Patent Application
20250143197
The present disclosure relates to work vehicles, control methods, and non-transitory computer-readable media each including a computer program.
As attempts in next-generation agriculture, research and development of smart agriculture utilizing ICT (Information and Communication Technology) and IoT (Internet of Things) are under way. Research and development are also directed to the automation and unmanned use of tractors or other work vehicles to be used in the field. For example, work vehicles which travel via automatic steering by utilizing a positioning system that is capable of precise positioning, e.g., a GNSS (Global Navigation Satellite System), are coming into practical use.
On the other hand, development of movable units which autonomously move by utilizing distance sensors, e.g., a LiDAR (Light Detection and Ranging) sensor, is also under way. For example, Japanese Laid-Open Patent Publication No. 2019-154379 discloses an example of a work vehicle which performs self-traveling in between crop rows in a field by utilizing the LiDAR sensor.
When a work vehicle performs self-traveling among crop rows in a field, there is a desire to reduce or prevent unwanted contact of the work vehicle with the crop rows.
A work vehicle according to an example embodiment of the present disclosure is a work vehicle to perform self-traveling among a plurality of crop rows, including wheels responsible for steering, a steering device to change a steering angle of the wheels responsible for steering, an exterior sensor to output sensor data indicating a distribution of geographic features around the work vehicle, and a controller configured or programmed to control self-traveling of the work vehicle, set a maximum steering angle for the wheels responsible for steering based on a state of at least one of the work vehicle or a surrounding environment of the work vehicle, detect two crop rows existing on opposite sides of the work vehicle based on the sensor data, set a target path for the work vehicle in between the two crop rows, compute a target steering angle for the wheels responsible for steering to cause the work vehicle to follow the target path, limit a value of the target steering angle to be equal to or smaller than the maximum steering angle when the computed target steering angle is greater than the maximum steering angle, and control the steering device so that the steering angle of the wheels responsible for steering equals the target steering angle.
Example embodiments of the present disclosure may be implemented using devices, systems, methods, integrated circuits, computer programs, non-transitory computer-readable media including computer programs, or any combination thereof. The computer-readable storage media may include volatile storage media, or non-volatile storage media. Each of the devices may include a plurality of devices. In the case where one of the devices includes two or more devices, the two or more devices may include a single apparatus, or two or more separate apparatuses.
According to an example embodiment of the present disclosure, a maximum steering angle for wheels responsible for steering is set based on the state of at least one of a work vehicle and a surrounding environment of the work vehicle, and the steering angle of the wheels responsible for steering is controlled so as to be equal to or smaller than the maximum steering angle. By setting the maximum steering angle based on the state of at least one of the work vehicle and the surrounding environment, the work vehicle can be prevented from coming into contact with crop rows. By controlling the steering angle of the wheels responsible for steering so as to be equal to or smaller than the maximum steering angle, the work vehicle can be prevented from coming into contact with crop rows, and driving stability can be improved.
The above and other elements, features, steps, characteristics and advantages of the present invention will become more apparent from the following detailed description of the example embodiments with reference to the attached drawings.
In the present disclosure, a “work vehicle” means a vehicle for use in performing work in a work area. A “work area” is any place where work may be performed, e.g., a field, a mountain forest, or a construction site. A “field” is any place where agricultural work may be performed, e.g., an orchard, an agricultural field, a paddy field, a cereal farm, or a pasture. A work vehicle can be an agricultural machine such as a tractor, a rice transplanter, a combine, a vehicle for crop management, or a riding mower, or a vehicle for non-agricultural purposes such as a construction vehicle or a snowplow vehicle. A work vehicle may be configured so that an implement (also referred to as a “task device” or a “task apparatus”) that is suitable for the content of work can be attached to at least one of its front and its rear. Traveling of a work vehicle that is made while it performs work by using an implement may be referred to as “tasked travel”.
“Self-driving” means controlling the travel of a vehicle based on the action of a controller, rather than through manual operation of a driver. During self-driving, not only the travel of the vehicle, but also the task operation (e.g., the operation of the implement) may also be automatically controlled. A vehicle that is traveling via self-driving is said to be “self-traveling”. The controller may be configured or programmed to control at least one of steering, adjustment of traveling speed, and starting and stopping of travel as are necessary for the travel of vehicle. In the case of controlling a work vehicle having an implement attached thereto, the controller may be configured or programmed to control operations such as raising or lowering of the implement, starting and stopping of the operation of the implement, and the like. Travel via self-driving includes not only the travel of a vehicle toward a destination along a predetermined path, but also the travel of merely following a target of tracking. A vehicle performing self-driving may travel based in part on a user's instruction. A vehicle performing self-driving may operate not only in a self-driving mode but also in a manual driving mode of traveling through manual operation of the driver. The steering of a vehicle that is based on the action of a controller, rather than manually, is referred to as “automatic steering”. A portion or an entirety of the controller may be external to the vehicle. Between the vehicle and a controller that is external to the vehicle, communication of control signals, commands, data, or the like may be performed. A vehicle performing self-driving may autonomously travel while sensing the surrounding environment, without any person being involved in the control of the travel of the vehicle. A vehicle that is capable of autonomous travel can travel in an unmanned manner. During autonomous travel, detection of obstacles and avoidance of obstacles may be performed.
An “exterior sensor” is a sensor that senses the external state of the work vehicle. Examples of exterior sensors include LiDAR sensors, cameras (or image sensors), laser range finders (also referred to as “range sensors”), ultrasonic sensors, millimeter wave radars, and magnetic sensors.
A “crop row” is a row of agricultural items, trees, or other plants that may grow in rows on a field, e.g., an orchard or an agricultural field, or in a forest or the like. In the present disclosure, a “crop row” is a notion that encompasses a “row of trees”.
An “obstacle map” is local map data in which the position or a region of an object around the work vehicle is expressed in a predetermined coordinate system. A coordinate system defining an obstacle map may be a vehicle coordinate system that is fixed to the work vehicle, or a world coordinate system that is fixed to the globe (e.g. a geographic coordinate system), for example. An obstacle map may include information other than position (e.g., attribute information) of an object around the work vehicle. The obstacle map may be expressed in various formats, e.g., a grid map or a point cloud map.
Hereinafter, example embodiments of the present disclosure will be described more specifically. Note however that unnecessarily detailed descriptions may be omitted. For example, detailed descriptions on what is well known in the art or redundant descriptions on what is substantially the same configuration may be omitted. This is to avoid lengthy description, and facilitate the understanding of those skilled in the art. The accompanying drawings and the following description are not intended to limit the scope of claims. In the following description, component elements having identical or similar functions are denoted by identical reference numerals.
The following example embodiments are only exemplary, and the techniques according to the present disclosure are not limited to the following example embodiments. For example, numerical values, shapes, materials, steps, orders of steps, etc., that are indicated in the following example embodiments are only exemplary, and allow for various modifications so long as it makes technological sense. Any one implementation may be combined with another.
