KR20190119213A - Agricultural machinery and automatic driving method thereof - Google Patents

Abstract

Disclosed is an agricultural machinery. The agricultural machinery of the present invention comprises: a driving unit; a sensor sensing a position and movement of the agricultural machinery; and a processor controlling the driving unit so that the agricultural machinery drives along an autonomous driving route based on memory storing the autonomous driving route and the position and movement of the agricultural machinery. The sensor includes a global navigation satellite system (GNSS) sensor. The autonomous driving route is generated based on data obtained in the GNSS sensor while the agricultural machinery is driving a predetermined route.

Description

AGRICULTURAL MACHINERY AND AUTOMATIC DRIVING METHOD THEREOF}

The present invention relates to an agricultural machine and its autonomous driving method, and relates to an agricultural machine and its autonomous driving method which can move unmannedly.

In the agricultural sector, it is urgent to improve the agricultural conditions due to the declining and aging population of the agricultural population and rising agricultural management costs. Therefore, it is necessary to be competitive in the agricultural sector, the most important of which is to transform into a high value-added industry by integrating with IT and sensor technology.

On the other hand, with the recent development of electronic technology, agricultural machines are operated unattended. In order to operate agricultural machinery unattended, an autonomous driving route is required, but there is a problem that a large cost is required to establish an autonomous driving route.

Accordingly, it is an object of the present invention to provide an agricultural machine and an autonomous driving method thereof capable of autonomous driving using an autonomous driving route generated using a Global Navigation Satellite System (GNSS) sensor.

Farm machinery according to an embodiment of the present invention for achieving the above object is based on a driving unit, a sensor for detecting the position and movement of the agricultural machine, a memory storing the autonomous driving path and the position and movement of the detected agricultural machine And a processor configured to control the driving unit to allow a farm machine to travel along the autonomous driving path, wherein the sensor includes a Global Navigation Satellite System (GNSS) sensor, and the autonomous driving path is configured to drive the predetermined path while the farm machine is driving. It may be generated based on the data obtained from the GNSS sensor.

In this case, the data obtained by the GNSS sensor may include the position, speed and direction angle of the agricultural machine.

Meanwhile, the processor acquires the geodetic coordinates of the agricultural machine through the GNSS sensor, converts the obtained geodetic coordinates into local coordinates while the agricultural machine is driving the predetermined path, and directs the direction of the agricultural machine through the GNSS sensor. Acquire an angle, determine a shape of a path along which the agricultural machine moves based on the obtained direction angle, generate the autonomous driving path based on the local coordinates and the determined path shape, and generate the autonomous driving The path can be stored in the memory.

In addition, the processor compares a factor for determining the quality of the GNSS sensor with a preset reference value, and when the factor satisfies the preset reference value, the processor predicts a navigation solution before a specific time before the current time. The current position of the agricultural machine and the current position of the agricultural machine obtained through the GNSS sensor are compared to determine whether the position of the agricultural machine obtained through the GNSS sensor is in a good state, and the driving of the agricultural machine is controlled according to the determined state. can do.

Here, when it is determined that the position of the agricultural machine acquired through the GNSS sensor is not good, the processor may stop the agricultural machine in motion.

In addition, when it is determined that the position of the agricultural machine acquired through the GNSS sensor is good, the processor may control the speed of the agricultural machine by comparing the speed of the agricultural machine detected by the GNSS sensor with a preset operating speed.

Here, the processor decreases the speed of the moving farm machinery when the detected speed exceeds a preset operating speed, and increases the speed of the moving farm machinery when the sensed speed is less than a preset operating speed. You can.

On the other hand, if it is determined that the position of the agricultural machine acquired through the GNSS sensor is good, the processor acquires the navigation solution before the time of the current time, and based on the obtained navigation solution, the processor calculates the current time on the autonomous driving route. Estimating a first position after a specific time on the basis of the reference, estimating a second position after a specific time after the current time on the basis of the obtained navigation solution, and comparing the first position to the first position on the basis of the current position of the agricultural machine. The direction angle difference between the first vector and the second vector up to the second position may be calculated based on the current position of the farm machine, and the moving direction of the farm machine being moved may be controlled based on the calculated direction angle difference. .

On the other hand, the autonomous driving method of a farm machine according to an embodiment of the present invention using a sensor, detecting the position and movement of the farm machine and the farm machinery is stored in the farm machine based on the detected position and movement of the farm machine And controlling the vehicle to travel along an autonomous driving path, wherein the sensor includes a Global Navigation Satellite System (GNSS) sensor, and the autonomous driving path is obtained by the GNSS sensor while the agricultural machine is driving a predetermined path. It may be generated based on the data.

According to various embodiments of the present disclosure as described above, an autonomous driving path for autonomous driving of an unmanned agricultural machine can be generated using an inexpensive GNSS sensor, thereby significantly securing a price competitiveness, and autonomous in a faster time than the conventional method. A driving route can be created.

And, by maneuvering the agricultural machinery by autonomous driving, it is possible to prevent a safety accident that can occur when a person directly operates the agricultural machinery to perform agricultural-related work.

