Driving control system, work vehicle, driving control method, and computer program

Abstract

The present invention provides a travel control system, a work vehicle, a travel control method, and a computer program that enable the travel of a work vehicle to which a work implement is attached, even when the work implement is rotatably attached to the work vehicle. [Solution] The travel control system is a system for controlling the movement of a work vehicle to which a work implement is attached, and comprises one or more LiDAR sensors attached to the work vehicle that output point cloud data showing the surrounding environment of the work vehicle including at least a part of the work implement, and a control device for controlling the movement of the work vehicle. The work implement is attached to the work vehicle so as to be rotatable relative to the work vehicle. The control device determines the position of feature points of the work implement based on the point cloud data acquired from the LiDAR sensors, and calculates the angle between the orientation of the work vehicle and the orientation of the work implement based on the position of the feature points.

Description

Technical Field

[0001] The present invention relates to a travel control system, a work vehicle, a travel control method, and a computer program.

Background Art

[0002] As next-generation agriculture, research and development of smart agriculture utilizing ICT (Information and Communication Technology) and IoT (Internet of Things) are underway. Research and development for automating and unmanning work vehicles such as tractors used in fields are also underway. For example, work vehicles that travel by automatic steering using a positioning system such as GNSS (Global Navigation Satellite System) capable of precise positioning have been put into practical use.

[0003] Patent Document 1 discloses a work vehicle capable of autonomously moving between a plurality of tree rows by using a SLAM (Simultaneous Localization and Mapping) technique that simultaneously executes position estimation and map creation in an orchard such as a vineyard. Patent Document 1 describes that in an orchard, while the work vehicle travels between a plurality of tree rows, operations such as mowing and control are performed using a work implement (agricultural implement) connected to the work vehicle.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In some cases, the implement is attached to the work vehicle in a way that allows it to rotate relative to the vehicle. Even in such cases, it is necessary to control the movement of the work vehicle to which the implement is attached.

[0006] The present invention aims to provide a travel control system, a work vehicle, a travel control method, and a computer program that can control the travel of a work vehicle to which a work machine is attached, even when the work machine is rotatably attached to the work vehicle. [Means for solving the problem]

[0007] According to embodiments of the present invention, the following solutions are provided.

[0008] [Item 1] A system for controlling the movement of a work vehicle to which a work machine is attached, One or more LiDAR sensors attached to the work vehicle, which output point cloud data showing the surrounding environment of the work vehicle including at least a part of the work machine, A control device for controlling the movement of the aforementioned work vehicle and Equipped with, The aforementioned work machine is connected to the work vehicle so as to be rotatable relative to the work vehicle, The control device is Based on the point cloud data acquired from the LiDAR sensor, the position of the feature points of the work machine is determined. A driving control system that calculates the angle between the orientation of the work vehicle and the orientation of the work machine based on the position of the aforementioned feature points.

[0009] [Item 2] The control device is The travel control system according to item 1, which calculates the angle between the orientation of the work vehicle and the orientation of the work machine based on the positional relationship between the position of the characteristic point and the position of the center of rotation of the work machine relative to the work vehicle.

[0010] [Item 3] The control device is By filtering the point cloud data acquired from the LiDAR sensor, point cloud data indicating reflection points on the surface of the work machine is extracted. A driving control system according to item 1 or 2, which calculates the position of the feature points based on the extracted point cloud data.

[0011] [Item 4] The control device is The driving control system according to item 3, which calculates the position of the feature points by obtaining the arithmetic mean or weighted mean of the extracted point cloud data.

[0012] [Item 5] The control device is The travel control system according to item 3, which determines the position of the characteristic points by detecting the characteristic shape of the work machine or a member attached to the work machine based on the extracted point cloud data.

[0013] [Item 6] The control device is A driving control system according to any one of items 3 to 5, wherein the point cloud data acquired from the LiDAR sensor is filtered by downsampling the point cloud data.

[0014] [Item 7] The control device is While the aforementioned work vehicle is in motion, the angle is calculated sequentially. A driving control system according to any one of items 3 to 6, which performs the filtering of point cloud data by extracting point cloud data within a predetermined angle range from the previously calculated angle.

[0015] [Item 8] The control device is While the aforementioned work vehicle is in motion, the angle is calculated sequentially. A driving control system according to any one of items 3 to 7, which performs the filtering of point cloud data by extracting point cloud data within a predetermined distance range from the previously calculated position of the feature point.

[0016] [Item 9] The control device is The trajectory of the feature point is obtained when the work vehicle is traveling along a curve. Based on the trajectory of the feature point, the position of the rotation center of the feature point is calculated. A driving control system according to any one of items 1 to 8, which calculates the angle based on the position of the rotation center of the feature point.

[0017] [Item 10] The control device is A driving control system according to any one of items 1 to 9, which acquires information on the position of each reflection point based on the distance and direction information of each reflection point from the LiDAR sensor, as indicated by the point cloud data acquired from the LiDAR sensor.

[0018] [Item 11] The aforementioned point cloud data is two-dimensional point cloud data including two-dimensional positional information, as described in any one of items 1 to 10 of the driving control system.

[0019] [Item 12] The control device is A driving control system according to any one of items 1 to 11, which generates a driving path for the work vehicle based on the calculated angle.

[0020] [Item 13] The travel control system according to any one of items 1 to 12, wherein a marker member located within the sensing range of the LiDAR sensor is attached to the work machine.

[0021] [Item 14] The control device is A driving control system according to any one of items 1 to 13, which causes the calculated angle to be displayed on a display device of the work vehicle.

[0022] [Item 15] A driving control system described in any one of items 1 to 14, Running gear including the steering wheels, A drive unit that drives the aforementioned traveling device and Equipped with, The control device controls the steering of the steering wheel by controlling the drive device based on the calculated angle, in a work vehicle.

[0023] [Item 16] The aforementioned work vehicle has a connecting part for connecting the aforementioned work machine, The aforementioned work machine is connected to the work vehicle so as to be rotatable around the connecting part, The work vehicle according to item 15, wherein the relative position of the connecting part of the work vehicle with respect to the vehicle body can be switched between when work using the work machine is being performed and when work is not being performed.

[0024] [Item 17] A method for controlling the movement of a work vehicle to which a work implement is attached, which is performed by one or more computing devices, The aforementioned work machine is connected to the work vehicle so as to be rotatable relative to the work vehicle, Based on the point cloud data acquired from one or more LiDAR sensors attached to the work vehicle, which output point cloud data indicating the surrounding environment of the work vehicle including at least a part of the work machine, the position of the feature points of the work machine is determined. Based on the position of the aforementioned feature point, the angle between the orientation of the work vehicle and the orientation of the work machine is calculated. Methods that include...

[0025] [Item 18] A computer program executed by a processor in a control device that controls the movement of a work vehicle to which a work machine is attached, The aforementioned work machine is connected to the work vehicle so as to be rotatable relative to the work vehicle, The aforementioned processor, Based on the point cloud data acquired from one or more LiDAR sensors attached to the work vehicle, which output point cloud data indicating the surrounding environment of the work vehicle including at least a part of the work machine, the position of the feature points of the work machine is determined. Based on the position of the aforementioned feature point, the angle between the orientation of the work vehicle and the orientation of the work machine is calculated. A computer program that executes something.

[0026] [Item 19] A control device that performs the method described in item 17.

[0027] [Item 20] A computer program executed by a computer that controls the movement of a work vehicle to which a work machine is attached, A computer program that causes the computer to perform the steps described in item 17.

[0028] [Item 21] A computer program medium executed by a computer that controls the movement of a work vehicle to which a work machine is attached, A computer program medium that causes the computer to perform the steps of the method described in item 17.

[0029] [Item 22] A system for controlling the movement of a work vehicle to which a work machine is attached, One or more LiDAR sensors attached to the work vehicle, which output point cloud data showing the surrounding environment of the work vehicle including at least a part of the work machine, The control device described in item 19 and A route generation system having the following features.

[0030] [Item 23] A control device for controlling the movement of a work vehicle to which a work machine is attached, The aforementioned work machine is connected to the work vehicle so as to be rotatable relative to the work vehicle, A means for determining the position of feature points of the work machine based on point cloud data acquired from one or more LiDAR sensors attached to the work vehicle and outputting point cloud data showing the surrounding environment of the work vehicle including at least a part of the work machine, A means for calculating the angle between the orientation of the work vehicle and the orientation of the work machine based on the position of the aforementioned feature point, A control device having

[0031] [Item 24] The control device according to item 23, further comprising means for controlling the movement of the work vehicle based on the calculated angle.

[0032] [Item 25] A travel control system for controlling the movement of a work vehicle to which a work machine is attached, The control device described in item 24, A drive system that drives the running gear, including the steering wheels Equipped with, The control device is a driving control system that controls the steering of the steering wheel by controlling the drive device based on the calculated angle.

