A method and device for unmanned aerial vehicle path planning based on cooperative rendezvous points and related

Abstract

The application discloses a kind of unmanned plane path planning method, device and related based on cooperative rendezvous point, belongs to unmanned plane path planning field.The present application is according to the position of unmanned plane cluster and task target, future task, unmanned plane residual path length and target residual task path length etc., by designing the cooperative rendezvous point of different task type, the optimal heading is calculated, then according to the optimal path of unmanned plane is planned in the turning strategy, and the path lengthening mechanism is introduced, to ensure that the multiple tasks of given target are executed in order.The application can make unmanned plane seek to the appropriate route in task area, thereby shorten task path, improve the work efficiency of unmanned plane cluster, optimize heading and ensure that multiple tasks are executed in order.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) path planning technology, and more specifically to a UAV path planning method, apparatus, and related technologies based on cooperative intersection points. Background Technology

[0002] Unmanned aerial vehicle (UAV) path planning is a core technology for achieving autonomous flight, intelligent operation, and safety management of UAVs, and it runs through the entire process of R&D, deployment, and application of low-altitude unmanned systems. With the rapid development of low-altitude technology, intelligent control, and communication technology, UAVs have gradually evolved from single platforms to multi-UAV collaborative swarms. UAV swarms, with their advantages of parallel operation, wide coverage, and strong resilience, are widely used in reconnaissance and inspection, environmental monitoring, logistics delivery, emergency search and rescue, and operations in complex scenarios. As a key technology for achieving safe and efficient swarm flight, UAV swarm path planning aims to plan conflict-free, low-loss, and highly efficient flight routes for multiple UAVs, and is a core support for ensuring stable swarm operation and mission completion.

[0003] In practical operations, UAV swarms typically operate in dynamic and complex environments, facing challenges such as terrain obstacles, airspace restrictions, airflow disturbances, and spatial overlap among multiple UAVs. Path planning requires a comprehensive consideration of environmental constraints, individual performance constraints, and mission constraints within three-dimensional space to generate feasible, safe, and optimized trajectories for each UAV. Unlike single-UAV path planning, swarm path planning must not only meet the obstacle avoidance requirements of individual UAVs but also achieve inter-UAV conflict avoidance, formation maintenance, spatial allocation, and overall trajectory coordination, enabling the swarm to operate efficiently and orderly in complex environments.

[0004] For diverse mission types, how to shorten mission paths as much as possible, improve mission efficiency, optimize heading, and ensure the orderly execution of multiple missions by UAVs has always been a pressing problem to be solved. Summary of the Invention

[0005] In view of the above problems, this invention proposes a UAV path planning algorithm based on cooperative intersection points. It is related to the calculation of the serialized task benefits and enables UAVs to find suitable routes within the task area to cooperate with the task execution, thereby improving the working efficiency of UAV swarms.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, embodiments of the present invention provide a UAV path planning method based on cooperative intersection points, comprising the following steps: S1. Obtain the drone pose, target pose, future mission type, drone remaining path length, and target remaining mission path length; S2. Determine the center of the UAV circle based on the UAV pose and preset turning radius; determine the optimal mission heading based on the future mission type; and determine the cooperative rendezvous distance based on the target pose, and determine the center of the cooperative rendezvous point circle based on the cooperative rendezvous distance. S3. Iterate through the UAV circle and cooperative intersection circle under each optimal mission flight direction, generate path points using the turn-straight-turn strategy and the turn-turn-turn strategy, calculate the path length, and select the candidate path with the shortest path length as the planned path. S4. When the sum of the length of the planned path and the remaining path length of the UAV is less than the remaining mission path length of the target, the planned path is extended to obtain the final path; otherwise, the planned path is used as the final path.

[0008] Preferably, in S2, determining the optimal mission heading based on the future mission type includes: When the future task type is a classification task, the diagonal direction of the target is calculated based on the length and width of the target corresponding to the target pose, and the four headings corresponding to the diagonal direction are taken as the optimal task headings. When the future task type is a job execution or detection task, determine whether the distance between the UAV and the target is less than a preset proximity threshold; if so, directly take the UAV's flight path from the UAV circle to the target as the optimal task flight path; otherwise, first determine the cooperative rendezvous circle away from the target, and take the flight path from the UAV to the target sequentially through the UAV circle and the cooperative rendezvous circle as the optimal task flight path.

