target routes within the field based on various information, such as pre-registered field outlines, field area, the location of field entrances and exits, the width of the work vehicle 100, the width of the implement, the type of work being performed, the type of crop being cultivated, the crop growing area, the crop growth conditions, or the spacing between crop rows or furrows. The management device 600 generates target routes within the field based on information input by the user using the terminal device 400 or another device, for example. The management device 600 generates routes within the field so as to cover the entire work area where work is to be performed, for example. On the other hand, the management device 600 generates target routes outside the field in accordance with a work plan or user instructions. 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 will be performed, the location of the entrance and exit to 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.

[0032] The management device 600 may be configured to generate a route that prioritizes a specific type of road according to a priority item selected by a user operating the terminal device 400. The specific type of road may be, for example, a road that follows a specific feature such as a farm road or a waterway, a road on which satellite signals can be received normally, or a road that allows the user to reach the destination in the shortest time. Details of a method for generating a route that prioritizes such a specific type of road will be described later.

[0033] 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 moves and performs farm work automatically based on this data.

[0034] 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 just the management device 600. For example, the control device of the work vehicle 100 may perform the global route design or the generation or editing of the environmental map.

[0035] The terminal device 400 is a computer used by a user located remotely from the work vehicle 100. While the terminal device 400 shown in FIG. 1 is a laptop computer, this is not limiting. The terminal device 400 may be a stationary computer such as a desktop personal computer (PC), or a mobile terminal such as a smartphone or tablet computer. The terminal device 400 may be used to remotely monitor or remotely operate the work vehicle 100. For example, the terminal device 400 can display on a display image captured by one or more cameras equipped on the work vehicle 100. The user can view the image to check the situation around the work vehicle 100 and send instructions to the work vehicle 100 to stop or start. The terminal device 400 can also display on a display a setting screen that allows the user to input information necessary to create a work plan for the work vehicle 100 (e.g., a schedule for each agricultural work). When the user inputs the necessary information on the setting screen and performs a send 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 will perform farm work, a storage location for the work vehicle 100, and one or more waiting locations where the work vehicle 100 will temporarily wait. The terminal device 400 may further have a function to display on the display a setting screen that allows the user to input information necessary to set a target route.

[0036] The configuration and operation of the system in this embodiment will be described in more detail below.

[0037] [1. Configuration] 2 is a side view that schematically shows an example of a work vehicle 100 and an implement 300 coupled to the work vehicle 100. The work vehicle 100 in this embodiment can operate in both a manual driving mode and an automatic driving mode. In the automatic driving mode, the work vehicle 100 can travel unmanned. The work vehicle 100 can be driven automatically both inside and outside a field.

[0038] As shown in Fig. 2, work vehicle 100 includes a vehicle body 101, a prime mover (engine) 102, and a transmission 103. Vehicle body 101 is provided with wheels 104 with tires and a cabin 105. Wheels 104 include a pair of front wheels 104F and a pair of rear wheels 104R. Inside cabin 105 are provided a driver's seat 107, a steering device 106, an operation terminal 200, and a group of switches for operation. When work vehicle 100 travels through a field, one or both of front wheels 104F and rear wheels 104R may be replaced with wheels (crawlers) equipped with tracks rather than with tires.

[0039] The work vehicle 100 is equipped with a plurality of sensing devices that sense the surroundings of the work vehicle 100. In the example of Figure 2, the sensing devices include a plurality of cameras 120, a LiDAR sensor 140, and a plurality of obstacle sensors 130.

[0040] Cameras 120 may be installed, for example, on the front, rear, left and right sides of work vehicle 100. Cameras 120 capture images of the environment around work vehicle 100 and generate image data. Images acquired by cameras 120 may be transmitted to terminal device 400 for remote monitoring. These images may be used to monitor work vehicle 100 during unmanned operation. Cameras 120 may also be used to generate images for recognizing surrounding features or obstacles, white lines, signs, or markings when work vehicle 100 travels on roads outside of fields (farm roads or public roads).

[0041] In the example of FIG. 2, the LiDAR sensor 140 is disposed on the lower front side of the vehicle body 101. The LiDAR sensor 140 may be disposed in another location. While the work vehicle 100 is traveling mainly outside the field, the LiDAR sensor 140 repeatedly outputs sensor data indicating the distance and direction to each measurement point of an object in the surrounding environment, or the two-dimensional or three-dimensional coordinate values ​​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 estimate the self-position of the work vehicle 100 by matching the sensor data with an environmental map. The control device can further detect objects such as obstacles present around the work vehicle 100 based on the sensor data, and generate a local path that the work vehicle 100 should actually travel along the global path. The control device can also generate or edit an environmental map using an algorithm such as SLAM (Simultaneous Localization and Mapping). Work vehicle 100 may be equipped with multiple LiDAR sensors positioned at different locations and with different orientations.

[0042] The multiple obstacle sensors 130 shown in FIG. 2 are provided at the front and rear of the cabin 105. The obstacle sensors 130 may also be located in other locations. For example, one or more obstacle sensors 130 may be provided at any position on the side, front, and rear of the vehicle body 101. The obstacle sensors 130 may include, for example, a laser scanner or ultrasonic sonar. The obstacle sensors 130 are 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.

[0043] 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 that receives signals from GNSS satellites and a processor that calculates the position of the work vehicle 100 based on the signals received by the antenna. The GNSS unit 110 receives satellite signals transmitted from multiple GNSS satellites and performs positioning based on the satellite signals. In this embodiment, the GNSS unit 110 is provided on top of the cabin 105, but it may be provided in another location.

[0044] The GNSS unit 110 may include an inertial measurement unit (IMU). Signals from the IMU can be used to complement position data. The IMU can measure the tilt and minute movements of the work vehicle 100. By complementing position data based on satellite signals with data acquired by the IMU, positioning performance can be improved.

[0045] The control device of the work vehicle 100 may use, in addition to the positioning results from the GNSS unit 110, sensing data acquired by sensing devices such as the camera 120 or LiDAR sensor 140 for positioning. If there are features that function as characteristic points in the environment in which the work vehicle 100 is traveling, such as farm roads, forest roads, public 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 that has been stored in advance in a storage device. By using the data acquired by the camera 120 or LiDAR sensor 140 to correct or complement position data based on satellite signals, the position of the work vehicle 100 can be determined with higher accuracy.

[0046] 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 travel.

[0047] 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 steerable 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 assisting force to change 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 electric motor under control of a control device arranged inside the work vehicle 100.

[0048] 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 allows the implement 300 to be attached to and detached from the work vehicle 100. The coupling device 108 can raise and lower the three-point link using, for example, a hydraulic device, thereby changing the position or attitude of the implement 300. Power can also be sent from the work vehicle 100 to the implement 300 via the universal joint. The work vehicle 100 can pull the implement 300 and cause the implement 300 to perform a predetermined task. The coupling device may be provided at the front of the vehicle body 101. In this case, the implement can be connected to the front of the work vehicle 100.

[0049] 2 is a rotary tiller, the implement 300 is not limited to a rotary tiller. For example, any implement such as a seeder (seed sowing machine), a spreader (fertilizer applicator), a transplanter, a mower (grass cutter), a rake, a baler (grass collector), a harvester (harvesting machine), a sprayer, or a harrow can be connected to the work vehicle 100 and used.

[0050] 2 is capable of being driven by a driver, but may also be capable of being driven only unmanned. In that case, components required only for driven 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.

[0051] 3 is a block diagram showing an example configuration of the work vehicle 100 and the implement 300. The work vehicle 100 and the implement 300 can communicate with each other via a communication cable included in the coupling device 108. The work vehicle 100 can communicate with the terminal device 400 and the management device 600 via the network 80.

[0052] In the example of FIG. 3 , the work vehicle 100 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 group of sensors 150 that detect the operating state of the work vehicle 100, a control system 160, a communication device 190, a group of operation switches 210, a buzzer 220, and a drive unit 240. These components are communicatively connected to 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 group of sensors 150 includes a steering wheel sensor 152, a turning angle sensor 154, and an axle sensor 156. The control system 160 includes a memory device 170 and a control device 180. The control device 180 includes multiple electronic control units (ECUs) 181 to 186. Implement 300 includes a drive unit 340, a control unit 380, and a communication unit 390. Note that Fig. 3 shows components that are relatively highly related to the operation of the autonomous driving by work vehicle 100, and does not show other components.

[0053] The GNSS receiver 111 in the GNSS unit 110 receives satellite signals transmitted from multiple 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, the 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, as a value such as the 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 multiple received satellite signals, and information indicating the reliability of the position information. The position information may be represented, for example, by latitude, longitude, and height above mean sea level. The reliability of the position information may be represented, for example, by a DOP value indicating the satellite configuration.

[0054] 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 using RTK-GNSS. Positioning using RTK-GNSS uses satellite signals transmitted from multiple GNSS satellites 50 as well as correction signals transmitted from a reference station 60. The reference station 60 may be installed near the field where the work vehicle 100 will be traveling (for example, within 10 km of the work vehicle 100). The reference station 60 generates correction signals, for example in RTCM format, based on the satellite signals received from the multiple GNSS satellites 50 and transmits them to the GNSS unit 110. The RTK receiver 112 includes an antenna and a modem and receives the correction signals transmitted from the reference station 60. The processing circuit 116 of the GNSS unit 110 corrects the positioning results obtained by the GNSS receiver 111 based on the correction signals. 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 obtained through highly accurate positioning using RTK-GNSS. The GNSS unit 110 calculates the position of the work vehicle 100, for example, at a frequency of approximately 1 to 10 times per second.

[0055] The positioning method is not limited to RTK-GNSS, and any positioning method (such as interferometric positioning or differential 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 this case, the GNSS unit 110 does not need to be equipped with the RTK receiver 112.

[0056] Even when RTK-GNSS is used, in places where correction signals 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 signals 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 camera 120 with a highly accurate environmental map.

[0057] 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 also include a direction 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, velocity, 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 signals output from the IMU 115 in addition to the satellite signals and correction signals. The signals output from the IMU 115 can be used to correct or complement the position calculated based on the satellite signals and correction signals. The IMU 115 outputs signals at a higher frequency than the GNSS receiver 111. Using these high-frequency signals, the processing circuit 116 can measure the position and orientation of the work vehicle 100 at a higher frequency (e.g., 10 Hz or higher). A three-axis acceleration sensor and a three-axis gyroscope may be provided separately instead of the IMU 115. The IMU 115 may be provided as a device separate from the GNSS unit 110.