1 is a block diagram for explaining the configuration of a farm machine according to an embodiment of the present invention;
2 is a view for explaining a method for generating an autonomous driving route according to an embodiment of the present invention;
3 is a flowchart illustrating a method for determining whether an GNSS sensor is abnormal according to an embodiment of the present invention;
4 and 5 are views for explaining a method for updating an autonomous driving route according to an embodiment of the present invention;
6 is a flowchart illustrating a method of controlling the traveling speed of agricultural machinery according to an embodiment of the present invention;
7 is a flowchart illustrating a method of controlling a driving direction of farm machinery according to an embodiment of the present invention;
8 is a view for explaining a user interface provided in an electronic device according to an embodiment of the present disclosure; and
9 is a flowchart illustrating an autonomous driving method according to an embodiment of the present invention.

Hereinafter, various embodiments of the present disclosure will be described with reference to the accompanying drawings.

1 is a block diagram illustrating a configuration of a farm machine according to an embodiment of the present invention.

First, the agricultural machine 100 according to an embodiment of the present invention may refer to various driving means used for work such as plowing, arranging fertilizer, fertilizer transportation, and various crops of a cultivated land such as a tractor, combine, and cultivator. To this end, the farm machinery 100 may include a wheel provided in the lower portion of the main body and the front and rear of the main body.

On the other hand, the agricultural machine 100 may be implemented as an unmanned agricultural machine that can move autonomously along a predetermined path even if a human being does not board, for this purpose, the agricultural machine 100 is a driving unit 110, a sensor ( 120, a memory 130, and a processor 140.

The driving unit 110 is a configuration for controlling the running of the agricultural machine 100. For example, the driving unit 110 increases the rotational speed of the wheels provided on the farm machinery 100 through the accelerator actuator, and reduces the rotational speed of the wheels provided on the farm machinery 100 through the brake actuator or stops the wheels. By rotating the rotary shaft of the wheel provided in the farm machinery 100 through the steering angle control actuator, the farm machinery 100 can be rotated in the left or right direction.

The sensor 120 detects the position and movement of the farm machine 100.

To this end, the sensor 120 may include a global navigation satellite system (GNSS) sensor 121 and a driver sensor 122 as shown in FIG. 1B.

The GNSS sensor 121 (or the GNSS receiver) may measure the position, speed, direction angle, etc. of the agricultural machine 100 using a satellite. Here, the position, speed, direction angle, etc. of the agricultural machine 100 obtained through the GNSS sensor 121 may be referred to as the side of the GNSS sensor 121.

GNSS refers to a system that calculates coordinates of a specific position by using radio waves from space satellites.GPS (Global Positioning System), GLONASS (Global Navigation Satellite System) in Russia, and GALILEO in Europe (Europian Satellite Navigation System) and China's Beidou (North China, Compass) are integrated names of various positioning systems using satellites.

As such, since the GNSS uses satellites, the GNSS can acquire position, velocity, and time information, regardless of time and space, and relatively stable compared to other systems.

The GNSS sensor 121 determines its position using the GNSS signal received from the satellite, receives the positioning correction information from the Real Time Kinematic (RTK) reference station 300, and uses the positioning correction information, the GNSS signal. It is possible to correct its position determined through.

On the other hand, according to an embodiment of the present invention, the GNSS sensor 121 may be implemented as a low-cost GNSS sensor based on a single frequency.

That is, in the case of farm machinery, the position can be measured sufficiently accurate with only a single frequency in that it moves at a relatively low speed compared to drones, flying vehicles, ships, and the like. As such, according to an embodiment of the present invention, in terms of using a single frequency-based GNSS sensor, it is possible to measure the position of the farm machine 100 at a lower cost than a sensor using two or more frequencies. In this case, the RTK reference station 300 may generate location correction information so as to calculate a location having a cm grade accuracy and provide the location correction information to the GNSS sensor 121 of low cost.

The driving body sensor 122 may measure the speed, the direction angle, and the like of the agricultural machine 100. To this end, the driving body sensor 122 may include a steering angle sensor for measuring the direction angle of the farm machinery 100 and a speed sensor for measuring the speed of the farm machinery 100.

The memory 130 stores an autonomous driving route. In this case, the farm machine 100 may run autonomously according to the autonomous driving route unattended by a person.

Here, the autonomous driving route may be generated based on the data acquired by the GNSS sensor 120 while the agricultural machine 100 runs the predetermined route.

For example, the autonomous driving path is a position of the agricultural machine 100 obtained from the GNSS sensor 120 while driving in advance on a path (for example, a farmland, a rough road, a road, etc.) to which the agricultural machine 100 travels forward. , Speed and direction angle.

A detailed method of generating such an autonomous driving route will be described later.

In addition, the memory 130 may store the path generation module 141 and the motion control module 142 illustrated in FIG. 1B. Meanwhile, although the modules are individually illustrated in FIG. 1B, at least two modules may be combined and implemented.

The processor 140 controls the overall operation of the farm machine 100. To this end, the processor 140 may execute a dedicated processor (eg, an embedded processor) for controlling the operation of the agricultural machine 100 or one or more software programs stored in a memory device, thereby executing the corresponding operations. It may be implemented as a generic-purpose processor (for example, a CPU or an application processor).

First, the processor 140 may generate an autonomous driving route. In this case, the processor 140 may execute the path generation module 141 and generate an autonomous driving path by using the data acquired by the GNSS sensor 121 as an input of the path generation module 141.

In detail, the processor 140 may acquire geodetic coordinates of the farm machine 100 through the GNSS sensor 121 while the farm machine 100 travels a predetermined path. Here, the geodetic coordinates may include information about latitude, longitude, and ellipsoid height.