[0009] Preferably, in S3, the switch-to-straight-turn strategy and the switch-to-turn-turn strategy are executed sequentially. When the switch-to-straight-turn strategy is not feasible, the switch-to-turn-turn strategy is executed directly.

[0010] Preferably, the straight-turn strategy is feasible when the distance between the center of the UAV circle and the center of the cooperative intersection point is greater than n times the minimum turning radius or when the UAV circle and the cooperative intersection circle have the same direction of rotation. The "turn-turn-turn" strategy is feasible when the distance between the center of the UAV circle and the center of the cooperative rendezvous point circle is less than n times the minimum turning radius and the UAV circle and the cooperative rendezvous circle have the same direction of rotation. When the distance between the center of the drone and the center of the cooperative intersection point is equal to n times the minimum turning radius, a selection is made based on planning requirements, including prioritizing planning efficiency by choosing a straight-turn strategy and prioritizing spatial fault tolerance by choosing a turn-turn-turn strategy; n is an integer greater than 0.

[0011] Preferably, in S3, the execution process of the straight-to-straight strategy and the turn-turn-turn-turn strategy includes: Coordinate transformation is performed with the center of the UAV as the origin; Based on the distance between the center of the UAV circle and the center of the cooperative rendezvous circle, and the preset turning radius, the coordinates of the first entry point of the UAV flying towards the cooperative rendezvous circle and the coordinates of the second entry point of the UAV entering the cooperative rendezvous circle are calculated using geometric relationships. Based on the coordinates of the first entry point and the second entry point, the arc length and the line segment length are accumulated to obtain the path length of the candidate path; If the path length of the current candidate path is the optimal length in the current iteration, then perform the inverse coordinate transformation and save the current optimal path; otherwise, exit and continue the iteration.

[0012] Preferably, in S4, extending the planned path includes: Determine whether the current distance between the drone and the target is greater than a preset distance threshold; If the value is greater than the target circle, a new first UAV circle is planned outside the target circle corresponding to the target. The planned path is extended by using the extra turning arc length generated by the first UAV circle and the increased flight distance during the flight to the cooperative rendezvous circle. If the value is not greater than the target value, remove all path points in the planned path except for the current location of the UAV, and plan a new second UAV circle inside the target circle corresponding to the target. Use the extra turning arc length generated by the second UAV circle and the increased flight distance during the flight to the cooperative rendezvous circle to extend the planned path.

[0013] Preferably, the preset distance threshold is the sum of the distance between the center of the cooperative rendezvous point and the target and m times the minimum turning radius of the UAV, where m is an integer greater than 0.

[0014] Secondly, embodiments of the present invention provide a UAV path planning device based on cooperative intersection points, the device being used to implement the UAV path planning method based on cooperative intersection points as described in any of the preceding claims, including: The information acquisition module is used to acquire the UAV pose, target pose, future mission type, UAV remaining path length, and target remaining mission path length. An initialization module is used to determine the center of the UAV circle based on the UAV pose and a preset turning radius; determine the optimal mission heading based on the future mission type; and determine the cooperative rendezvous distance based on the target pose, and determine the center of the cooperative rendezvous point circle based on the cooperative rendezvous distance. The path planning module is used to traverse and iterate the UAV circle and cooperative rendezvous circle under each optimal mission flight direction, generate path points using the turn-straight-turn strategy and the turn-turn-turn strategy, calculate the path length, and select the candidate path with the shortest path length as the planned path. The path extension module is used to extend the planned path to obtain the final path when the sum of the length of the planned path and the remaining path length of the UAV is less than the remaining mission path length of the target; otherwise, the planned path is used as the final path.

[0015] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement the UAV path planning method based on cooperative intersection points as described in any of the preceding claims.

[0016] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the UAV path planning method based on cooperative intersection points as described in any of the preceding claims.

