An unmanned aerial vehicle route preview confirmation method and device for an agricultural field inspection task

Abstract

The application discloses a kind of unmanned aerial vehicle route preview confirmation method and device for agricultural field patrol task, belong to unmanned aerial vehicle agricultural field patrol route planning and management technical field.The method includes: obtaining farmland area boundary data, constructs the continuously displayed farmland area constraint layer;Obtain the position data of take-off point, construct the continuously displayed take-off point constraint layer;Receive field patrol task parameter and carry out joint validity judgment;Through the preview route point set of post-generation, build the preview layer display independent of constraint layer;When task parameter changes, keep farmland area constraint layer and take-off point constraint layer continue to display, only clear and rebuild preview layer;After receiving confirmation instruction, the current preview route point set, field patrol task parameter and farmland main body mark are associated and saved as formal route data.The application is layered by constraint layer and preview layer Organize, maintain stable space reference in multiple route trial calculation process, improve preview comparison efficiency and formal route confirmation reliability.

Description

Technical Field

[0001] This invention belongs to the field of flight path planning and management technology for unmanned aerial vehicle (UAV) agricultural field patrol, specifically relating to a method and device for previewing and confirming UAV flight paths for agricultural field patrol tasks. Background Technology

[0002] With the rapid development of precision agriculture and low-altitude operations, unmanned aerial vehicles (UAVs) have been widely deployed in tasks such as farmland inspection, crop growth monitoring, pest and disease identification, disaster assessment, and land boundary verification. These agricultural inspection tasks typically require generating operational flight paths covering the target area based on parameters such as farmland boundaries, takeoff point location, flight altitude, heading angle, lateral overlap rate, flight path spacing, edge distance, and flight speed. These flight paths are then presented to operators on a map or 3D geographic scene for verification and confirmation.

[0003] Existing technologies offer various solutions related to flight path planning. Some solutions focus on automatically solving for the optimal flight path using optimization algorithms based on conditions such as mission area boundaries, obstacle distribution, flight stability, flight duration, or energy consumption constraints. Other solutions focus on safety checks of the generated flight paths, such as checking whether the path crosses no-fly zones, meets elevation constraints, has reasonable turning angles, or exceeds flight duration limits. Additionally, some solutions address issues such as waypoint generation, flight path smoothing, and path optimization for 3D model reconstruction or complex inspection objects. These technical solutions address specific problems in automatic flight path planning, safety checks, or path optimization to varying degrees, but their primary focus is on the correctness and optimality of the algorithm's solution.

[0004] In agricultural field patrol operations, operators often need to repeatedly preview, compare, and adjust flight path results for the same farmland area under different parameter configurations until a satisfactory operational plan is confirmed. However, existing systems have several shortcomings in handling such scenarios involving multiple trial calculations. First, when task parameters change, the system typically needs to refresh all elements in the map scene, including farmland areas, takeoff points, and flight path results. This global refresh method can easily cause operators to lose a stable spatial reference benchmark, hindering intuitive comparison of different parameter schemes. Second, there is a lack of clear data boundaries between the trial calculation results in the preview stage and the final confirmed official flight path. Operators may mistakenly save temporary preview results as the official task plan without fully verifying them, increasing the risk of misoperation. Furthermore, when editing and adjusting based on historically confirmed flight paths are required, existing systems often lack a unified data recovery mechanism, making it difficult to simultaneously revert area boundaries, takeoff points, and historical flight path results to their original state, thus reducing the efficiency of task adjustment. In summary, existing technologies have not yet provided a complete and systematic solution for the closed-loop process of "preview-comparison-confirmation" in agricultural field patrol operations. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method and apparatus for previewing and confirming UAV flight paths for agricultural field patrol tasks. By constructing the farmland area and takeoff point as a continuously displayed constraint layer and the flight path results as a reconstructable preview layer, only the preview layer is reconstructed when parameters change, thereby maintaining a stable spatial reference, improving the efficiency of multiple preview comparisons and the reliability of formal flight path confirmation.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for previewing and confirming the flight path of a drone for agricultural field inspection tasks, the method comprising:

