Method and system for intelligent operation control of agricultural machinery based on beidou RTK

Abstract

The application belongs to the technical field of autonomous operation, and discloses a Beidou RTK-based intelligent agricultural machine operation control method and system; the method comprises the following steps: collecting real-time position information of an agricultural machine and preset path segment information; calculating a deviation value of the agricultural machine from the preset path segment; setting a deviation threshold value and judging whether the deviation value exceeds the deviation threshold value; collecting basic data required for deviation correction of the agricultural machine; according to different types of the preset path segment, corresponding target segment points are set respectively, the target segment points are taken as the regression direction, the maximum angle of deviation correction and the actual turning angle are calculated according to the basic data, and the deviation correction is started; obstacles in front are scanned, when it is detected that the obstacles block the deviation correction path, an obstacle avoidance instruction is sent, the actual obstacle avoidance angle is calculated, and autonomous obstacle avoidance is performed; by introducing the influence of the slope and obstacle factors when the agricultural machine is deviated in a complex mountainous environment, the stability of the autonomous operation of the agricultural machine is improved, and the safety hidden danger caused by the terrain is reduced.

Description

Technical Field

[0001] This invention relates to the field of autonomous operation technology, and more specifically, to a method and system for intelligent operation control of agricultural machinery based on BeiDou RTK. Background Technology

[0002] With the development of intelligent agriculture, autonomous agricultural machinery operation has achieved 24-hour continuous and efficient operation through technologies such as automatic driving and intelligent sensing. This has improved the accuracy and standardization of operations, while reducing reliance on manual labor and labor intensity, lowering long-term costs and safety risks. It can also support large-scale operation through data management and help the development of smart agriculture. It is an important manifestation of the modernization and efficiency of agricultural production methods. However, complex terrain conditions have brought many challenges to autonomous agricultural machinery operation.

[0003] Most current mainstream agricultural machinery path planning algorithms are designed based on flat terrain. This limitation means that when faced with complex terrain such as mountains, where there is a significant deviation between the actual trajectory of the agricultural machinery and the preset path segment, the algorithm cannot successfully return to the preset path segment. The slope of the mountain can cause the agricultural machinery to tip over during adjustments, which not only affects the accuracy and efficiency of the operation, but may also cause safety hazards.

[0004] In view of this, the present invention proposes an intelligent agricultural machinery operation control method and system based on Beidou RTK to solve the above problems. Summary of the Invention

[0005] To overcome the aforementioned shortcomings of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a BeiDou RTK-based intelligent agricultural machinery operation control method, comprising:

[0006] Collect real-time location information and preset path segment information of agricultural machinery;

[0007] The deviation value between the agricultural machinery and the preset path segment is calculated based on the real-time location information of the agricultural machinery and the preset path segment information.

[0008] Set a deviation threshold and determine whether the deviation value exceeds the deviation threshold; if the deviation value is greater than or equal to the deviation threshold, the agricultural machine immediately stops working and outputs a correction command; if the deviation value is less than the deviation threshold, the agricultural machine continues to work.

[0009] Collect the basic data required for correcting the movement of agricultural machinery;

[0010] Based on the different types of preset path segments, corresponding target segment points are set. Taking the target segment points as the return direction, the maximum correction angle and the actual turning angle are calculated based on the basic data, and the correction begins.

[0011] Scan for obstacles ahead. When an obstacle is detected blocking the correction path, an obstacle avoidance command is issued, and the actual obstacle avoidance angle is calculated to perform autonomous obstacle avoidance.

[0012] Furthermore, the specific steps for correcting the deviation are as follows:

[0013] S111: The maximum angle calculated based on the collected basic data is used as the rollover critical angle;

[0014] S112: Based on the determined target line segment Select coordinate point Calculate the target direction angle of the agricultural machinery from the target segment point;

[0015] S113: Calculate and correct the heading angle based on the operating status of the agricultural machinery;

[0016] S114: Employs proportional control to map the corrected steering angle proportionally to the actual steering angle;

[0017] S115: Stop correcting deviation when the agricultural machinery returns to the preset path segment.