In addition, the processor 140 may convert the obtained geodetic coordinates into local coordinates. That is, since geodetic coordinates are geospheroid-based coordinates, the processor 140 may convert geodetic coordinates into local coordinates in a rectangular coordinate format. Here, the local coordinates may include information about x, y coordinates (eg, east, north coordinates based on a specific reference point) and height based on a specific reference point.

In addition, the processor 140 may acquire a direction angle of the farm machine 100 through the GNSS sensor 121, and determine a form of a path along which the farm machine 100 moves based on the obtained direction angle.

Here, the shape of the path may include a rotation path and a straight path.

In this case, the processor 140 compares the direction angle of the current farm machine 100 with the direction angle of the farm machine 100 acquired before a specific time before the current time through the GNSS sensor 121, and then the farm machine 100 proceeds. It may be determined whether the path corresponds to the rotation path or the straight path.

In detail, the processor 140 may determine that the path that the agricultural machine 100 proceeds to the rotation path when the difference between the direction angle of the current agricultural machine 100 and the direction angle of the agricultural machine 100 acquired before a specific time is greater than or equal to a predetermined value. If the difference between the direction angle of the current agricultural machinery 100 and the direction angle of the agricultural machinery 100 obtained before a specific time is less than the predetermined value, the path that the agricultural machinery 100 proceeds corresponds to a straight path. You can judge that.

Thereafter, the processor 140 may generate the autonomous driving route based on the determined route type and the local coordinates, and store the generated autonomous driving route in the memory 130.

In detail, the processor 140 may set waypoints according to the determined path type, and generate autonomous driving paths by mapping local coordinates and a path vector for each waypoints.

First, a method of setting waypoints will be described with reference to FIG. 2.

For example, as shown in (a) of FIG. 2, the agricultural machine 100 moves along a point 211 → a point 212 → a point 213 → a point 214 → a point 215 → a point 216 → a point 217 → a point 218 → a point 219. Assume

In this case, the local coordinates for each point consist of x, y coordinates and height h relative to a particular reference point, and in FIG. 2 for each point (x _n , y _n , h _n ) where n is 1 to 9).

In this case, the processor 140 corresponds to a straight path in that the path traveled along the point 211 → point 212 → point 213 is that the difference between the direction angles between these points is less than the predetermined value. For a path that has traveled along point 213 → point 214 → point 215 → point 216, it is determined that the path corresponds to a curved path in that the difference between the direction angles between these points is more than a predetermined value. For a path that has traveled along point 216 → point 217 → point 218 → point 219, it may be determined that the path corresponds to a straight path in that the difference between the direction angles between these points is less than a predetermined value. .

In this case, the processor 140 may set the start point and the end point of the straight path as waypoints for the points included in the straight path. In addition, the processor 140 may map local coordinates to waypoints and map a path vector from the start point toward the end point to the waypoint of the start point to generate an autonomous driving path for the straight path.

In addition, the processor 140 may set the points included in the curved path as waypoints with respect to the points included in the curved path. In addition, the processor 140 may map local coordinates to waypoints and map a path vector from each point to the next point to the waypoint of each point to generate an autonomous driving path for the curved path.

For example, in FIG. 2 (a), the processor 140 moves along a point 211 → point 212 → point 213 to correspond to a straight path, so that the processor 140 corresponds to FIG. 2 (b). as such, the set point 211 and point 213 to waypoints on its route, and map the local coordinates (x _1, y _1, h ₁₎ to the waypoint 1 (that is, point 211), local coordinates (x _3, and y ₃ , h ₃ ) is mapped to waypoint 2 (ie, point 213), and the vector 221 connecting waypoint 2 to waypoint 1 is mapped to waypoint 1 (ie, point 211), so that the agricultural machine 100 is at point 211 → You can create an autonomous driving route for the route traveled along point 212 → point 213.

In addition, in FIG. 2 (a), the processor 140 moves along a point 213 → point 214 → point 215 → point 216 to correspond to a curved path. Set point 213, point 214, point 215 and point 216 as waypoints for that route, map local coordinates (x ₃ , y ₃ , h ₃ ) to waypoint 2 (ie, point 213), Map local coordinates (x ₄ , y ₄ , h ₄ ) to waypoint 3 (ie, point 214), map local coordinates (x ₅ , y ₅ , h ₅ ) to waypoint 4 (ie, point 215), Map a local coordinate (x ₆ , y ₆ , h ₆ ) to waypoint 5 (ie point 216), map a vector 222 connecting waypoint 3 to waypoint 2 to waypoint 2 (ie point 213), and waypoint Map a vector 223 connecting waypoint 4 to 3 to waypoint 3 (i.e. point 214), and a vector 224 connecting waypoint 5 to waypoint 4 to waypoint 4 (i.e. point 215), Point 214 → Point 215 → Follow point 216 An autonomous driving route may be generated for the moved route.

In addition, in FIG. 2 (a), the processor 140 moves along a point 216 → point 217 → point 218 → point 219 to correspond to a straight line path. ), Set points 216 and 219 as waypoints for that route, map local coordinates (x ₆ , y ₆ , h ₆ ) to waypoint 5 (ie, point 216), and map local coordinates (x ₉ , y ₉ , h ₉ ) is mapped to waypoint 6 (ie, point 219), and a vector 225 joining waypoint 6 to waypoint 5 to waypoint 5 (ie, point 216), so that agricultural machine 100 is at point 216. → point 217 → point 218 → create an autonomous driving route for the route taken along point 219.