[0008] Step 1: Obtain the location data of the regional boundary corresponding to the main body of the target farmland, and construct the farmland region constraint layer in the three-dimensional geographic scene;

[0009] Step 2: Receive the user-inputted or selected takeoff point spatial location data, and construct a takeoff point constraint layer in the three-dimensional geographic scene;

[0010] Step 3: Receive the field patrol task parameters and perform a joint validity judgment on the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters; when the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters all meet the preset conditions, generate a preview route point set and construct a preview layer display in the 3D geographic scene that is independent of the farmland area constraint layer and takeoff point constraint layer; when the field patrol task parameters change, keep the farmland area constraint layer and takeoff point constraint layer displayed, only clear and rebuild the preview layer;

[0011] Step 4: Upon receiving the confirmation instruction, associate and save the current preview route point set, the current field patrol task parameters, and the farmland main identifier corresponding to the target farmland as formal route data.

[0012] Furthermore, in step 2, the takeoff point spatial location data is received by the user through click operations, drag operations, coordinate input operations, or historical takeoff point selection operations in the three-dimensional geographic scene. The takeoff point constraint layer remains displayed during multiple preview layer reconstruction processes before receiving deletion instructions, reselection instructions, or editing instructions.

[0013] Furthermore, in step 3, the joint validity judgment includes: determining whether the area boundary location data exists and can be parsed; determining whether the takeoff point spatial location data exists and the coordinates are valid; determining whether the flight altitude, speed, edge distance, and overlap rate in the field patrol task parameters are within the preset range; determining whether the route length estimated based on the farmland area and route spacing exceeds the UAV's endurance threshold; and determining whether the generated route has crossed the boundary, broken, or cannot be connected.

[0014] Furthermore, in step 3, the preview layer includes waypoint entities, flight segment lines, heading arrows, sequence number markers, flight route statistics, and parameter version identifiers; the official flight route data also includes generation time, user identifier, and version number, making multiple confirmation results under the same farmland entity traceable.

[0015] Furthermore, in step 3, the generation of the preview waypoint set includes: shrinking the polygon corresponding to the boundary position data of the area according to the margin parameter in the field patrol task parameters to obtain the correction operation area; calculating the line spacing according to the flight altitude, load field of view angle and lateral overlap rate in the field patrol task parameters; generating multiple parallel scan lines in the correction operation area according to the heading angle in the field patrol task parameters; calculating the intersection of each scan line with the boundary of the correction operation area and extracting the effective flight segments; sorting and connecting the effective flight segments according to the takeoff point spatial position data, the distance of the flight segment endpoints and the turning cost; discretely generating multiple preview waypoints along the connected lines; and attaching latitude and longitude, altitude, heading, speed, photo-taking action, sequence number and task parameter version identifier to each preview waypoint.

[0016] Furthermore, after generating the preview route point set, the estimated flight time is estimated based on the total length of the preview route, average flight speed, distance from the takeoff point to the first waypoint and the distance from the last waypoint back to the takeoff point, and the number of photo-taking actions. When the estimated flight time is greater than the available flight time of the UAV or exceeds the threshold after the safety factor correction, it is determined that the current preview scheme has a flight endurance risk.

[0017] Furthermore, in step 4, after receiving the confirmation instruction, before associating and saving the current preview route point set as the official route data, it is verified whether the current preview layer is the result of being regenerated after the most recent parameter change. If the current preview layer is not the result of being regenerated after the most recent parameter change, then the hardening is prohibited or the user is prompted to update the preview first.

[0018] On the other hand, the present invention provides a drone flight path preview and confirmation device for agricultural field inspection tasks, comprising:

[0019] The regional constraint layer construction module is used to obtain the regional boundary location data corresponding to the main body of the target farmland and construct the farmland regional constraint layer in the three-dimensional geographic scene;

[0020] The takeoff point constraint layer construction module is used to receive takeoff point spatial location data input or selected by the user and construct a takeoff point constraint layer in the three-dimensional geographic scene.