[0018] Furthermore, the steps for autonomous obstacle avoidance are as follows:

[0019] S121: In the point cloud cluster of obstacles, find the leftmost point perpendicular to the direction of the agricultural machinery's travel. and the rightmost point Take line segments The midpoint is Calculate line segments The length is used as the width of the obstacle. as well as The distance to the agricultural machinery is considered as the distance from the obstacle to the agricultural machinery. ;

[0020] S122: Set a safe distance , with point With the center as the center, The obstacle area circle is set as the radius. The agricultural machinery takes the minimum angle that allows it to return to the preset path segment without passing through the obstacle area circle as the obstacle avoidance target direction angle. At this time, the return path is tangent to the obstacle area circle. The point of tangency is taken as the target point and the obstacle avoidance target direction angle.

[0021] S123: Calculate the actual obstacle avoidance angle by combining the heading angle, lateral tilt angle and longitudinal tilt angle of the agricultural machinery; the agricultural machinery performs obstacle avoidance according to the calculated obstacle avoidance angle, and if the calculated obstacle avoidance angle is greater than the critical rollover angle, the machine stops and an alarm is issued;

[0022] S124: If the agricultural machinery has returned to the preset path segment when reaching the target point, then obstacle avoidance and correction will stop; if it has not yet returned to the preset path segment, then the obstacle avoidance command will stop and the correction command will be re-executed.

[0023] Furthermore, when agricultural machinery is equipped with implements, after successfully passing through obstacles, a set of obstacle avoidance parameters needs to be established immediately. The set of obstacle avoidance parameters needs to systematically integrate the fixed parameters collected in the early stage, the dynamic parameters monitored in real time, and the control parameters verified at the end.

[0024] After each obstacle avoidance is completed, a new record is generated and added to the collection. For the same fixed combination of parameters, a dense data distribution covering different distances, angles, and slope ranges is formed through continuous accumulation, ensuring that there are corresponding reference records for various scenarios.

[0025] When a new obstacle is encountered, all records that are consistent with the current fixed parameters are directly extracted from the set, sorted according to the similarity of the dynamic parameter values, and the average control parameter of the first p records is selected as the initial obstacle avoidance scheme, where p is an integer greater than 1;

[0026] During execution, the current status parameters are compared with the dynamic parameters of the selected record in real time. If the deviation exceeds the preset threshold, a secondary search is triggered to re-select a more suitable record.

[0027] Furthermore, the method for obtaining real-time location information of agricultural machinery is as follows:

[0028] The high-precision latitude and longitude coordinates of the agricultural machinery's current location are directly output through the BeiDou RTK system, denoted as... ,in At the current latitude, For the current longitude, convert the high-precision latitude and longitude coordinates into UTM plane coordinates using the QGIS open-source tool. .

[0029] Furthermore, the method for obtaining the preset path segment information is as follows:

[0030] The preset path segments are digitally represented, and these preset path segments are pre-stored as continuous latitude and longitude coordinates. Adjacent points form straight line segments on the path, with segment lengths set according to operational accuracy requirements to ensure smoothness; then, the latitude and longitude coordinates are converted to UTM plane coordinates using the QGIS open-source tool. Where n is the total number of path points after discretizing the preset path segment. For the nth latitude and longitude coordinate point, The coordinates of the nth UTM plane.

[0031] Furthermore, the preset path segments are divided into straight sections and turning sections; when the preset path segment is a straight section, the target segment is used... Calculating agricultural machinery Segmentation point with target The distance is calculated and compared with a distance threshold. If the distance is greater than the distance threshold, the coordinate point is selected. Select the target segmentation point; choose when the distance is less than or equal to the distance judgment threshold. Establish new target segmentation points;

[0032] When the preset path segment is a turning section, take the next nearest segment point. and The midpoint between them is the target segmentation point, ensuring a smooth entry into the preset path segment;

[0033] Furthermore, the deviation value is calculated as follows:

[0034] S101: Traverse all segments of the preset path segment , The current position of the agricultural machinery is calculated using the Euclidean distance formula. To both ends of each line segment Find the shortest line segment by the distance and set it as the target line segment. This line segment is the path segment corresponding to the current position.

[0035] S102: For a given path segment ;

[0036] First find the path segments The slope of the line it lies on;

[0037] like equal At this point, the deviation value is ;

[0038] like Not equal to Calculated using the formula for the distance from a point to a line. arrive The vertical distance is the deviation value.

[0039] Furthermore, during the correction process, the system scans and collects reflection point data of the environment ahead, filters out noise points, forms a point cloud cluster, and identifies obstacles using the DBSCAN clustering algorithm.