As such, according to an embodiment of the present invention, instead of storing the entire route including the route and the vicinity of the route for autonomous driving, the farm machine 100 actually travels in advance on the route to be driven for the corresponding route. Only information can be stored. In addition, instead of storing all the location related information obtained from the corresponding path, the autonomous driving path may be generated by selectively storing the location related information according to the type of the path.

Accordingly, according to an embodiment of the present invention, since an optimal autonomous driving route can be generated without using a drone or a mobile mapping system (MMS) equipped with an expensive sensor, time and In economic terms, efficiency can be maximized.

Meanwhile, the processor 140 may control the farm machine 100 to travel along the autonomous driving path.

In detail, the processor 140 may control the driving unit 110 to allow the farm machine 100 to travel along the autonomous driving path based on the position and the movement of the farm machine 100 detected by the sensor 120.

In this case, the processor 140 may determine whether the GNSS sensor 121 is abnormal, and accordingly, control the running of the agricultural machine 100.

Hereinafter, a method of determining whether the GNSS sensor 121 is abnormal will be described in more detail with reference to FIG. 2.

First, the processor 140 compares a factor for determining the quality of the GNSS sensor 121 with a preset reference value (S310).

Here, the quality determining factor may include at least one of an ambiguous number of the GNSS sensor 121, a location precision, the number of satellites, and a dilution of precision (DOP), and such information may be obtained from the GNSS sensor 121. Can be.

In this case, when the quality determination factor does not satisfy the preset reference value (S320-N), the processor 140 may determine that the current position state is poor (S330). As such, when the quality determination factor does not satisfy the preset reference value, the processor 140 may be regarded as having a lower accuracy of data acquired from the GNSS sensor 121. Accordingly, the processor 140 does not use the position-related information obtained from the GNSS sensor 121 to control the running of the agricultural machine 100, and stops the running of the agricultural machine 100 when the agricultural machine 100 is running. The driving unit 110 may be controlled to be controlled.

For example, the processor 140 may generate a control signal for stopping driving of the wheel and provide the generated control signal to the driver 110. In this case, the driving unit 110 may drive the brake actuator according to the control signal provided from the processor 140 to stop the driving of the wheel.

On the other hand, when the quality determination factor satisfies the preset reference value (S320-Y), the processor 140 stores the data acquired through the GNSS sensor 121 in the memory 130 (S340). Here, the data obtained through the GNSS sensor 121 may include a position, a speed and a direction angle of the agricultural machine 100.

Thereafter, the processor 140 predicts the current position of the farm machinery 100 through a navigation solution before a specific time than the current time (S250).

That is, the processor 140 uses the data acquired through the GNSS sensor 121 before a specific time before the current time, so that the position of the agricultural machine 100 after the specific time from the corresponding time, that is, the agricultural machine at the current time ( The position of 100) can be predicted.

Specifically, the processor 140 is a position at a previous time, a speed at a previous time, a direction angle at a previous time, and between the previous time and the current time, obtained by the GNSS sensor 121 at the previous time. Using the time difference, it is possible to predict the position of the agricultural machine 100 at the current time.

That is, when the agricultural machine 100 moves for a time difference at a speed at a previous time along a direction at a previous time from a position at a previous time, the processor 140 determines a position to which the agricultural machine 100 will reach at the current time. It can be predicted by the position of the agricultural machine 100 at the current time.

In addition, the processor 140 may measure the position of the current agricultural machine 100 based on the GNSS (S360). That is, the processor 140 may obtain the current position of the farm machine 100 through the GNSS sensor 121 at the current time.

Thereafter, the processor 140 compares the predicted current position of the agricultural machine 100 with the current position of the agricultural machine 100 acquired through the GNSS sensor 121, and then obtains the agricultural machine 100 obtained through the GNSS sensor 121. It can be determined whether the position of is in a good state.

In detail, the processor 140 may calculate a distance difference between the predicted current position of the agricultural machine 100 and the current position of the agricultural machine 100 acquired through the GNSS sensor 121 (S370).

When the distance difference does not satisfy the reference value (S380-N) (that is, when the distance difference exceeds a preset reference value), the processor 140 may determine that the current position state is poor (S330). That is, when the distance difference does not satisfy the reference value, the processor 140 may determine that the position of the agricultural machine 100 measured by the GNSS sensor 121 is poor.

As such, when it is determined that the position of the agricultural machine 100 measured by the GNSS sensor 121 is inferior, the processor 140 transmits the position related information obtained from the GNSS sensor 121 to the control of the running of the agricultural machine 100. When not in use, when the agricultural machine 100 is running, the driving unit 110 may be controlled to stop the driving of the agricultural machine 100 (S380).

Meanwhile, when the distance difference satisfies the reference value (S380 -Y) (that is, when the distance difference is less than or equal to the predetermined reference value), the processor 140 may determine that the current position state is good (S290). That is, when the distance difference satisfies the reference value, the processor 140 may determine that the position of the agricultural machine 100 measured by the GNSS sensor 121 is good.

In this case, when it is determined that the position of the agricultural machine 100 measured by the GNSS sensor 121 is good, the processor 140 uses the position-related data measured by the GNSS sensor 121 to drive the agricultural machine 100. Can be controlled.

As such, according to an embodiment of the present disclosure, inaccurate data may be measured in relation to the position of the agricultural machine 100 in the GNSS sensor 121 according to the surrounding environment, thereby controlling the running of the agricultural machine 100. In this case, it is possible to determine whether abnormality of the data acquired by the GNSS sensor 121, and to control the running of the agricultural machine 100 according to the result, it is possible to control the autonomous driving more accurately.