[0058] The camera 120 is an imaging device that captures images of the environment surrounding 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 images of the environment surrounding 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 higher. 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 surrounding 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 installed at different positions on the work vehicle 100, or a single camera may be installed. A visible light camera that generates a visible light image and an infrared camera that generates an infrared image may be provided separately. Both a visible light camera and an infrared camera may be provided as cameras that generate images for surveillance. The infrared camera can also be used to detect obstacles at night.

[0059] 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. The obstacle sensor 130 outputs a signal indicating the presence of an obstacle when an object is present closer than a predetermined distance from the obstacle sensor 130. Multiple obstacle sensors 130 may be provided at different positions on the work vehicle 100. For example, multiple laser scanners and multiple ultrasonic sonars may be arranged at different positions on 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.

[0060] 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 the steered wheels. The measurement values ​​from the steering wheel sensor 152 and the turning angle sensor 154 are used for steering control by the control device 180.

[0061] The axle sensor 156 measures the rotational speed of the axle connected to the wheel 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 a numerical value that indicates, for example, 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.

[0062] The drive device 240 includes various devices necessary for the travel of the work vehicle 100 and the driving of the implement 300, such as the prime mover 102, transmission 103, steering device 106, and coupling device 108 described above. The prime mover 102 may be equipped with an internal combustion engine such as a diesel engine. The drive device 240 may be equipped with an electric motor for traction instead of or in addition to the internal combustion engine.

[0063] The buzzer 220 is an audio output device that emits a warning sound to notify of an abnormality. For example, the buzzer 220 emits the warning sound when an obstacle is detected during automatic driving. The buzzer 220 is controlled by the control device 180.

[0064] 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 on a global route (target route) for autonomous driving. The environmental map includes information on multiple fields in which the work vehicle 100 will perform agricultural work and the roads in their surroundings. The environmental map and target route may be generated by a processing device (i.e., a processor) in the management device 600. Note that the control device 180 in this embodiment may have a function for generating or editing the environmental map and target route. The control device 180 can edit the environmental map and target route obtained from the management device 600 according to the travel environment of the work vehicle 100. The storage device 170 also stores work plan data received by the communication device 190 from the management device 600. The work plan includes information regarding multiple agricultural tasks to be performed by the work vehicle 100 over multiple work days. The work plan may be, for example, work schedule data including information on the scheduled times for each agricultural task to be performed by the work vehicle 100 on each work day. The storage device 170 also stores computer programs that cause each ECU in the control device 180 to perform 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 also be sold as commercial software.

[0065] The control device 180 includes a plurality of ECUs, such as an ECU 181 for speed control, an ECU 182 for steering control, an ECU 183 for implement control, an ECU 184 for automatic driving control, an ECU 185 for route generation, and an ECU 186 for map generation.

[0066] The ECU 181 controls the speed of the work vehicle 100 by controlling the prime mover 102 , the transmission 103 , and the brakes included in the drive unit 240 .

[0067] 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 value of the steering wheel sensor 152 .

[0068] The ECU 183 controls the operation of the three-point link and PTO shaft included in the coupling device 108, etc., in order to cause the implement 300 to perform a desired operation. The ECU 183 also generates a signal that controls the operation of the implement 300, and transmits the signal from the communication device 190 to the implement 300.

[0069] The ECU 184 performs calculations and controls to achieve 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 determines 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. Within a farm field, the ECU 184 may determine the position of the work vehicle 100 based solely on data output from the GNSS unit 110. The ECU 184 may also 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 of a 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, ECU 184 may estimate the position of work vehicle 100 by matching data output from LiDAR sensor 140 or camera 120 with an environmental map. During autonomous driving, ECU 184 performs calculations necessary for work vehicle 100 to travel along a target path or a local path based on the estimated position of work vehicle 100. ECU 184 sends a speed change command to ECU 181 and a steering angle change command to ECU 182. In response to the speed change command, ECU 181 changes the speed of work vehicle 100 by controlling prime mover 102, transmission 103, or brakes. In response to the steering angle change command, ECU 182 changes the steering angle by controlling steering device 106.

[0070] ECU 185 sequentially generates local paths that can avoid obstacles while work vehicle 100 is traveling along the target path. While work vehicle 100 is traveling, ECU 185 recognizes obstacles that exist around work vehicle 100 based on data output from camera 120, obstacle sensor 130, and LiDAR sensor 140. ECU 185 generates local paths that avoid the recognized obstacles.

[0071] ECU 185 may have a function for performing global route design instead of management device 600. In this case, ECU 185 determines the destination of work vehicle 100 based on the work plan stored in storage device 170, and determines a target route from the start point of work vehicle 100's movement to the destination point. ECU 185 can create, for example, a route that will allow the work vehicle to reach the destination in the shortest time as the target route based on an environmental map that includes road information stored in storage device 170. Alternatively, ECU 185 may generate, as the target route, a route that prioritizes specific types of roads (for example, roads that follow specific features such as farm roads or waterways, or roads that have good reception of satellite signals from GNSS satellites) based on attribute information of each road included in the environmental map.

[0072] 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. The following describes the operation when the ECU 186 generates an environmental map. 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 sequentially generated point cloud data using an algorithm such as SLAM. The environmental map generated in this manner is a highly accurate three-dimensional map and can be used by the ECU 184 for self-localization estimation. A two-dimensional map used for global path planning can be generated based on this three-dimensional map. In this specification, both the 3D map used for self-localization and the 2D map used for global route planning are referred to as “environment maps.” ECU 186 can also edit the map by adding various attribute information to the map, such as features (e.g., waterways, rivers, grass, trees, etc.) recognized based on data output from camera 120 or LiDAR sensor 140, road type (e.g., whether it is a farm road), road surface condition, or road passability.

[0073] Through the operation of these ECUs, control device 180 realizes autonomous driving. During autonomous driving, control device 180 controls drive device 240 based on the measured or estimated position of work vehicle 100 and the generated route. In this way, control device 180 can cause work vehicle 100 to travel along the target route.

[0074] The multiple ECUs included in the control device 180 can communicate with each other in accordance with a vehicle bus standard such as CAN (Controller Area Network). Instead of CAN, a faster communication method such as Automotive Ethernet (registered trademark) may be used. 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 on-board 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.

[0075] The communication device 190 includes circuits for communicating with the implement 300, the terminal device 400, and the management device 600. The communication device 190 includes circuits for transmitting and receiving signals compliant with ISOBUS standards, such as ISOBUS-TIM, between the communication device 390 of the implement 300. This allows the implement 300 to perform desired operations and acquire information from the implement 300. The communication device 190 may further include an antenna and communication circuits for transmitting and receiving signals via the network 80 between the communication devices of the terminal device 400 and the management device 600. 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 also have a function for communicating with a mobile device used by a supervisor near the work vehicle 100. Communication between such mobile terminals may be performed in accordance with any wireless communication standard, such as Wi-Fi (registered trademark), cellular mobile communication such as 3G, 4G or 5G, or Bluetooth (registered trademark).

[0076] The operation terminal 200 is a terminal through which a user performs operations related to the travel of the work vehicle 100 and the operation of the implement 300, and is also referred to as a virtual terminal (VT). The operation terminal 200 may include a display device such as a touch screen and / or one or more buttons. The display device may be, for example, a liquid crystal display or an organic light-emitting diode (OLED) display. By operating the operation terminal 200, a user can perform various operations, such as switching the autonomous driving mode on / off, recording or editing an environmental map, setting a target route, and switching the implement 300 on / off. At least some of these operations can also be achieved by operating the operation switch group 210. The operation terminal 200 may be configured to be detachable from the work vehicle 100. A user located remotely from the work vehicle 100 may operate the detached operation terminal 200 to control the operation of the work vehicle 100. Instead of the operation terminal 200, the user may control the operation of the work vehicle 100 by operating a computer, such as a terminal device 400, on which necessary application software is installed.

[0077] 5 is a diagram showing an example of operation terminal 200 and operation switch group 210 provided inside cabin 105. Switch group 210 including a plurality of switches that can be operated by the user is arranged inside cabin 105. Operation switch group 210 may include, for example, a switch for selecting the gear stage of the main transmission or auxiliary transmission, a switch for switching between automatic driving mode and manual driving mode, a switch for switching between forward and reverse, and a switch for raising and lowering implement 300. Note that if work vehicle 100 only performs unmanned operation and does not have the function of manned operation, work vehicle 100 does not need to be equipped with operation switch group 210.

[0078] The drive device 340 in the implement 300 shown in FIG. 3 performs the operations required for the implement 300 to perform a predetermined task. The drive device 340 includes devices appropriate for the application of the implement 300, such as a hydraulic device, an electric motor, or a pump. The control device 380 controls the operation of the drive device 340. The control device 380 causes the drive device 340 to perform various operations in response to signals transmitted from the work vehicle 100 via the communication device 390. In addition, a signal appropriate for the state of the implement 300 can also be transmitted from the communication device 390 to the work vehicle 100.

[0079] 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.

[0080] The management device 600 includes a storage device 650, a processor 660, a read-only memory (ROM) 670, a random access memory (RAM) 680, and a communication device 690. These components are communicatively connected to each other via a bus. The management device 600 manages the schedule of agricultural work performed in the field by the work vehicle 100 and can function as a cloud server that supports agriculture by utilizing the data it manages. A user can input information necessary for creating a work plan using the terminal device 400 and upload that information to the management device 600 via the network 80. The management device 600 can create a schedule for agricultural work, i.e., a work plan, based on that information. The management device 600 can also generate or edit an environmental map and perform global path planning for the work vehicle 100. The environmental map may be distributed from a computer external to the management device 600.

[0081] 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 in accordance with communication standards such as IEEE1394 (registered trademark) or Ethernet (registered trademark). The communication device 690 may also perform wireless communication in accordance with the Bluetooth (registered trademark) standard or the Wi-Fi standard, or cellular mobile communication such as 3G, 4G, or 5G.