[0033] Comprehensive or specific embodiments of the present invention may be realized by apparatus, systems, methods, integrated circuits, computer programs, or computer-readable non-temporary storage media, or any combination thereof. Computer-readable storage media may include volatile storage media or non-volatile storage media. An apparatus may consist of multiple devices. If an apparatus consists of two or more devices, these two or more devices may be located in a single device or in two or more separate devices. [Effects of the Invention]

[0034] According to embodiments of the present invention, a travel control system, a work vehicle, a travel control method, and a computer program are provided that can control the travel of a work vehicle to which a work machine is attached, even when the work machine is rotatably attached to the work vehicle. [Brief explanation of the drawing]

[0035] [Figure 1A] This is a schematic top view of a work vehicle and a work machine connected to the work vehicle in an embodiment of the present invention. [Figure 1B] This is a schematic top view of a work vehicle and a work machine connected to the work vehicle in an embodiment of the present invention. [Figure 1C] This is a schematic front view of a work machine in an embodiment of the present invention. [Figure 1D] This is a schematic perspective view of a work machine in an embodiment of the present invention. [Figure 2] This flowchart shows an example of a procedure for calculating the angle β between the orientation of the work vehicle and the orientation of the work machine according to an embodiment of the present invention. [Figure 3A] This is a schematic diagram illustrating the procedure for calculating the angle β according to an embodiment of the present invention. [Figure 3B] This diagram schematically illustrates an example of the relationship between the sensor coordinate system and the vehicle coordinate system. [Figure 4A] This block diagram shows a schematic configuration example of a driving control system according to an embodiment of the present invention. [Figure 4B] This is a block diagram showing an example of the configuration of a control device in a driving control system according to an embodiment of the present invention. [Figure 5] This is a schematic diagram showing another configuration example of a driving control system according to an embodiment of the present invention. [Figure 6A] This flowchart shows an example of a procedure for calculating the angle β between the orientation of the work vehicle and the orientation of the work machine according to an embodiment of the present invention. [Figure 6B] This is a schematic diagram illustrating the processes that may take place in step S100. [Figure 7]This flowchart shows an example of a procedure for calculating the angle β between the orientation of the work vehicle and the orientation of the work machine according to an embodiment of the present invention. [Figure 8] This is a schematic diagram illustrating an example of the process performed in step S220. [Figure 9A] This is a schematic diagram illustrating an example of the process performed in step S220. [Figure 9B] This is a schematic diagram illustrating an example of the process performed in step S220. [Figure 10] This is a schematic diagram illustrating an example of the process performed in step S240. [Figure 11A] This is a schematic diagram illustrating an example of the process performed in step S240. [Figure 11B] This is a schematic diagram illustrating an example of the process performed in step S240. [Figure 11C] This is a schematic diagram illustrating an example of the process performed in step S240. [Figure 12A] This is a schematic diagram illustrating an example of the process performed in step S240. [Figure 12B] This is a schematic diagram illustrating an example of the process performed in step S240. [Figure 12C] This is a schematic diagram illustrating an example of the process performed in step S240. [Figure 13] This block diagram shows an example of a procedure for calculating the angle β between the orientation of a work vehicle and the orientation of a work machine, according to an embodiment of the present invention. [Figure 14] This is a schematic diagram illustrating the method for calculating the position of the pivot center of a work machine relative to the work vehicle. [Figure 15] This is a schematic diagram illustrating the method for calculating the position of the pivot center of a work machine relative to the work vehicle. [Figure 16]This diagram schematically illustrates an example of a work vehicle in which the position of the pivot center of the work machine relative to the work vehicle's body can be switched. [Figure 17] This is a schematic side view showing an example of a work vehicle in an embodiment of the present invention. [Figure 18] This is a block diagram schematically showing an example configuration of a work vehicle and work machine. [Modes for carrying out the invention]

[0036] (Definition of terms) In this specification, “work vehicle” means a vehicle used to perform work in a work area. “Work area” is any place where work can be performed, such as a field, forest, or construction site. “Field” is any place where agricultural work can be performed, such as an orchard, farm, rice paddy, grain farm, or pasture. A work vehicle may be agricultural machinery such as a tractor, rice transplanter, combine harvester, riding cultivator, or riding mower, or a vehicle used for non-agricultural purposes, such as a construction vehicle or snowplow. A work vehicle may be configured to be equipped with work implements (also called “working devices” or “implements”) on at least one of its front and rear ends, depending on the work being performed. In particular, work implements attached to agricultural tractors are sometimes called “agricultural implements.” The act of a work vehicle moving while performing work with work implements may be referred to as “working movement.” The “operation” of a work vehicle includes not only the movement of the work vehicle but also other operations.

[0037] There are two main types of methods for connecting implements to work vehicles: "direct mounting" and "towing." In the direct mounting method, the implement is mounted on the front or rear of the work vehicle, with its orientation fixed relative to the orientation of the work vehicle. Implements connected in the direct mounting method are generally configured not to touch the ground while the work vehicle is moving (i.e., driving). In the towing method, the implement is connected to the rear of the work vehicle, with its orientation not fixed relative to the orientation of the work vehicle, and the implement is towed by the work vehicle. Towing implements may have wheels. Towing implements may or may not have their own power source for movement (driving).

[0038] In this specification, unless otherwise specified, the "orientation" of a work vehicle or work machine refers to the orientation of the work vehicle or work machine in a two-dimensional coordinate system. For example, it may refer to the orientation of the work vehicle or work machine as projected onto the xy-plane (i.e., the horizontal plane) where the direction opposite to the direction of gravity (vertically upward) is defined as the +z direction.

[0039] "Automated driving" means that the vehicle's movement is controlled by a control device, without manual operation by the driver. During automated driving, not only the vehicle's movement but also the operation of work (e.g., the operation of work equipment) may be controlled automatically. The movement of the vehicle under automated driving conditions is referred to as "automated driving." The control device can control at least one of the following necessary for the vehicle's movement: steering, adjustment of driving speed, starting and stopping the vehicle. When controlling a work vehicle equipped with work equipment, the control device may also control operations such as raising and lowering the work equipment and starting and stopping the operation of the work equipment. Driving under automated driving conditions may include not only driving the vehicle along a predetermined route toward a destination but also driving while following a target. In addition to automated driving mode, a vehicle performing automated driving may also operate in manual driving mode, where it is driven by the driver's manual operation. Driving under the driver's manual operation is referred to as "manual driving." "Driver's manual operation" includes not only manual operation by the driver on the vehicle but also remote operation by an operator outside the vehicle. A vehicle performing automated driving conditions may be driven partially based on the driver's manual operation. "Automatic steering" refers to the steering of a vehicle by a control device, without manual operation by the driver. Part or all of the control device may be located outside the vehicle. Communication, such as control signals, commands, or data, may take place between the external control device and the vehicle. A vehicle capable of autonomous driving may operate autonomously, sensing its surroundings without human intervention in controlling its movement. A vehicle capable of autonomous driving can operate unmanned. Obstacle detection and obstacle avoidance may occur during autonomous driving.

[0040] A "crop row" refers to a row of crops, trees, or other plants growing in a field such as an orchard or farm, or in a forest. In this specification, the concept of a "crop row" includes a "tree row."

[0041] (Embodiment) Embodiments of the present invention will be described below. However, unnecessarily detailed descriptions may be omitted. For example, detailed descriptions of already well-known matters and redundant descriptions of substantially identical configurations may be omitted. This is to avoid the following description becoming unnecessarily verbose and to facilitate understanding for those skilled in the art. The inventors provide the accompanying drawings and the following description so that those skilled in the art can fully understand the present invention, and not to limit the subject matter described in the claims. In the following description, components having the same or similar function are denoted by the same reference numerals.

[0042] The following embodiments are illustrative, and the technology of the present invention is not limited to these embodiments. For example, the numerical values, shapes, materials, steps, and order of steps shown in the following embodiments are merely examples, and various modifications are possible as long as they do not create a technical inconsistency. Furthermore, it is possible to combine one embodiment with another.

[0043] [Driving control system] A travel control system according to an embodiment of the present invention will be described. The travel control system according to an embodiment of the present invention controls the movement of a work vehicle to which a work implement is attached.

[0044] With reference to Figures 1A, 1B, 1C, and 1D, examples of work vehicles and work machines to which the travel control system according to embodiments of the present invention may be applied will be described. Figures 1A and 1B are schematic top views (i.e., schematic views in a plane perpendicular to the vertical direction) of a work vehicle 100 and a work machine 300 connected to the work vehicle 100. Figure 1C is a schematic front view of the work machine 300, and Figure 1D is a schematic perspective view of the work machine 300.

[0045] As shown in Figures 1A and 1B, the implement 300 is rotatably attached to the work vehicle 100. That is, the implement 300 is attached to the work vehicle 100 in such a way that its orientation θ2 is not fixed relative to the orientation θ1 of the work vehicle 100. In this example, the implement 300 is attached to the rear of the work vehicle 100. Typically, the implement 300 is towed to the work vehicle 100. Figure 1A shows a state where the orientation θ1 of the work vehicle 100 and the orientation θ2 of the implement 300 coincide, and Figure 1B shows a state where the orientation θ1 of the work vehicle 100 and the orientation θ2 of the implement 300 are different. The fact that the implement 300 is rotatable relative to the work vehicle 100 means that the angle β between the orientation of the work vehicle 100 and the orientation of the implement 300 can change.

[0046] In the illustrated example, implement 300 is a sprayer. The implement 300, being a sprayer, is used, for example, towed by a work vehicle 100 within a field such as an orchard, and to spray pesticides on crops (e.g., fruit trees) while traveling between multiple rows of crops (e.g., rows of fruit trees) within the field. It should be noted that the embodiments of the present invention are not limited to this example and can be applied to various implements.

[0047] The work vehicle 100 is equipped with one or more LiDAR sensors 140. The LiDAR sensors 140 output point cloud data showing the three-dimensional structure of the environment surrounding the work vehicle 100, including at least a portion of the work machine 300. That is, the LiDAR sensors 140 include at least a portion of the work machine 300 in their sensing range. The work vehicle 100 may further have LiDAR sensors that do not include the work machine 300 in their sensing range (for example, LiDAR sensors that sense only the area in front of the work vehicle 100).