The processor 140 may update the autonomous driving path and control the farm machine 100 to travel along the updated autonomous driving path.

That is, the processor 140 determines which waypoint among the plurality of waypoints existing around the target point to which the agricultural machine 100 travels, when the agricultural machine 100 deviates from the autonomous driving path, and determines the determined waypoint. The autonomous driving route can be updated based on this. In addition, the processor 140 may control the farm machine 100 to travel along the updated autonomous driving path.

First, the processor 140 may determine whether the position of the agricultural machine 100 acquired through the GNSS sensor 121 is in a good state (S410). This has been described in detail with reference to FIG. 3.

Subsequently, when the position of the agricultural machine 100 obtained through the GNSS sensor 121 is good, the processor 140 may acquire the current position of the agricultural machine 100 through the GNSS sensor 121 (S420).

In addition, the processor 140 may determine whether the agricultural machine 100 has left the autonomous driving path, based on the current position and the autonomous driving path of the agricultural machine 100 (S430).

Specifically, the processor 140 compares the current position of the agricultural machine 100 obtained through the GNSS sensor 121 with a position defined between waypoints according to the position and the path vector of the waypoints, and thus, the current of the agricultural machine 100. When the location is not included in the locations or is separated from the locations by more than a predetermined distance, it may be determined that the farm machinery 100 has left the autonomous driving path.

In addition, when it is determined that the agricultural machine 100 deviates from the autonomous driving path (S430 -Y), the processor 140 may determine a vertical line orthogonal to the path vector based on the current position of the agricultural machine 100. (S440).

Thereafter, the processor 140 may update the autonomous driving path based on the vertical line (S450).

In detail, the processor 140 determines a vertical line having the shortest distance among vertical lines orthogonal to the path vector, and a new waypoint to which the farm machine 100 having moved from the current path moves a waypoint to which the path vector meeting the determined vertical line is directed. Can be set to update the autonomous driving route.

For example, as shown in FIG. 5, the agricultural machine 100 deviates from the autonomous driving path, is currently located at the point 510, and three waypoints 520, 530, and 540 are located around the current position 510 of the agricultural machine 100. Assume that it exists.

In this case, the processor 140 is a vertical line 570 and the agricultural machine (the vertical line 570 perpendicular to the path vector 550 from the waypoint 1 520 to the waypoint 2 530 using the current position 510 of the agricultural machine 100 as a starting point). A vertical line 580 perpendicular to the path vector 560 from the waypoint 2 530 to the waypoint 3 540 may be determined based on the current position 510 of 100.

In addition, the processor 140 compares the distance between the vertical line 570 and the vertical line 580 to determine a relatively short vertical line 570 among them, and the waypoint to which the path vector 550 where the vertical line 570 meets is directed. Set 2 530 as the waypoint that the agricultural machine 100 should move from the current position 510 and position the path vector 590 from the current position 510 towards waypoint 2 530 relative to the current position 510. By mapping to, the autonomous driving route may be updated from the current location 510 to the waypoint 2 530 to the waypoint 3 540.

On the other hand, the processor 140 may control the driving unit 110 so that the farm machinery 100 travels along the autonomous driving path.

That is, when the farm machine 100 moves along the autonomous driving path, the processor 140 may control the driving unit 110 so that the farm machine 100 travels along the autonomous driving path at a constant operating speed without departing from the autonomous driving path. Can be.

In this case, the processor 140 executes the motion control module 142, and inputs data obtained from the sensor 120, data about an autonomous driving path obtained from the memory 130, and the like to the motion control module 142. As a result, a control signal for controlling the driver 110 may be generated, and the generated control signal may be output to the driver 110. Accordingly, the driving unit 110 may drive the accelerator actuator, the brake actuator and the steering angle control actuator according to the control signal provided from the processor 140 to control the running of the farm machine 100.

Hereinafter, referring to FIG. 6, a method of controlling the traveling speed of the farm machinery 100 will be described.

First, the processor 140 may determine whether the position of the agricultural machine 100 obtained through the GNSS sensor 121 is good. In this case, the processor 140 may determine whether the position of the agricultural machine 100 obtained through the GNSS sensor 121 is good according to the method illustrated in FIG. 3 (S610).

In addition, when it is determined that the position of the farm machine 100 acquired through the GNSS sensor 121 is not good (S620 -N), the processor 140 may stop the farm machine 100 in motion.

In this case, the processor 140 may drive the brake actuator (S630).

In detail, the processor 140 may generate a control signal for stopping driving of the wheel and provide the generated control signal to the driver 110. In this case, the driving unit 110 may drive the brake actuator according to the control signal provided from the processor 140 to stop the driving of the wheel.

On the other hand, when the processor 140 determines that the position of the agricultural machine 100 acquired through the GNSS sensor 121 is good (S620-Y), the processor 140 measures the speed of the agricultural machine 100 detected by the GNSS sensor 121. The speed of the agricultural machine 100 can be controlled compared to the set operating speed.

In this case, when the speed detected by the GNSS sensor 121 exceeds a preset operating speed, the processor 140 decreases the speed of the agricultural machine 100 that is moving, and the speed detected by the GNSS sensor 121. If is less than the predetermined operating speed, it is possible to increase the speed of the agricultural machine 100 in motion.

In detail, the processor 140 may calculate a difference between the current speed of the farm machine 100 detected by the GNSS sensor 121 and a preset operating speed (S640).