Hereinafter, as one example, an example embodiment where the work vehicle is a tractor for use in agricultural work in a field such as an orchard will be described. Without being limited to tractors, the techniques according to the present disclosure are also applicable to other type of agricultural machines such as rice transplanters, combines, vehicles for crop management, or riding lawn mowers, for example. The example embodiments and techniques according to the present disclosure are also applicable to vehicles for non-agricultural purposes such as construction vehicles or snowplow vehicles.
As shown in
The work vehicle 100 includes a plurality of exterior sensors to sense the surroundings of the work vehicle 100. In the example of
The cameras 120 may be provided at the front/rear/right/left of the work vehicle 100, for example. The cameras 120 image the surrounding environment of the work vehicle 100 and generate image data. The images acquired with the cameras 120 may be transmitted to the terminal device, which is responsible for remote monitoring, for example. The images may be used to monitor the work vehicle 100 during unmanned driving. The cameras 120 may be provided according to the needs, and any number of them may be provided.
The LiDAR sensors 140 are one example of exterior sensors that output sensor data indicating a distribution of geographic features around the work vehicle 100. In the example of
The LiDAR sensor(s) 140 may be configured or programmed to output two-dimensional or three-dimensional point cloud data as sensor data. In the present specification, “point cloud data” broadly means data indicating a distribution of multiple reflection points that are observed with a LiDAR sensor(s) 140. The point cloud data may include coordinate values of each reflection point in a two-dimensional space or a three-dimensional space or information indicating the distance and direction of each reflection point, for example. The point cloud data may include information of luminance of each reflection point. The LiDAR sensor(s) 140 may be configured or programmed to repeatedly output point cloud data with a pre-designated cycle, for example. Thus, the exterior sensors may include one or more LiDAR sensors 140 that output point cloud data as sensor data.
The sensor data that is output from the LiDAR sensor(s) 140 is processed by a controller configured or programmed to control self-traveling of the work vehicle 100. During travel of the work vehicle 100, based on the sensor data that is output from the LiDAR sensor (s) 140, the controller can consecutively generate an obstacle map indicating a distribution of objects existing around the work vehicle 100. The controller may generate an environment map by joining together obstacle maps with the use of an algorithm such as SLAM (Simultaneous Localization and Mapping), for example, during self-traveling. The controller can perform estimation of the position and orientation of the work vehicle 100 (i.e., localization) by matching the sensor data against the environment map.
In an environment in which trees or crops are distributed with a high density, e.g., vineyards or other orchards or forests, leaves thriving in upper portions of the trees create canopies, each of which serves as an obstacle or a multiple reflector against radio waves from a satellite. Such an environment may hinder accurate positioning using a GNSS in some cases. In an environment where GNSS cannot be used, SLAM is used, where localization and map generation simultaneously take place. Use of SLAM allows the work vehicle 100 to travel automatically in an environment with a multitude of trees.
The plurality of obstacle sensors 130 shown in
The work vehicle 100 further includes a GNSS unit 110. GNSS is a collective term for satellite positioning systems such as the GPS (Global Positioning System), QZSS (Quasi-Zenith Satellite System, e.g., MICHIBIKI), GLONASS, Galileo, and BeiDou. A GNSS unit 110 receives satellite signals (also referred to as GNSS signals) that are transmitted from a plurality of GNSS satellites, and performs positioning based on the satellite signals. Although the GNSS unit 110 in the present example embodiment is disposed above the cabin 105, it may be disposed at any other position. The GNSS unit 110 includes an antenna to receive signals from the GNSS satellites, and a processing circuit. The work vehicle 100 in the present example embodiment is used in environments where multiple trees grow to make it difficult to use a GNSS, e.g., a vineyard. In such environments, the LiDAR sensor(s) 140 is mainly used in positioning. However, in an environment where it is possible to receive GNSS signals, positioning may be performed by using the GNSS unit 110. By combining the positioning based on the LiDAR sensor(s) 140 and the positioning based on the GNSS unit 110, the stability or accuracy of positioning can be improved.
The GNSS unit 110 may include an inertial measurement unit (IMU). Signals from the IMU can be used to complement position data. The IMU can measure a tilt or a small motion of the work vehicle 100. The data acquired by the IMU can be used to complement the position data based on the satellite signals, so as to improve the performance of positioning.
The prime mover 102 may be a diesel engine, for example. Instead of a diesel engine, an electric motor may be used. The transmission 103 can change the propulsion and the moving speed of the work vehicle 100 through a speed changing mechanism. The transmission 103 can also switch between forward travel and backward travel of the work vehicle 100.
The steering device 106 includes a steering wheel, a steering shaft connected to the steering wheel, and a power steering device to assist in the steering by the steering wheel. The front wheels 104F are the wheels responsible for steering, such that changing their steering angle (also referred to as “angle of turn”) can cause a change in the traveling direction of the work vehicle 100. The steering angle of the front wheels 104F can be changed by manipulating the steering wheel. The power steering device includes a hydraulic device or an electric motor to supply an assisting force for changing the steering angle of the front wheels 104F. When automatic steering is performed, under the control of the controller disposed in the work vehicle 100, the steering angle may be automatically adjusted by the power of the hydraulic device or the electric motor.
A linkage device 108 is provided at the rear of the vehicle body 101. The linkage device 108 includes, e.g., a three-point linkage (also referred to as a “three-point link” or a “three-point hitch”), a PTO (Power Take Off) shaft, a universal joint, and a communication cable. The linkage device 108 allows the implement 300 to be attached to, or detached from, the work vehicle 100. The linkage device 108 is able to raise or lower the three-point link with a hydraulic device, for example, thus changing the position or attitude of the implement 300. Moreover, motive power can be sent from the work vehicle 100 to the implement 300 via the universal joint. While towing the implement 300, the work vehicle 100 allows the implement 300 to perform a predetermined task. The linkage device may be provided at the front portion of the vehicle body 101. In that case, the implement can be connected at the front portion of the work vehicle 100.
Although the implement 300 shown in
The work vehicle 100 shown in
In addition to the GNSS unit 110, the camera(s) 120, the obstacle sensors 130, the LiDAR sensor(s) 140, and the operational terminal 200, the work vehicle 100 in the example of
The GNSS unit 110 includes a GNSS receiver 111, an RTK receiver 112, an inertial measurement unit (IMU) 115, and a processing circuit 116. The sensors 150 include a steering wheel sensor 152, an steering angle sensor 154, and a wheel axis sensor 156. The travel control system 160 includes a storage device 170 and a controller 180. The controller 180 is configured or programmed to include a plurality of electronic control units (ECU) 181 to 184. The implement 300 includes a drive device 340, a controller 380, and a communicator 390. Note that
The GNSS receiver 111 in the GNSS unit 110 receives satellite signals transmitted from the plurality of GNSS satellites and generates GNSS data based on the satellite signals. The GNSS data is generated in a predetermined format such as, for example, the NMEA-0183 format. The GNSS data may include, for example, the ID number, the angle of elevation, the azimuth angle, and a value representing the reception intensity of each of the satellites from which the satellite signals are received.