[0021] The preview layer construction module is used to receive field patrol task parameters and perform a joint validity judgment on the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters; when the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters all meet preset conditions, a preview route point set is generated and a preview layer display is constructed in the three-dimensional geographic scene, independent of the farmland area constraint layer and takeoff point constraint layer; when the field patrol task parameters change, the farmland area constraint layer and takeoff point constraint layer continue to be displayed, only the preview layer is cleared and rebuilt.

[0022] The save module is used to associate and save the current preview route point set, the current field patrol task parameters, and the farmland main identifier corresponding to the target farmland as formal route data after receiving a confirmation instruction.

[0023] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned method for previewing and confirming drone flight routes for agricultural field patrol tasks.

[0024] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned method for previewing and confirming drone flight paths for agricultural field patrol tasks.

[0025] The beneficial effects of this invention are as follows:

[0026] By constructing farmland areas and takeoff points as constraint layers that are continuously displayed in a 3D geographic scene, and constructing flight path results as independent preview layers, the constraint layers remain unchanged and only the preview layers are rebuilt when parameters change. This allows operators to always have a stable spatial reference benchmark during multiple trial calculations, facilitating intuitive comparisons of different parameter schemes.

[0027] The preview layer and the official route data are completely separated at the storage level. The preview results are only solidified into the official route data after the user actively confirms them, which avoids the risk of temporary trial calculation results being mistakenly saved as the official task plan.

[0028] The takeoff point is continuously displayed as an independent constraint layer, eliminating the need to reselect the point or repeatedly confirm it every time parameters are adjusted, thus reducing repetitive operations and improving task configuration efficiency.

[0029] Before confirming the solidification, the validity of the preview layer is verified to ensure that the current preview corresponds to the latest parameters, prevent expired preview results from being saved, and ensure data consistency and reliability.

[0030] In edit mode, the system supports the unified restoration of farmland area constraint layers, takeoff point constraint layers, and historical preview layers. After the user modifies any element, the system automatically generates a new preview layer, reducing the complexity of adjusting historical tasks.

[0031] A version number is assigned to the official flight route to make multiple confirmation results under the same farmland entity traceable, which facilitates task review and historical change management. Attached Figure Description

[0032] Figure 1 This is a flowchart of a method for previewing and confirming drone flight paths for agricultural field patrol tasks according to the present invention.

[0033] Figure 2 This is a schematic diagram illustrating the construction process of the farmland area constraint layer and the takeoff point constraint layer of the present invention;

[0034] Figure 3 This is a schematic diagram illustrating the process of rebuilding the preview layer while maintaining the display of the constraint layer when the parameters of the field patrol task change, according to the present invention.

[0035] Figure 4 This is a schematic diagram of the interface for jointly displaying the farmland area constraint layer, takeoff point constraint layer, and preview layer in a three-dimensional geographic scene according to the present invention.

[0036] Figure 5 This is a schematic diagram illustrating the process of restoring historical official routes and then reconfirming and solidifying new official routes in edit mode according to the present invention. Detailed Implementation

[0037] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0038] like Figure 1 As shown, this invention proposes a method for previewing and confirming UAV flight paths for agricultural field patrol tasks, the method comprising:

[0039] Step 1: Obtain the location data of the regional boundary corresponding to the main body of the target farmland, and construct the farmland region constraint layer in the three-dimensional geographic scene;

[0040] Step 2: Receive the user-inputted or selected takeoff point spatial location data, and construct a takeoff point constraint layer in the three-dimensional geographic scene;

[0041] Step 3: Receive the field patrol task parameters and perform a joint validity judgment on the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters; when the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters all meet the preset conditions, generate a preview route point set and construct an independent preview layer display in the 3D geographic scene, independent of the farmland area constraint layer and takeoff point constraint layer; when the field patrol task parameters change, keep the farmland area constraint layer and takeoff point constraint layer displayed, only clear and rebuild the preview layer;

[0042] Step 4: Upon receiving the confirmation instruction, associate and save the current preview route point set, the current field patrol task parameters, and the farmland main identifier corresponding to the target farmland as formal route data.