[0048] In the examples in Figures 1A and 1B, in the three-dimensional Cartesian coordinate system fixed to the work vehicle 100, the direction opposite to the direction of gravity (i.e., vertically upward) is defined as the +z direction, and the direction of travel of the work vehicle 100 is defined as the +x direction. The origin of the three-dimensional Cartesian coordinate system fixed to the work vehicle 100 is located at the front of the work vehicle 100 in the figures, but is not limited to this and can be set arbitrarily. The orientation θ1 of the work vehicle 100 and the orientation θ2 of the work machine 300 are defined as angles with respect to the +x direction in the xy-plane. In the figures, the orientation θ1 of the work vehicle 100 and the orientation θ2 of the work machine 300 are indicated by arrows. Since the direction of travel of the work vehicle 100 and the orientation θ1 of the work vehicle 100 coincide, θ1 = 0° in this example. However, the orientation of the work vehicle 100 or the work machine 300 can be defined as an angle with respect to the reference direction, not limited to this example. The orientation θ1 of the work vehicle 100 is the longitudinal direction of the work vehicle 100, and is, for example, the direction of the straight line CL1 connecting the center points of the left and right front wheels 104F and the center points of the left and right rear wheels 104R. The orientation θ2 of the work implement 300 is the longitudinal direction of the work implement 300, and is, for example, the direction of the straight line CL2 passing through the center points of the left and right wheels 304R.

[0049] As shown in the examples in Figures 1A and 1B, the angle β can constantly change while the work vehicle 100, to which the work machine 300 is rotatably connected, is in motion. To control the movement of such a work vehicle 100, it is necessary to calculate the angle β. As will be described below, the travel control system according to an embodiment of the present invention can calculate the angle β when the work vehicle 100 is in motion.

[0050] Figure 2 is a flowchart illustrating an example of a procedure for calculating the angle β between the orientation of the work vehicle 100 and the orientation of the work machine 300 according to an embodiment of the present invention. Figure 3A is a schematic diagram illustrating the procedure for calculating the angle β according to an embodiment of the present invention, and is a schematic top view of the work vehicle 100 and the work machine 300 connected to the work vehicle 100.

[0051] In the example shown in Figure 3A, the xy plane of the sensor coordinate system fixed to the LiDAR sensor 140 is shown. In the illustrated example, the direction opposite to the direction of travel of the work vehicle 100 is defined as the +x direction. The parameters for the coordinate transformation from the sensor coordinate system fixed to the LiDAR sensor 140 to the vehicle coordinate system fixed to the work vehicle 100 can be determined by performing calibration before the work vehicle 100 begins normal operation (for example, during a trial run). Figure 3B schematically shows an example of the relationship between the sensor coordinate system and the vehicle coordinate system.

[0052] Figure 3A schematically shows an example of the range Rsa sensed by the LiDAR sensor 140a. The range Rsa sensed by the LiDAR sensor 140a includes at least a portion of the work machine 300. Although only one LiDAR sensor 140 is shown in Figure 3A for simplicity, this is not an example, and multiple LiDAR sensors 140 may be mounted on the work vehicle 100.

[0053] As shown in Figures 2 and 3A, the procedure for calculating the angle β between the orientation of the work vehicle 100 and the orientation of the work machine 300 is to acquire point cloud data (step S100) that shows the surrounding environment of the work vehicle 100, including at least a part of the work machine 300, output from the LiDAR sensor 140, and to calculate the feature points P of the work machine 300 based on the point cloud data acquired in step S100. G The position of (step S200) and the feature point P determined in step S200 G This includes calculating the angle β between the orientation of the work vehicle 100 and the orientation of the work machine 300 based on the position of (step S300). In this specification, calculating (or determining) based on something means that it has some influence on the calculation (or determination), and does not exclude other factors that may also influence the calculation (or determination). For example, in step S200, based on the point cloud data acquired in step S100 and other factors, feature point P GThe position of may be determined. The same applies when the phrase "based on" is used for purposes other than calculation or determination.

[0054] A "feature point of the work machine 300" is one or more points used to identify the position of the work machine 300. The feature points of the work machine 300 may be defined by, for example, the characteristic shape (e.g., edge, corner, etc.) of the work machine 300 or a component attached to the work machine 300, or they may be characteristic points determined or calculated from point cloud data acquired by sensing the work machine 300 or a component attached to the work machine 300. Here, "a component attached to the work machine 300" refers to a component attached in a fixed positional relationship to the work machine 300. Specific examples of feature points of the work machine 300 will be described later.

[0055] The driving control system according to an embodiment of the present invention calculates the angle β using point cloud data output from a LiDAR sensor, thereby reducing the processing load required for calculation compared to, for example, the case where image data is used for calculation. When calculating the angle β using image data, for example, a marker member attached to the work machine may be used. In such cases, if dirt or other contaminants adhere to the marker member, the accuracy of the calculation may decrease. According to the embodiment of the present invention, even when a marker member attached to the work machine is used, point cloud data output from a LiDAR sensor is used, so the influence of dirt or other contaminants on the marker member is small. Furthermore, according to the embodiment of the present invention, the angle β can be calculated without attaching a positioning device (e.g., a GNSS unit) to the work machine, so there is no need to prepare additional wiring, for example. Therefore, the increase in cost for calculating the angle β can be suppressed.

[0056] Figure 4A is a block diagram showing a schematic configuration example of a driving control system 1000 according to an embodiment of the present invention. Figure 4B is a block diagram showing a configuration example of a control device 180 included in the driving control system 1000.

[0057] As shown in Figure 4A, the driving control system 1000 includes one or more LiDAR sensors 140 mounted on the work vehicle 100 and a control device 180 that controls the driving of the work vehicle 100. The control device 180 may include, for example, an ECU mounted on the work vehicle 100. For example, a group of ECUs mounted on the work vehicle 100 may function as the control device 180 and, in cooperation with the LiDAR sensors 140, function as the driving control system 1000 of the work vehicle 100. The control device 180 and the LiDAR sensors 140 may be connected to communicate with each other via a bus 810.

[0058] Figure 4A also shows a storage device 870 in which information acquired by the control device 180 is recorded. The storage device 870 may be included in the travel control system 1000 or it may be an external component of the travel control system 1000. The storage device 870 may be mounted, for example, on the work vehicle 100 or the work machine 300. In such a case, the storage device 870 may be connected to the control device 180 so as to be able to communicate with each other via the bus 810. The storage device 870 may be located outside the work vehicle 100 and the work machine 300. A storage device 870 located outside the work vehicle 100 and the work machine 300 may be connected to the control device 180 via a communication network.

[0059] Figure 4A also shows a sensor group 150 that detects the status of the work vehicle 100 and outputs sensor data related to the status of the work vehicle 100. The sensor group 150 includes one or more sensors. Some or all of the sensor group 150 may be included in the driving control system 1000 or may be an external element of the driving control system 1000. The sensor group 150 is mounted on the work vehicle 100 and may be connected to the control device 180 and / or the LiDAR sensor 140 so as to be able to communicate with each other via the bus 810.

[0060] The sensor group 150 includes, for example, an IMU (Inertial Measurement Unit) 151. The IMU 151 may include a 3-axis accelerometer and a 3-axis gyroscope. The IMU 151 may also include an orientation sensor such as a 3-axis geomagnetic sensor. The IMU 151 functions as a motion sensor and can output signals indicating various quantities such as acceleration, velocity, displacement, and attitude of the work vehicle 100. Instead of the IMU 151, a 3-axis accelerometer and a 3-axis gyroscope may be provided separately.

[0061] The sensor group 150 is not limited to the IMU 151 and may include various sensors mounted on the work vehicle 100. For example, the sensor group 150 may include one or more sensors selected from among a steering wheel sensor, steering angle sensor, axle sensor, temperature sensor, illuminance sensor, fuel sensor, water temperature sensor, oil level gauge, engine speed sensor, vehicle speed sensor, battery voltage sensor, shuttle sensor, hand accelerator sensor, accelerator pedal sensor, main transmission lever sensor, sub-transmission lever sensor, seat belt sensor, PM sensor, acceleration sensor, angular velocity sensor, and geomagnetic sensor. The sensor group 150 may further include sensors that output sensor data regarding the status of the work machine 300. The sensor group 150 may also include one or more sensors mounted on the work machine 300. For example, the sensor group 150 may include an IMU attached to the work machine 300.

[0062] The control device 180 in the travel control system according to an embodiment of the present invention can control the travel of the work vehicle 100 based on a calculated angle β. For example, the control device 180 can generate a path (i.e., a target path) on which the work vehicle 100 travels based on the calculated angle β. For example, the control device 180 can control the steering of the front wheel 104F, which is a steering wheel, by controlling the drive system that drives the travel system (including the front wheel 104F and the rear wheel 104R) of the work vehicle 100 based on the calculated angle β.

[0063] The driving control system according to an embodiment of the present invention can be used not only when the work vehicle 100 is driving automatically, but also when the work vehicle 100 is driving manually. For example, the control device 180 may display the calculated angle β information on a display device of the work vehicle 100. The control device 180 may also display the calculated angle β information on an operation terminal of a driver (operator) outside the work vehicle 100. The driver on the work vehicle 100 or the driver (operator) outside the work vehicle 100 who operates the work vehicle 100 can operate the work vehicle 100 while looking at the angle β information displayed on the display device or operation terminal.