[0082] 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), or an application specific standard product (ASSP). 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.

[0083] The ROM 670 is, for example, a writable memory (e.g., a PROM), a rewritable memory (e.g., a 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, but may be a collection of multiple storage media. Part of the collection of multiple storage media may be removable memory.

[0084] The RAM 680 provides a working area for temporarily loading the control program stored in the ROM 670 at boot time. The RAM 680 does not have to be a single storage medium, but may be a collection of multiple storage media.

[0085] The storage device 650 mainly functions as 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 device.

[0086] 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 communicatively connected to one another via a bus. The input device 420 is a device for converting user instructions 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 therefore their description will be omitted.

[0087] [2. Operation] Next, the operations of the work vehicle 100, the terminal device 400, and the management device 600 will be described.

[0088] [2-1.Automatic driving operation] First, an example of the operation of autonomous driving by the work vehicle 100 will be described. The work vehicle 100 in this embodiment can travel autonomously both inside and outside the field. In the field, the work vehicle 100 drives the implement 300 to perform predetermined agricultural work while traveling along a predetermined target route. If the obstacle sensor 130 detects an obstacle while traveling in the field, the work vehicle 100 stops traveling, emits a warning sound from the buzzer 220, and transmits a warning signal to the terminal device 400. In the field, the position of the work vehicle 100 is determined mainly based on data output from the GNSS unit 110. On the other hand, outside the field, the work vehicle 100 travels autonomously along a target route set on a farm road or public road outside the field. While traveling outside the field, the work vehicle 100 travels while performing local route planning based on data acquired by the camera 120 or the LiDAR sensor 140. When the work vehicle 100 detects an obstacle outside the field, it either avoids the obstacle or stops on the spot. Outside the field, the position of the work vehicle 100 is estimated based on the positioning data output from the GNSS unit 110 as well as the data output from the LiDAR sensor 140 or the camera 120.

[0089] Below, we will first explain the operation of the work vehicle 100 when it travels automatically within a field. The operation of the work vehicle 100 when it travels automatically outside a field, and the processing of global route design and local route design outside a field will be described later.

[0090] FIG. 7 is a diagram schematically illustrating an example of a work vehicle 100 that automatically travels through a field along a target route. In this example, the field includes a work area 72 where the work vehicle 100 performs work using an implement 300, and a headland 74 located near the outer periphery of the field. The user can set in advance which areas of the field on the map correspond to the work area 72 or the headland 74. 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 routes P1 are located within the work area 72, and the turning routes P2 are located within the headland 74. Although each main route P1 shown in FIG. 7 is a straight route, each main route P1 may also include curved portions. The main path P1 can be automatically generated, for example, by a user viewing a map of the field displayed on the operation terminal 200 or the terminal device 400 and specifying two points near the edge of the field (points A and B in FIG. 7). In this case, multiple main paths P1 are set parallel to a line segment connecting points A and B specified by the user, and a target path within the field is generated by connecting these main paths P1 with a turning path P2. The dashed line in FIG. 7 represents the working width of the implement 300. The working width is set in advance and recorded in the storage device 170. The working width can be set and recorded by the user operating the operation terminal 200 or the terminal device 400. Alternatively, the working width can be automatically recognized and recorded when the implement 300 is connected to the work vehicle 100. The spacing between the multiple main paths P1 can be set to match the working width. The target path can be created based on user operation before automatic driving begins. The target route can be created so as to cover the entire work area 72 in a farm field, for example. 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 target route can be determined in any way.

[0091] Next, an example of control by the control device 180 during automatic operation in a farm field will be described.

[0092] 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, for example, a preset speed. While the work vehicle 100 is traveling, the control device 180 acquires data indicating the position of the work vehicle 100 generated by the GNSS unit 110 (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 calculated position deviation exceeds a preset threshold (step S123). If the deviation exceeds the threshold, the control device 180 changes the steering angle by changing the control parameters of the steering device included in the drive device 240 so as to reduce the deviation. If the deviation does not exceed the threshold value in step S123, the operation of step S124 is skipped. In the following step S125, the control device 180 determines whether or not a command to end the operation has been received. A command to end the operation may be issued, for example, when a user remotely instructs the work vehicle 100 to stop autonomous driving, or when the work vehicle 100 reaches its destination. If a command to end the operation has not been issued, the process returns to step S121, and the same operation is performed 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.

[0093] 8, the control device 180 controls the drive 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 deviation in heading. For example, when the heading 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 the control parameters (e.g., steering angle) of the steering device of the drive device 240 in accordance with the deviation.

[0094] An example of steering control by the control device 180 will be described in more detail below with reference to FIGS. 9A to 9D.

[0095] FIG. 9A is a diagram showing an example of a work vehicle 100 traveling along a target route P. FIG. 9B is a diagram showing an example of a work vehicle 100 shifted to the right from the target route P. FIG. 9C is a diagram showing an example of a work vehicle 100 shifted to the left from the target route P. FIG. 9D is a diagram showing an example of a 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 located at the position where the GNSS antenna is installed on the cabin, but the position of the reference point is arbitrary. θ is an angle representing the measured orientation of the work vehicle 100. In the examples shown, the target route P is parallel to the Y axis, but generally, the target route P is not necessarily parallel to the Y axis.

[0096] 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 unchanged.

[0097] As shown in Fig. 9B, when the position of work vehicle 100 has shifted to the right from target route P, control device 180 changes the steering angle so that the traveling direction of work vehicle 100 leans leftward and approaches route P. At this time, the speed may also be changed in addition to the steering angle. The magnitude of the steering angle can be adjusted, for example, according to the magnitude of position deviation Δx.

[0098] As shown in Fig. 9C, when the position of work vehicle 100 has shifted to the left from target route P, control device 180 changes the steering angle so that the traveling direction of work vehicle 100 tilts to the right and approaches route P. In this case, too, the speed may be changed in addition to the steering angle. The amount of change in the steering angle may be adjusted, for example, according to the magnitude of position deviation Δx.

[0099] As shown in FIG. 9D , when the position of the work vehicle 100 is not significantly deviated from the target route P but the heading is different from the direction of the target route P, the control device 180 changes the steering angle to reduce the azimuth deviation Δθ. 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 greater the amount of change in the steering angle according to the azimuth deviation Δθ. When the absolute value of the position deviation Δx is large, the steering angle will be changed significantly to return to the route P, which inevitably increases the absolute value of the azimuth deviation Δθ. 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) used to determine the steering angle.

[0100] Control techniques such as PID control or MPC control (model predictive control) can be applied to the steering control and speed control of work vehicle 100. By applying these control techniques, it is possible to smooth the control that brings work vehicle 100 closer to target path P.

[0101] If an obstacle is detected by one or more obstacle sensors 130 while the work vehicle 100 is traveling, the control device 180 will 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 control the drive device 240 to avoid the obstacle.

[0102] The work vehicle 100 in this embodiment is capable of autonomous driving not only in farm fields but also outside of farm fields. Outside of farm fields, the control device 180 can detect objects (e.g., other vehicles or pedestrians) that are located relatively far from the work vehicle 100 based on data output from the camera 120 or the LiDAR sensor 140. The control device 180 generates a local route to avoid the detected object, and performs speed control and steering control along the local route, thereby realizing autonomous driving on roads outside of farm fields.

[0103] In this manner, the work vehicle 100 in this embodiment can autonomously travel unmanned within and outside a field. FIG. 10 is a diagram schematically illustrating an example of a situation in which multiple work vehicles 100 are autonomously traveling within a field 70 and on a road 76 outside the field 70. An environmental map and a target route for an area including multiple fields and their surrounding roads are stored in the storage device 170. The environmental map and 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 with the implement 300 raised while sensing the surroundings using sensing devices such as the camera 120 and the LiDAR sensor 140. While traveling, the control device 180 sequentially generates local routes and causes the work vehicle 100 to travel along the local routes. This enables autonomous traveling while avoiding obstacles. The target route may be changed during travel depending on the situation.

[0104] [2-2. Creating a work plan] In this embodiment, the work vehicle 100 automatically moves between fields and performs agricultural work in each field according to a work plan and target route created by the management device 600. The work plan includes information about one or more agricultural works to be performed by the work vehicle 100. For example, the work plan includes information about one or more agricultural works to be performed by the work vehicle 100 and the fields on which each agricultural work will be performed. The work plan may also include information about multiple agricultural works to be performed by the work vehicle 100 over multiple work days and the fields on which each agricultural work will be performed. More specifically, the work plan may be a database containing work schedule information indicating which agricultural machine will perform which agricultural work in which field at what time for each work day. An example of a case in which the work plan is data on such a work schedule will be described below. The work plan may be created by the processor 660 of the management device 600 based on information entered by the user using the terminal device 400. An example of a method for creating a work schedule will be described below.

[0105] 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 the setting screen 760 shown in Fig. 11. The user can input information necessary for creating a work schedule on this setting screen 760.

[0106] 11 shows an example of a settings screen 760 for when tilling with fertilizer application is performed as agricultural work in a rice field. The settings screen 760 is not limited to the one shown in the figure and can be modified as appropriate. The settings 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.

[0107] 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 performed.

[0108] The crop plan selection unit 763 displays a list of names of crop plans created in advance. The user can select a desired crop plan from the list. Crop plans are created in advance for each type and variety of crop and are recorded in the storage device 650 of the management device 600. A crop plan is a plan that determines which crops will be cultivated (i.e., planted) in which fields. A crop plan is created by a manager who manages multiple fields before planting crops in the fields. In the example of Figure 11, a crop plan for the rice variety "Koshihibuki" is selected. In this case, the content set on the setting screen 760 is associated with the crop plan for "Koshihibuki."

[0109] The field selection section 764 displays the fields on the map. 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.

[0110] The work selection section 765 displays a plurality of farming works required to cultivate the selected crop. The user can select one farming work from the plurality of farming works. In the example of FIG. 11, "plowing" is selected from the plurality of farming works. In this case, the selected "plowing" is set as the farming work to be performed.

[0111] The worker selection section 766 displays workers who have been 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 worker does not actually perform the agricultural work, but may simply remotely monitor the agricultural work performed by the agricultural machine.

[0112] 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 the farm work to be performed.