[0043] Furthermore, in step 1:

[0044] refer to Figure 2 The system reads the regional boundary location data based on the user-selected site, farmland entity, or plot number. The regional boundary location data can be a latitude and longitude array, GeoJSON, a polygon vertex set, or a spatial field from a database. The system performs format validation, coordinate standardization, closure checks, and outlier filtering on the regional boundary location data. The validated regional boundary location data is then converted into polygon entities, boundary line entities, or filled surface entities in the 3D geographic scene. These polygon entities, boundary line entities, or filled surface entities are written into the entity set corresponding to the farmland region constraint layer. The farmland entity identifier, regional boundary vertex set, coordinate system, area information, and display entity identifier are stored as farmland region constraint layer data.

[0045] In one embodiment, the system can also read farmland morphology type, slope grade, plot area, crop type, or farmland detection layer, and use these as auxiliary constraints for flight path parameter recommendations or validity assessments. These auxiliary constraints do not change the continuous display attributes of the farmland area constraint layer.

[0046] Furthermore, in step 2:

[0047] Refer again Figure 2 After the farmland area constraint layer is displayed, the system receives user click operations, drag operations, coordinate input operations, or historical takeoff point selection operations in the three-dimensional geographic scene to obtain takeoff point spatial location data; performs coordinate validity judgment and takeoff and landing safety judgment on the takeoff point spatial location data; when the judgment is successful, the takeoff point spatial location data is converted into takeoff point entities, and the takeoff point entities are written into the entity set corresponding to the takeoff point constraint layer. At the same time, the takeoff point longitude, latitude, altitude, source type, and display entity identifier are stored as takeoff point constraint layer data.

[0048] The farmland area constraint layer, takeoff point constraint layer, and preview layer each have independent data identifiers and entity sets. Specifically, the farmland area constraint layer stores and displays farmland area boundary entities, the takeoff point constraint layer stores and displays takeoff point entities, and the preview layer stores and displays preview waypoints, segment connections, heading arrows, route statistics, and parameter version identifiers. The preview layer can be temporarily stored in the front-end status management object, map entity data source, or server-side temporary result table, and is not written to the official route data table before formal confirmation. When the field patrol task parameters change, the system only clears the entity set corresponding to the preview layer based on its data identifier and regenerates a new preview layer; it does not delete the entity sets corresponding to the farmland area constraint layer and takeoff point constraint layer, thus demonstrating the independence of the three layers in terms of storage structure and display control.

[0049] Furthermore, in step 3:

[0050] The parameters for field patrol missions include at least one or more of the following: flight altitude, flight path spacing or lateral overlap rate, heading angle, edge distance, flight speed, photo interval, and mission payload type. After receiving the parameters, the system performs a joint validity assessment of the farmland area constraint layer, the takeoff point constraint layer, and the field patrol mission parameters.

[0051] The joint validity assessment can include: whether the farmland area boundary exists and can be resolved; whether the takeoff point exists and its coordinates are valid; whether the flight altitude, speed, margin, and overlap rate are within preset ranges; whether the estimated flight path length based on the farmland area and flight path spacing exceeds the UAV's endurance threshold; and whether the generated flight path has obvious boundary violations, breaks, or inability to connect. Only when the joint validity assessment passes will the system trigger the generation of a preview flight path.

[0052] For example, this invention provides the calculation of route spacing and edge distance parameters. The other field patrol task parameters mentioned above can be calculated based on existing technical algorithms, and will not be elaborated here.