The GNSS unit 110 may perform positioning of the work vehicle 100 by utilizing an RTK (Real Time Kinematic)-GNSS. In the positioning based on the RTK-GNSS, not only satellite signals transmitted from a plurality of GNSS satellites, but also a correction signal that is transmitted from a reference station is used. The reference station may be disposed near the work area where the work vehicle 100 performs tasked travel (e.g., at a position within 10 km of the work vehicle 100). The reference station generates a correction signal of, for example, an RTCM format based on the satellite signals received from the plurality of GNSS satellites, and transmits the correction signal to the GNSS unit 110. The RTK receiver 112, which includes an antenna and a modem, receives the correction signal transmitted from the reference station. Based on the correction signal, the processing circuit 116 of the GNSS unit 110 corrects the results of the positioning performed by the GNSS receiver 111. Use of the RTK-GNSS enables positioning with an accuracy on the order of several centimeters of errors, for example. Positional information including latitude, longitude, and altitude information is acquired through the highly accurate positioning by the RTK-GNSS. The GNSS unit 110 calculates the position of the work vehicle 100 as frequently as, for example, one to ten times per second. Note that the positioning method is not limited to being performed by using an RTK-GNSS, any arbitrary positioning method (e.g., an interferometric positioning method or a relative positioning method) that provides positional information with the necessary accuracy can be used. For example, positioning may be performed by utilizing a VRS (Virtual Reference Station) or a DGPS (Differential Global Positioning System).
The GNSS unit 110 according to the present example embodiment further includes the IMU 115. The IMU 115 may include a 3-axis accelerometer and a 3-axis gyroscope. The IMU 115 may include a direction sensor such as a 3-axis geomagnetic sensor. The IMU 115 functions as a motion sensor which can output signals representing parameters such as acceleration, velocity, displacement, and attitude of the work vehicle 100. Based not only on the satellite signals and the correction signal but also on a signal that is output from the IMU 115, the processing circuit 116 can estimate the position and orientation of the work vehicle 100 with a higher accuracy. The signal that is output from the IMU 115 may be used for the correction or complementation of the position that is calculated based on the satellite signals and the correction signal. The IMU 115 outputs a signal more frequently than the GNSS receiver 111. For example, the IMU 115 outputs a signal as frequently as approximately several ten times to several thousand times per second. Utilizing this signal that is output highly frequently, the processing circuit 116 allows the position and orientation of the work vehicle 100 to be measured more frequently (e.g., about 10 Hz or above). Instead of the IMU 115, a 3-axis accelerometer and a 3-axis gyroscope may be separately provided. The IMU 115 may be provided as a separate device from the GNSS unit 110.
The cameras 120 are imagers that image the surrounding environment of the work vehicle 100. Each camera 120 includes an image sensor such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor), for example. In addition, each camera 120 may include an optical system including one or more lenses and a signal processing circuit. During travel of the work vehicle 100, the cameras 120 image the surrounding environment of the work vehicle 100, and generate image (e.g., motion picture) data. The cameras 120 are able to capture motion pictures at a frame rate of 3 frames/second (fps: frames per second) or greater, for example. The images generated by the cameras 120 may be used by a remote supervisor to check the surrounding environment of the work vehicle 100 with the terminal device 400, for example. The images generated by the cameras 120 may also be used for the purpose of positioning or detection of obstacles. As shown in
An obstacle sensor 130 detects objects around the work vehicle 100. The obstacle sensor 130 may include a laser scanner or an ultrasonic sonar, for example. When an object exists at a position closer to the obstacle sensor 130 than a predetermined distance, the obstacle sensor 130 outputs a signal indicating the presence of an obstacle. A plurality of obstacle sensors 130 may be provided at different positions of the work vehicle 100. For example, a plurality of laser scanners and a plurality of ultrasonic sonars may be disposed at different positions of the work vehicle 100. Providing a multitude of obstacle sensors 130 can reduce blind spots in monitoring obstacles around the work vehicle 100.
The steering wheel sensor 152 measures the angle of rotation 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 wheels responsible for steering. Measurement values by the steering wheel sensor 152 and the steering angle sensor 154 may be used for steering control by the controller 180.
The wheel axis sensor 156 measures the rotational speed, i.e., the number of revolutions per unit time, of a wheel axis that is connected to the wheels 104. The wheel axis sensor 156 may be a sensor including a magnetoresistive element (MR), a Hall generator, or an electromagnetic pickup, for example. The wheel axis sensor 156 outputs a numerical value indicating the number of revolutions per minute (unit: rpm) of the wheel axis, for example. The wheel axis sensor 156 is used to measure the speed of the work vehicle 100. Measurement values from the wheel axis sensor 156 can be utilized for the speed control by the controller 180.
The drive device 240 includes various types of devices required to cause the work vehicle 100 to travel and to drive the implement 300, for example, the prime mover 102, the transmission 103, the steering device 106, the linkage device 108 and the like described above. The prime mover 102 may include an internal combustion engine such as, for example, a diesel engine. The drive device 240 may include an electric motor for traction instead of, or in addition to, the internal combustion engine.
The storage device 170 includes one or more storage media such as a flash memory or a magnetic disc. The storage device 170 stores various data that is generated by the GNSS unit 110, the camera(s) 120, the obstacle sensor(s) 130, the LiDAR sensor(s) 140, the sensors 150, and the controller 180. The data that is stored by the storage device 170 may include an environment map of the environment where the work vehicle 100 travels, an obstacle map that is consecutively generated during travel, and path data for self-driving. The storage device 170 also stores a computer program(s) to cause each of the ECUs in the controller 180 to perform various operations described below. Such a computer program(s) may be provided to the work vehicle 100 via a storage medium (e.g., a semiconductor memory, an optical disc, etc.) or through telecommunication lines (e.g., the Internet). Such a computer program(s) may be marketed as commercial software.
The controller 180 is configured or programmed to include the plurality of ECUs. The plurality of ECUs include, for example, the ECU 181 for speed control, the ECU 182 for steering control, the ECU 183 for implement control, and the ECU 184 for self-driving control.
The ECU 181 controls the prime mover 102, the transmission 103, and brakes included in the drive device 240, thus controlling the speed of the work vehicle 100.
The ECU 182 controls the hydraulic device or the electric motor included in the steering device 106 based on a measurement value of the steering wheel sensor 152, thus controlling the steering of the work vehicle 100.
In order to cause the implement 300 to perform a desired operation, the ECU 183 controls the operations of the three-point link, the PTO shaft and the like that are included in the linkage device 108. Also, the ECU 183 generates a signal to control the operation of the implement 300, and transmits this signal from the communicator 190 to the implement 300.