[0113] The machine selection unit 768 is a section for setting the agricultural machine to be used in the agricultural work. The machine selection unit 768 may display, for example, the type or model of the agricultural machine previously registered by the management device 600, and the type or model of the implement that can be used. The user can select a specific machine from the displayed machines. In the example of FIG. 11, an implement with the model number "NW4511" has been selected. In this case, that implement is set as the machine to be used in the agricultural work.

[0114] 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.

[0115] The dispersion amount setting section 770 displays a numerical value input from the input device 420. The input numerical value is set as the dispersion amount.

[0116] When the crop plan, field, agricultural 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. Based on the received information, the processor 660 creates a schedule of agricultural work to be performed by each agricultural machine and stores the schedule in the storage device 650.

[0117] The information on agricultural work managed by the management device 600 is not limited to the information described 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 also be set.

[0118] FIG. 12 is a diagram showing an example of an agricultural work schedule (i.e., a work plan) created by the management device 600. The schedule in this example includes information indicating, for each registered agricultural machine, the date and time the agricultural work will be performed, the field, the work content, and the implement to be used. In addition to the information shown in FIG. 12, the schedule may also include other information depending on the work content, such as the type of pesticide or the amount of pesticide to be sprayed. In accordance with this schedule, the processor 660 of the management device 600 issues agricultural work instructions 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 this case, the control device 180 may autonomously start operating according to the schedule stored in the storage device 170.

[0119] In this embodiment, the work plan is created by management device 600, but the work plan may also be created by another device. For example, processor 460 of terminal device 400 or control device 180 in work vehicle 100 may have a function for generating or updating a work plan.

[0120] [2-3. Global Path Planning] Next, the operation of the route planning in this embodiment will be described in more detail.

[0121] In this embodiment, the management device 600 and the control system 160 of the work vehicle 100 work together to function as a route planning system for the work vehicle 100. The storage device 650 stores a map including multiple fields and roads in the vicinity of those fields. The map includes attribute information indicating at least one of the following: whether each road is a farm road, whether each road runs along a specific feature such as a waterway, and whether each road is capable of successfully receiving satellite signals from GNSS satellites. The processor 660 of the management device 600 functions as a processing device that generates a route for the work vehicle 100 on the map. The processor 660 can be configured to generate a route for the work vehicle 100 outside the field according to a previously created farm work schedule. When generating a route to a farm field or a route from the farm field to another location, the processor 660 generates at least one of the following routes for the work vehicle 100: a route that prioritizes farm roads, a route that prioritizes roads that follow specific features, and a route that prioritizes roads on which satellite signals can be received normally, based on the attribute information of each road. This makes it possible to generate a route suitable for autonomous driving of the work vehicle 100. Note that part or all of the route generation process executed by the management device 600 may be executed by the ECU 185 in the control device 180 of the work vehicle 100. In this case, the combination of the ECU 185 and the management device 600 functions as a processing device that generates a route for the work vehicle 100. Also, part or all of the route generation process executed by the management device 600 may be executed by the operation terminal 200 of the work vehicle 100. In this case, the combination of the operation terminal 200 and the management device 600 functions as a processing device that generates a route for the work vehicle 100.

[0122] It is preferable that an autonomously traveling work vehicle 100 preferentially travels on farm roads with little traffic over public roads with a lot of general vehicles or pedestrians. Furthermore, when autonomously traveling outside a field, the work vehicle 100 can be configured to travel while estimating its own position based on data output from at least one of the LiDAR sensor 140 and the camera 120. In this case, it is preferable that the work vehicle 100 preferentially travels on roads that run along specific features that can serve as landmarks for self-position estimation (e.g., waterways, rivers, tree lines, buildings, etc.). Furthermore, if the work vehicle 100 also uses data output from the GNSS unit 110 for self-position estimation, it is preferable that the work vehicle 100 preferentially travels on roads where it can successfully receive satellite signals from GNSS satellites.

[0123] For this reason, in this embodiment, the management device 600 generates at least one of the following routes for the work vehicle 100 based on the attribute information of each road on the map: a route that prioritizes farm roads, a route that prioritizes roads that follow specific features, and a route that prioritizes roads on which satellite signals can be received normally. This makes it possible to generate a route that is more suitable for autonomous driving than simply selecting a route that minimizes travel distance or travel time.

[0124] The management device 600 may have the function of generating all of a route that prioritizes farm roads, a route that prioritizes roads that follow specific features, and a route that prioritizes roads on which satellite signals can be received normally, or it may generate only one or two of these routes. Alternatively, the management device 600 may be configured to generate a route that prioritizes farm roads, roads that follow specific features, and roads on which satellite signals can be received normally. The management device 600 may select one route from the multiple generated routes based on a predetermined criterion and determine it as the route for the work vehicle 100. For example, the management device 600 may display the multiple generated routes on the display device 430 of the terminal device 400 and determine a route selected by the user from these routes as the route for the work vehicle 100.

[0125] The management device 600 may generate a route in a mode selected by the user from a plurality of modes including at least one of a first mode in which a route is generated by preferentially selecting farm roads, a second mode in which a route is generated by preferentially selecting roads that follow specific features, and a third mode in which a route is generated by preferentially selecting roads on which satellite signals can be received normally. The plurality of modes may further include a fourth mode in which a route is generated so as to minimize the travel time or travel distance of the work vehicle 100. The management device 600 may display a graphical user interface (GUI) on the display device 430 of the terminal device 400, which allows the user to select one mode from the plurality of modes, and generate a route in the selected mode.

[0126] Fig. 13 is a diagram showing an example of a GUI displayed on the display device 430. In this example, a GUI is displayed that allows the user to select one of three modes: "farm road priority," "waterway priority," and "GNSS priority." In the example of Fig. 13, "farm road priority" corresponds to the first mode, "waterway priority" corresponds to the second mode, and "GNSS priority" corresponds to the third mode. Fig. 13 shows, as an example, a state in which "farm road priority" has been selected.

[0127] The management device 600 automatically generates a route from the start point to the destination point of the automated driving of the work vehicle 100. The start point and destination point can be set in advance by the user, or can be set by the management device 600 in accordance with a work plan created in advance. After the start point and destination point are set, the management device 600 generates a route from the start point to the destination point at a predetermined timing before the automated driving starts.

[0128] When "Farm road priority" is selected in the GUI shown in FIG. 13, the management device 600 generates a route by giving priority to farm roads. On the other hand, when "Waterway priority" is selected, the management device 600 generates a route by giving priority to roads along waterways. A waterway is an example of a specific feature that functions as a landmark for self-localization estimation using the LiDAR sensor 140 or the camera 120. In addition to or instead of a waterway, a mode may be provided for generating a route by giving priority to roads along other types of features. When "GNSS priority" is selected, the management device 600 generates a route by giving priority to roads on which satellite signals from GNSS satellites can be received normally.

[0129] An example of the route generation process performed by the management device 600 will now be described with reference to Fig. 14. It is assumed that the starting point and destination point for the automated driving of the work vehicle 100 have already been set.

[0130] FIG. 14 is a flowchart showing the route generation process by the management device 600 in the example of FIG. 13. In this example, first, in step S201, the management device 600 determines whether any mode has been selected by the user. When the user selects one of "farm road priority," "waterway priority," and "GNSS priority" shown in FIG. 13 and presses "OK," the process proceeds to step S202. In step S202, the management device 600 determines the selected mode. If "farm road priority" is selected, the process proceeds to step S203. If "waterway priority" is selected, the process proceeds to step S204. If "GNSS priority" is selected, the process proceeds to step S205. In step S203, the management device 600 generates a route for the work vehicle 100 that prioritizes farm roads. In step S204, the management device 600 generates a route for the work vehicle 100 that prioritizes roads along waterways. In step S205, the management device 600 generates a route for the work vehicle 100 that prioritizes roads where satellite signals can be received normally. Specific examples of the processing in steps S203, S204, and S205 will be described later. After generating the route, the management device 600 performs step S 206 Then, the generated route is stored in the storage device 650.207 In the above process, the management device 600 transmits the generated route to the work vehicle 100 at a predetermined timing. The work vehicle 100 performs autonomous driving according to the generated route and the work schedule acquired in advance.

[0131] 13 and 14, the management device 600 generates a route in one mode selected by the user from three modes: "farm road priority," "waterway priority," and "GNSS priority." Alternatively, the system may be configured to allow the user to select a desired priority item from more modes.

[0132] FIG. 15 is a diagram showing another example of a GUI displayed on the display device 430. In this example, in addition to "farm road priority," "waterway priority," and "GNSS priority," modes of "time priority" and "manual setting" are added. The user can select one of these five modes. In this example, "farm road priority" corresponds to the first mode, "waterway priority" corresponds to the second mode, "GNSS priority" corresponds to the third mode, and "time priority" corresponds to the fourth mode. "Manual setting" is a mode in which the user manually sets a route while looking at the displayed map.

[0133] The route generation process when "Farm road priority," "Waterway priority," or "GNSS priority" is selected is as described above. When "Time priority" is selected, the management device 600 generates a route connecting the departure point and destination point so as to minimize the travel time of the work vehicle 100. When "Manual setting" is selected, the management device 600 displays a map of the area in which the work vehicle 100 will travel on the display device 430 and allows the user to select a route. Specific examples of operation in each mode are described below.

[0134] FIG. 16 is a diagram showing an example of a map of the area in which the work vehicle 100 travels. Such a map can 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. 16 can be created for the entire area in which the work vehicle 100 can travel. Note that although the map shown in FIG. 16 is a two-dimensional map, a three-dimensional map can also be used for route planning.

[0135] The map shown in FIG. 16 includes information on the positions (e.g., latitude and longitude) of points on multiple fields 70 where the work vehicle 100 will perform farm work, surrounding roads 76, and features such as waterways 78. The map also 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 received normally. In addition to this attribute information, the map may also include attribute information indicating, for example, the width of each point on each road 76. Based on the width of each point on each road 76, the management device 600 can determine whether the work vehicle 100 can travel on that road 76. The map may also include attribute information indicating whether each road 76 is a public road other than a farm road. Based on such attribute information, a route that avoids public roads can be generated.