[0017] This invention provides a method, apparatus, and related components for UAV path planning based on cooperative intersection points, applicable to serialized task scenarios executed by UAV swarms. Compared with existing technologies, this application relates to the calculation of UAV serialized task benefits, enabling UAVs to find suitable routes within the task area, thereby shortening task paths, improving the working efficiency of UAV swarms, optimizing headings, and ensuring the orderly execution of multiple tasks. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0019] Figure 1 This refers to the task list of the drone cluster provided in this embodiment of the invention; Figure 2 This is a flowchart of the UAV path planning method based on cooperative intersection points provided in this embodiment of the invention; Figure 3 This is an initialization flowchart provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the set cooperative intersection points and completion points provided in the embodiments of the present invention; Figure 5 This is a schematic diagram of the optimal heading when the distance is relatively long, provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the optimal heading when the distance is relatively short, provided in an embodiment of the present invention; Figure 7This is a flowchart of the optimal path planning provided in this embodiment of the invention; Figure 8 This is a diagram illustrating the execution steps of the path planning strategy provided in this embodiment of the invention. Figure 9 This is a schematic diagram of the path planning strategy provided in an embodiment of the present invention; Figure 10 This is a schematic diagram illustrating the extended path of the drone when the distance is relatively long, as provided in this embodiment of the invention. Figure 11 This is a schematic diagram illustrating the extended path of the drone when the distance is relatively short, as provided in an embodiment of the present invention. Detailed Implementation

[0020] 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.

[0021] This invention discloses a method, apparatus, and related technologies for UAV path planning based on cooperative rendezvous points. The core of the method is as follows: based on information such as the location of the UAV cluster and the mission target, future missions, the remaining path length of the UAVs, and the remaining path length of the target mission, the optimal heading is calculated by designing cooperative rendezvous points and completion points for different mission types. Then, the optimal path of the UAVs is planned according to the turning strategy, and a path extension mechanism is introduced to extend the UAV path, thereby ensuring the orderly execution of multiple missions for a given target. Finally, the desired path points are recorded.

[0022] This application relates to the calculation of the benefits of serialized UAV missions, enabling UAVs to find suitable routes within the mission area. This, combined with mission execution, ensures the orderly execution of multiple tasks and improves the operational efficiency of UAV swarms. This application is applicable to serialized mission scenarios executed by UAV swarms, such as... Figure 1 The list of executable tasks is shown.

[0023] In one embodiment, the UAV path planning method based on cooperative intersection points provided in this application includes the following steps: Obtain the drone pose, target pose, future mission type, remaining path length of the drone, and remaining mission path length of the target; Based on the UAV pose and preset turning radius, determine the center of the UAV circle; determine the optimal mission heading based on the future mission type; and determine the cooperative rendezvous distance based on the target pose, and determine the center of the cooperative rendezvous point circle based on the cooperative rendezvous distance. For each optimal mission flight path, the UAV circle and cooperative rendezvous circle are traversed and iterated. Path points are generated using the turn-straight-turn strategy and the turn-turn-turn strategy. The path length is calculated and the candidate path with the shortest path length is selected as the planned path. When the sum of the length of the planned path and the remaining path length of the UAV is less than the remaining path length of the target mission, the planned path is extended to obtain the final path; otherwise, the planned path is used as the final path.

[0024] It should be noted that the above description does not constitute a strict limitation on the order of execution of the steps. In some implementations, some steps may be executed in parallel or their order may be adjusted in an equivalent manner.

[0025] Figure 2 The overall path planning process of this application is provided, including information acquisition, initialization, planning the optimal path for the UAV, extending the UAV path, and recording the desired path points.

[0026] The execution process of each step is explained in detail below.

[0027] 1. Information Acquisition: Obtain information such as UAV pose, target pose, future task, UAV remaining path length, and target remaining task path length. Establish a path planning algorithm for UAV swarm based on cooperative intersection points. Here, "future task" specifically refers to the task corresponding to this path planning; "UAV remaining path length" specifically refers to the path length from the current moment to the start of the future task; "target remaining task path length" specifically refers to the path length from the current moment to the completion moment; and "previous task" specifically refers to tasks that are not yet completed at the current moment and precede the future task.

[0028] 2. Initialization: Based on the UAV pose and preset turning radius, determine the center of the UAV circle; determine the optimal mission heading based on the future mission type; and determine the cooperative rendezvous distance based on the target pose, and determine the center of the cooperative rendezvous point circle based on the cooperative rendezvous distance; in an optional implementation, the specific process is as follows. Figure 3 ,include: 2.1 First, set the corresponding cooperative rendezvous distance. Distance to completion Different types of tasks have different points of collaboration and completion, depending on the characters, the scenario, and the requirements. Figure 4 As shown. The rendezvous point is the point where the UAV prepares to perform its mission towards the target, and the completion point is the point where the UAV flies away after completing its mission.