[0064] In the example shown in Figure 4A, the control device 180 includes multiple ECUs. The multiple ECUs included in the control device 180 may include, for example, ECUs 181 to 184 shown in Figure 18, which will be described later. The control device 180 is not limited to this example and may be a single ECU or other computing device. Figure 4B is a block diagram showing an example configuration of such a control device 180. In the example of Figure 4B, the control device 180 includes a processor 281, a ROM (Read Only Memory) 283, a RAM (Random Access Memory) 285, a communication device 287, and a storage device 289. These components may be interconnected via a bus 290.

[0065] The processor 281 is a semiconductor integrated circuit, also referred to as a central processing unit (CPU) or microprocessor. The processor 281 may include an image processing unit (GPU). The processor 281 sequentially executes a computer program describing a predetermined set of instructions stored in the ROM 283, thereby realizing the processing performed by the driving control system according to an embodiment of the present invention. The control device 180 may comprise a plurality of processors 281. The processing performed by the driving control system according to an embodiment of the present invention may be performed collaboratively by the plurality of processors 281. Part or all of the processor 281 may be an FPGA (Field Programmable Gate Array), ASIC (Application Specific Integrated Circuit), or ASSP (Application Specific Standard Product) equipped with a CPU.

[0066] The communication device 287 is an interface for data communication between the control device 180 and an external computing device. The communication device 287 can perform wired communication such as CAN (Controller Area Network), or wireless communication compliant with the Bluetooth® standard and / or Wi-Fi® standard.

[0067] The storage device 289 can store point cloud data acquired from the LiDAR sensor 140, sensor data acquired from the sensor group 150, data during processing, etc. The storage device 289 includes, for example, a hard disk drive or a non-volatile semiconductor memory. In this example, the storage device 289 may also function as the storage device 870 in the example in Figure 4A.

[0068] The hardware configuration of the control device 180 is not limited to the example above. It is not necessary for part or all of the control device 180 to be mounted on the work vehicle 100. By utilizing the communication device 287, one or more computing devices located outside the work vehicle 100 can function as part or all of the control device 180. For example, one or more server computers and / or computing devices included in a terminal device connected to a network can function as part or all of the control device 180. Alternatively, one or more computing devices mounted on the work vehicle 100 may perform all the functions required of the control device 180.

[0069] Figure 5 is a schematic diagram showing another configuration example of a driving control system according to an embodiment of the present invention. The system shown in Figure 5 includes a work vehicle 100, other work vehicles 700, a server computer 500, and a plurality of terminal devices 600. The terminal devices 600 may be portable or fixed. Some or all of the functions of the control device 180 shown in Figure 4B may be implemented by one or more computing devices connected to the communication device 287 of the control device 180 in the work vehicle 100 via a communication network 800. Such computing devices may be the server computer 500 or the terminal devices 600. Other work vehicles (e.g., agricultural machinery) 700 may be connected to such a communication network 800. Communication may take place between the control device 180 in the work vehicle 100 and the other work vehicles 700. Some of the data used for processing by the control device 180 in the work vehicle 100 may be provided to the control device 180 from the other work vehicles 700 via the communication network 800.

[0070] As shown in Figure 4B, one example of a "control device" in an embodiment of the present invention is a computing device comprising at least one processor and at least one memory that stores a computer program (code) that defines a control process executed by the processor. The "control device" may also be a computing device comprising a hardware accelerator such as an FPGA (Field-Programmable Gate Array), ASSP (Application Specific Standard Product), or ASIC (Application-Specific Integrated Circuit) configured to execute the control process.

[0071] In embodiments of the present invention, "processor" refers to hardware electronic circuits such as a CPU (Central Processing Unit), GPU (Graphics Processing Unit), DSP (Digital Signal Processor), ISP (Image Signal Processor), or NPU (Neural Network Processing Unit). "Memory" refers to hardware electronic circuits such as ROM (Read Only Memory) or RAM (Random Access Memory). Part of the memory may be a storage medium connected to the processor by wiring or a network. These hardware electronic circuits may be implemented by one or more integrated circuits (ICs) or large-scale integrated circuits (LSIs). Each functional unit or block and associated component within the electronic circuit may be manufactured individually as separate integrated circuit chips, or some or all of these functional units or blocks may be combined and manufactured as a single integrated circuit chip.

[0072] A program defining the operation of the processor is designed to cause the processor to perform one or more functions, operations, steps, or processes in embodiments of the present invention.

[0073] The details and specific examples of the processes performed in each of the steps shown in Figure 2 will be explained below.

[0074] (Acquisition of point cloud data) Referring to Figures 3A, 6A, and 6B, examples of processes that may be performed in step S100 will be described. In step S100, the control device 180 acquires point cloud data from the LiDAR sensor 140 that shows the surrounding environment of the work vehicle 100, including at least a portion of the work machine 300. Figure 6A is a flowchart of an example of a procedure for calculating the angle β between the orientation of the work vehicle 100 and the orientation of the work machine 300 according to an embodiment of the present invention. The flowchart in Figure 6A differs from the flowchart in Figure 2 in that step S100 includes steps S120, S140, and S160. Figure 6B is a schematic diagram for illustrating the processes that may be performed in step S100.

[0075] As shown in Figure 6A, in step S100, the following steps S120, S140, and S160 may be performed.

[0076] In step S120, the control device 180 acquires point cloud data from the LiDAR sensor 140 that shows the surrounding environment of the work vehicle 100, including at least a portion of the work machine 300. The driving control system according to the embodiment of the present invention can sequentially calculate the angle β while the work vehicle 100 is moving. For example, while the work vehicle 100 is moving, the surrounding environment is scanned with a laser beam using the LiDAR sensor 140. This makes it possible to obtain information on the distance and direction to the reflection point of the surface of an object (in this case, including at least a portion of the work machine 300) located within the sensing range of the LiDAR sensor 140. That is, the LiDAR sensor 140 calculates each reflection point Pr i Sensor data indicating distance and direction to (dr i θr i Outputs (i=1,2,···,n). Here, the reflection point Pr i The distance to dr i, reflection point Pr i has an orientation of θr i .

[0077] In step S140, the control device 180 obtains information on the position of each reflection point based on the distance and direction information of each reflection point from the LiDAR sensor 140 indicated by the point cloud data obtained from the LiDAR sensor 140 in step S120. For example, as shown in FIG. 6B, the control device 180 uses the sensor data (dr i , θr i ) output from the LiDAR sensor 140 to convert it into point cloud data including the position information (x i , y i ) of each reflection point in the two-dimensional coordinate system represented in the sensor coordinate system fixed to the LiDAR sensor 140. Note that if the LiDAR sensor 140 outputs the point cloud data of the distance and orientation to each reflection point after converting it into the point cloud data of the coordinates of the position of each reflection point, the conversion process by the control device 180 is omitted.

[0078] As will be described later, if the information on the position of each reflection point in the two-dimensional coordinate system is obtained, the position of the feature point P G of the work machine 300 can be determined. Therefore, a two-dimensional LiDAR sensor can be used as the LiDAR sensor 140. In such a case, the point cloud data obtained from the LiDAR sensor 140 is two-dimensional point cloud data including two-dimensional position information. Of course, a three-dimensional LiDAR sensor may be used as the LiDAR sensor 140. For example, part or all of the LiDAR sensors provided in the work vehicle 100 can also be used as the LiDAR sensor of the travel control system according to the embodiment of the present invention. When a new LiDAR sensor is prepared to calculate the angle β, since the two-dimensional LiDAR sensor is less expensive than the three-dimensional LiDAR sensor, the increase in cost for calculating the angle β can be suppressed by using the two-dimensional LiDAR sensor.

[0079] In step S160, the control device 180 may perform a correction based on the IMU data output from the IMU 151, according to the tilt angle of the sensor coordinate system fixed to the LiDAR sensor 140. For example, when the work vehicle 100 is traveling on an inclined surface or uneven ground, and the xy plane in the sensor coordinate system fixed to the LiDAR sensor 140 is significantly tilted from the horizontal plane, the coordinate information of the position of each reflection point can be obtained with high accuracy by performing a correction according to the tilt angle of the sensor coordinate system. The IMU data output from the IMU 151 may include information such as the acceleration, velocity, displacement, attitude, and measurement time (timestamp) of the work vehicle 100. Based on the attitude information of the work vehicle 100 included in the IMU data (e.g., roll angle information), the control device 180 can determine the tilt angle of the LiDAR sensor 140 (i.e., the tilt angle of the sensor coordinate system). The IMU data is output at a frequency of, for example, several tens to several thousand times per second. This output period is generally shorter than the output period of the scan data from the LiDAR sensor 140. Alternatively, if an IMU is also attached to the work machine 300, the relative attitude angle (e.g., roll angle) of the work machine 300 with respect to the work vehicle 100 can be calculated based on the IMU data output from the IMU 151 and the IMU data output from the IMU attached to the work machine 300, and the tilt angle of the sensor coordinate system can be corrected using the calculated value. Note that the processing in step S160 is optional and can be omitted.

[0080] (Determination of the location of feature points) Referring to Figure 7, an example of the processing that may be performed in step S200 will be explained. In step S200, the control device 180 uses the point cloud data acquired in step S100 to identify the feature points P of the work machine 300. G The position is determined. Figure 7 is a flowchart showing an example of a procedure for calculating the angle β between the orientation of the work vehicle 100 and the orientation of the work machine 300 according to an embodiment of the present invention. The flowchart in Figure 7 differs from the flowchart in Figure 2 in that step S200 has steps S220 and S240.