[0136] In the map shown in FIG. 16, the starting point S and destination point G of the automatic driving of the work vehicle 100 are indicated by a star. The starting point S and destination point G may be set by the user, for example. Alternatively, the management device 600 may set the starting point S and destination point G according to the 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, destination point G, and waypoint, one or both of the scheduled arrival time and the scheduled departure time may be recorded.

[0137] When "Manual Setting" is selected, the user can specify a desired route by, for example, specifying multiple waypoints at intersections on the displayed map. When a mode other than "Manual Setting" is selected, the management device 600 automatically generates a route from the starting point S to the destination point G using a predetermined algorithm corresponding to the selected mode.

[0138] FIG. 17 is a diagram showing an example of a route that is generated when the "farm road priority" mode is selected. In this mode, the management device 600 determines, as the route for the work vehicle 100, a route 75A in which the proportion of farm roads in the overall route is relatively high and which has a relatively short travel distance or travel time, out of multiple routes that reach the destination point G from the departure point S. For example, the management device 600 may determine, as the route for the work vehicle 100, a route in which the proportion of farm roads in the overall route is higher than a predetermined value (e.g., 80% or 90%) and which has the shortest travel distance or travel time. In the "farm road priority" mode, the management device 600 determines, as the route for the work vehicle 100, farm road 76A, as in the example shown in FIG. 16, out of multiple candidate routes that reach the destination point G from the departure point S. f Possible routes passing through and public road 76 g of passing If the route includes the route candidate, g Farm Road 76 is better than the route that passes through fAlternatively, the management device 600 may determine, as the route for the work vehicle 100, a route in which the proportion of farm roads in the overall route is higher than a predetermined value and which matches the schedule for agricultural work on that work day. For example, the management device 600 may determine, in accordance with the schedule, as the route for the work vehicle 100, a route in which the proportion of farm roads is higher than a predetermined value and in which the last agricultural work on that work day will be completed by the scheduled end time. Alternatively, if the work vehicle 100 performs agricultural work in multiple fields on its way from the departure point S to the destination point G, the management device 600 may generate, based on the schedule, a route in which the proportion of farm roads is higher than a predetermined value and which allows the work vehicle 100 to arrive at each field before the scheduled start time for each field. In addition to the condition that the proportion of farm roads is higher than a predetermined value, a condition that the proportion of public roads is equal to or less than a reference value may be added.

[0139] FIG. 18 is a diagram showing an example of a route generated when the "waterway priority" mode is selected. In this mode, the management device 600 determines, as the route for the work vehicle 100, a route 75B that includes a relatively high proportion of roads along a waterway 78 and has a relatively short travel distance or travel time among multiple routes from the starting point S to the destination point G. The waterway 78 can function as a landmark in self-localization estimation using the LiDAR sensor 140 or the camera 120. By prioritizing roads along the waterway 78, a route with a small error in self-localization estimation can be generated. Note that features other than the waterway 78 (e.g., a river, a row of trees, grass, or a building) may also be used as a landmark for self-localization estimation. In this case, the management device 600 may determine the route for the work vehicle 100 by prioritizing roads along one or more types of features that can function as landmarks, not limited to the waterway 78. In this mode, the management device 600 may, for example, determine as the route for the work vehicle 100 a route in which the proportion of roads that follow specific features in the overall route is higher than a predetermined value (e.g., 30% or 50%) and which has the shortest travel distance or travel time. Alternatively, the management device 600 may determine as the route for the work vehicle 100 a route in which the proportion of roads that follow specific features in the overall route is higher than a predetermined value and which matches the farm work schedule for that work day. For example, the management device 600 may determine as the route for the work vehicle 100 a route in which the proportion of roads that follow specific features is higher than a predetermined value and which will allow the final farm work for that work day to be completed by the scheduled end time in accordance with that schedule. Alternatively, if the work vehicle 100 performs agricultural work in multiple fields on the way from the starting point S to the destination point G, the management device 600 may determine, based on the schedule, as the route for the work vehicle 100, a route in which the proportion of roads that follow specific features is higher than a predetermined value and which allows the work vehicle 100 to arrive at each field before the scheduled start time for each.

[0140] Figure 19 is a diagram showing another example of a map of an area traveled by work vehicle 100. The map shown in Figure 19 includes multiple fields 70 and roads 76 in the surrounding areas, as well as a forest or mountain containing multiple trees 77, and a river 79. In this example, a start point S and a destination point G are set on a road adjacent to a row of trees 77.

[0141] FIG. 20 is a diagram showing an example of a route generated when the "GNSS priority" mode is selected in the example shown in FIG. 19. In this mode, the management device 600 preferentially selects, from among multiple routes from the starting point S to the destination point G, a route 75C that has a high percentage of routes on which satellite signals from GNSS satellites can be received normally. In the example shown in FIG. 20, the route that can travel from the starting point S to the destination point G in the shortest time is prone to interference with satellite signal reception because nearby trees, mountains, and the like partially block radio waves from GNSS satellites. Therefore, instead of such a route, a route 75C with a stable and high reception strength of satellite signals is determined as the route for the work vehicle 100. Note that in the example shown in FIG. 20, roads on both sides of a river 79 are considered impassable to the work vehicle 100. Therefore, a relatively long route 75C is generated that travels from the starting point S to the destination point G over the river 79. If a road along the river 79 is passable, the management device 600 may generate a route to the destination point G via that road. Alternatively, the management device 600 may generate a route that prioritizes both roads where satellite signals can be received properly and roads that follow particular features such as rivers 79 or waterways.

[0142] 20, the management device 600 determines, from among multiple routes from the departure point S to the destination point G, a route that has a high proportion of roads on which satellite signals can be received normally and that has a relatively short travel distance, as the route for the work vehicle 100. For example, the management device 600 may determine, as the route for the work vehicle 100, a route on which the proportion of roads on which satellite signals can be received normally across the entire route is higher than a predetermined value (e.g., 80% or 90%) and that has the shortest travel time. In the "GNSS priority" mode, when generating a route from the departure point S to the destination point G, the management device 600 generates a route by preferentially selecting roads that extend in a direction away from a row of trees, mountains, etc., a predetermined distance or more, or roads that are located a predetermined distance or more away from a row of trees, mountains, etc., over other roads that are located less than the predetermined distance from a row of trees, mountains, etc. For example, in the example of FIG. 20 , the management device 600, of the multiple roads 76a, 76b, 76c, and 76d, preferentially selects roads 76b and 76d that extend in a direction away from the row of trees, mountains, etc., by a predetermined distance or more, and road 76c that is located at a position away from the row of trees, mountains, etc., by a predetermined distance or more, and generates a route that connects continuously along these roads, and also forms a route on a portion of road 76a that leads to destination point G. Alternatively, the management device 600 may determine, as the route for the work vehicle 100, a route on which the proportion of roads on which satellite signals can be received normally is higher than a predetermined value and that matches the farm work schedule for that work day. For example, the management device 600 may determine, in accordance with the schedule, as the route for the work vehicle 100, a route on which the proportion of roads on which satellite signals can be received normally is higher than a predetermined value and that allows the final farm work on that work day to be completed by the scheduled end time. Alternatively, if the work vehicle 100 performs agricultural work in multiple fields while traveling from the starting point S to the destination point G, the management device 600 may determine, based on the schedule, as the route for the work vehicle 100, a route in which the percentage of roads on which satellite signals can be received normally is higher than a predetermined value and which allows the work vehicle 100 to arrive at each field before the scheduled start time for each.

[0143] FIG. 21 is a diagram that schematically illustrates an example of a situation in which the work vehicle 100 is traveling near a row of trees. In this example, multiple trees 77 grow thickly near the travel path of the work vehicle 100. The branches and leaves of some of the trees 77 obscure the work vehicle 100, preventing it from receiving satellite signals. In such an environment, many of the signals transmitted from satellite 50 are blocked by the branches of the trees 77. As a result, the overall reception strength of the satellite signals decreases, reducing the reliability of positioning. In the "GNSS priority" mode, the route of the work vehicle 100 is determined so as to avoid such roads as much as possible. This makes it possible to avoid a decrease in the reliability of positioning based on GNSS data and stabilize automated driving.

[0144] When the "GNSS-first" mode is selected, the management device 600 determines whether each road is a road on which satellite signals can be received normally based on attribute information for each road included in the map. This attribute information can be generated based on GNSS data output from a GNSS receiver mounted on the work vehicle 100 or another mobile object. The other mobile object may be a type of mobile object different from the work vehicle 100, such as a passenger car or a drone (i.e., an unmanned aerial vehicle: UAV). The work vehicle 100 or another mobile object collects GNSS data while traveling along the road on which the work vehicle 100 is scheduled to travel automatically. GNSS data collection can be performed multiple times at different times for each road. This is because the positions of multiple GNSS satellites vary depending on the season. Because the degree to which tree branches and leaves interfere with satellite signal reception can vary depending on the season, GNSS data for each road can be collected in multiple different seasons. Attribute information indicating whether each road is a road on which satellite signals can be received normally can be generated based on GNSS data collected multiple times for each road. The attribute information can be generated by, for example, the management device 600.

[0145] 22A and 22B are diagrams showing examples of satellite signal reception strength. FIG. 22A shows an example of the reception strength of each satellite signal on a route where satellite signals can be received normally. FIG. 22B shows an example of the reception strength of each satellite signal on a route where satellite signals cannot be received normally (i.e., where reception interference may occur). In this example, satellite signals from 12 satellites are received, and the reception strength is expressed as a carrier-to-noise power density ratio (C / N0) value. Note that this is just one example, and the number of satellites from which satellite signals 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 the number of satellites whose reception strength exceeds a predetermined reference value is equal to or greater than a threshold value (e.g., 4). In FIGS. 22A and 22B, an example of the reception strength reference value is shown by a dashed line. If the threshold value is, for example, 4, in the example of FIG. 22A, 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 no reception interference is occurring. On the other hand, in the example of FIG. 22B, the number of satellites whose reception strength exceeds the reference value is 1, which is less than the threshold. Therefore, in such cases, it may be determined that a signal interference is occurring. For example, a road determined to have no signal interference at any time based on GNSS data collected for each road at different times can be determined as a "road on which satellite signals can be normally received." Note that the ease of receiving satellite signals may vary depending on the location, even on the same road. Therefore, attribute information indicating whether satellite signals can be normally received may be recorded for each coordinate on the road (e.g., latitude and longitude). Note that the above method is merely an example, and other methods may be used to determine whether a road can normally receive satellite signals. 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.