In addition, the processor 140 may control the speed of the farm machine 100 based on a difference between the current speed of the farm machine 100 and a preset operating speed.

In detail, the processor 140 may determine whether a difference between the current speed of the farm machine 100 and a preset operating speed exceeds a preset reference value (S650).

In this case, when the difference between the current speed of the agricultural machine 100 and the preset operating speed exceeds a preset reference value (S650-Y), the processor 140 may drive the brake actuator (S630).

In detail, the processor 140 determines a speed that should be reduced from the current speed in order for the speed of the farm machine 100 to be a preset operating speed, and a control signal for reducing the speed of the farm machine 100 by the determined speed. May be generated and provided to the driver 110. In this case, the driving unit 110 may reduce the speed of the wheel by driving the brake actuator according to the control signal provided from the processor 140. Accordingly, the agricultural machine 100 can travel at a predetermined operating speed.

Meanwhile, the processor 140 may determine whether the difference is less than the preset reference value when the difference between the current speed of the farm machine 100 and the preset operating speed does not exceed the preset reference value (S650-N).

In addition, when the difference between the current speed of the farm machine 100 and the preset operating speed is less than the predetermined reference value (S660-Y), the processor 140 may drive the accelerator actuator (S670).

Specifically, the processor 140 determines a speed that should be increased from the current speed in order for the speed of the farm machine 100 to be a preset operating speed, and a control signal for increasing the speed of the farm machine 100 by the determined speed. May be generated and provided to the driver 110. In this case, the driving unit 110 may drive the accelerator actuator according to a control signal provided from the processor 140 to increase the speed of the wheel. Accordingly, the agricultural machine 100 can travel at a predetermined operating speed.

On the other hand, if the difference between the current speed and the predetermined operating speed of the agricultural machine 100 is less than the predetermined reference value (S660-N), the processor 140 may return to step S610 and repeat the above.

As a result, the processor 140 may control the farm machine 100 to travel along the autonomous driving path at a predetermined operating speed through the above-described method.

Hereinafter, a method of controlling the driving direction of the farm machinery 100 will be described with reference to FIG. 7.

First, the processor 140 may determine whether the position of the agricultural machine 100 obtained through the GNSS sensor 121 is good. In this case, the processor 140 may determine whether the position of the agricultural machine 100 obtained through the GNSS sensor 121 is good according to the method illustrated in FIG. 3.

In addition, if it is determined that the position of the agricultural machine 100 obtained through the GNSS sensor 121 is good, the processor 140 obtains a navigation solution (S710). In detail, the processor 140 may acquire a position, a speed, a direction angle, and the like of the agricultural machine 100 through the GNSS sensor 121 at the present time.

The processor 140 may estimate a first position after a specific time on the autonomous driving route based on the current time based on the obtained navigation solution (S720).

That is, the processor 140 may estimate the position at which the agricultural machine 100 will travel on the autonomous driving path after a specific time from the current time, using the data acquired through the GNSS sensor 121 at the current time.

In detail, when the agricultural machine 100 travels along the autonomous driving path for a specific time at a speed of the current time from the location of the current time, the processor 140 may determine a position that arrives on the autonomous driving path when a specific time elapses. After a certain time, the agricultural machine 100 may estimate a position to travel on the autonomous driving path.

In addition, the processor 140 may estimate a second position after a specific time based on the current time based on the obtained navigation solution (S730).

In detail, when the agricultural machine 100 travels for a specific time from the location of the current time at the speed of the current time along the moving direction at the current time, not on the autonomous driving path, the specific time has elapsed. The position arriving at the viewpoint may be estimated as the position at which the agricultural machine 100 will travel after a specific time.

In addition, the processor 140 may determine a direction angle difference between the first vector up to the first position based on the current position of the farm machine 100 and the second vector up to the second position based on the current position of the farm machine 100. It may be calculated (S740).

That is, the processor 140 generates a first vector connecting the first position from the current position of the farm machine 100 and a second vector connecting the second position from the current position, respectively, and between the first and second vectors. The direction angle difference can be calculated.

Thereafter, the processor 140 may control the moving direction of the agricultural machine 100 that is moving based on the calculated direction angle difference.

In detail, the processor 140 may calculate a steering angle at which the rotation axis of the wheel should rotate in order to change the driving direction of the farm machine 100 by the calculated direction angle using the Steering Dynamic Model (S450).

In addition, the processor 140 may drive the steering angle control actuator based on the calculated steering angle.

That is, the processor 140 may generate a control signal for rotating the rotation axis of the wheel by the calculated steering angle and provide the generated control signal to the driver 110. In this case, the driving unit 110 may drive the steering angle control actuator according to a control signal provided from the processor 140 to rotate the rotation axis of the wheel in the left direction or the right direction by the calculated steering angle. Accordingly, the farm machine 100 can travel along the autonomous driving path without departing from the autonomous driving path.

On the other hand, in the above-described example, in order to control the running of the farm machinery 100, the processor 140 may use data acquired from the drive sensor 122, for example, the speed and the direction angle of the farm machinery 100, and the like.

In addition, in the above-described example, the processor 140 may estimate the position at which the agricultural machine 100 will travel on the autonomous driving path after a specific time using the updated autonomous driving path.