[0029] 2.2 Calculating the center of the UAV circle; Since the UAV has a minimum turning radius, it needs to use a circular path to turn. In this embodiment, the center of the UAV circle is calculated based on the UAV's pose information and a specified turning radius, using the following formula:

[0030]

[0031] In the formula, Indicates the coordinates of the center of the circle of the first UAV. Indicates the coordinates of the center of the circle of the second UAV. Indicates the specified turning radius. Indicates the drone's heading. This indicates the location coordinates of the drone.

[0032] 2.3 Calculate the optimal course for the mission; In this embodiment, when the future task type is a classification task, the length of the target corresponding to the target pose is determined (…). ) and width ( ), calculate the diagonal direction of the target, and take the four headings corresponding to the diagonal direction as the optimal mission headings; specifically expressed as follows:

[0033] In the formula, Indicates the target's heading. Indicates the length of the target. Indicates the breadth of the target.

[0034] When the future task type is a job execution or detection task, determine whether the distance between the UAV and the target is less than a preset proximity threshold; if so, i.e. the UAV moves away from the target, directly take the UAV's flight path based on the UAV circle towards the target as the optimal task flight path; otherwise, first determine the cooperative rendezvous circle away from the target, and take the flight path from the UAV sequentially through the UAV circle and the cooperative rendezvous circle towards the target as the optimal task flight path.

[0035] In some implementation schemes, the proximity threshold is first preset to:

[0036] in, This represents the distance from the center of the first UAV's circle to the target T. This represents the distance from the center of the second UAV's circle to the target T. This represents the distance from the center of the intersection circle to the target T. Indicates the rendezvous distance. This indicates the specified turning radius.

[0037] When the drone is far from the target, the optimal heading diagram is shown below. Figure 5 And obtained through the following formula:

[0038] This indicates the heading from the center of the first UAV to the target. This indicates the heading from the center of the first UAV to the target.

[0039] When the drone is close to the target, refer to the optimal heading diagram. Figure 6 And it is obtained by calculation using the following formula:

[0040] 2.4 Calculate the center of the cooperative rendezvous point. Based on the cooperative rendezvous distance, the optimal heading, and the specified turning radius, the coordinates of the center of the cooperative rendezvous point can be obtained using geometric relationships.

[0041]

[0042]

[0043]

[0044] In the formula, Indicates the coordinates of the joint intersection point. Indicates the coordinates of the target point. and These represent the coordinates of the center of the co-intersection circle.

[0045] 3. Plan the optimal path for the UAV; this step iterates through the UAV circle and the cooperative intersection circle under each optimal mission flight direction to find the optimal path. In one embodiment, a turn-straight-turn strategy and a turn-turn-turn strategy are used to generate path points, and the path length is calculated and the candidate path with the shortest path length is selected as the planned path; specifically, when generating path points, the turn-straight-turn strategy and the turn-turn-turn strategy are executed sequentially. When the turn-straight-turn strategy is not feasible, the turn-turn-turn-turn strategy is executed directly.

[0046] In some implementation schemes, the execution process is as follows: Figure 7 As shown, it includes: 1) Iterate through all optimal mission headings and UAV cooperative rendezvous circles; 2) Is the direct-turn strategy feasible? If yes, proceed to step 3) Plan the optimal path; otherwise, proceed to step 4). 3) Plan the optimal path according to the straight-turn strategy; 4) Is the spinning strategy feasible? If yes, proceed to step 5) Plan the optimal path; otherwise, proceed to step 6). 5) Plan the optimal path according to the spinning strategy; 6) Determine if the iteration is complete. If yes, the planning is complete; otherwise, proceed to step 1.

[0047] In this embodiment, there are two strategies for planning the optimal path of the UAV: ​​turning straight and turning in turns. When judging whether a strategy is feasible, the following principle is followed: (n is preferred to be 2). When the distance between the center of the UAV circle and the center of the cooperative intersection point is greater than n times the minimum turning radius, or when the UAV circle and the cooperative intersection circle have the same direction of rotation, the straight-turn strategy is feasible. The "turn-turn-turn" strategy is feasible when the distance between the center of the UAV circle and the center of the cooperative rendezvous point circle is less than n times the minimum turning radius and the UAV circle and the cooperative rendezvous circle have the same direction of rotation. When the distance between the center of the drone and the center of the cooperative intersection point is equal to n times the minimum turning radius, a selection is made based on planning requirements, including prioritizing planning efficiency by choosing a straight-turn strategy and prioritizing spatial fault tolerance by choosing a turn-turn-turn strategy; n is an integer greater than 0.