Based on data output from the GNSS unit 110, the camera(s) 120, the obstacle sensor(s) 130, the LiDAR sensor(s) 140, and the sensors 150, the ECU 184 performs computation and control for achieving self-driving. For example, the ECU 184 estimates the position of the work vehicle 100 based on the data output from at least one of the GNSS unit 110, the camera (s) 120, and the LiDAR sensor(s) 140. In a situation where a sufficiently high reception intensity exists for the satellite signals from the GNSS satellites, the ECU 184 may determine the position of the work vehicle 100 based only on the data output from the GNSS unit 110. On the other hand, in an environment where obstructions, such as trees, that may hinder reception of the satellite signals exist around the work vehicle 100, e.g., an orchard, the ECU 184 estimates the position of the work vehicle 100 by using the data output from the LiDAR sensor(s) 140 or the camera(s) 120. During self-driving, the ECU 184 performs computation necessary for the work vehicle 100 to travel along a target path, based on the estimated position of the work vehicle 100. The ECU 184 sends the ECU 181 a command to change the speed, and sends the ECU 182 a command to change the steering angle. In response to the command to change the speed, the ECU 181 controls the prime mover 102, the transmission 103, or the brakes to change the speed of the work vehicle 100. In response to the command to change the steering angle, the ECU 182 controls the steering device 106 to change the steering angle.
Through the actions of these ECUs, the controller 180 realizes self-traveling. During self-traveling, the controller 180 is configured or programmed to control the drive device 240 based on the measured or estimated position of the work vehicle 100 and on the consecutively-generated target path. As a result, the controller 180 can cause the work vehicle 100 to travel along the target path.
The plurality of ECUs included in the controller 180 can communicate with one another in accordance with a vehicle bus standard such as, for example, a CAN (Controller Area Network). Instead of a CAN, faster communication methods such as Automotive Ethernet (registered trademark) may be used. Although the ECUs 181 to 184 are illustrated as individual blocks in
The communicator 190 is a device including a circuit communicating with the implement 300 and the terminal device 400. The communicator 190 includes circuitry to perform exchanges of signals complying with an ISOBUS standard such as ISOBUS-TIM, for example, between itself and the communicator 390 of the implement 300. This allows the implement 300 to perform a desired operation, or allows information to be acquired from the implement 300. The communicator 190 may further include an antenna and a communication circuit to exchange signals via the network 80 with the respective communicators of the terminal device 400. The network 80 may include a 3G, 4G, 5G, or any other cellular mobile communications network and the Internet, for example. The communicator 190 may have a function of communicating with a mobile terminal that is used by a supervisor who is situated near the work vehicle 100. With such a mobile terminal, communication may be performed based on any arbitrary wireless communication standard, e.g., Wi-Fi (registered trademark), 3G, 4G, 5G or any other cellular mobile communication standard, or Bluetooth (registered trademark).
The operational terminal 200 is a terminal for the user to perform a manipulation related to the travel of the work vehicle 100 and the operation of the implement 300, and is also referred to as a virtual terminal (VT). The operational terminal 200 may include a display device such as a touch screen panel, and/or one or more buttons. The display device may be a display such as a liquid crystal display or an organic light-emitting diode (OLED) display, for example. By manipulating the operational terminal 200, the user can perform various manipulations, such as, for example, switching ON/OFF the self-driving mode, and switching ON/OFF the implement 300. At least a portion of these manipulations may also be realized by manipulating the operation switches 210. The operational terminal 200 may be configured so as to be detachable from the work vehicle 100. A user who is at a remote place from the work vehicle 100 may manipulate the detached operational terminal 200 to control the operation of the work vehicle 100.
The drive device 340 in the implement 300 shown in
Next, with reference to
The LiDAR sensor 140 in the example of
A LiDAR sensor having an N of 1 may be referred to as a “two-dimensional LiDAR”, while a LiDAR sensor having an N of 2 or more may be referred to as a “three-dimensional LiDAR”. When N is 2 or more, the angle made by the first laser beam and an Nth laser beam is referred to as the “vertical viewing angle”. The vertical viewing angle may be set in a range from about 20° to 60°, for example.
As shown in
Each laser light source 142 includes a laser diode, and emits a pulsed laser beam of a predetermined wavelength in response to a command from the control circuit 145. The wavelength of the laser beam may be a wavelength that is included in the near-infrared wavelength region (approximately 700 nm to 2.5 μm), for example. The wavelength used depends on the material of the photoelectric conversion element used for the photodetector 143. In the case where silicon (Si) is used as the material of the photoelectric conversion element, for example, a wavelength around 900 nm may be mainly used. In the case where indium gallium arsenide (InGaAs) is used as the material of the photoelectric conversion element, a wavelength of not less than 1000 nm and not more than 1650 nm may be used, for example. Note that the wavelength of the laser beam is not limited to the near-infrared wavelength region. In applications where influences of ambient light are not a problem (e.g., for nighttime use), a wavelength included in the visible region (approximately 400 nm to 700 nm) may be used. Depending on the application, the ultraviolet wavelength region may also be used. In the present specification, any radiation in the ultraviolet, visible light, and infrared wavelength regions in general is referred to as “light”.
Each photodetector 143 detects laser pulses that are emitted from the laser light source 142 and reflected or scattered by an object. The photodetector 143 includes a photoelectric conversion element such as an avalanche photodiode (APD), for example. The photodetector 143 outputs an electrical signal which is in accordance with the amount of received light.
In response to a command from the control circuit 145, the motor 144 rotates the mirror that is placed on the optical path of a laser beam emitted from each laser light source 142. This realizes a scan operation that changes the outgoing directions of laser beams.
The control circuit 145 controls emission of laser pulses by the laser light sources 142, detection of reflection pulses by the photodetectors 143, and rotational operation by the motor 144. The control circuit 145 can be implemented by a circuit that includes a processor and a memory, e.g., a microcontroller unit (MCU), for example.
The signal processing circuit 146 is a circuit to perform computations based on signals that are output from the photodetectors 143. The signal processing circuit 146 uses a ToF (Time of Flight) technique to calculate a distance to an object that has reflected a laser pulse emitted from a laser light source 142, for example. ToF techniques include direct ToF and indirect ToF. Under direct ToF, the time from the emission of a laser pulse from the laser light source 142 until reflected light is received by the photodetector 143 is directly measured to calculate the distance to the reflection point. Under indirect ToF, a plurality of exposure periods are set in the photodetector 143, and the distance to each reflection point is calculated based on a ratio of light amounts detected in the respective exposure periods. Either the direct ToF or indirect ToF method may be used. The signal processing circuit 146 generates and outputs sensor data indicating the distance to each reflection point and the direction of that reflection point, for example. Furthermore, the signal processing circuit 146 may calculate coordinates (u,v) or (u,v,w) in the sensor coordinate system based on the distance to each reflection point and the direction of that reflection point, and include these in the sensor data for output.