[0053] Regarding the calculation of flight path spacing: When the equivalent ground coverage width of the UAV payload is W and the lateral overlap rate is rho, the recommended spacing d between adjacent flight paths can be expressed as:

[0054] d = W × (1 - rho),

[0055] Where rho ranges from 0 to 1. If the horizontal field of view of the load is theta and the flight altitude is h, then W can be approximately expressed as:

[0056] W = 2 × h ×tan(theta / 2),

[0057] Therefore, the distance between flight lines can be further expressed as:

[0058] d = 2 × h × tan(theta / 2) × (1 - rho),

[0059] When the user directly inputs the flight path spacing d, the system uses the user's input value as the priority parameter; when the user inputs the flight altitude h, field of view angle theta, and lateral overlap rate rho, the system calculates the recommended flight path spacing according to the above formula and determines whether it is between the preset minimum spacing d_min and maximum spacing d_max, i.e., it satisfies:

[0060] d_min <= d <= d_max.

[0061] To avoid flight paths running close to or crossing farmland boundaries, the system shrinks the polygon P of the farmland area based on the boundary distance parameter b, resulting in a corrected operating area P'. This can be represented as:

[0062] P' = Offset(P, -b)

[0063] Here, Offset represents the polygon offset operation, and -b indicates offsetting inwards into the polygon. If P' is empty after shrinking, has self-intersections, or its area is below the threshold A_min, then the current margin parameter is considered invalid.

[0064] When the farmland area constraint layer, takeoff point constraint layer, and patrol task parameters all meet the preset conditions, a preview route point set is generated. In one embodiment, the system generates the preview route point set according to the following steps:

[0065] (1) Read the regional boundary data corresponding to the farmland area constraint layer and parse it to obtain the set of polygon vertices;

[0066] (2) The polygon is shrunk according to the margin parameter to obtain the correction area;

[0067] (3) Calculate the flight path spacing based on flight altitude, load field of view, or lateral overlap rate;

[0068] (4) Generate multiple parallel scan lines within the correction operation area based on the heading angle;

[0069] (5) Calculate the intersection of the scan line and the boundary of the correction operation area, and extract the valid flight segments located within the area;

[0070] (6) Sort and connect valid segments according to the takeoff point location, segment endpoint distance, turning cost, or serpentine connection rules;

[0071] (7) Generate multiple preview waypoints along the connected preview route, and add latitude and longitude, altitude, heading, speed, photo action, sequence number and version identifier of the task parameter to each preview waypoint.

[0072] The system determines the scanning direction vector u using the heading angle alpha, and constructs its normal vector n:

[0073] u = (cos alpha, sin alpha),

[0074] n = (-sin alpha, cos alpha),

[0075] Within the bounded area of ​​the correction operation region P', multiple scan lines L_i are generated by translating along the normal vector n according to the line spacing d. The i-th scan line can be represented as:

[0076] L_i(t) = c + i × d × n + t × u,

[0077] Where c is the reference center point and t is the line parameter. For the i-th scan line L_i, the system calculates its intersection S_i with the correction work area P':

[0078] S_i = L_i intersection P',

[0079] intersection means finding the intersection.

[0080] When S_i is a valid line segment, it is used as a candidate line segment; when S_i is empty or its length is less than the minimum line segment threshold l_min, the corresponding scan line is discarded. This method ensures that the preview line is mainly located within the correction operation area.

[0081] For a set of candidate segments {S_i}, the system can determine the segment access order using either a serpentine connection rule or a minimum distance cost rule. The distance cost C between any two candidate segments can be expressed as:

[0082] C(i,j) = dist(end(S_i), start(S_j)) + lambda × turn(i,j),

[0083] Where dist represents the distance between two points, turn represents the turning angle cost, lambda is the weighting coefficient, and i and j represent the candidate segment indices corresponding to different scan lines. The connected continuous route is denoted as R, and the system discretizes R according to the preset waypoint interval s. The k-th waypoint can be represented as:

[0084] Q_k = R(k × s), k = 0, 1, 2, ... , floor(Length(R) / s),

[0085] Where Length(R) represents the total length of the continuous route R, and floor represents the floor function, which is used to convert the result of Length(R) / s into the largest integer not exceeding the result, thereby determining the upper limit of the waypoint number that can be discretely generated.