[0146] FIG. 23 is a diagram showing an example of a route generated by the management device 600 when the "time priority" mode is selected. In this example, the management device 600 generates, as the route for the work vehicle 100, a route 75D that enables travel from the starting point S to the destination point G in the shortest time. The route 75D is generated on a road that follows a row of trees 77. This type of route is effective, for example, when the work vehicle 100 estimates its own position based on data acquired by the LiDAR sensor 140 or the camera 120, rather than using GNSS data. When estimating its own position based on data acquired by the LiDAR sensor 140 or the camera 120, the management device 600 may determine, as the route for the work vehicle 100, a route that includes a road on which satellite signals cannot be received normally.

[0147] In the above example, the management device 600 performs global route design for the work vehicle 100 in a mode selected by the user from among multiple modes. This makes it possible to generate a route that reflects the user's intentions. In the above example, five modes, "farm road priority," "waterway priority," "GNSS priority," "time priority," and "manual setting," are illustrated, but these are merely examples. The management device 600 may generate a route in at least one mode from among "farm road priority," "waterway priority," and "GNSS priority." Alternatively, without providing a user mode selection function, the management device 600 may generate a route for the work vehicle 100 according to a predetermined algorithm that prioritizes at least one of roads that follow specific features, such as farm roads and waterways, and roads on which satellite signals can be received normally.

[0148] For example, the management device 600 may calculate an evaluation value for each of multiple routes from the departure point of the work vehicle 100 to the destination point based on attribute information for each road taken along the route and a predetermined evaluation function, and determine one route selected based on the evaluation value as the route for the work vehicle 100. Specifically, the management device 600 may determine, as the route for the work vehicle 100, the route that minimizes an evaluation function in which the evaluation value decreases the higher the proportion of farm roads, roads along specific features, or roads on which satellite signals can be properly received, and the evaluation value increases the longer the travel time or travel distance. For example, the evaluation function can be expressed by the following function f, where r1 is the proportion of the length of farm roads in the entire route, r2 is the proportion of the length of roads along specific features in the entire route, r3 is the proportion of the length of roads on which satellite signals can be properly received in the entire route, and d is the total length of the route.

number

[0149] Contrary to the above example, the management device 600 may determine, as the route for the work vehicle 100, the route that maximizes an evaluation function in which, among multiple routes from the starting point to the destination, the evaluation value increases the higher the proportion of farm roads, roads that follow specific features, or roads where satellite signals can be received normally, and the evaluation value decreases the longer the travel time or travel distance.

[0150] Next, a specific example of a route planning method based on a work plan will be described.

[0151] Before agricultural work begins on each work day, the management device 600 reads from the storage device 650 a map of the area including the field where agricultural work is scheduled for that work day, and generates a route for the work vehicle 100 based on that map. More specifically, the management device 600 generates a first route (also referred to as a "work travel route") in the field 70 on the map along which the work vehicle 100 will travel while performing agricultural work in that field, and generates a second route (on a road) on the map along which the work vehicle 100 will travel toward the field 70. After generating the first and second routes, the management device 600 connects the two to generate a global route for the work vehicle 100. As described above, the second route can be generated so as to prioritize at least one of farm roads, roads that follow specific features, and roads on which satellite signals can be received normally.

[0152] Fig. 24 is a diagram showing an example of a generated global route. Fig. 24 illustrates a group of fields 70A where farm work will be carried out on one work day, a group of fields 70B where farm work will be carried out on the next work day, and a group of fields 70C where farm work will be carried out on the work day after that. Fig. 24 also illustrates a storage location 90 for the work vehicle 100, a user's home 92 that remotely monitors the work vehicle 100, and two waiting locations 96A and 96B where the work vehicle 100 will wait. 24For ease of explanation, group of fields 70A, group of fields 70B, group of fields 70C, storage location 90, waiting location 96A, and waiting location 96B are depicted as being located relatively close to one another. In reality, the mutual distances between group of fields 70A, group of fields 70B, group of fields 70C, storage location 90, waiting location 96A, and waiting location 96B may be long, for example, 500 m to 10 km or more.

[0153] The storage location may be, for example, a garage, barn, or parking lot adjacent to the user's home or business. The waiting location may be, for example, a location jointly managed or used by multiple users. The waiting location may be a facility such as a parking lot or garage managed and operated by a municipality, agricultural cooperative, or company. If the waiting location is a facility that is locked at night, theft of the work vehicle 100 parked at the waiting location can be prevented. While two waiting locations 96A and 96B are illustrated in FIG. 24, the number of waiting locations is arbitrary. If the work vehicle 100 moves within a relatively small area, there is no need to provide a waiting location 96 separate from the storage location 90. The storage location 90 and waiting location 96 can be registered by the user through operation of the terminal device 400.

[0154] In Figure 24, of the routes generated by the management device 600, routes generated on road 76 are indicated by arrows. Work travel routes generated within the field are not shown. Solid arrows indicate an example of a route for the work vehicle 100 on a certain work day. Dashed arrows indicate an example of a route for the work vehicle 100 on the next work day.

[0155] In the example shown in FIG. 24 , the management device 600 generates a route for one work day that starts from the storage location 90, passes through the group of fields 70A, and reaches the waiting location 96A. This is because the waiting location 96A is the closest waiting location to the group of fields 70B where work is scheduled for the next work day. The management device 600 generates a route for the next work day that starts from the waiting location 96A, passes through the group of fields 70B, and reaches the waiting location 96B. This is because the waiting location 96B is the closest waiting location to the group of fields 70C where work is scheduled for the next work day. In this way, the management device 600 generates a route from the last field where work is performed on each work day to the waiting location that is the shortest on average from the group of fields where work is scheduled for the next work day. As described above, the management device 600 can generate routes that prioritize farm roads, roads that follow specific features, or roads where satellite signals can be received normally, for example, according to the user's selection. The work vehicle 100 travels along the generated route.

[0156] In the example shown in FIG. 24, on a certain work day, the work vehicle 100 departs from the storage location 90 and sequentially visits the group of fields 70A where work is scheduled for that day, performing the work indicated in the schedule in each field. In each field, the work vehicle 100 performs the work while automatically traveling along the work travel route, for example, using the method described with reference to FIGS. 7 to 9D. When work in one field is completed, the work vehicle 100 enters the next field and performs the work in the same way. In this way, when work in the last field of the day is completed, the work vehicle 100 moves to the waiting location 96A. The work vehicle 100 waits at the waiting location 96A until the next work day. On the next work day, the work vehicle 100 departs from the waiting location 96A and sequentially visits the group of fields 70B where work is scheduled for that day, performing the work indicated in the schedule in each field. When work in the last field of the day is completed, work vehicle 100 moves to standby location 96B, where it waits until the next work day. On the next work day, work vehicle 100 similarly departs from standby location 96B, performs work in each of group of fields 70C in turn, and then heads to the designated standby location. This operation allows work vehicle 100 to move efficiently along the optimal route according to the schedule, completing the planned work.

[0157] In the case where multiple waiting locations (including storage location 90) are provided within the environment in which work vehicle 100 travels, as in the present embodiment, data (e.g., a table) indicating the correspondence between the multiple waiting locations and multiple fields may be pre-stored in storage device 650. FIG. 25 is a diagram showing an example of a table indicating the correspondence between waiting locations and fields. The correspondence between waiting locations and fields may be determined, for example, based on the travel distance from each waiting location to each field. In the example shown in FIG. 25, the waiting location closest to fields #1 to #30 is waiting location A, the waiting location closest to fields #31 to #60 is waiting location B, and the waiting location closest to fields #61 to #100 is waiting location C. By referencing such a table, management device 600 can determine the waiting location closest to the fields scheduled for the next work day. As in this example, by providing one or more waiting locations 96 separate from the storage location 90, it is possible to reduce the time and fuel consumption required for the work vehicle 100 to travel compared to returning to the storage location 90 each time. As a result, it is possible to improve the efficiency of a series of agricultural work tasks that span multiple work days.

[0158] Next, an example of a method for generating a global route will be described in more detail with reference to FIG. 26. FIG. 26 is a diagram showing an example of a global route generated on a certain work day. In this example, the management device 600 generates a route that returns from a waiting location 96 to the waiting location 96 via four fields 70. The management device 600 generates a first route (work travel route) 30A within the field 70, and generates a second route 30B on a road 76 around the field 70. In FIG. 26, the first route 30A is shown only for the field 70 on the lower left, and the first routes in the other fields 70 are not shown.

[0159] The management device 600 generates a first path 30A as indicated by the solid arrow in FIG. 26 within each field 70 on the map. The management device 600 generates the first path 30A based on the user's prior settings, as described with reference to FIG. 7. The first path 30A can be generated to cover the entire work area 72 by repeatedly traveling back and forth from a start point 30S to an end point 30G. The spacing between rows on the first path 30A can be determined taking into account the width and turning performance of the work vehicle 100 and the implement 300.

[0160] The management device 600 further generates a route from the waiting location 96 to the field 70 and a route connecting multiple fields 70 as second routes 30B. In the example of FIG. 26, in addition to the road 76, the management device 600 generates a second route 30B at the entrance of the field 70 and generates a third route 30C connecting the second route 30B generated at the entrance with the starting point 30S of the first route 30A. In addition to the road 76, the management device 600 also generates a second route 30B at the exit of the field 70 and generates a fourth route 30D connecting the second route 30B generated at the exit with the ending point 30G of the first route 30A. In the example shown in FIG. 26, the entrance and exit of the field 70 are common, and will be referred to as an entrance / exit 71 hereinafter. Each field 70 may have multiple entrances / exits 71, and the entrance and exit may be located in different locations. The environmental map includes, in addition to the position information of each field 70, position information of the entrance / exit 71 (or the entrance and exit) of each field 70. The management device 600 can generate the second route 30B based on the position information.