Although the control circuit 145 and the signal processing circuit 146 are two separate circuits in the example of
The memory 147 is a storage medium to store data that is generated by the control circuit 145 and the signal processing circuit 146. For example, the memory 147 stores data that associates the emission timing of a laser pulse emitted from each laser unit 141, the outgoing direction, the reflected light intensity, the distance to the reflection point, and the coordinates (u,v) or (u,v,w) in the sensor coordinate system. Such data is generated each time a laser pulse is emitted, and recorded to the memory 147. The control circuit 145 outputs such data with a predetermined cycle (e.g., the length of time required to emit a predetermined number of pulses, a half scan period, or one scan period). The output data is recorded in the storage device 170 of the work vehicle 100.
The LiDAR sensor 140 outputs sensor data with a frequency of about 1 to 20 times per second, for example. This sensor data may include the coordinates of multiple points expressed by the sensor coordinate system, and time stamp information. The sensor data may include the information of distance and direction toward each reflection point but not include coordinate information. In such cases, the controller 180 performs conversion from the distance and direction information into coordinate information.
Note that the method of distance measurement is not limited to the ToF technique, but other methods such as the FMCW (Frequency Modulated Continuous Wave) technique may also be used. In the FMCW technique, light whose frequency is linearly changed is emitted, and distance is calculated based on the frequency of beats that occur due to interferences between the emitted light and the reflected light.
As described above, the LiDAR sensor(s) 140 according to the present example embodiment may be scan-type sensors, which acquire information on the distance distribution of objects in space by scanning a laser beam. However, the LiDAR sensors 140 are not limited to scan-type sensors. For example, the LiDAR sensor(s) 140 may be flash-type sensors, which acquire information on the distance distribution of objects in space by using light diffused over a wide area. A scan-type LiDAR sensor uses a higher intensity light than does a flash-type LiDAR sensor, and thus can acquire distance information at a greater distance. On the other hand, flash-type LiDAR sensors are suitable for applications that do not require intense light because they are simple in structure and can be manufactured at low cost.
Next, an operation of the work vehicle 100 will be described.
Therefore, the controller 180 according to the present example embodiment is configured or programmed to detect two crop rows existing on opposite sides of the work vehicle 100 based on sensor data that is output from the LiDAR sensor(s) 140, and cause the work vehicle 100 to travel along a path between the two crop rows.
At timings when the GNSS unit 110 is able to receive a GNSS signal, positioning may be conducted based on the GNSS signal. For example, at any timing of turning around along the path 30 illustrated in either
The controller 180 of the work vehicle 100 according to the present example embodiment operates in an inter-row travel mode of causing the work vehicle 100 to travel along a path between two adjacent rows of trees, and a turning travel mode of causing the work vehicle 100 to turn in a headland. A headland is a region between an end of each row of trees and the boundary of the orchard. In the inter-row travel mode, based on the sensor data being consecutively output from the LiDAR sensor(s) 140, the controller 180 detects two rows of trees existing on opposite sides of the work vehicle 100, and while setting a target path in between the two rows of trees, causes the work vehicle 100 to travel along the target path. During turning, based on the sensor data being consecutively output from the LiDAR sensor(s) 140, the controller 180 causes the work vehicle 100 to travel along the turning path, while performing localization for the work vehicle 100. In the turning travel mode, the controller 180 may utilize not only the sensor data but also utilize a signal that is output from the GNSS receiver 111 and/or a signal that is output from the IMU 115 to perform positioning. Once completing the turn, the work vehicle 100 again transitions to the inter-row travel mode. Thereafter, similar operations are repeated until the last instance of inter-row travel is finished. Through the above operation, self-traveling between rows of trees 20 is achieved. The above control is mainly realized by the ECU 184 of the controller 180 (
The obstacle map 40 has a predetermined length Lh and width Lw. The length Lh is a longitudinal size corresponding to the traveling direction of the work vehicle 100. The width Lw is a lateral size that is perpendicular to both of the traveling direction of the work vehicle 100 and the vertical direction.
In the example shown in
The target path 45 may be defined by a plurality of waypoints 45p. Each waypoint 45p may include information of the position and orientation (or velocity) of the point to be passed by the work vehicle 100. The interval between waypoints 45p may be set to a value of, e.g., several ten centimeters (cm) to several meters (m).
The controller 180 causes the work vehicle 100 to travel along the target path 45 that has been set. For example, the controller 180 performs steering control for the work vehicle 100 so as to reduce or minimize the deviation of the position and orientation of the work vehicle 100 with respect to the target path 45. As a result, the work vehicle 100 can be made to travel along the target path 45.
The obstacle map 40 shown in
The obstacle map 40 moves together with the work vehicle 100.
The controller 180 may generate the obstacle map 40 by eliminating data of any points that are estimated as corresponding to unwanted objects, e.g., the ground surface and weeds, from the sensor data that is output from the LiDAR sensor(s) 140. In a case where three-dimensional point cloud data is output as the sensor data, from the point cloud data, the controller 180 may extract only the data of points whose height from the ground surface is within a predetermined range (e.g., within a range of 0.1 m to 1.5 m), and generate the obstacle map from the extracted data of points. By such a method, an obstacle map indicating a distribution of trees (mainly the trunks) can be generated.
Based on the obstacle map 40, the controller 180 detects two rows of trees 20R and 20L existing on opposite sides of the work vehicle 100. For example, as shown in
Next, control of the steering angle of the wheels responsible for steering 104F will be described.
When the work vehicle 100 performs self-traveling between crop rows 20, it is desirable to control the steering angle θr so that the work vehicle 100 is prevented from coming into unwanted contact with the crop rows 20.
First, the ECU 184 acquires information on at least one of the work vehicle 100 or the surrounding environment of the work vehicle 100 (step S101). Based on the information on at least one of the work vehicle 100 or the surrounding environment of the work vehicle 100, the ECU 184 sets a maximum steering angle θmax for the wheels responsible for steering 104F (step S102). The maximum steering angle θmax is a maximum value that can be taken by the steering angle θr in the control of the steering angle θr of the wheels responsible for steering 104F, and is changeable depending on the condition.
For example, the ECU 184 acquires the value of traveling speed of the work vehicle 100, and sets the maximum steering angle θmax based on the value of traveling speed. For example, the ECU 184 can compute the traveling speed of the work vehicle 100 based on an output signal from the wheel axis sensor 156 (
The ECU 184 changes the maximum steering angle θmax in accordance with the traveling speed of the work vehicle 100. For example, the ECU 184 decreases the maximum steering angle θmax when the traveling speed is larger than when it is smaller. For example, as shown by solid lines in
The ECU 184 sets the target path 45 for the work vehicle 100 between two rows of trees 20 (step S103). Setting of the target path 45 includes setting of waypoints 45p. As described above, based on sensor data that is output from the LiDAR sensor (s) 140 or the like, the ECU 184 detects two rows of trees 20 existing on both right and left sides of the work vehicle 100, and sets the target path 45 in between the two detected rows of trees 20.