[0081] As shown in Figure 7, in step S200, the following steps S220 and S240 may be performed.

[0082] In step S220, the control device 180 extracts data indicating the reflection points on the surface of the work machine 300 by filtering the point cloud data acquired in step S100. For example, as described above, point cloud data of the two-dimensional coordinates of each reflection point in the sensor coordinate system fixed to the LiDAR sensor 140 is acquired and filtered.

[0083] For example, the control device 180 filters the point cloud data acquired from the LiDAR sensor 140 by downsampling it. Downsampling can be performed using a voxel grid filter, for example. In a voxel grid filter, the following processes are performed: First, the three-dimensional space in the sensor coordinate system is divided into multiple voxels of a certain size. The length of one side of the cube that makes up each voxel can be set arbitrarily, but for example, it can be between 1 cm and 10 cm, or for example, about 5 cm. If each voxel contains multiple points, those multiple points are replaced with a single point. For example, multiple points contained in each voxel are replaced with a single point located at the centroid of that voxel. By downsampling the point cloud data, the number of points in the point cloud data can be reduced, and processing can be sped up. By using a voxel grid filter, the number of points can be uniformly reduced from the point cloud data acquired from the LiDAR sensor 140. Note that it is not limited to a voxel grid filter, and known downsampling methods may also be used. If the data size of the point cloud data acquired from the LiDAR sensor 140 is not a problem, the downsampling process may be omitted.

[0084] Examples of other filtering methods will be described with reference to Figures 8, 9A, and 9B. The filtering processes shown in Figures 8, 9A, and 9B can be performed in combination with the downsampling process described above. Figures 8, 9A, and 9B are schematic diagrams illustrating an example of the process performed in step S220.

[0085] As shown in Figures 8, 9A, and 9B, for example, the control device 180 filters the point cloud data acquired from the LiDAR sensor 140 by the coordinates of the reflection points. As shown in Figures 8, 9A, and 9B, it extracts reflection points located within a predetermined range in the xy plane of the sensor coordinate system fixed to the LiDAR sensor 140. In the figures, the predetermined range where the extracted reflection points are located is hatched. For example, in the example of Figure 8, reflection points located within the range x1 ≤ x ≤ x2 and y1 ≤ y ≤ y2 are extracted. In the example of Figure 9A, reflection points located within the range between equations (1) and (2) are extracted. In the example of Figure 9B, reflection points located within the range between equations (1), (2), and (3) are extracted. Here, the symbols in Figures 8, 9A, and 9B and in the equations represent the following: Point Pc: Center of rotation of the work machine 300 relative to the work vehicle 100. point P G0 : Characteristics of the 300 work machines calculated previously β0: Previously calculated angle β α: Angle that determines the extraction range d1: Length that determines the extraction range The x and y coordinates of point Pc are denoted as (xc, yc), and the characteristic point P of the work machine 300 is represented as P. G0 The x and y coordinates of (x G0 , y G0 This is expressed as follows. Angles β0 and α are angles with respect to the +x direction of the sensor coordinate system fixed to the LiDAR sensor 140.

[0086] The angle α and length d1 can be set appropriately depending on the range to be extracted (for example, depending on the size and position of the work machine 300). For example, they may be determined by the user entering a value. For example, the angle α may be determined based on the relationship between the distance D2 between the wheels 304R of the work machine 300 (see Figure 9A) and the angle α. Point cloud data may be filtered by extracting point cloud data within a predetermined angle range (β0±α in the illustrated example) from the previously calculated angle β0, as shown in the example in Figure 9A or Figure 9B. The position P of the previously calculated feature point can be used to filter the point cloud data. G0 Point cloud data may be filtered by extracting point cloud data within a predetermined distance range.

[0087] Angle β0 is the previously calculated angle β, and for example, if the control device 180 calculates angle β at predetermined time intervals, it may be the angle β calculated immediately before. Similarly, point P G0 These are feature points of the work machine 300 that were calculated previously. For example, if the control device 180 calculates the angle β and feature points at predetermined time intervals, these may be feature points that were calculated immediately before.

[0088] As shown in the examples in Figures 1A to 1D, the work machine 300 may be fitted with a marker member 322 located within the sensing range of the LiDAR sensor 140. The marker member 322 reflects the light emitted from the LiDAR sensor 140. Having the marker member 322 can facilitate the filtering process of the point cloud data described above. However, the marker member is not essential and can be omitted. In the illustrated example, the marker member 322 has a pair of columnar structures 321. The shape of the columnar structures 321 may be a rectangular prism (e.g., a triangular or square prism) or a cylinder. Only one columnar structure may be provided. The marker member 322 is preferably symmetrical with respect to an axis extending in the front-rear direction of the work machine 300. For example, the marker member 322 is preferably provided on an axis extending in the front-rear direction of the work machine 300. If the marker member 322 is not symmetrical with respect to the axis extending in the front-rear direction of the work machine 300, it is preferable to perform calibration in advance (when the work vehicle 100 is traveling in a straight line) to obtain parameters indicating the positional relationship between the marker member 322 and the LiDAR sensor 140.

[0089] In step S240, the control device 180 calculates the position of the feature points of the work machine 300 by calculating the arithmetic mean of the point cloud data extracted in step S220.

[0090] Specifically, the point cloud data extracted in step S220

number

number

[0091] By calculating the arithmetic mean of the point cloud data, feature points P GSince the position can be determined, the processing load can be suppressed.

[0092] Referring to Figure 10, another example of the process performed in step S240 will be illustrated.

[0093] In step S240, the control device 180 may calculate the position of the feature points of the work machine 300 by calculating the weighted average of the point cloud data extracted in step S220. The weighted average is the average calculated by assigning a weight to each data point. The upper part of Figure 10 schematically shows an example of calculating the arithmetic mean of point cloud data, and the lower part of Figure 10 schematically shows an example of calculating the weighted average for the same point cloud data. The horizontal axis of the figure indicates position, and the white circles indicate the distribution of the point cloud data extracted in step S220. Even if the work machine 300 has a symmetrical shape, if there is a bias in the number of point cloud data points on the left and right sides, as in the example in the figure, the result of calculating the arithmetic mean (shown by black circles), as shown in the upper part of Figure 10, is off the left and right center lines shown by the dashed lines. That is, feature point P G The deviation from the left and right centerlines becomes large. In such cases, the deviation of the feature points from the left and right centerlines can be suppressed by calculating a weighted average, as shown in the lower part of Figure 10. In the example in the lower part of Figure 10, the point cloud data is divided into left and right groups along the left and right centerlines, the arithmetic mean of each is calculated (the result is shown as a circle with hatched diagonal lines), and then the arithmetic mean of these is calculated (the result is shown as a black circle). The calculated feature points P G The deviation from the left and right centerlines is suppressed.

[0094] Other examples of the processing performed in step S240 will be described with reference to Figures 11A, 11B, and 11C, and Figures 12A, 12B, and 12C. As described below, the control device 180 may determine the position of feature points by detecting characteristic shapes of the work machine 300 or members attached to the work machine 300 based on the point cloud data extracted in step S220.

[0095] In the example shown in Figures 11A and 11C, as shown in Figure 11A, a marker member 322a located within the sensing range of the LiDAR sensor 140 is attached to the work machine 300. The marker member 322a has a pair of prismatic structures 321a1 and 321a2. On the left side of Figure 11B, the white circles schematically represent the point cloud data extracted in step S220. From these, as shown on the right side of Figure 11B, the reflection point of corner 321c1 of prismatic structure 321a1 and the reflection point of corner 321c2 of prismatic structure 321a2 are extracted to obtain feature point P G1 and feature point P G2 Determine the feature point P. G1 and feature point P G2 These are indicated by black circles. A known method can be used to extract the corner reflection points. Feature point P G1 and feature point P G2 Feature point P G It is sometimes referred to collectively as such. As shown in Figure 11C, feature point P G The angle β is calculated based on the position. The method for calculating angle β will be described later.

[0096] In the examples shown in Figures 12A to 12C, as shown in Figure 12A, the edges 323 of the work machine 300 or a member attached to the work machine 300 are used to determine feature points. On the left side of Figure 12B, the white circles schematically represent the point cloud data extracted in step S220. From these, as shown on the right side of Figure 12B, the reflection points of the edges 323 are extracted to determine feature points P G Determine the feature point P. G The black circle indicates the feature point P. G This may include multiple points. Known methods can be used to extract the reflection points of the edge. As shown in Figure 12C, feature point P G The angle β is calculated based on the position. The method for calculating angle β will be described later.

[0097] (Calculation of angle β) In step S300, the control device 180 determines the characteristic points P of the work machine 300 calculated in step S200. G Position (xG ,y G The angle β is calculated based on the following.

[0098] Angle β is, for example, the feature point P of the work machine 300. G The position of the work machine 300 and the center of rotation P of the work vehicle 100. c It is calculated based on the positional relationship with the position of the work machine 300. The pivot center P of the work machine 300 relative to the work vehicle 100. c The position is determined, for example, by the position of the coupling part that connects the work machine 300 to the work vehicle 100. Since the size and position information of the coupling part may be known to the user, the control device 180, for example, determines the pivot center P of the work machine 300 relative to the work vehicle 100 based on the user's input. c The control device 180 may acquire information on the position of the work machine 300. Alternatively, information on the size and position of the coupling part may be stored in a storage device outside or inside the work machine 100 as information associated with the model of the work machine 100. Based on the information acquired through communication with such storage device, the control device 180 determines the pivot center P of the work machine 300 relative to the work machine 100. c Information about the position may also be obtained. As another example, as will be described later with reference to Figures 14 and 15, the pivot center P of the work machine 300 relative to the work vehicle 100 c The position may be calculated based on the trajectory of the work vehicle 100 as it travels along a curve.