[0161] In this embodiment, the management device 600 generates the third route 30C and the fourth route 30D in an area of ​​the field 70 excluding areas where agricultural work has been performed. In the example of FIG. 26 , it is assumed that the previous agricultural work has already been performed in the work area 72. Therefore, the management device 600 generates the third route 30C and the fourth route 30D in the headland 74, avoiding the work area 72. This prevents the work area 72, where agricultural work has already been performed, from being trampled by the work vehicle 100. If no agricultural work has been performed in the field 70 this season (i.e., the current agricultural work is the first agricultural work), the third route 30C may overlap with the work area 72. On the other hand, the fourth route 30D is a route after the current agricultural work has already been completed, and is therefore set so as not to overlap with the work area 72.

[0162] In the work area 72, multiple types of agricultural work are performed at different times. For example, work such as plowing, planting, fertilizing, pest control, and harvesting may be performed at different times. If some agricultural work is already being performed in the work area 72, the effectiveness of the agricultural work that has already been performed will be diminished if the work vehicle 100 passes over the work area 72. Therefore, in this embodiment, the management device 600 generates the third route 30C and the fourth route 30D to avoid the work area 72 when some agricultural work is already being performed in the work area 72. The areas in which agricultural work has already been performed can be determined based on the work plan. Based on the work plan, the management device 600 can generate the third route 30C and the fourth route 30D in areas excluding areas where work has already been performed.

[0163] The management device 600 can generate all routes for a predetermined period (e.g., half a day, one day, three days, etc.) by executing the above-described route generation process for each field 70 and the roads 76 in its vicinity. For example, for each work day, the management device 600 may generate all routes necessary to complete all of the farm work scheduled for that work day before the work vehicle 100 begins traveling. Alternatively, the management device 600 may first generate routes for performing part of the farm work scheduled for each work day, and then, after that part of the farm work is completed, generate routes for performing the remaining farm work for that work day. Furthermore, the management device 600 may generate all routes necessary to complete all of the farm work scheduled for multiple work days at once. The management device 600 may change the routes once generated depending on various conditions, such as the progress of the farm work, weather conditions, traffic conditions, or the condition of farm roads.

[0164] In the example shown in FIG. 26 , the work plan indicates that agricultural work will be carried out in multiple fields 70 over a predetermined period (e.g., one work day). Therefore, the management device 600 generates a route from a waiting location 96 to one field 70 and routes between the fields 70 along the road 76. In addition to this example, there are cases where the work plan indicates that agricultural work will be carried out in one field 70 over a predetermined period. In such cases, the management device 600 generates a route from the waiting location 96 to one field 70 along the road 76 leading to the field 70. The management device 600 further generates a route in the work plan along the road 76 from the field 70 where agricultural work will be carried out last within the predetermined period to a return location to which the work vehicle 100 will return. In the example of FIG. 26 , the waiting location 96 corresponds to the return location. The return location may be a location different from the waiting location 96 (e.g., the storage location 90 shown in FIG. 24 ).

[0165] Through the above operations, management device 600 can generate a global route for work vehicle 100 from a departure point to a destination point via one or more fields 70 for each predetermined period (e.g., work day). Management device 600 can generate a global route for work vehicle 100 so that work vehicle 100 performs farm work in a specified field 70 at a specified time according to a schedule created in advance. Information on the generated global route is transmitted to work vehicle 100 and stored in storage device 170. ECU 184, which performs automatic driving control, controls ECUs 181 and 182 so that work vehicle 100 travels along the global route. As a result, work vehicle 100 begins traveling along the global route.

[0166] [2-4. Local Path Planning] When the work vehicle 100 is traveling outside a field, an obstacle such as a pedestrian or another vehicle may be present on or near the global route. 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 (such as the obstacle sensor 130, the LiDAR sensor 140, and the camera 120) 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 portion of the second route 30B. The ECU 185 determines whether an obstacle is present on or near the path of the work vehicle 100 based on the sensing data. If such an obstacle is present, the ECU 185 sets a plurality of waypoints to avoid the obstacle and generates a local route. If no obstacles are present, ECU 185 generates a local route that is approximately 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. Note that if there are traffic lights on the road on which work vehicle 100 is traveling, work vehicle 100 may, for example, recognize the traffic lights based on images captured by camera 120, stop when the light is red, and start when the light is green.

[0167] FIG. 27 is a diagram illustrating an example of a global route and a local route generated in an environment where obstacles are present. In FIG. 27, the global route 30 is illustrated by dotted arrows, and the local route 32, which is generated sequentially during travel, is illustrated by solid arrows. The global route 30 is defined by multiple waypoints 30p. The local route 32 is defined by multiple 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 multiple waypoints 30p at multiple locations, including intersections on a 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 multiple waypoints 32p based on sensing data output from the sensing device while the work vehicle 100 is traveling. The intervals between waypoints 32p on the local route 32 are shorter than the intervals between waypoints 30p on the global route 30. The intervals between waypoints 32p can 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. 27 shows an example of 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. While the work vehicle 100 is moving, 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. The work vehicle 100 travels along the local routes that are successively generated.

[0168] In the example shown in FIG. 27, an obstacle 40 (e.g., a person) is present ahead of the work vehicle 100. In FIG. 27, an example of a range sensed by a sensing device such as the camera 120, obstacle sensor 130, or 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, for example, based on the sensing data and the width of the work vehicle 100 (including the width of the implement if one is attached). If there is a possibility that the work vehicle 100 will collide with the obstacle 40, the ECU 185 sets multiple waypoints 32p so as to avoid the obstacle 40, and generates the local route 32. Note that the ECU 185 may recognize not only the presence or absence of an obstacle 40 but also the state of the road surface (for example, mud, depressions, etc.) based on sensing data, and if a location where travel is difficult is detected, it may generate a local route 32 to avoid such a location. The work vehicle 100 travels along the local route 32. If 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 monitor. After stopping, if it is recognized that the obstacle 40 has moved and there is no longer any risk of collision, the control device 180 may resume travel of the work vehicle 100.

[0169] Fig. 28 is a flowchart showing the route planning and travel control operations in this embodiment. By executing the operations of steps S141 to S146 shown in Fig. 28, route planning can be performed and the automatic travel of work vehicle 100 can be controlled.

[0170] In the example shown in FIG. 28, 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 using the method described above based on the map and the work plan (step S142). Global route design can be performed at any timing before the work vehicle 100 starts traveling. Global route design may be performed immediately before the work vehicle 100 starts traveling, or may be performed one day or earlier before the start of traveling. In addition, the global route may be generated based on information (e.g., starting point, destination point, waypoints, etc.) input by the user using the terminal device 400. As described above, when generating a route to a farm field or a route from the farm field to another location (for example, a storage location or waiting location for the work vehicle 100), the management device 600 generates at least one of the following routes for the work vehicle 100: a route that prioritizes farm roads, a route that prioritizes roads that follow specific features, and a route that prioritizes roads on which satellite signals can be received normally, based on attribute information for each road on the map. The management device 600 transmits data indicating the generated global route to the work vehicle 100. The management device 600 then 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 unit 240 to start the work vehicle 100 traveling (step S143). This causes the work vehicle 100 to start traveling. The timing to start traveling can be set, for example, to an appropriate timing that enables the work vehicle 100 to arrive at the farm field by the scheduled start time of the first agricultural work on each work day indicated in the work plan. While the work vehicle 100 is traveling, the ECU 185 of the control device 180 uses the method described above to design a local route to avoid a collision with an obstacle (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 has ended.

[0171] Through the above operations, the work vehicle 100 can automatically travel along the generated route without colliding with any obstacles.

[0172] In the example of FIG. 28 , once the global route is generated, it is not changed until the destination is reached. This example is not limiting, and the global route may be modified while the work vehicle 100 is traveling. For example, while the work vehicle 100 is traveling, the ECU 185 may recognize at least one of the condition of the road on which the work vehicle 100 is traveling, the condition of the vegetation around the work vehicle 100, and the weather condition based on sensing data acquired by a sensing device such as the camera 120 or the LiDAR sensor 140, and may change the global route if the recognized condition satisfies a predetermined condition. When the work vehicle 100 is traveling along the global route, some roads may be impassable. For example, heavy rain may cause the road to become muddy, the road surface may collapse, or the road may be impassable due to an accident or other cause. Alternatively, the vegetation around a farm road may grow longer than expected, or new buildings may have been constructed, making it difficult to receive satellite signals from GNSS satellites. Taking such situations into consideration, ECU 185 may detect roads that are difficult to travel based on 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 about the changed route to management device 600. In that case, management device 600 may use the changed route the next time it generates a route to the same field. This enables flexible route planning that responds to changes in the traveling environment.

[0173] (Other embodiments) The configurations and operations of the above-described embodiments are merely examples, and the present disclosure is not limited to the above-described embodiments. Other embodiments will be described below.

[0174] In the above embodiment, the processor 660 of the management device 600 creates a work plan, generates an environmental map, and designs a global route for the work vehicle 100, and the control device 180 inside the work vehicle 100 designs a local route and controls the travel of the work vehicle 100. Alternatively, some of the operations of the management device 600 described above may be executed by the control device 180, the operation terminal 200, or the terminal device 400. For example, the generation of the environmental map and the generation of the global route may be executed by the control device 180, the operation terminal 200, or the terminal device 400.

[0175] The management device 600 may manage the operations of multiple agricultural machines including the work vehicle 100. In this case, the management device 600 may perform global route planning and driving instructions for each agricultural machine based on the schedule of farm work to be performed by each agricultural machine.

[0176] The system for performing path planning or automatic driving control in the above embodiments can also be retrofitted to an agricultural machine that does not have those functions. Such a system can be manufactured and sold independently of the agricultural machine. The computer program used in such a system can also be manufactured and sold independently of the agricultural machine. The computer program can be provided, for example, by being stored on a computer-readable non-transitory storage medium. The computer program can also be provided by downloading via a telecommunications line (for example, the Internet).