The ECU 184 computes a target steering angle θn for the wheels responsible for steering 104F to cause the work vehicle 100 to follow the target path 45 (step S104). For example, the ECU 184 computes a steering angle that is needed for the work vehicle 100 to pass through a next waypoint 45p that is located forward of the work vehicle 100, and this steering angle is deemed as the target steering angle θn.
The ECU 184 determines which one of the target steering angle θn having been computed at step S104 and the maximum steering angle θmax having been set step S102 is greater (step S105). The determination as to which one of the target steering angle θn and the maximum steering angle θmax is greater can be made by finding a greater one of the absolute value of the target steering angle θn and the absolute value of the maximum steering angle θmax.
If the computed target steering angle θn is equal to or smaller than the maximum steering angle θmax, the ECU 184 updates the value of the target steering angle θn to be used to control the steering device 106 from the value of the previously-adopted target steering angle θn−1 to the value of the currently computed target steering angle θn (step S106).
When the computed target steering angle θn is greater than the maximum steering angle θmax, the ECU 184 maintains the value of the previously-adopted target steering angle θn−1 as a value of the target steering angle θn to be used to control the steering device 106 (step S107).
The ECU 184 sends a command value to the ECU 182 so that the steering angle θr of the wheels responsible for steering 104F equals the target steering angle θn determined through the processes of steps S105 to S107. By controlling the steering device 106 in accordance with the command value, the ECU 182 changes the steering angle θr of the wheels responsible for steering 104F. As a result, the steering angle θr of the wheels responsible for steering 104F can be controlled so that it equals the target steering angle θn (step S108).
The ECU 184 returns to the process of step S101, and repeats the processes from step S101 to S108. When ending the aforementioned control for the steering angle θr, e.g., when finishing work between rows of trees 20, the process shown in
As described above, when the computed target steering angle θn is greater than the maximum steering angle θmax, the value of the previous target steering angle θn−1 is maintained, such that the steering angle of the wheels responsible for steering 104F can be controlled so as to be equal to or smaller than the maximum steering angle θmax.
In an implementation where a maximum steering angle θmax that is once set is never changed thereafter, the ECU 184 may return to the process of step S103 after the process of step S108. After determining the maximum steering angle θmax at the start of travel, the maximum steering angle θmax may be fixed to that value and not changed, or it may be changed during travel.
In a case where the target path 45 is not updated as frequently as the steering angle θr is changed, the ECU 184 may return to the process of step S104 after the process of step S108. After repeating the processes from step S104 to step S108 several times, control may return to the process of any of steps S101 to S103.
According to the present example embodiment, based on a state of at least one of the work vehicle 100 or the surrounding environment of the work vehicle 100, a maximum steering angle θmax for the wheels responsible for steering 104F is set, and the steering angle θr of the wheels responsible for steering 104F is controlled so as to be equal to or smaller than the maximum steering angle θmax. By setting the maximum steering angle θmax based on a state of at least one of the work vehicle 100 or the surrounding environment, the work vehicle 100 can be prevented from coming into contact with the rows of trees 20. By controlling the steering angle θr of the wheels responsible for steering 104F so as to be equal to or smaller than the maximum steering angle θmax, the work vehicle 100 can be prevented from coming into contact with the rows of trees 20, and driving stability can be improved.
At step S107 shown in
Moreover, for example, when the wheels responsible for steering 104F are to be steered right in order to follow the target path 45, the previous target steering angle to be maintained at step S107 may have been an angle of steering left. In that case, the steering angle θr of the wheels responsible for steering 104F may be controlled to be an angle of steering right.
The ECU 184 performs control so that the steering angle θr of the wheels responsible for steering 104F equals the processes of steps S105, S106, S107 and S117 target steering angle θn. When determining that the work vehicle 100 cannot be made to follow the target path 45 through such control of the steering angle θr, the ECU 184 may perform a control of halting the work vehicle 100. For example, when determining that following the target path 45 will result in a collision with some object in the surroundings (a tree, etc.), a control of halting the work vehicle 100 may be performed.
When determining that the work vehicle 100 cannot be made to follow the target path 45, the ECU 184 may perform a control of making the traveling speed of the work vehicle 100 smaller than the current traveling speed. The ECU 184 changes the maximum steering angle θmax based on the reduced traveling speed, and determines the target steering angle θn based on the changed maximum steering angle Amax. By reducing the traveling speed, the maximum steering angle θmax can be increased. By increasing the maximum steering angle θmax, the target steering angle θn can be increased, thus making it easier for the work vehicle 100 to follow the target path 45.
In the above description, the maximum steering angle θmax is set based on the traveling speed of the work vehicle 100. Alternatively, the maximum steering angle θmax may be set based on another parameter. For example, the ECU 184 may set the maximum steering angle θmax based on at least one of the following parameters.
As a result, a maximum steering angle θmax that is suitable for the surrounding environment of the work vehicle 100 and/or the work vehicle 100 can be set.
Next, an example of setting the maximum steering angle θmax in accordance with the size of the implement 300 connected to the work vehicle 100 will be described.
The size of an implement 300 shown on the right side of
For example, as shown by the solid lines in
Next, an example of setting the maximum steering angle θmax in accordance with the wheelbase of the work vehicle 100 will be described.
The wheelbase WB of a work vehicle 100 shown on the right side of
For example, the ECU 184 makes the maximum steering angle θmax larger when the wheelbase WB is large than when it is small. For example, as shown by solid lines in
Next, an example of setting the maximum steering angle θmax in accordance with the curvature of the row of trees 20 will be described.
The curvature of the row of trees 20 shown on the right side of
For example, as shown by the solid lines in
Next, an example of setting the maximum steering angle θmax in accordance with the size of dimension between two rows of trees 20 will be described.
The sensor data that is output from the LiDAR sensor(s) 140 includes point cloud data representing the rows of trees 20. From within the point cloud data representing the rows of trees 20, the ECU 184 extracts a point that is located closer to the work vehicle 100. By computing a distance between the point extracted from within the point cloud data representing the row of trees 20L and the point extracted from within the point cloud data representing the row of trees 20R, a value of the width L3 between the two rows of trees 20L and 20R can be acquired.
The width L3 shown on the left side of
For example, as shown by the solid lines in
Next, an example of setting the maximum steering angle θmax in accordance with a value D of difference between the width L3 between the rows of trees 20L and 20R and the width L4 of the work vehicle 100 will be described.
Information of the width L4 of the work vehicle 100 may be previously stored in the storage device 170. Information of the width L4 of the work vehicle 100 may be input by the user who manipulates the operation terminal 200 (
When an implement 300 whose width is larger than that of the work vehicle 100 is connected to the work vehicle 100, a value of the width of the implement 300 may be adopted as the width L4 of the work vehicle 100. Information of the size of the implement 300 may be input by the user who manipulates the operation terminal 200 (
The difference value D in the example shown on the left side of
For example, as shown in by the solid lines in
Next, an example of setting the maximum steering angle θmax in accordance with an angle of a dip of the ground surface of a current location of the work vehicle 100 will be described.