[0099] In the examples in Figures 8, 9A, and 9B, feature point P G The coordinates (x) of the position in the sensor coordinate system fixed to the LiDAR sensor 140. G ,y G ) in a coordinate system with the pivot center Pc as the origin, coordinate (x' G ,y' G By converting to ), the angle β can be calculated from the following formula.

number

[0100] Figure 13 is a block diagram illustrating an example of a procedure for calculating the angle β between the orientation of the work vehicle 100 and the orientation of the work machine 300 according to an embodiment of the present invention. The parameters obtained in each step are indicated by the same reference numerals as in steps S120, S140, S220, S240, and S300 of the flowcharts in Figures 6A and 7. The relational expressions used to calculate the parameters obtained in steps S140, S220, S240, and S300 are indicated by e140, e220, e240, and e300. The arrows to each step indicate input values ​​or referenced values. The filtering in step S220 corresponds to the example described with reference to Figure 9B. Note that the transformation using the inclination angle φ (see Figure 3B) of the sensor coordinate system with respect to the vertical direction in step S140 may be omitted (i.e., φ = 0).

[0101] It should be noted that the embodiments of the present invention are not limited to the example shown in Figure 13. When calculating the angle β sequentially, it is possible to perform a simplified process using the previous value without having to perform all of the processes shown in Figure 13 each time. For example, it is possible to calculate the angle β without performing the coordinate transformation in step S140.

[0102] Referring to Figures 14 and 15, the pivot center P of the work machine 300 relative to the work vehicle 100. c The method for calculating the position is explained below. Figures 14 and 15 show the pivot center P of the work machine 300 relative to the work vehicle 100. cThis is a schematic diagram illustrating the method for calculating the position of a feature point P when the work vehicle 100 is traveling along a curve. In this example, the control device 180 calculates the position of the feature point P G The trajectory is obtained, and feature points P G Based on its trajectory, feature point P G The position of the rotation center P2 is calculated. The control device 180 calculates the position of the feature point P G The position of the rotation center P2 is used as the pivot center of the work machine 300 relative to the work vehicle 100, and the angle β is used in calculating the angle β. Curved travel is travel involving the turning of the work vehicle 100. For example, it may travel in an S-shape or along a circular arc.

[0103] For example, as shown in the upper part of Figure 15, when the work vehicle 100 is traveling on a curve, characteristic point P G Obtain the trajectory. Feature point P G The trajectory is obtained in a two-dimensional plane (e.g., the horizontal plane). As shown in the lower part of Figure 15, the obtained feature points P G The circle representing the trajectory is determined using approximation (for example, least squares approximation). The center P2 of the determined circle is taken as the pivot center of the work machine 300 relative to the work vehicle 100. The method for determining the circle using the least squares method is well known to those skilled in the art, so a detailed explanation is omitted.

[0104] Even when the angle β is calculated sequentially, it is not necessary to calculate the position of the pivot center Pc each time. For example, it is sufficient to do so when the work implement 300 is connected to the work vehicle 100, or when the work implement 300 is replaced.

[0105] In this way, feature point P G Based on its trajectory, feature point P GBy calculating the position of the rotation center P2, the position of the pivot center of the implement 300 relative to the work vehicle 100 can be calculated with high accuracy. If the calculation is based solely on the vehicle specifications, the accuracy of calculating the pivot center position of the implement 300 relative to the work vehicle 100 may be insufficient. For example, even if the work vehicle and / or implement are of the same model, errors and variations may occur in the position of the pivot center of the implement 300 relative to the work vehicle 100 due to errors in the mounting position of the coupling part or play in the rotation axis. Characteristic point P when the work vehicle 100 is traveling on a curve G By using the trajectory information, the position of the pivot center of the work machine 300 relative to the work vehicle 100 can be calculated with greater accuracy.

[0106] Furthermore, depending on the type of implement 300, the position of the pivot center Pc of the implement 300 relative to the work vehicle 100 may be switched depending on whether work is being performed using the implement 300 or not. Figure 16 schematically shows a work vehicle 100 in which the relative position of the pivot center Pc of the implement 300 relative to the work vehicle 100 is switchable. In the example in Figure 16, the position of the pivot center Pc of the implement 300 relative to the work vehicle 100 can be switched between a relatively short distance (distance Lb) and a relatively long distance (distance Lb+L0). For example, in such a case, feature point P G Based on its trajectory, feature point P G Calculating the position of the rotation center P2 is particularly useful.

[0107] [Outline of the work vehicle configuration] Figure 17 is a schematic side view showing an example of a work vehicle 100. Figure 18 is a schematic block diagram showing an example configuration of the work vehicle 100 and the work machine 300. Figure 17 shows an example in which a directly mounted work machine 300a is connected to the work vehicle 100, but the following explanation also applies to the work vehicle 100 and work machine 300 described above, unless otherwise specified.

[0108] As shown in Figures 17 and 18, the work vehicle 100 includes a positioning device 110 (e.g., a GNSS unit) that outputs position data relating to the position of the work vehicle 100, a group of sensors 150 that detects the state of the work vehicle 100 and outputs sensor data, and a control device 180 that controls the operation of the work vehicle 100. The group of sensors 150 includes one or more sensors.

[0109] The work vehicle 100 may further be equipped with multiple external sensors that sense the surroundings of the work vehicle 100. "External sensors" are sensors that sense the external conditions of the work vehicle. In the example in Figure 17, the external sensors include multiple LiDAR sensors 140, multiple cameras 120, and multiple obstacle sensors 130.

[0110] In the example shown in Figure 18, the work vehicle 100 includes a positioning device 110, a camera 120, an obstacle sensor 130, a LiDAR sensor 140, a sensor group 150, a storage device 170, a control device 180, and an operating terminal 200, as well as a communication device 190, an operating switch group 210, and a drive device 240 (sometimes referred to as the "first drive device"). These components are connected to each other via a bus so as to be able to communicate with one another.

[0111] As shown in Figure 17, the work vehicle 100 comprises a body 101, a prime mover (engine) 102, and a transmission 103. The body 101 is provided with a running gear including wheels with tires 104 and a cabin 105. The running gear includes four wheels 104, axles that rotate the four wheels, and brakes that brake each axle. The wheels 104 include a pair of front wheels 104F and a pair of rear wheels 104R. Inside the cabin 105 are a driver's seat 107, a steering gear 106, an operating terminal 200, and a group of switches for operation. One or both of the front wheels 104F and the rear wheels 104R may be replaced with multiple wheels fitted with tracks (crawlers) instead of wheels with tires.

[0112] 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 propulsion force and travel speed of the work vehicle 100 by shifting gears. The transmission 103 can also switch the work vehicle 100 between forward and reverse.

[0113] The steering system 106 includes a steering wheel, a steering shaft connected to the steering wheel, and a power steering system that assists steering by the steering wheel. The front wheels 104F are steering wheels, and the direction of travel of the work vehicle 100 can be changed by changing their steering 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 system includes a hydraulic system or electric motor that supplies auxiliary 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 system or electric motor under control from a control device located inside the work vehicle 100.

[0114] 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 called a "three-point hitch" or "three-point link"), a PTO (Power Take Off) shaft, a universal joint, and a communication cable. The coupling device 108 allows the work implement 300 to be attached to and detached from the work vehicle 100. The coupling device 108 can change the position or orientation of the work implement 300 by raising and lowering the three-point hitch, for example, by a hydraulic system. Power can also be supplied from the work vehicle 100 to the work implement 300 via the universal joint. The work vehicle 100 can pull the work implement 300 and have the work implement 300 perform a predetermined task. The coupling device may be provided at the front of the vehicle body 101. In that case, the work implement can be connected to the front of the work vehicle 100.

[0115] The implement 300a shown in Figure 17 is a sprayer for spraying chemicals onto crops, but the implements connected to the work vehicle 100 are not limited to sprayers. For example, any implement such as a mower, seeder, spreader, rake, baler, harvester, plow, harrow, or rotary tiller can be connected to the work vehicle 100 and used.

[0116] The positioning device 110 receives satellite signals (also referred to as GNSS signals) transmitted from multiple GNSS satellites and performs positioning based on these satellite signals. GNSS is a general term for satellite positioning systems such as GPS (Global Positioning System), QZSS (Quasi-Zenith Satellite System, e.g., Michibiki), GLONASS, Galileo, and BeiDou. In this embodiment, the positioning device 110 is located on top of the cabin 105, but it may be located in other positions.

[0117] As shown in Figure 18, the positioning device 110 comprises a GNSS receiver 111, an RTK receiver 112, and a processing circuit 116. The positioning device 110 may further include an inertial measuring unit (IMU) 115.

[0118] The GNSS receiver 111 includes an antenna for receiving signals from GNSS satellites and a processing circuit for determining the position of the work vehicle 100 based on the signals received by the antenna. The GNSS receiver 111 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 NMEA-0183 format. The GNSS data may include, for example, the identification number, elevation angle, azimuth angle, and received signal strength of each satellite from which the satellite signal was received.