In addition, in the above-described example, the processor 140 determines a case where the position of the agricultural machine 100 obtained through the GNSS sensor 121 is good, and accordingly controls the traveling speed and the driving direction of the agricultural machine 100. According to the embodiment, the traveling speed of the agricultural machine 100 using the data acquired through the GNSS sensor 121 without determining whether the position of the agricultural machine 100 obtained through the GNSS sensor 121 is good. Of course, the driving direction can be controlled.

Meanwhile, referring to FIG. 1B, the communication unit 150 may communicate with the server 200 based on various types of communication methods. For example, the communication unit 150 may communicate with the server 200 through a mobile communication network such as 3G (3 Generation) and Long Term Evolution (LTE).

In this case, the processor 140 may transmit and receive various data with the server 200 through the communication unit 150.

For example, the processor 140 may provide information on the side hazards including the position, speed and direction angle of the farm machinery 100 and information on the driving / operation status of the farm machinery 100 (for example, the driving of the farm machinery 100). Start time information, travel time information, information on an abnormal state, etc.) may be transmitted to the server 200 through the communication unit 150. In addition, the processor 140 may receive control information for controlling the operation of the farm machine 100, information for firmware update, etc. from the server 200 through the communication unit 150.

The server 200 (eg, an Internet of Things (IoT) server) is an IoT-based platform that allows a user or administrator to check information related to the operation of the agricultural machine 100, and includes information provided from the agricultural machine 100. Various information related to the operation of the agricultural machine 100 can be stored.

The server 200 may transmit various types of information related to the operation of the farm machine 100 to the electronic device 300 of the user or the manager.

For example, the server 200 is a mobile communication network such as 3G, LTE, and the like to the information about the hazards, including the position, speed and direction angle of the agricultural machine 100 and the driving / operating situation of the agricultural machine 100 Information and the like may be transmitted to the electronic device 300.

The electronic device 300 may perform a function for controlling the farm machine 100. In this case, the electronic device 300 may be implemented as a dedicated controller for controlling the agricultural machine 100, or may be implemented as a smartphone or a tablet personal computer installed with an application for executing a corresponding function. Can be.

To this end, as shown in FIG. 8, the electronic device 300 may display a user interface 800 for controlling the agricultural machine 100 on a display provided in the electronic device 300.

In this case, the user interface 800 may display information (for example, 810, 820, 830, and 840 of FIG. 8) indicating a current operating state of the farm machine 100 provided from the server 200. A graphical user interface (GUI) (eg, 850 of FIG. 8) that receives a user command to control 100 may be displayed.

Accordingly, when the GUI 850 is selected, the electronic device 300 may transmit control information for controlling the operation of the farm machine 100 to the farm machine 100 through the server 200 according to the selected GUI.

In this case, the processor 140 may control the operation of the farm machine 100 according to the control information received from the server 200.

For example, when the control information for starting the driving of the farm machine 100 is received, the processor 140 may provide a control command to the driving unit 110 to start the farming machine 100, and the driving unit 110. ) Can drive the wheel by controlling the accelerator actuator according to the control command.

As such, the user may monitor various operating conditions of the farm machine 100 and control various operations of the farm machine 100 through the electronic device 300.

Meanwhile, the electronic device 300 may transmit the information on the firmware update to the farm machine 100 through the server 200 according to a user command.

In this case, the processor 140 may update the firmware of the agricultural machine 100 according to the information on the firmware update received from the server 200.

As such, the manager monitors various operating conditions of the farm machine 100 through the electronic device 300 to check whether the farm machine 100 has a technical abnormality, and if there is a problem, the farm machine 100 through the electronic device 300. You can proceed with the update of the firmware.

9 is a flowchart illustrating a method for autonomous running of agricultural machinery according to an embodiment of the present invention.

First, using a sensor, to detect the position and movement of the agricultural machinery (S910).

Then, based on the detected position and movement of the agricultural machine is controlled to run along the autonomous driving path stored in the agricultural machine (S920).

Herein, the sensor may include a Global Navigation Satellite System (GNSS) sensor.

The autonomous driving route may be generated based on data obtained by the GNSS sensor while the agricultural machinery is driving the predetermined route.

Here, the data obtained from the GNSS sensor may include the position, speed and direction angle of the agricultural machinery.

On the other hand, while the agricultural machine is driving on a predetermined path, the geodetic coordinates of the agricultural machine is acquired through the GNSS sensor, the geodetic coordinates obtained are converted to the local coordinates, the direction angle of the agricultural machine is obtained through the GNSS sensor, and the acquired direction angle The autonomous driving route may be generated based on the local coordinates and the determined route type, and the generated autonomous driving route may be stored in the agricultural machine.

On the other hand, step S920 compares a factor for determining the quality of the GNSS sensor with a predetermined reference value, and if the factor satisfies the predetermined reference value, the current of the agricultural machine predicted through the navigation solution before a specific time than the current time By comparing the position and the current position of the agricultural machine acquired through the GNSS sensor, it is possible to determine whether the position of the agricultural machine obtained through the GNSS sensor is in a good state, and control the running of the agricultural machine according to the determined state.

In this case, if it is determined that the position of the agricultural machine obtained through the GNSS sensor is not good, the moving agricultural machine may be stopped.

In addition, when it is determined that the position of the agricultural machine acquired through the GNSS sensor is good, the speed of the agricultural machine may be controlled by comparing the speed of the agricultural machine detected by the GNSS sensor with a preset operating speed.

Specifically, when the detected speed exceeds the preset operating speed, the speed of the moving farm machinery may be reduced, and when the detected speed is less than the preset operating speed, the speed of the moving farm machinery may be increased.