For example, as shown by the solid lines in
In the above example embodiments, the one or more exterior sensors included in the work vehicle are a LiDAR sensor(s) to output two-dimensional or three-dimensional point cloud data as sensor data through scanning of a laser beam. However, the exterior sensors are not limited to such LiDAR sensors. For example, other types of sensors such as flash-type LiDAR sensors or image sensors may be used. Such other types of sensors may be used in combination with scan-type LiDAR sensors.
Although in the above example embodiments the work vehicle performs self-traveling between rows of trees in an orchard, the work vehicle may be used for the purposes of self-traveling between crop rows other than rows of trees. For example, the techniques according to example embodiments of the present disclosure are applicable to work vehicles, such as tractors, which perform self-traveling among a plurality of crop rows in an agricultural field.
Devices that perform the processing needed for the self-traveling of the work vehicle according to the above example embodiments may be mounted to a work vehicle lacking such functionality as an add-on. For example, controllers configured or programmed to control the operation of work vehicles that travel among a plurality of crop rows may be attached to the work vehicle in use.
Thus, the present disclosure encompasses work vehicles, control methods, and computer programs as recited in the following Items.
A work vehicle 100 to perform self-traveling among a plurality of crop rows 20, the work vehicle 100 including wheels responsible for steering 104F, a steering device 106 to change a steering angle of the wheels responsible for steering 104F, an exterior sensor 140 to output sensor data indicating a distribution of geographic features around the work vehicle 100, and a controller 160 configured or programmed to control self-traveling of the work vehicle 100, set a maximum steering angle θmax for the wheels responsible for steering 104F based on a state of at least one of the work vehicle 100 or a surrounding environment of the work vehicle 100, detect two crop rows 20 existing on opposite sides of the work vehicle 100 based on the sensor data, set a target path 45 for the work vehicle 100 in between the two crop rows 20, compute a target steering angle θn for the wheels responsible for steering 104F to cause the work vehicle 100 to follow the target path 45, limit a value of the target steering angle θn to equal to or smaller than the maximum steering angle θmax when the computed target steering angle θn is greater than the maximum steering angle θmax, and control the steering device 106 so that the steering angle θr of the wheels responsible for steering 104F equals the target steering angle θn.
In one example embodiment, a maximum steering angle θmax for the wheels responsible for steering 104F is set based on a state of at least one of the work vehicle 100 or the surrounding environment of the work vehicle 100, and the steering angle θr of the wheels responsible for steering 104F is controlled so as to be equal to or smaller than the maximum steering angle θmax. By setting the maximum steering angle θmax based on a state of at least one of the work vehicle 100 or the surrounding environment, the work vehicle 100 can be prevented from coming into contact with the crop rows 20. By controlling the steering angle θr of the wheels responsible for steering 104F so as to be equal to or smaller than the maximum steering angle θmax, the work vehicle 100 can be prevented from coming into contact with the crop rows 20, and driving stability can be improved.
The work vehicle 100 of Item 1, wherein the controller 160 is configured or programmed to, when the computed target steering angle θn is equal to or smaller than the maximum steering angle θmax, update a value of the target steering angle θn to be used to control the steering device 106 from a value of a previous target steering angle θn−1 to a value of the computed target steering angle θn, and when the computed target steering angle θn is greater than the maximum steering angle θmax, maintain a value of a previous target steering angle θn−1 as a value of the target steering angle θn to be used to control the steering device 106.
When the computed target steering angle θn is greater than the maximum steering angle θmax, the value of the previous target steering angle θn−1 is maintained, such that the steering angle of the wheels responsible for steering 104F can be controlled so as to be equal to or smaller than the maximum steering angle θmax.
The work vehicle 100 of Item 1, wherein the controller 160 is configured or programmed to, when the computed target steering angle θn is equal to or smaller than the maximum steering angle θmax, update a value of the target steering angle θn to be used to control the steering device 106 from a value of a previous target steering angle θn−1 to a value of the computed target steering angle θn, and when the computed target steering angle θn is greater than the maximum steering angle θmax, adopt a value of the maximum steering angle θmax as a value of the target steering angle θn to be used to control the steering device 106.
When the computed target steering angle θn is greater than the maximum steering angle θmax, adopting the maximum steering angle θmax, i.e., the largest adoptable value, makes it easier for the work vehicle 100 to follow the target path 45.
The work vehicle 100 of any of Items 1 to 3, wherein the controller 160 is configured or programmed to set the maximum steering angle θmax based on at least one of a traveling speed of the work vehicle 100, a wheelbase WB of the work vehicle 100, a size of an implement 300 connected to the work vehicle 100, a curvature of the two crop rows 20, an angle of a dip of a current location of the work vehicle 100, a size of a distance between the two crop rows 20, or a difference between the distance between the two crop rows 20 and a width of the work vehicle 100.
A maximum steering angle θmax that is suitable for the surrounding environment of the work vehicle 100 and/or the work vehicle 100 can be set.
The work vehicle 100 of any of Items 1 to 4, wherein the controller 160 is configured or programmed to change the maximum steering angle θmax in accordance with a traveling speed of the work vehicle 100, and make the maximum steering angle θmax smaller when the traveling speed is larger than when the traveling speed is smaller.
A maximum steering angle θmax that is suitable for the magnitude of the traveling speed can be set. By decreasing the maximum steering angle θmax when the traveling speed is larger, driving stability can be improved.
The work vehicle 100 of any of Items 1 to 4, wherein the controller 160 is configured or programmed to change the maximum steering angle θmax in accordance with a size of an implement 300 connected to the work vehicle 100, and make the maximum steering angle θmax smaller when the size of the implement 300 is larger than when the size of the implement 300 is smaller.
A maximum steering angle θmax that is suitable for the size of the implement 300 can be set. When the size of the implement 300 (length along the front-rear direction and/or length along the width direction) is larger, the work vehicle 100 and the implement 300 can be prevented from coming into contact with the crop rows 20 by reducing the maximum steering angle θmax.
The work vehicle 100 of any of Items 1 to 4, wherein the controller 160 is configured or programmed to change the maximum steering angle θmax in accordance with a curvature of the two crop rows 20, and make the maximum steering angle θmax larger when the curvature is larger than when the curvature is smaller.
A maximum steering angle θmax that is suitable for the curvature(s) of the crop rows 20 can be set. By increasing the maximum steering angle θmax when the curvature(s) of the crop rows 20 is larger, the work vehicle 100 can be prevented from coming into contact with the crop rows 20.
The work vehicle 100 of any of Items 1 to 4, wherein the controller 160 is configured or programmed to change the maximum steering angle θmax in accordance with an angle of a dip of a current location of the work vehicle 100, and make the maximum steering angle θmax smaller when the angle of a dip is larger than when the angle of a dip is smaller.