[0119] The positioning device 110 may perform positioning of the work vehicle 100 using RTK (Real Time Kinematic)-GNSS. In RTK-GNSS positioning, in addition to satellite signals transmitted from multiple GNSS satellites, correction signals transmitted from a base station are used. The base station may be installed near the work site where the work vehicle 100 will be driving (for example, within 10 km of the work vehicle 100). Based on the satellite signals received from multiple GNSS satellites, the base station generates a correction signal, for example, in RTCM format and transmits it to the positioning device 110. The RTK receiver 112 includes an antenna and a modem and receives the correction signal transmitted from the base station. The processing circuit 116 of the positioning device 110 corrects the positioning result from the GNSS receiver 111 based on the correction signal. By using RTK-GNSS, it is possible to perform positioning with an accuracy of, for example, an error of a few centimeters. Position information, including latitude, longitude, and altitude information, is acquired by high-precision positioning using RTK-GNSS. The positioning device 110 calculates the position of the work vehicle 100 at a frequency of, for example, 1 to 10 times per second. The positioning method is not limited to RTK-GNSS; any positioning method that can obtain the necessary accuracy of positional information (such as interferometric positioning or relative positioning) can be used. For example, positioning may be performed using VRS (Virtual Reference Station) or DGPS (Differential Global Positioning System).

[0120] The positioning device 110 in this embodiment further includes an IMU 115. By including the IMU 115, the positioning device 110 can supplement position data using signals from the IMU 115. By supplementing position data based on satellite signals using data acquired by the IMU 115, the positioning performance can be improved.

[0121] The IMU115 may be equipped with a 3-axis accelerometer and a 3-axis gyroscope. The IMU115 may also be equipped with an orientation sensor, such as a 3-axis geomagnetic sensor. The IMU115 functions as a motion sensor and can output signals indicating various quantities such as 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 IMU115 in addition to the satellite signals and correction signals. The signals output from the IMU115 can be used to correct or complement the position calculated based on the satellite signals and correction signals. The IMU115 outputs signals at a higher frequency than the GNSS receiver 111. For example, the IMU115 outputs signals at a frequency of several tens to several thousand times per second. 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). Instead of the IMU115, a 3-axis accelerometer and a 3-axis gyroscope may be provided separately. The IMU 115 may be provided as a separate device from the positioning device 110.

[0122] The sensor group 150 may include various sensors (i.e., internal sensors) that detect the state of the work vehicle 100 or work machine 300. For example, the sensor group 150 may include a steering wheel sensor 152, a steering angle sensor 154, and an axle sensor 156.

[0123] The steering wheel sensor 152 measures the rotation angle of the steering wheel of the work vehicle 100. The steering angle sensor 154 measures the steering angle of the front wheels 104F, which are the steering wheels. The values ​​measured by the steering wheel sensor 152 and the steering angle sensor 154 can be used for steering control by the control device 180.

[0124] 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 utilizes, for example, a magnetoresistive element (MR), a Hall element, or an electromagnetic pickup. The axle sensor 156 outputs a numerical value indicating, for example, the number of rotations of the axle per minute (unit: rpm). The axle sensor 156 is used to measure the speed of the work vehicle 100. The value measured by the axle sensor 156 can be used for speed control by the control device 180.

[0125] The storage device 170 includes one or more storage media, such as flash memory or magnetic disks. The storage device 170 stores various data generated by the positioning device 110, camera 120, obstacle sensor 130, LiDAR sensor 140, sensor group 150, and control device 180. The data stored in the storage device 170 may include an environmental map of the environment in which the work vehicle 100 travels, an obstacle map that is generated sequentially during travel, and route data for autonomous driving. The storage device 170 also stores computer programs that cause each ECU in the control device 180 to perform various operations described later. Such computer programs may be provided to the work vehicle 100 via a storage medium (e.g., semiconductor memory or optical disk) or a telecommunications line (e.g., the Internet). Such computer programs may be sold as commercial software.

[0126] The control device 180 includes a plurality of ECUs. These plurality of ECUs include, for example, an ECU 181 for speed control, an ECU 182 for steering control, an ECU 183 for work equipment control, and an ECU 184 for automatic driving control.

[0127] The ECU 181 controls the speed of the work vehicle 100 by controlling the prime mover 102, the transmission 103, and the brakes, which are included in the drive unit 240.

[0128] The ECU 182 controls the steering of the work vehicle 100 by controlling the hydraulic system or electric motor included in the steering device 106 based on the measurements of the steering wheel sensor 152.

[0129] The ECU 183 controls the operation of the three-point hitch and PTO shaft, etc., included in the coupling device 108, in order to make the work implement 300 perform the desired operation. The ECU 183 also generates signals to control the operation of the work implement 300 and transmits these signals from the communication device 190 to the work implement 300.

[0130] The ECU 184 performs calculations and controls to achieve autonomous driving based on data output from the positioning device 110, camera 120, obstacle sensor 130, LiDAR sensor 140, and sensor group 150. For example, the ECU 184 estimates the position of the work vehicle 100 based on data output from at least one of the positioning device 110, camera 120, and LiDAR sensor 140. In situations where the reception strength of satellite signals from GNSS satellites is sufficiently high, the ECU 184 may determine the position of the work vehicle 100 based only on data output from the positioning device 110. On the other hand, in environments such as orchards where there are obstacles such as trees that obstruct the reception of satellite signals around the work vehicle 100, the ECU 184 estimates the position of the work vehicle 100 using data output from the LiDAR sensor 140 or camera 120. During autonomous driving, the ECU 184 performs calculations necessary for the work vehicle 100 to travel along the target path based on the estimated position of the work vehicle 100. ECU184 sends a command to ECU181 to change speed and a command to ECU182 to change steering angle. ECU181 changes the speed of the work vehicle 100 by controlling the prime mover 102, the transmission 103, or the brakes in response to the command to change speed. ECU182 changes the steering angle by controlling the steering device 106 in response to the command to change steering angle.

[0131] Through the operation of these ECUs, the control unit 180 enables autonomous driving. During autonomous driving, the control unit 180 controls the drive unit 240 based on the measured or estimated position of the work vehicle 100 and the sequentially generated target path. This allows the control unit 180 to drive the work vehicle 100 along the target path.

[0132] Multiple ECUs included in the control unit 180 can communicate with each other according to 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 Figure 18, each of the ECUs 181 to 184 is shown as a separate block, but each of these functions may be implemented by multiple ECUs. An on-board computer integrating at least some of the functions of ECUs 181 to 184 may be provided. The control unit 180 may also include ECUs other than ECUs 181 to 184, and any number of ECUs may be provided depending on their function. Each ECU includes a processing circuit containing one or more processors.

[0133] Cameras 120 may be installed, for example, on the front, rear, left, and right sides of the work vehicle 100. Cameras 120 capture images of the environment around the work vehicle 100 and generate image data. The images acquired by cameras 120 may be transmitted, for example, to a terminal device for remote monitoring. These images may be used to monitor the work vehicle 100 during unmanned operation. Cameras 120 may be installed as needed, and their number is arbitrary.

[0134] The LiDAR sensor 140 is an example of an external sensor that outputs sensor data showing the distribution of features around the work vehicle 100. In the example in Figure 17, two LiDAR sensors 140 are located at the front and rear of the cabin 105. The LiDAR sensors 140 may be located in other places (for example, at the lower front of the vehicle body 101). Each LiDAR sensor 140 repeatedly outputs sensor data showing 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, while the work vehicle 100 is in motion. The number of LiDAR sensors 140 is not limited to two; it may be one or three or more.

[0135] The LiDAR sensor 140 may be configured to output two-dimensional or three-dimensional point cloud data as sensor data. In this specification, “point cloud data” broadly means data showing the distribution of multiple reflection points observed by the LiDAR sensor 140. The point cloud data may include, for example, the coordinate values ​​of each reflection point in two-dimensional or three-dimensional space, or information indicating the distance and direction of each reflection point. The point cloud data may also include brightness information for each reflection point. The LiDAR sensor 140 may be configured to repeatedly output the point cloud data, for example, at a preset period. Thus, the ambient sensor may include one or more LiDAR sensors 140 that output point cloud data as sensor data.

[0136] Sensor data output from the LiDAR sensor 140 is processed by a control device that controls the automatic driving of the work vehicle 100. While the work vehicle 100 is driving, the control device can sequentially generate an obstacle map showing the distribution of objects around the work vehicle 100 based on the sensor data output from the LiDAR sensor 140. The control device can also generate an environmental map by stitching together the obstacle maps during automatic driving, for example, using an algorithm such as SLAM. The control device can also estimate the position and orientation of the work vehicle 100 (i.e., self-localization) by matching the sensor data with the environmental map.

[0137] The multiple obstacle sensors 130 shown in Figure 17 are located at the front and rear of the cabin 105. Obstacle sensors 130 may also be located in other areas. For example, one or more obstacle sensors 130 may be provided at any location on the sides, front, and rear of the vehicle body 101. Obstacle sensors 130 may include, for example, laser scanners or ultrasonic sonar. Obstacle sensors 130 are used to detect surrounding obstacles during autonomous driving and to stop or bypass the work vehicle 100.

[0138] The control device of the work vehicle 100 may use sensing data acquired by a sensing device such as a camera 120 or a LiDAR sensor 140 for positioning, in addition to the positioning results from the positioning device 110. If there are features that function as characteristic points in the environment in which the work vehicle 100 travels, 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 stored in a storage device in advance. By correcting or supplementing the position data based on satellite signals using the data acquired by the camera 120 or LiDAR sensor 140, the position of the work vehicle 100 can be determined with even higher accuracy.