[0040] The BeiDou RTK-based intelligent agricultural machinery operation control system is used to implement the BeiDou RTK-based intelligent agricultural machinery operation control method, including:

[0041] The first data acquisition module is used to collect real-time location information of agricultural machinery and preset path segment information;

[0042] The first processing module calculates the deviation value between the agricultural machinery and the preset path segment based on the real-time location information of the agricultural machinery and the preset path segment information.

[0043] The first judgment module sets a deviation threshold and determines whether the deviation value exceeds the deviation threshold. If the deviation value is greater than or equal to the deviation threshold, the agricultural machinery immediately stops working, outputs a correction command, and begins correction.

[0044] The second data acquisition module collects the basic data required for agricultural machinery correction.

[0045] The correction module sets different target segment points based on whether the preset path segment is a straight section or a turning section. Using the target segment point as the return direction, it calculates the maximum correction angle and the actual steering angle based on the basic data and the tilt angle of the agricultural machinery, and then starts the correction process.

[0046] The autonomous obstacle avoidance module scans for obstacles ahead. When an obstacle is found to be blocking the correction path, it issues an obstacle avoidance command and calculates the actual obstacle avoidance angle to perform autonomous obstacle avoidance.

[0047] The technical effects and advantages of this invention are as follows:

[0048] First, this invention leverages the high-precision positioning capabilities of BeiDou RTK technology, combined with slope perception and analysis, to overcome the design limitations of current mainstream algorithms based on flat terrain, specifically addressing operational challenges in mountainous areas. When the actual trajectory of agricultural machinery deviates significantly from the preset path in complex terrain such as mountains, it ensures the machinery smoothly adjusts its trajectory back to the preset path, reducing the risk of rollover due to steep slopes and guaranteeing operational safety.

[0049] Secondly, by combining lidar technology, when encountering obstacles during correction, the obstacle avoidance angle can be calculated based on the actual situation to return to the preset route, and the risk of rollover caused by mountain slopes can be minimized, thus improving the availability of autonomous agricultural machinery in mountainous areas.

[0050] In summary, this invention, through the deep integration of BeiDou RTK technology and slope perception, breaks through the application bottleneck of traditional algorithms in mountainous operations, providing support for the smooth trajectory adjustment of agricultural machinery in complex terrain and reducing the risk of rollover. The integration of lidar technology allows agricultural machinery to flexibly avoid obstacles and return to the preset route when facing obstacles, while always minimizing the safety hazards caused by slope, significantly enhancing the practical value of autonomous agricultural machinery in mountainous environments. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the agricultural machinery autonomous correction method in Embodiment 1 of the present invention;

[0052] Figure 2 This is a schematic diagram of the agricultural machinery autonomous obstacle avoidance method in Embodiment 1 of the present invention;

[0053] Figure 3This is a schematic diagram of the intelligent agricultural machinery operation control system based on Beidou RTK in Embodiment 3 of the present invention. Detailed Implementation

[0054] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] Example 1

[0056] This embodiment provides a method for intelligent agricultural machinery operation control based on BeiDou RTK, including:

[0057] Collect real-time location information and preset path segment information of agricultural machinery.

[0058] The method for obtaining the real-time location information of the agricultural machinery is as follows: The high-precision latitude and longitude coordinates of the current location of the agricultural machinery are directly output through the BeiDou RTK system, denoted as... ,in At the current latitude, For the current longitude, convert the high-precision latitude and longitude coordinates into UTM plane coordinates using the QGIS open-source tool. .

[0059] The method for obtaining the preset path segment information is as follows: the preset path segment is digitally represented, and the preset path segment is pre-stored as continuous latitude and longitude coordinate points. Adjacent points form straight line segments on the path, with segment lengths set according to operational accuracy requirements to ensure smoothness; then, the latitude and longitude coordinates are converted to UTM plane coordinates using the QGIS open-source tool. Where n is the total number of path points after discretizing the preset path segment. For the nth latitude and longitude coordinate point, The coordinates of the nth UTM plane.

[0060] The deviation of the agricultural machinery from the preset path segment is calculated based on the real-time location information of the agricultural machinery and the preset path segment information.