[0048] Furthermore, the execution steps of the two strategies are as follows: Figure 8 ,include: Coordinate transformation is performed with the center of the UAV as the origin; Based on the distance between the center of the UAV circle and the center of the cooperative rendezvous circle, and the preset turning radius, the coordinates of the first entry point of the UAV flying towards the cooperative rendezvous circle and the coordinates of the second entry point of the UAV entering the cooperative rendezvous circle are calculated using geometric relationships. Based on the coordinates of the first entry point and the second entry point, the arc length and the line segment length are accumulated to obtain the path length of the candidate path; If the path length of the current candidate path is the optimal length in the current iteration, then perform the inverse coordinate transformation and save the current optimal path; otherwise, exit and continue the iteration.

[0049] In one specific implementation plan, Figure 9 Two strategic planning diagrams are provided; Reference Figure 9 The execution process of the direct-to-direct strategy is as follows: 1) Using the center of the UAV as the origin, perform coordinate transformation on all points according to the following formula, and replace the coordinate system with the coordinate system using the center of the UAV as the origin;

[0050] The origin is the center of the drone's circle, and the angle between the center of the drone's circle and the center of the Hezhi circle and the x-axis. It is the x-axis coordinate in the new coordinate system; It is the y-axis coordinate in the new coordinate system; It is the x-axis coordinate in the original coordinate system; It is the y-axis coordinate in the original coordinate system.

[0051] 2) Using geometric relationships, calculate the coordinates of the first entry point of the UAV flying towards the cooperative intersection circle and the second entry point of the UAV entering the cooperative intersection circle; If the UAV circle and the cooperative rendezvous circle are both clockwise, then using routes A1 and B1, the coordinates can be obtained as follows: ,

[0052] If the UAV circle and the cooperative rendezvous circle are both counterclockwise, then using routes A2 and B2, the coordinates can be obtained as follows: ,

[0053] If the UAV circle is clockwise and the cooperative intersection circle is counterclockwise, then using routes C1 and D1, the coordinates can be obtained as follows: ,

[0054] If the drone's circle is counterclockwise and the cooperative rendezvous circle is clockwise, then using routes C2 and D2, the coordinates can be obtained as follows: ,

[0055] in:

[0056] The origin is the center of the drone's circle, and the angle between the center of the drone's circle, C1, and the x-axis. The origin is the center of the drone's circle, and the angle between the center of the drone's circle, C2, and the x-axis. It is the angle between the center of the co-intersection circle and D1 and the x-axis, with the center of the co-intersection circle as the origin; It is the angle between the center of the co-intersection circle and D2 and the x-axis, with the center of the co-intersection circle as the origin.

[0057] 3) Calculate the path length, where the straight segment is calculated as the Euclidean distance and the arc segment is calculated as the arc length; 4) If it is the optimal path, perform the inverse coordinate transformation according to the inverse transformation in step 1), and record this path.

[0058] Reference Figure 9 The execution process of the spinning strategy is as follows: (1) Using the center of the UAV as the origin, perform coordinate transformation on all points according to the following formula, the transformation method is the same as in step 1 above). (2) Using geometric relationships, calculate the coordinates of the first point of contact between the UAV and the second point of contact between the UAV and the cooperative intersection circle: If both circles are counterclockwise, then using routes E1 and F1, the coordinates can be obtained as follows: ,

[0059] If both circles are clockwise, then using routes E2 and F2, the coordinates can be obtained as follows: ,

[0060] in:

[0061] (3) Calculate the path length, where the straight line segment is calculated as the Euclidean distance and the arc segment is calculated as the arc length.

[0062] (4) If it is the optimal path, perform the inverse coordinate transformation and record the path.

[0063] If all optimal mission headings, UAV circles, and cooperative rendezvous circles have been iterated, and it is found that the planned path length plus the remaining UAV path length is less than the remaining target mission path length, then the mission cannot be completed sequentially. In this case, step 4 below needs to be executed to extend the UAV path.

[0064] 4. When the sum of the length of the planned path and the remaining path length of the UAV is less than the remaining mission path length of the target, the planned path is extended to obtain the final path; otherwise, the planned path is used as the final path.

[0065] In this embodiment, there are two types of extension methods, which are selected based on a preset distance threshold.