[0139] The work vehicle 100 and the work machine 300 can communicate with each other via a communication cable included in the coupling device 108. The work vehicle 100 can also communicate with a terminal device 400 for remote monitoring via the network 80. The terminal device 400 is any computer, such as a personal computer (PC), laptop computer, tablet computer, or smartphone.

[0140] The work machine 300 includes a drive unit 340 (sometimes referred to as the "second drive unit"), a control device 380, and a communication device 390. Figure 18 shows components that are relatively highly relevant to the operation of the work vehicle 100's automatic driving function, and other components are not shown.

[0141] Camera 120 is an imaging device that captures the environment around the work vehicle 100. Camera 120 includes an image sensor such as a CCD (Charge Coupled Device) or CMOS (Complementary Metal Oxide Semiconductor). Camera 120 may also include an optical system including one or more lenses and a signal processing circuit. While the work vehicle 100 is in motion, Camera 120 captures the environment around the work vehicle 100 and generates image (e.g., video) data. Camera 120 can capture video at a frame rate of, for example, 3 frames per second (fps) or higher. The images generated by Camera 120 can be used, for example, when a remote observer uses a terminal device 400 to check the environment around the work vehicle 100. The images generated by Camera 120 may be used for positioning or obstacle detection. As shown in Figure 17, multiple cameras 120 may be installed at different locations on the work vehicle 100, or a single camera may be installed. A visible light camera that generates visible light images and an infrared camera that generates infrared images may be provided separately. Both the visible light camera and the infrared camera may be provided as cameras that generate surveillance images. The infrared camera can also be used for detecting obstacles at night.

[0142] 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 closer than a predetermined distance from the obstacle sensor 130. Multiple obstacle sensors 130 may be installed at different locations on the work vehicle 100. For example, multiple laser scanners and multiple ultrasonic sonars may be placed at different locations on the work vehicle 100. By providing many such obstacle sensors 130, blind spots in monitoring obstacles around the work vehicle 100 can be reduced.

[0143] The drive system 240 includes various devices necessary for the movement of the work vehicle 100 and the driving of the work equipment 300, such as the prime mover 102, the transmission 103, the steering system 106, and the coupling device 108. The prime mover 102 may be an internal combustion engine, such as a diesel engine. The drive system 240 may also be equipped with an electric motor for traction, either in place of or in conjunction with the internal combustion engine.

[0144] The communication device 190 is a device that includes circuits for communicating with the work machine 300 and the terminal device 400. The communication device 190 includes circuits for transmitting and receiving signals compliant with ISOBUS standards, such as ISOBUS-TIM, to and from the communication device 390 of the work machine 300. This makes it possible to make the work machine 300 perform desired operations or to obtain information from the work machine 300. The communication device 190 may further include an antenna and communication circuits for transmitting and receiving signals via the network 80 to and from the terminal device 400. 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 to communicate with a mobile terminal used by a supervisor near the work vehicle 100. Communication with such a mobile terminal may be conducted in accordance with any wireless communication standard, such as Wi-Fi®, cellular mobile communication such as 3G, 4G, or 5G, or Bluetooth®.

[0145] The operation terminal 200 is a terminal for the user to perform operations related to the movement of the work vehicle 100 and the operation of the work machine 300, and is also called a virtual terminal (VT). The operation terminal 200 may be equipped with a display device such as a touchscreen and / or one or more buttons. The display device may be a display such as a liquid crystal or organic light-emitting diode (OLED). By operating the operation terminal 200, the user can perform various operations such as switching the automatic driving mode on / off, switching the recording (teaching) mode and playback mode on / off, and switching the work machine 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 away from the work vehicle 100 may control the operation of the work vehicle 100 by operating the detached operation terminal 200. The operation terminal 200 may be equipped with a storage device. The storage device in the operating terminal 200 may store various data necessary for the operation of the work vehicle 100 instead of the storage device 170.

[0146] The drive unit 340 in the work machine 300 shown in Figure 18 performs the operations necessary for the work machine 300 to perform a predetermined operation. The drive unit 340 includes devices such as a hydraulic system, an electric motor, or a pump, depending on the application of the work machine 300. The control device 380 controls the operation of the drive unit 340. The control device 380 causes the drive unit 340 to perform various operations in response to signals transmitted from the work vehicle 100 via the communication device 390. It can also transmit signals corresponding to the status of the work machine 300 from the communication device 390 to the work vehicle 100. [Industrial applicability]

[0147] The route generation method according to the embodiment of the present invention is widely applicable to various types of work vehicles used in smart agriculture. According to the route generation method and travel control system according to the embodiment of the present invention, work vehicles with attached implements can travel efficiently within the field. [Explanation of symbols]

[0148] 70...Field, 70A...Work area, 70B...Surrounding area, 100...Work vehicle, 300...Implement, 530...Processing device, 1000...Travel control system, Pr...Temporary stopping position

Claims

1. A system for controlling the movement of a work vehicle to which a work machine is attached, One or more LiDAR sensors attached to the work vehicle, which output point cloud data indicating the surrounding environment of the work vehicle including at least a part of the work machine, A control device for controlling the movement of the aforementioned work vehicle and Equipped with, The aforementioned work machine is connected to the work vehicle so as to be rotatable relative to the work vehicle, The control device is Based on the point cloud data acquired from the LiDAR sensor, the position of the characteristic points of the work machine is determined. A driving control system that calculates the angle between the orientation of the work vehicle and the orientation of the work machine based on the position of the aforementioned feature points.

2. The control device is The travel control system according to claim 1, which calculates the angle between the orientation of the work vehicle and the orientation of the work machine based on the positional relationship between the position of the characteristic point and the position of the center of rotation of the work machine relative to the work vehicle.

3. The control device is By filtering the point cloud data acquired from the LiDAR sensor, point cloud data indicating reflection points on the surface of the work machine is extracted. A driving control system according to claim 1 or 2, which calculates the position of the feature points based on the extracted point cloud data.

4. The control device is The driving control system according to claim 3, wherein the position of the feature point is calculated by obtaining the arithmetic mean or weighted mean of the extracted point cloud data.

5. The control device is The travel control system according to claim 3, wherein the position of the characteristic points is determined by detecting the characteristic shape of the work machine or a member attached to the work machine based on the extracted point cloud data.

6. The control device is The driving control system according to claim 3, wherein the filtering of the point cloud data is performed by downsampling the point cloud data acquired from the LiDAR sensor.

7. The control device is While the aforementioned work vehicle is in motion, the angle is calculated sequentially. The driving control system according to claim 3, wherein the filtering of the point cloud data is performed by extracting point cloud data within a predetermined angle range from the previously calculated angle.

8. The control device is While the aforementioned work vehicle is in motion, the angle is calculated sequentially. The driving control system according to claim 3, wherein the filtering of the point cloud data is performed by extracting the point cloud data within a predetermined distance range from the previously calculated position of the feature point.

9. The control device is The trajectory of the feature point is obtained when the work vehicle is traveling along a curve. Based on the trajectory of the feature point, the position of the rotation center of the feature point is calculated. A driving control system according to claim 1 or 2, which calculates the angle based on the position of the rotation center of the feature point.

10. The control device is A driving control system according to claim 1 or 2, wherein information on the position of each reflection point is obtained based on the distance and direction information of each reflection point from the LiDAR sensor, as indicated by the point cloud data obtained from the LiDAR sensor.

11. The driving control system according to claim 1 or 2, wherein the point cloud data is two-dimensional point cloud data including two-dimensional position information.

12. The control device is A driving control system according to claim 1 or 2, which generates a driving path for the work vehicle based on the calculated angle.

13. The travel control system according to claim 1 or 2, wherein a marker member located within the sensing range of the LiDAR sensor is attached to the work machine.

14. The control device is The driving control system according to claim 1 or 2, wherein the calculated angle is displayed on a display device of the work vehicle.

15. A driving control system according to claim 1 or 2, Running gear including the steering wheels, A drive unit that drives the aforementioned traveling device and Equipped with, The control device controls the steering of the steering wheel by controlling the drive device based on the calculated angle, in a work vehicle.

16. The aforementioned work vehicle has a connecting part for connecting the aforementioned work machine, The aforementioned work machine is connected to the work vehicle so as to be rotatable around the connecting part, The work vehicle according to claim 15, wherein the relative position of the connecting portion of the work vehicle with respect to the vehicle body can be switched between when work using the work machine is being performed and when work is not being performed.

17. A method for controlling the movement of a work vehicle to which a work implement is attached, which is performed by one or more computing devices, The aforementioned work machine is connected to the work vehicle so as to be rotatable relative to the work vehicle, Based on the point cloud data acquired from one or more LiDAR sensors attached to the work vehicle, which output point cloud data indicating the surrounding environment of the work vehicle including at least a part of the work machine, the position of the feature points of the work machine is determined. Based on the position of the aforementioned feature point, the angle between the orientation of the work vehicle and the orientation of the work machine is calculated. Methods that include...

18. A computer program executed by a processor in a control device that controls the movement of a work vehicle to which a work machine is attached, The aforementioned work machine is connected to the work vehicle so as to be rotatable relative to the work vehicle, The aforementioned processor, Based on the point cloud data acquired from one or more LiDAR sensors attached to the work vehicle, which output point cloud data indicating the surrounding environment of the work vehicle including at least a part of the work machine, the position of the feature points of the work machine is determined. Based on the position of the aforementioned feature point, the angle between the orientation of the work vehicle and the orientation of the work machine is calculated. A computer program that executes something.

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