[0061] The method for calculating the deviation value is as follows:

[0062] S101: Traverse all segments of the preset path segment Calculate the current position of the agricultural machinery To both ends of each line segment Find the shortest line segment from the given distance and set it as the target line segment. This target line segment is the path segment corresponding to the current position. Calculate the distance using the Euclidean distance method. :

[0063] ;

[0064] in, ,Right now For line segments endpoints or endpoint .

[0065] S102: For a given path segment ,calculate The perpendicular distance to the path segment is the deviation of the agricultural machinery from the preset path segment. The calculation method is as follows:

[0066] First find the path segments The slope of the line :

[0067] ;

[0068] like =0, at this time the deviation value is ;like The result is not 0; calculate according to the formula for the distance from a point to a line. arrive The vertical distance, i.e., the deviation value :

[0069] ;

[0070] Set deviation threshold Determine the deviation value Does it exceed the deviation threshold? If the deviation value is greater than or equal to the deviation threshold, the agricultural machine will immediately stop working and output a correction command; if the deviation value is less than the deviation threshold, the agricultural machine will continue to operate.

[0071] The deviation threshold Configure according to the required accuracy of the task.

[0072] Collect the basic data required for correcting the movement of agricultural machinery.

[0073] The basic data includes the wheelbase, center of gravity height, heading angle, longitudinal tilt angle, and lateral tilt angle of the agricultural machinery during operation.

[0074] The wheelbase and center of gravity height of the agricultural machinery were obtained by consulting the design drawings; the flight angle was obtained directly by the IMU inertial measurement unit; and the longitudinal tilt angle and lateral tilt angle were obtained directly by the dual-axis tilt sensor.

[0075] The maximum angle during correction was calculated based on the basic data. and actual steering angle And began to correct the course;

[0076] See Figure 1 As shown, the specific correction steps are as follows:

[0077] S111: The maximum angle calculated based on the collected basic data during correction is used as the rollover critical angle. The calculation formula is:

[0078] ;

[0079] in, The critical angle for rollover. For the wheel track of agricultural machinery, For the height of the center of gravity, The lateral tilt angle, It is the arctangent function. The preset safety factor is set by those skilled in the art based on their own experience.

[0080] The maximum correction angle is the maximum steering angle of the agricultural machinery allowed when performing correction.

[0081] S112: Based on the determined path segment Select coordinate points Let the target segmentation point be denoted as . ; Calculate the target orientation angle from the agricultural machinery to the target segment point:

[0082] ;

[0083] in, The target direction angle, and Based on the current UTM plane coordinates of the agricultural machinery Substitute, and Based on the target segmentation points Substitute, It is a two-parameter arctangent function.

[0084] The target segmentation point There are different settings when the preset path segment is a straight section and when it is a turning section: when the preset path segment is a straight section, it is set according to the path segment. Select coordinate points Calculate the agricultural machinery based on the target segmentation point. Segmentation point with target The distance is calculated and compared with a distance threshold. If the distance is less than or equal to the threshold, then a decision needs to be made. Set the new target segment point; when the preset path segment is a turning section, take the next nearest segment point. and The midpoint between them is the target segment point, ensuring a smooth entry into the preset path segment.

[0085] Among them, agricultural machinery Distance from the target segment point The calculation formula is:

[0086] ;

[0087] The distance judgment threshold is set according to the actual operation situation, and is usually set to 2 meters.

[0088] S113: Due to the slope, the target orientation angle will deviate from that on flat ground. Calculate the corrected orientation angle:

[0089] ;

[0090] in, To correct the direction angle, The target direction angle, This represents the current heading angle of the agricultural machinery. The longitudinal tilt angle, The lateral tilt angle, The downward tilt of the agricultural machinery to the right is considered positive, and the downward tilt to the left is considered negative.

[0091] S114: To avoid rollover caused by sharp turns, proportional control is used to correct the steering angle. Mapped proportionally to the actual steering angle The specific formula is as follows:

[0092] ;

[0093] in, This is the actual steering angle. The basic proportionality coefficient (with a value of 2). Let v be the longitudinal tilt angle, and v be the velocity during correction. The correction speed threshold (the maximum correction speed set, taken as 1.5m / s). To correct the direction angle.

[0094] It should be noted that the actual steering angle must be less than or equal to the rollover critical angle. If the calculated actual steering angle is greater than the rollover critical angle, then the rollover critical angle shall be used as the steering angle.

[0095] S115: Stop correcting the course when the agricultural machinery returns to the preset path segment.