[0177] As described above, the path planning system according to an embodiment of the present disclosure is a path planning system for an agricultural machine that automatically travels within and outside a field. The path planning system includes a storage device that stores a map of an area including multiple fields and roads surrounding the multiple fields, and a processing device that generates a route for the agricultural machine on the map. The map includes attribute information indicating at least one of whether each road is a farm road, whether each road runs along specific features, and whether each road can successfully receive satellite signals from GNSS satellites. When generating a route to a field or a route from the field to another location, the processing device generates at least one of the following routes based on the attribute information: a route that prioritizes farm roads, a route that prioritizes roads that run along the specific features, and a route that can successfully receive satellite signals. This configuration makes it possible to generate a route that is optimal for autonomous driving of the agricultural machine.

[0178] The map may include attribute information indicating whether each road is along a waterway, which is the specific feature. The processing device may generate a route for the agricultural machine that prioritizes roads along the waterway based on the attribute information. This makes it possible to generate a route that includes many roads along waterways that are suitable as landmarks for use in self-localization using a LiDAR sensor or a camera.

[0179] The processing device may determine, as the route for the agricultural machine, a route that minimizes an evaluation function, of multiple routes from a starting point to a destination point, in which the evaluation value decreases as the proportion of farm roads, roads along the specific feature, or roads where satellite signals can be received normally increases, and the evaluation value increases as the travel time or travel distance increases. This makes it possible to stably generate routes that have a high proportion of farm roads, roads along the specific feature, or roads where satellite signals can be received normally.

[0180] The processing device may generate the route in a mode selected by a user from a plurality of modes including at least one of a first mode in which farm roads are preferentially selected to generate the route, a second mode in which roads along the specific features are preferentially selected to generate the route, and a third mode in which roads on which satellite signals can be normally received are preferentially selected to generate the route. This makes it possible to generate a route that reflects the priorities that the user places importance on.

[0181] The processing device may generate the route in a mode selected by a user from a plurality of modes including all of the first mode, the second mode, and the third mode, thereby making it possible to generate a route that reflects the priority items emphasized by the user from among a route that prioritizes farm roads, a route that prioritizes roads that follow specific features, and a route that prioritizes roads where satellite signals can be received normally.

[0182] The processing device may generate the route in a mode selected by a user from the plurality of modes, which further includes a fourth mode for generating the route so as to minimize the travel time or travel distance of the agricultural machine, thereby making it possible to generate a route that minimizes the travel time or travel distance.

[0183] The processing device may display a graphical user interface (GUI) on a display device that allows a user to select one mode from the plurality of modes, thereby enabling the user to select a mode corresponding to a priority item that the user values ​​on the GUI.

[0184] The storage device may further store a schedule of one or more agricultural tasks to be performed by the agricultural machine each work day. The processing device may generate the route based on the schedule so that the last agricultural task in each work day is completed by its scheduled end time. This makes it possible to generate a route that enables the agricultural tasks to be completed by their scheduled end times shown in the schedule.

[0185] The processing device may generate the route based on the schedule so that the agricultural machine arrives at a field where each agricultural work is to be performed before the scheduled start time of the work. This makes it possible to generate a route that allows the agricultural machine to arrive at each field before the scheduled start time of each agricultural work indicated in the schedule.

[0186] While the agricultural machine is traveling along the route, the processing device may repeatedly generate a local route that can avoid obstacles, the local route being defined by a plurality of waypoints along a portion of the route, based on data acquired by a sensing device provided in the agricultural machine, and output information indicating the local route to a control device that controls the traveling of the agricultural machine, thereby allowing the agricultural machine to travel along the local route that can avoid obstacles.

[0187] A control system according to another embodiment of the present disclosure includes the path planning system of any of the above embodiments, and a control device that causes the agricultural machine to travel along the path generated by the processing device.

[0188] According to yet another embodiment of the present disclosure, there is provided an agricultural machine including the control system according to any one of the above embodiments and a sensing device that senses the environment around the agricultural machine, and the control device causes the agricultural machine to travel along a route generated by the processing device based on a signal output from the sensing device.

[0189] A path planning method according to yet another embodiment of the present disclosure is a path planning method for an agricultural machine that automatically travels within and outside a field. The path planning method includes: acquiring from a storage device a map of an area including a plurality of fields and roads surrounding the plurality of fields, the map including attribute information indicating at least one of whether each road is a farm road, whether each road is a road along a waterway, and whether each road is a road on which satellite signals from GNSS satellites can be normally received; and generating a route for the agricultural machine on the map, wherein when generating a route toward the field or a route from the field to another location, at least one of a route that prioritizes farm roads, a route that prioritizes roads along waterways, and a route that prioritizes roads on which satellite signals can be normally received is generated as the route for the agricultural machine based on the attribute information.

[0190] According to yet another embodiment of the present disclosure, there is provided a computer program for planning a path for an agricultural machine that automatically travels within and outside a field. The program may be stored in a computer-readable non-transitory storage medium. The program causes a computer to: acquire from a storage device a map of an area including a plurality of fields and roads surrounding the plurality of fields, the map including attribute information indicating at least one of whether each road is a farm road, whether each road is a road along a waterway, and whether each road is a road on which satellite signals from GNSS satellites can be normally received; and generate a route for the agricultural machine on the map, wherein, when generating a route toward the field or a route from the field to another location, the program generates, based on the attribute information, at least one of a route that prioritizes farm roads, a route that prioritizes roads along waterways, and a route on which satellite signals can be normally received. [Industrial Applicability]

[0191] The technology disclosed herein can be applied to a path planning system for autonomously operating agricultural machinery such as a tractor, a harvester, a rice transplanter, a riding tiller, a vegetable transplanter, a grass cutter, a seed sowing machine, a fertilizer applicator, or an agricultural robot. [Explanation of symbols]

[0192] 30 Global route, 32 Local route, 40 Obstacle, 50 GNSS satellite, 60 Reference station, 70 Field, 71 Entrance / exit, 72 Work area, 74 Headland, 76 Road, 77 Tree, 78 Waterway, 79 River, 80 Network, 90 Storage area, 92 User's home, 96 Waiting area, 100 Work vehicle, 101 Vehicle body, 102 Engine, 103 Transmission, 104 Wheels, 105 Cabin, 106 Steering gear, 107 Driver's seat, 108 Coupling, 110 GNSS unit 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···Turn angle sensor, 156···Axle sensor, 160···Control system, 170···Storage device, 180···Control device, 181~186···ECU, 1 90 communication device, 200 operation terminal, 210 operation switch group, 220 buzzer, 240 drive device, 300 implement, 340 drive device, 380 control device, 390 communication device, 400 terminal device, 420 input device, 430 display device, 450 storage device, 460 processor, 470 ROM, 480 RAM, 490 communication device, 600 management device, 650...Storage device, 660 processor 、6 70...ROM, 680...RAM, 690...communication device

Claims

1. A path planning system for an agricultural machine that automatically travels in and out of a field, comprising: a storage device that stores a map of an area including a plurality of fields and roads around the plurality of fields; a processing device that generates a route for the agricultural machine on the map; Equipped with the map includes attribute information indicating whether each road is a farm road or not, and whether each road is a road that follows a specific feature or not; When generating a route to the farm field or a route from the farm field to another location, the processing device generates the route in a mode selected by a user from a plurality of modes, including a first mode in which farm roads are preferentially selected to generate the route based on the attribute information, and a second mode in which roads along the specific features are preferentially selected to generate the route. Route planning system.

2. the map includes attribute information indicating whether each road is a road along a waterway that is the specific feature; In the second mode, the processing device generates, based on the attribute information, a route that prioritizes roads along the waterways as a route for the agricultural machine. The route planning system of claim 1 .

3. The map includes attribute information indicating whether each road is a farm road, whether each road is a road that follows a specific feature, and whether each road is a road that can normally receive satellite signals from GNSS satellites; the processing device generates the route in a mode selected by a user from a plurality of modes, including a first mode for generating the route by preferentially selecting farm roads based on the attribute information, a second mode for generating the route by preferentially selecting roads along the specific features, and a third mode for generating the route by preferentially selecting roads along which the satellite signals can be normally received. The route planning system of claim 1 .

4. 4. The route planning system according to claim 3, wherein the processing device determines, as the route for the agricultural machine, a route that minimizes an evaluation function, the evaluation value of which decreases as the proportion of farm roads, roads along the specific feature, or roads on which satellite signals can be received normally increases, and the evaluation value increases as the travel time or travel distance increases, from among a plurality of routes that reach the destination from the departure point.

5. 4. The path planning system according to claim 3, wherein the processing device generates the path in a mode selected by a user from among the plurality of modes, the mode further including a fourth mode that generates the path so as to minimize a travel time or a travel distance of the agricultural machine.

6. The route planning system according to claim 1 , wherein the processing unit causes a display device to display a graphical user interface that allows a user to select one mode from the plurality of modes.

7. the storage device further stores a schedule of one or more farm works to be performed by the agricultural machine for each work day; the processing device generates the route based on the schedule so that the last agricultural work in each work day is completed by a scheduled end time. The route planning system of claim 1 .

8. 8. The path planning system according to claim 7, wherein the processing device generates the path based on the schedule so that the agricultural machine arrives at a field where each agricultural work is to be performed before the scheduled start time of each work.

9. 2. The path planning system according to claim 1, wherein, while the agricultural machine is traveling along the path, the processing device generates a local path that can avoid obstacles, defined by a plurality of waypoints along part of the path, based on data acquired by a sensing device provided in the agricultural machine, and repeats the operation of outputting information indicating the local path to a control device that controls the traveling of the agricultural machine.

10. A route planning system according to any one of claims 1 to 9; a control device that causes the agricultural machine to travel along the route generated by the processing device; A control system comprising:

11. A control system according to claim 10; a sensing device that senses the environment around the agricultural machine; Equipped with the control device causes the agricultural machine to travel along the route generated by the processing device based on the signal output from the sensing device. Agricultural machinery.

12. A path planning method for an agricultural machine that automatically travels in and out of a field, comprising: acquiring from a storage device a map of an area including a plurality of farm fields and roads around the plurality of farm fields, the map including attribute information indicating whether each road is a farm road or not and whether each road is a road that follows a specific feature or not; generating a route for the agricultural machine on the map, wherein when generating a route to a farm field or a route from the farm field to another location, the route is generated in a mode selected by a user from a plurality of modes including a first mode in which farm roads are preferentially selected to generate the route based on the attribute information, and a second mode in which roads along specific features are preferentially selected to generate the route; A path planning method comprising:

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