A maximum steering angle θmax that is suitable for the angle of a dip of the current location of the work vehicle 100 can be set. By decreasing the maximum steering angle θmax when the angle of a dip is large, driving stability can be improved.
The work vehicle 100 of any of Items 1 to 4, wherein the controller 160 is configured or programmed to change the maximum steering angle θmax in accordance with a size of a distance between the two crop rows 20, and make the maximum steering angle θmax smaller when the distance between the two crop rows 20 is smaller than when the distance between the two crop rows 20 is larger.
A maximum steering angle θmax that is suitable for the distance between two crop rows 20 can be set. By decreasing the maximum steering angle θmax when the distance between two crop rows 20 is small, the work vehicle 100 can be prevented from coming into contact with the crop rows 20.
The work vehicle 100 of any of Items 1 to 4, wherein the controller 160 is configured or programmed to change the maximum steering angle θmax in accordance with a difference between a distance between the two crop rows 20 and a width of the work vehicle 100, and make the maximum steering angle θmax smaller when the difference is smaller than when the difference is larger.
A maximum steering angle θmax that is suitable for the magnitude of the difference between the width between crop rows 20 and the width of the work vehicle 100 can be set. By decreasing the maximum steering angle θmax when the difference is small, the work vehicle 100 can be prevented from coming into contact with the crop rows 20.
The work vehicle 100 of any of Items 1 to 4, wherein the controller 160 is configured or programmed to set the maximum steering angle θmax in accordance with a wheelbase WB of the work vehicle 100.
A maximum steering angle θmax that is suitable for the wheelbase WB of the work vehicle 100 can be set. For example, by increasing the maximum steering angle θmax for a work vehicle 100 with a wheelbase WB that is large, the work vehicle 100 can be prevented from coming into contact with the crop rows 20.
The work vehicle 100 of any of Items 1 to 11, wherein, when determining an impossibility to cause the work vehicle 100 to follow the target path 45, the controller 160 is configured or programmed to perform a control of halting the work vehicle 100.
By halting the work vehicle 100 when determining an impossibility to cause the work vehicle 100 to follow the target path 45, the work vehicle 100 can be prevented from coming into contact with the crop rows 20.
The work vehicle 100 of Item 5, wherein the controller 160 is configured or programmed to, when determining an impossibility to cause the work vehicle 100 to follow the target path 45, perform a control of making the traveling speed of the work vehicle 100 smaller than a current traveling speed, change the maximum steering angle θmax based on the reduced traveling speed, and determine the target steering angle based on the changed maximum steering angle θmax.
When determining that the work vehicle 100 cannot be made to follow the target path 45, the maximum steering angle θmax can be increased by reducing the traveling speed. By increasing the maximum steering angle θmax, the target steering angle θn can be increased, thus making it easier for the work vehicle 100 to follow the target path 45.
A control method of controlling a steering angle of a work vehicle 100 to perform self-traveling among a plurality of crop rows 20, including setting a maximum steering angle θmax for wheels responsible for steering 104F of the work vehicle 100 based on a state of at least one of the work vehicle 100 or a surrounding environment of the work vehicle 100, detecting two crop rows 20 existing on opposite sides of the work vehicle 100 based on sensor data output from an exterior sensor 140, the sensor data indicating a distribution of geographic features around the work vehicle 100, setting a target path 45 for the work vehicle 100 in between the two crop rows 20, computing a target steering angle θn for the wheels responsible for steering 104F to cause the work vehicle 100 to follow the target path 45, limiting a value of the target steering angle θn to equal to or smaller than the maximum steering angle θmax when the computed target steering angle θn is greater than the maximum steering angle θmax, and controlling a steering device of the work vehicle 100 so that the steering angle θr of the wheels responsible for steering 104F equals the target steering angle θn.
In one example embodiment, a maximum steering angle θmax for the wheels responsible for steering 104F is set based on a state of at least one of the work vehicle 100 or the surrounding environment of the work vehicle 100, and the steering angle θr of the wheels responsible for steering 104F is controlled so as to be equal to or smaller than the maximum steering angle Amax. By setting the maximum steering angle θmax based on a state of at least one of the work vehicle 100 or the surrounding environment, the work vehicle 100 can be prevented from coming into contact with the crop rows 20. By controlling the steering angle θr of the wheels responsible for steering 104F so as to be equal to or smaller than the maximum steering angle θmax, the work vehicle 100 can be prevented from coming into contact with the crop rows 20, and driving stability can be improved.
A non-transitory computer-readable medium including a computer program to cause a computer to control a steering angle of a work vehicle 100 to perform self-traveling among a plurality of crop rows 20, the computer program causing the computer to execute setting a maximum steering angle θmax for wheels responsible for steering 104F of the work vehicle 100, based on a state of at least one of the work vehicle 100 or a surrounding environment of the work vehicle 100, detecting two crop rows 20 existing on opposite sides of the work vehicle 100 based on sensor data output from an exterior sensor 140, the sensor data indicating a distribution of geographic features around the work vehicle 100, setting a target path 45 for the work vehicle 100 in between the two crop rows 20, computing a target steering angle θn for the wheels responsible for steering 104F to cause the work vehicle 100 to follow the target path 45, limiting a value of the target steering angle θn to equal to or smaller than the maximum steering angle θmax when the computed target steering angle θn is greater than the maximum steering angle θmax, and controlling a steering device of the work vehicle 100 so that the steering angle θr of the wheels responsible for steering 104F equals the target steering angle θn.
In one example embodiment, a maximum steering angle θmax for the wheels responsible for steering 104F is set based on a state of at least one of the work vehicle 100 or the surrounding environment of the work vehicle 100, and the steering angle θr of the wheels responsible for steering 104F is controlled so as to be equal to or smaller than the maximum steering angle θmax. By setting the maximum steering angle θmax based on a state of at least one of the work vehicle 100 or the surrounding environment, the work vehicle 100 can be prevented from coming into contact with the crop rows 20. By controlling the steering angle θr of the wheels responsible for steering 104F so as to be equal to or smaller than the maximum steering angle θmax, the work vehicle 100 can be prevented from coming into contact with the crop rows 20, and driving stability can be improved.
The example embodiments and techniques according to the present disclosure are applicable to work vehicles, e.g., tractors, that move in an environment in which a plurality of crop rows (e.g., rows of trees) exist, such as an orchard, an agricultural field, or a mountain forest.
While example embodiments of the present invention have been described above, it is to be understood that variations and modifications will be apparent to those skilled in the art without departing from the scope and spirit of the present invention. The scope of the present invention, therefore, is to be determined solely by the following claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2022-103962 | Jun 2022 | JP | national |
This application claims the benefit of priority to Japanese Patent Application No. 2022-103962 filed on Jun. 28, 2022 and is a Continuation application of PCT Application No. PCT/JP2023/021409 filed on Jun. 8, 2023. The entire contents of each application are hereby incorporated herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/JP2023/021409 | Jun 2023 | WO |
| Child | 19001702 | US |