[0096] During the correction process, the lidar installed at the front of the agricultural machinery scans and collects reflection point data of the environment in front, and identifies obstacles through the DBSCAN clustering algorithm; if an obstacle is found to be blocking the correction path, an obstacle avoidance command is issued, and the actual obstacle avoidance angle is calculated to perform autonomous obstacle avoidance.

[0097] It should be noted that the clustering steps of the DBSCAN clustering algorithm are as follows:

[0098] First, unify the scanned obstacle point cloud to the UTM coordinate system. Then, by counting the number of neighboring points of each point (e.g., fewer than 3 points within a radius of 0.5m), filter out noise points caused by LiDAR scanning errors and set the neighborhood radius. The maximum distance between two points within the same obstacle is defined by the minimum size of the actual obstacle. The minimum number of points (MinPts) is defined as the minimum number of points required to form an obstacle cluster, and is related to the point cloud density. An unlabeled point p is randomly selected from the point cloud, and its... The number of points in the neighborhood is determined. If the number of neighborhood points is greater than or equal to MinPts: p is marked as a "core point" and clustering is initiated; if the number of neighborhood points is less than MinPts: p is marked as a "noise point" (not processed for now); starting from the core point p, clustering is performed... All points within the neighborhood are added to the current cluster, and these points are recursively checked to see if they are core points: if a point q is a core point, then q's... All unmarked points in the neighborhood are added to the cluster; this process is repeated until all density-reachable points are included in the cluster, forming an obstacle cluster; the next unmarked point is selected, and this process continues until all points are marked.

[0099] See Figure 2 As shown, the steps for autonomous obstacle avoidance are as follows:

[0100] S121: In the point cloud cluster of obstacles, find the leftmost point perpendicular to the direction of the agricultural machinery's travel. and the rightmost point , and For the left and right boundary points of the point cloud in the direction perpendicular to the direction of travel, take line segments. The midpoint is Calculate line segments The length is used as the width of the obstacle. as well as The distance to the agricultural machinery is considered as the distance from the obstacle to the agricultural machinery. .

[0101] The width of the obstacle The calculation formula is:

[0102] ;

[0103] The distance from the obstacle to the agricultural machinery The calculation formula is:

[0104] ;

[0105] S122: Set a safe distance , with point With the center as the center, The obstacle area circle is defined by a radius. The agricultural machinery takes the minimum angle required to return to the preset path segment without passing through the obstacle area circle as the obstacle avoidance target direction angle. At this point, the return path is tangent to the obstacle area circle, and the point of tangency is taken as the target point. The obstacle avoidance target direction angle is:

[0106] ;

[0107] in, The target direction angle for obstacle avoidance indicates the direction from the connecting line. Rotate to the deflection angle in the tangential direction of obstacle avoidance. Set a safe distance (the safe distance between agricultural machinery and obstacles should be set according to the actual situation). The distance between the obstacle and the agricultural machinery. The equivalent width of the obstacle. For the arcsine function, when When the machine is deemed to have entered a dangerous area, it stops and issues an alarm.

[0108] S123: Due to the slope, the target heading angle will deviate from that on flat ground. The actual obstacle avoidance angle should be calculated by combining the agricultural machinery's heading angle and tilt angle. :

[0109] First, calculate the connections. Direction angle : ;

[0110] but ;

[0111] in, From the actual obstacle avoidance perspective, To avoid the target's direction angle, This is the current heading angle of the agricultural machinery. The longitudinal tilt angle, This is the lateral tilt angle.

[0112] It should be noted that the direction of detouring is determined by whether the obstacle is located to the left or right of the direction of travel. "+" indicates detouring to the left and "-" indicates detouring to the right.

[0113] The agricultural machinery will perform obstacle avoidance according to the calculated obstacle avoidance angle. If the calculated obstacle avoidance angle is greater than the critical angle for tipping over, the machine will stop and issue an alarm.

[0114] S124: If the agricultural machinery has returned to the preset path segment when reaching the target point, then obstacle avoidance and correction will stop; if it has not yet returned to the preset path segment, then the obstacle avoidance command will stop and the correction command will be re-executed.

[0115] Example 2

[0116] Based on Example 1, the tractor is used to avoid obstacles while equipped with farm implements.