[0086] The heading angle beta_k of each waypoint can be calculated from the adjacent waypoints:

[0087] beta_k = atan2(y_{k+1} - y_k, x_{k+1} - x_k),

[0088] Where x_k and y_k represent the x-coordinate and y-coordinate of the k-th waypoint in the plane coordinate system, respectively, and x_{k+1} and y_{k+1} represent the x-coordinate and y-coordinate of the next adjacent waypoint, respectively.

[0089] Let the total length of the preview route be L_total, the average flight speed be v, and the distances from the takeoff point to the first waypoint and the distances from the last waypoint back to the takeoff point be L_start and L_return, respectively. Then the estimated flight time T can be expressed as:

[0090] T = (L_start + L_total + L_return) / v + N × tau,

[0091] Where N represents the number of times the camera or hovering action is performed, and tau represents the time taken for a single action. If T is greater than the drone's available flight time T_max or exceeds the safety factor-corrected threshold eta x T_max, the system determines that the current preview scheme has a flight time risk.

[0092] In another embodiment, the preview waypoint set can be generated by the server. The front end is responsible for organizing the area boundaries, take-off points and parameters and submitting them to the server. The server returns the preview waypoint set, route statistics and validity results, and the front end then builds the preview layer.

[0093] After the preview route point set is generated, the system displays it as a preview layer independent of the farmland area constraint layer and the takeoff point constraint layer. The preview layer can include waypoint entities, route segments, heading arrows, sequence markers, route statistics, and parameter version identifiers.

[0094] refer to Figure 3 When the parameters of the field patrol task change, the system performs the following processing: clears existing preview waypoint entities, flight segment connections, and preview statistics; retains the area boundary entities in the farmland area constraint layer; retains the takeoff point entities in the takeoff point constraint layer; and regenerates and displays the updated preview route point set based on the changed parameters. In this way, the system maintains a stable spatial reference during multiple trial calculations, updating only the route results that need to be compared.

[0095] Furthermore, in step 4:

[0096] refer to Figure 4 The preview layer is only used for display before confirmation and is not directly persisted as official flight route data. Upon receiving the confirmation command, the system associates and saves the current preview flight route point set, field patrol task parameters, farmland main identifier, takeoff point spatial location data, generation time, and operator user identifier to form the official flight route data. The official flight route data can be used for subsequent task issuance, flight route review, version tracking, or historical editing.

[0097] To reduce the risk of accidental operation, the system can verify whether the current preview layer is the result of the most recent parameter generation before confirmation; if the user does not regenerate the preview layer after the parameters change, the system will prevent the data from being fixed or prompt the user to update the preview first. The system can also set a version number for the official flight route data, making multiple confirmation results under the same farmland entity traceable.

[0098] refer to Figure 5 In edit mode, the system reads the farmland area boundary location data, takeoff point spatial location data, historical route point set data, and patrol task parameters corresponding to the historical official flight routes. It then restores the farmland area constraint layer, takeoff point constraint layer, and historical preview layer in the 3D geographic scene. After the user modifies the area boundary, takeoff point, or task parameters, the system clears the historical preview layer, maintains the current valid constraint layer, and regenerates a new preview layer. Upon receiving a new confirmation command, the system replaces the original data with the new official flight route data or generates a new version of data associated with the original official flight route data.

[0099] Without loss of generality, farmland area constraint layer data may include: farmland main body identifier, set of area boundary vertices, coordinate system, area, shape type, and display entity identifier. Takeoff point constraint layer data may include: takeoff point longitude, latitude, altitude, source type, and display entity identifier. Preview layer data may include: parameter version identifier, waypoint set, flight segment set, total route length, estimated flight duration, and validity status. Official route data may include: official route identifier, farmland main body identifier, takeoff point data, mission parameters, waypoint set, confirmation time, confirming user, and version number.