On the other hand, in step S920, if it is determined that the position of the agricultural machine acquired through the GNSS sensor is good, the navigation solution is acquired before the time of the current time, and based on the obtained navigation solution, the specific time based on the current time on the autonomous driving route. Estimate a first position thereafter, based on the obtained navigation solution, estimate a second position after a certain time from the current time, and based on the current position of the agricultural machine, the first vector up to the first position and the current position of the agricultural machine The direction angle difference between the second vectors up to the second position may be calculated based on, and the moving direction of the agricultural machine in motion may be controlled based on the calculated direction angle difference.

On the other hand, in this regard, the specific method for controlling the autonomous running of agricultural machinery has been described above.

Meanwhile, various embodiments of the present disclosure may be implemented in software that includes instructions stored in a machine-readable storage media. A device capable of calling a command and operating in accordance with the called command may include an electronic device according to the disclosed embodiments (eg, the electronic device A.) When the command is executed by a processor, the processor directly In addition, under the control of the processor, other components may be used to perform a function corresponding to the instruction, and the instruction may include code generated or executed by a compiler or an interpreter. May be provided in the form of a non-transitory storage medium, where 'non-transitory' means that the storage medium does not contain a signal. It does not mean that data is stored semi-permanently or temporarily on the storage medium.

According to one embodiment, a method according to various embodiments of the present disclosure may be included in a computer program product. The computer program product may be traded between the seller and the buyer as a product. The computer program product may be distributed online in the form of a device-readable storage medium (eg compact disc read only memory (CD-ROM)) or through an application store (eg Play StoreTM). In the case of online distribution, at least a portion of the computer program product may be stored at least temporarily or temporarily created in a storage medium such as a server of a manufacturer, a server of an application store, or a relay server.

Each component (eg, a module or a program) according to various embodiments may be composed of a singular or plural number of objects, and some of the above-described subcomponents may be omitted, or various other subcomponents may be used. It may be further included in the embodiment. Alternatively or additionally, some components (eg, modules or programs) may be integrated into one entity to perform the same or similar functions performed by each corresponding component prior to integration. According to various embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, repeatedly, or heuristically, or at least some of the operations may be executed in a different order, omitted, or another operation may be added. Can be.

100: agricultural machinery 110: drive unit
120: sensor 130: memory
140: processor

Claims (9)

In farm machinery,
A drive unit;
A sensor for detecting the position and movement of the agricultural machine;
A memory in which an autonomous driving route is stored; And
And a processor configured to control the driving unit to cause the farm machine to travel along the autonomous driving path based on the detected position and movement of the farm machine.
The sensor includes a Global Navigation Satellite System (GNSS) sensor,
The autonomous driving route,
And a predetermined route is generated based on data acquired by the GNSS sensor while the agricultural machine is traveling. The method of claim 1,
The data obtained from the GNSS sensor, the position, speed and direction angle of the farm machinery, agricultural machinery. The method of claim 2,
The processor,
While the agricultural machine is driving the predetermined route, the geodetic coordinates of the agricultural machine are obtained through the GNSS sensor, the geodetic coordinates are converted into local coordinates, and the direction angle of the agricultural machine is obtained through the GNSS sensor. Determine the shape of the path on which the agricultural machine moves based on the obtained direction angle, generate the autonomous driving path based on the local coordinates and the determined path shape, and generate the autonomous driving path into the memory. Stored in, agricultural machinery. The method of claim 2,
The processor,
Compares a factor for determining the quality of the GNSS sensor with a preset reference value, and if the factor satisfies the preset reference value, the current position of the agricultural machine predicted through a navigation solution before a specific time before the current time. And comparing the current position of the agricultural machine obtained through the GNSS sensor to determine whether the position of the agricultural machine obtained through the GNSS sensor is in a good state, and controlling the running of the agricultural machine according to the determined state. The method of claim 4, wherein
The processor,
If it is determined that the position of the agricultural machine obtained through the GNSS sensor is not good, stopping the agricultural machine in motion, agricultural machinery. The method of claim 4, wherein
The processor,
And if it is determined that the position of the agricultural machine obtained through the GNSS sensor is good, the speed of the agricultural machine is controlled by comparing the speed of the agricultural machine detected by the GNSS sensor with a preset operating speed. The method of claim 6,
The processor,
Reducing the speed of the moving agricultural machine when the detected speed exceeds a preset operating speed and increasing the speed of the moving agricultural machine when the detected speed is less than a preset operating speed. The method of claim 4, wherein
The processor,
If it is determined that the position of the agricultural machine obtained through the GNSS sensor is good, the navigation solution is obtained before the time of the current time, and after the specific time on the autonomous driving route based on the current time on the basis of the obtained navigation solution. Estimate a first position of, estimate a second position after a specific time after the current time, based on the obtained navigation solution, the first vector up to the first position based on the current position of the agricultural machine, and the And calculating a direction angle difference between the second vectors up to the second position based on the current position of the farm machine, and controlling the moving direction of the farm machine being moved based on the calculated direction angle difference. In the autonomous driving method of agricultural machinery,
Detecting the position and movement of the agricultural machine using a sensor; And
And controlling the farm machine to travel along an autonomous driving path stored in the farm machine based on the detected position and movement of the farm machine.
The sensor includes a Global Navigation Satellite System (GNSS) sensor,
The autonomous driving route,
And a predetermined route is generated based on data acquired by the GNSS sensor while the agricultural machine is traveling.

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