[0117] This embodiment provides a method for intelligent agricultural machinery operation control based on BeiDou RTK, and also includes:

[0118] Collect data on agricultural machinery and implements, including the wheelbase D of the agricultural machinery. z Width D of agricultural implements n The distance L from the rear axle of the agricultural machinery to the end of the implement and the height h1 of the implement's center of gravity.

[0119] A millimeter-wave radar is installed on the middle of the side of the agricultural implement, and a coordinate system is established with the center of the rear wheel axle of the agricultural machine as the origin (X-axis forward, Y-axis to the right, Z-axis upward).

[0120] When encountering obstacles during the correction process, the lidar and millimeter-wave radar work together to scan the obstacles. The distance d between the obstacle and the millimeter-wave radar, as well as the angle θ between the obstacle and the X-axis of the coordinate system, are calculated through point cloud data processing. x The specific calculation method is as follows:

[0121] S201: With the center of the rear wheel axle of the agricultural machinery as the origin of the unified coordinate system, the installation position of the millimeter-wave radar in the unified coordinate system is: The point cloud coordinates in the millimeter-wave radar's own coordinate system Transform to a unified coordinate system: ,in, Let (x, y, z) be the coordinates of the millimeter-wave radar, and (x, y, z) be the coordinates after the point cloud coordinates have been transformed to a unified coordinate system.

[0122] S202: The DBSCAN clustering algorithm is used to identify obstacles. For each obstacle cluster, the geometric center is calculated as a feature point, representing the spatial location of the obstacle.

[0123] ;

[0124] in, This represents the number of points in the point cluster. For the first point in the cluster The coordinates of the points;

[0125] S203: Distance d is calculated using the Euclidean distance method. ;

[0126] Angle with the X-axis: , The angle range is from -180° to 180°, with positive values ​​indicated on the right side of the X-axis.

[0127] The agricultural machinery first calculates the initial obstacle avoidance angle according to the algorithm in Example 1 and initiates the obstacle avoidance operation. During the obstacle avoidance process, the millimeter-wave radar data on both sides of the implement is monitored in real time. If the distance between the implement and the obstacle is detected to be less than the safety threshold, the turning action is stopped immediately, and the agricultural machinery is controlled to reverse along the original driving route to the initial position before obstacle avoidance to eliminate the collision risk.

[0128] If the initial obstacle avoidance angle fails, a gradual angle adjustment strategy is adopted: the original obstacle avoidance angle is increased by 3° as a new attempt angle, and the obstacle avoidance is re-executed. If it fails again, the angle is increased further until it is successfully passed. Throughout the adjustment process, the current attempt angle is compared with the rollover critical angle in real time. When the angle reaches the rollover critical angle, obstacle avoidance is stopped and an alarm is issued.

[0129] After successfully navigating the obstacle, a parameter set for obstacle avoidance success must be established immediately. This parameter set needs to integrate previously collected fixed parameters, real-time monitored dynamic parameters, and final verified control parameters. The fixed parameters include the agricultural machinery wheelbase D. z Agricultural implement width D n The distance L from the rear axle of the agricultural machinery to the end of the implement, and the height h1 of the implement's center of gravity; dynamic parameters include the distance d between the obstacle and the millimeter-wave radar, and the angle θ between the obstacle and the X-axis of the coordinate system. x The current lateral slope β and longitudinal slope α; control parameters include the turning angle θ for successful obstacle avoidance. n Turning speed v n .

[0130] After each obstacle avoidance operation, a new record is generated and added to the collection. For the same fixed combination of parameters, a dense data distribution covering different distances, angles, and slope ranges is formed through continuous accumulation, ensuring that there are corresponding reference records for various scenarios.

[0131] When a new obstacle is encountered, all records matching the current fixed parameters are directly extracted from the set, sorted by the similarity of the dynamic parameter values, and the average control parameter value of the top 5 records is selected as the initial obstacle avoidance scheme. During execution, the current state parameters are compared with the dynamic parameters of the selected records in real time. If the deviation exceeds a preset threshold, a secondary search is triggered to reselect more suitable records.

[0132] Example 3

[0133] See Figure 3 As shown, this embodiment provides an intelligent agricultural machinery operation control system based on BeiDou RTK, and the implementation of the intelligent agricultural machinery operation control method based on BeiDou RTK includes:

[0134] The first data acquisition module is used to collect real-time location information of agricultural machinery and preset path segment information;

[0135] The first processing module calculates the deviation value between the agricultural machinery and the preset path segment based on the real-time location information of the agricultural machinery and the preset path segment information.