[0100] In one embodiment, the boundary of the main farmland area is a closed polygon composed of six latitude and longitude vertices, and the takeoff point is located approximately 20m outside the farmland boundary. The user sets the flight altitude to 100m, flight speed to 5m / s, forward overlap rate to 80%, lateral overlap rate to 70%, edge distance to 5m, takeoff time to 12:00, solar azimuth angle to 90 degrees, and selects a visible light camera and photo-taking action. The system first displays the farmland area constraint layer and the takeoff point constraint layer in the 3D geographic scene, and then calls the preview route generation service to generate a preview waypoint set.

[0101] In the above embodiments, when the user only adjusts the lateral overlap rate from 70% to 75% or the edge distance from 5m to 8m, the system retains the farmland area constraint layer and the takeoff point constraint layer unchanged, only clearing the original preview waypoints and segment connections and rebuilding a new preview layer; when the user clicks confirm, the system writes the current preview waypoint set, current task parameters, takeoff point data, farmland main identifier, confirmation time, and version number into the official route data. This verifies that the present invention can reduce the repeated selection of points and repeated loading of farmland areas, and avoids unconfirmed preview results directly becoming official routes.

[0102] On the other hand, the present invention provides a drone flight path preview and confirmation device for agricultural field inspection tasks, which includes various modules capable of implementing the various steps of the aforementioned method, specifically including:

[0103] The regional constraint layer construction module is used to obtain the regional boundary location data corresponding to the main body of the target farmland and construct the farmland regional constraint layer in the three-dimensional geographic scene;

[0104] The takeoff point constraint layer construction module is used to receive takeoff point spatial location data input or selected by the user and construct a takeoff point constraint layer in the three-dimensional geographic scene.

[0105] The preview layer construction module is used to receive field patrol task parameters and perform a joint validity judgment on the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters; when the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters all meet preset conditions, a preview route point set is generated and a preview layer display is constructed in the three-dimensional geographic scene, independent of the farmland area constraint layer and takeoff point constraint layer; when the field patrol task parameters change, the farmland area constraint layer and takeoff point constraint layer continue to be displayed, only the preview layer is cleared and rebuilt.

[0106] The save module is used to associate and save the current preview route point set, the current field patrol task parameters, and the farmland main identifier corresponding to the target farmland as formal route data after receiving a confirmation instruction.

[0107] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned method for previewing and confirming drone flight routes for agricultural field patrol tasks.

[0108] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned method for previewing and confirming drone flight paths for agricultural field patrol tasks.

[0109] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are 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 previewing and confirming UAV flight paths for agricultural field patrol tasks, characterized in that, The method includes: Obtain the location data of the regional boundary corresponding to the main body of the target farmland, and construct a farmland region constraint layer in the three-dimensional geographic scene; Receive user-inputted or selected takeoff point spatial location data and construct a takeoff point constraint layer in the three-dimensional geographic scene; The system receives field patrol task parameters and performs a joint validity assessment of the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters. When all three conditions are met, a preview route point set is generated, and a preview layer independent of the farmland area constraint layer and takeoff point constraint layer is constructed and displayed in the 3D geographic scene. When the field patrol task parameters change, the farmland area constraint layer and takeoff point constraint layer are kept displayed, and only the preview layer is cleared and rebuilt. Upon receiving the confirmation command, the current preview route point set, the current field patrol task parameters, and the farmland entity identifier corresponding to the target farmland are associated and saved as formal route data.

2. The method for previewing and confirming UAV flight paths for agricultural field patrol tasks according to claim 1, characterized in that, The takeoff point spatial location data is received by the user through click operations, drag operations, coordinate input operations, or historical takeoff point selection operations in the three-dimensional geographic scene. The takeoff point constraint layer remains displayed during multiple preview layer reconstruction processes before receiving deletion instructions, reselection instructions, or editing instructions.