[0136] The first judgment module sets a deviation threshold and determines whether the deviation value exceeds the deviation threshold. If the deviation value is greater than or equal to the deviation threshold, the agricultural machinery immediately stops working, outputs a correction command, and begins correction.

[0137] The second data acquisition module collects the basic data required for agricultural machinery correction.

[0138] The correction module sets different target segment points based on whether the preset path segment is a straight section or a turning section. Using the target segment point as the return direction, it calculates the maximum correction angle and the actual steering angle based on the basic data and the tilt angle of the agricultural machinery, and then starts the correction process.

[0139] The autonomous obstacle avoidance module scans for obstacles ahead. When an obstacle is found to be blocking the correction path, it issues an obstacle avoidance command and calculates the actual obstacle avoidance angle to perform autonomous obstacle avoidance.

[0140] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0141] In conclusion, the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligent agricultural machinery operation control based on BeiDou RTK, characterized in that, include: Collect real-time location information and preset path segment information of agricultural machinery; The deviation value between the agricultural machinery and the preset path segment is calculated based on the real-time location information of the agricultural machinery and the preset path segment information. Set a deviation threshold and determine whether the deviation value exceeds the deviation threshold; If the deviation value is greater than or equal to the deviation threshold, the agricultural machinery will immediately stop working and output a correction command. If the deviation value is less than the deviation threshold, the agricultural machinery continues to operate; Collect the basic data required for correcting the movement of agricultural machinery; Based on the different types of preset path segments, corresponding target segment points are set. Taking the target segment points as the return direction, the maximum correction angle and the actual turning angle are calculated based on the basic data, and the correction begins. Scan for obstacles ahead. When an obstacle is detected blocking the correction path, an obstacle avoidance command is issued, and the actual obstacle avoidance angle is calculated to perform autonomous obstacle avoidance.

2. The intelligent agricultural machinery operation control method based on Beidou RTK according to claim 1, characterized in that, The specific steps for the correction are as follows: S111: The maximum angle calculated based on the collected basic data during correction is used as the rollover critical angle; S112: Based on the determined path segment Select coordinate points Calculate the target direction angle from the agricultural machinery to the target segment point, using the target segment point as the target segment point as the target point; S113: Calculate and correct the heading angle based on the operating status of the agricultural machinery; S114: Employs proportional control to map the corrected steering angle proportionally to the actual steering angle; S115: Stop correcting the course when the agricultural machinery returns to the preset path segment.

3. The intelligent agricultural machinery operation control method based on Beidou RTK according to claim 1, characterized in that, The steps for autonomous obstacle avoidance are as follows: S121: In the point cloud cluster of obstacles, find the leftmost point perpendicular to the direction of the agricultural machinery's travel. and the rightmost point Take line segments The midpoint is Calculate line segments The length is used as the width of the obstacle. as well as The distance to the agricultural machinery is considered as the distance from the obstacle to the agricultural machinery. ; S122: Set a safe distance , with point With the center as the center, The obstacle area circle is set as the radius. The agricultural machinery takes the minimum angle that allows it to return to the preset path segment without passing through the obstacle area circle as the obstacle avoidance target direction angle. At this time, the return path is tangent to the obstacle area circle. The point of tangency is taken as the target point and the obstacle avoidance target direction angle. S123: Calculate the actual obstacle avoidance angle by combining the heading angle, lateral tilt angle and longitudinal tilt angle of the agricultural machinery; the agricultural machinery performs obstacle avoidance according to the calculated obstacle avoidance angle, and if the calculated obstacle avoidance angle is greater than the critical rollover angle, the machine stops and an alarm is issued; S124: If the agricultural machinery has returned to the preset path segment when reaching the target point, then obstacle avoidance and correction will stop; if it has not yet returned to the preset path segment, then the obstacle avoidance command will stop and the correction command will be re-executed.

4. The intelligent agricultural machinery operation control method based on Beidou RTK according to claim 1, characterized in that, When agricultural machinery is equipped with implements, after successfully passing through obstacles, a set of obstacle avoidance parameters must be established immediately. The set of obstacle avoidance parameters must integrate the fixed parameters collected in the early stage, the dynamic parameters monitored in real time, and the control parameters verified in the final stage. After each obstacle avoidance is completed, a new record is generated and added to the collection. For the same fixed combination of parameters, a dense data distribution covering different distances, angles, and slope ranges is formed through continuous accumulation, ensuring that there are corresponding reference records for various scenarios. When a new obstacle is encountered, all records that are consistent with the current fixed parameters are directly extracted from the set, sorted according to the similarity of the dynamic parameter values, and the average control parameter of the first p records is selected as the initial obstacle avoidance scheme, where p is an integer greater than 1; During execution, the current status parameters are compared with the dynamic parameters of the selected record in real time. If the deviation exceeds the preset threshold, a secondary search is triggered to re-select a more suitable record.

5. The intelligent agricultural machinery operation control method based on Beidou RTK according to claim 1, characterized in that, The method for obtaining the real-time location information of the agricultural machinery is as follows: The high-precision latitude and longitude coordinates of the agricultural machinery's current location are directly output through the BeiDou RTK system, denoted as... ,in At the current latitude, For the current longitude, convert the high-precision latitude and longitude coordinates into UTM plane coordinates using the QGIS open-source tool. .

6. The intelligent agricultural machinery operation control method based on Beidou RTK according to claim 1, characterized in that, The method for obtaining the preset path segment information is as follows: The preset path segments are digitally represented, and these preset path segments are pre-stored as continuous latitude and longitude coordinates. Adjacent points form straight line segments of the path; then, the latitude and longitude coordinates are converted to UTM plane coordinates using the QGIS open-source tool. Where n is the total number of path points after discretizing the preset path segment. For the nth latitude and longitude coordinate point, The coordinates of the nth UTM plane.

7. The intelligent agricultural machinery operation control method based on Beidou RTK according to claim 1, characterized in that, The preset path segments are divided into straight sections and turning sections; when the preset path segment is a straight section, it is based on the path segment... Calculating agricultural machinery Segmentation point with target The distance is calculated and compared with a distance threshold. If the distance is greater than the distance threshold, the coordinate point is selected. Select the target segmentation point; choose when the distance is less than or equal to the distance judgment threshold. Establish new target segmentation points; When the preset path segment is a turning section, take the next nearest segment point. and The midpoint between them is the target segment point, ensuring a smooth entry into the preset path segment.

8. The intelligent agricultural machinery operation control method based on Beidou RTK according to claim 1, characterized in that, The method for calculating the deviation value is as follows: S101: Traverse all segments of the preset path segment , The current position of the agricultural machinery is calculated using the Euclidean distance formula. To both ends of each line segment Find the shortest line segment by distance and set it as the target line segment. This target line segment is the path line segment corresponding to the current position. S102: For a given path segment ; First find the path segments The slope of the line it lies on; like equal At this point, the deviation value is ; like Not equal to Calculated using the formula for the distance from a point to a line. arrive The vertical distance is the deviation value.

9. The intelligent agricultural machinery operation control method based on Beidou RTK according to claim 1, characterized in that, During the correction process, the system scans and collects reflection point data of the environment ahead, filters out noise points, forms a point cloud cluster, and identifies obstacles using the DBSCAN clustering algorithm.

10. A BeiDou RTK-based intelligent agricultural machinery operation control system, used to implement the BeiDou RTK-based intelligent agricultural machinery operation control method according to any one of claims 1-10, characterized in that, include: The first data acquisition module is used to collect real-time location information of agricultural machinery and preset path segment information; The first processing module calculates the deviation value between the agricultural machinery and the preset path segment based on the real-time location information of the agricultural machinery and the preset path segment information. The first judgment module sets a deviation threshold and determines whether the deviation value exceeds the deviation threshold. If the deviation value is greater than or equal to the deviation threshold, the agricultural machinery immediately stops working, outputs a correction command, and begins correction. The second data acquisition module collects the basic data required for agricultural machinery correction. The correction module sets different target segment points based on whether the preset path segment is a straight section or a turning section. Using the target segment point as the return direction, it calculates the maximum correction angle and the actual steering angle based on the basic data and the tilt angle of the agricultural machinery, and then starts the correction process. The autonomous obstacle avoidance module scans for obstacles ahead. When an obstacle is found to be blocking the correction path, it issues an obstacle avoidance command and calculates the actual obstacle avoidance angle to perform autonomous obstacle avoidance.

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