3. The method for previewing and confirming UAV flight paths for agricultural field patrol tasks according to claim 1, characterized in that, The joint validity judgment includes: determining whether the area boundary location data exists and can be parsed; determining whether the takeoff point spatial location data exists and the coordinates are valid; determining whether the flight altitude, speed, edge distance and overlap rate in the field patrol task parameters are within the preset range; determining whether the route length estimated based on the farmland area and route spacing exceeds the UAV endurance threshold; and determining whether the generated route has crossed the boundary, broken or cannot be connected.

4. The method for previewing and confirming UAV flight paths for agricultural field patrol tasks according to claim 1, characterized in that, The preview layer includes waypoint entities, flight segment lines, heading arrows, sequence number markers, flight route statistics, and parameter version identifiers; the official flight route data also includes generation time, user identifier, and version number, making multiple confirmation results under the same farmland entity traceable.

5. The method for previewing and confirming UAV flight paths for agricultural field patrol tasks according to claim 1, characterized in that, The generation of the preview waypoint set includes: shrinking the polygon corresponding to the boundary position data of the area according to the margin parameter in the field patrol task parameters to obtain the correction operation area; calculating the line spacing according to the flight altitude, load field of view and lateral overlap rate in the field patrol task parameters; generating multiple parallel scan lines in the correction operation area according to the heading angle in the field patrol task parameters; calculating the intersection of each scan line with the boundary of the correction operation area and extracting the effective flight segments; sorting and connecting the effective flight segments according to the takeoff point spatial position data, the distance of the flight segment endpoints and the turning cost; discretely generating multiple preview waypoints along the connected lines; and attaching latitude and longitude, altitude, heading, speed, photo-taking action, sequence number and task parameter version identifier to each preview waypoint.

6. The method for previewing and confirming UAV flight paths for agricultural field patrol tasks according to claim 5, characterized in that, After generating the preview route point set, the estimated flight time is estimated based on the total length of the preview route, average flight speed, distance from the takeoff point to the first waypoint and the distance from the last waypoint back to the takeoff point, and the number of photo-taking actions. When the estimated flight time is greater than the available flight time of the UAV or exceeds the threshold after the safety factor correction, it is determined that the current preview scheme has a flight endurance risk.

7. The method for previewing and confirming UAV flight paths for agricultural field patrol tasks according to claim 1, characterized in that, Upon receiving the confirmation instruction, before associating and saving the current preview route point set as the official route data, it verifies whether the current preview layer is the result of being regenerated after the most recent parameter change. If the current preview layer is not the result of being regenerated after the most recent parameter change, then the system prohibits the solidification process or prompts the user to update the preview first.

8. A drone flight path preview and confirmation device for agricultural field inspection tasks, characterized in that, include: The regional constraint layer construction module is used to obtain the regional boundary location data corresponding to the main body of the target farmland and construct the farmland regional constraint layer in the three-dimensional geographic scene; The takeoff point constraint layer construction module is used to receive takeoff point spatial location data input or selected by the user and construct a takeoff point constraint layer in the three-dimensional geographic scene. The preview layer construction module is used to receive field patrol task parameters and perform a joint validity judgment on the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters; when the farmland area constraint layer, takeoff point constraint layer, and field patrol task parameters all meet preset conditions, a preview route point set is generated and a preview layer display is constructed in the three-dimensional geographic scene, independent of the farmland area constraint layer and takeoff point constraint layer; when the field patrol task parameters change, the farmland area constraint layer and takeoff point constraint layer continue to be displayed, only the preview layer is cleared and rebuilt. The save module is used to associate and save the current preview route point set, the current field patrol task parameters, and the farmland main identifier corresponding to the target farmland as formal route data after receiving a confirmation instruction.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When one or more programs are executed by the one or more processors, the one or more processors implement the method for previewing and confirming drone flight paths for agricultural field patrol tasks as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, It stores executable instructions that, when executed by a processor, enable the processor to implement the UAV route preview and confirmation method for agricultural field patrol tasks as described in any one of claims 1-7.

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