[0066] 4.1 When the current distance between the UAV and the target is greater than a preset distance threshold, a new first UAV circle is planned outside the target circle corresponding to the target. The planned path is extended by using the extra turning arc length generated by the first UAV circle and the increased flight distance during the flight to the cooperative rendezvous circle.

[0067] For example, the distance between the point where the drone leaves the drone circle and the target point is greater than the distance between the center of the cooperative intersection point and the target point plus twice the drone's minimum turning radius. That is, when the drone is far from the target, a new drone circle is planned outside the target circle, and the path is extended by increasing the turning arc length and the increased flight distance during the process of the target circle reaching the cooperative rendezvous circle; At this point, the extended path is as follows Figure 10As shown; the steps for calculating the extended path length include: 4.11 Calculate the coordinates of path point 1 based on the coordinates of the UAV center and the target; When the drone's circle is clockwise:

[0068] In the formula, Indicates the coordinates of the target point; When the drone's circle is counterclockwise:

[0069] 4.12 Calculate the coordinates of path points 2 and 3 using the following formula;

[0070]

[0071]

[0072]

[0073]

[0074] 4.13 Calculate the coordinates of path point 5 using the target's remaining mission path length, the UAV's remaining path length, the coordinates of path point 1, and the cooperative rendezvous distance (i.e., the completion distance):

[0075]

[0076] In the formula, This represents the path length from path point 3 to path point 5. Indicates the remaining path length of the target task. This represents the path length from the drone point to path point 3. This indicates the path length from path point 5 to the completion point.

[0077] 4.14 If Then, set a path point 4 every 90 degrees between path points 3 and 5, and calculate the coordinates of path point 4:

[0078] 4.15 Further calculation of the co-intersection point and completion point yields the extended path:

[0079]

[0080] 4.2 When the current distance between the UAV and the target is not greater than a preset distance threshold, remove all path points in the planned path except for the current UAV location, and plan a new second UAV circle inside the target circle corresponding to the target. Use the extra turning arc length generated by the second UAV circle and the increased flight distance during the flight to the cooperative rendezvous circle to extend the planned path.

[0081] For example, the distance between the point where the drone leaves the drone circle and the target point is less than the distance between the center of the cooperative intersection point and the target + 2 times the drone's minimum turning radius. That is, when the drone is close to the target, the optimal path points calculated in all planned drone paths except the point where the drone is located are deleted, and a new drone circle is planned inside the target circle, using the increased turning arc length and the increased flight distance during the process of the target circle reaching the cooperative intersection circle to extend the path.

[0082] At this point, the path reference is extended. Figure 11 As shown; the steps to calculate the extended path length are as follows: 4.21 Because the UAV is too close to the target, there is no space to extend its range in the initial stage. Therefore, the path points 1 and 2 in the first half of the flight path are the same as the path points for leaving the UAV circle and flying into the cooperative intersection circle in the "planned optimal path for the UAV". This is the cooperative intersection circle of the optimal path.

[0083] 4.22 Using the center of the original collinear intersection circle Calculate path point 3 for the joint intersection distance:

[0084]

[0085] 4.23 Using the remaining target path length, the remaining UAV path length, the coordinates of path point 1, and the collaborative rendezvous distance (i.e., the distance to be completed), calculate the coordinates of path point 5:

[0086]

[0087] 4.24 If Then, set a path point 4 every 90 degrees between path points 3 and 5, and calculate the coordinates of path point 4:

[0088] 4.25 Further calculation of the co-intersection point and completion point yields the extended path:

[0089]

[0090] 5. Record the expected path points calculated above.

[0091] Furthermore, to facilitate the implementation of this solution, one embodiment also provides a UAV path planning device based on cooperative intersection points, based on the same inventive concept. This device includes: The information acquisition module is used to acquire the UAV pose, target pose, future mission type, UAV remaining path length, and target remaining mission path length. An initialization module is used to determine the center of the UAV circle based on the UAV pose and a preset turning radius; determine the optimal mission heading based on the future mission type; and determine the cooperative rendezvous distance based on the target pose, and determine the center of the cooperative rendezvous point circle based on the cooperative rendezvous distance. The path planning module is used to traverse and iterate the UAV circle and cooperative rendezvous circle under each optimal mission flight direction, generate path points using the turn-straight-turn strategy and the turn-turn-turn strategy, calculate the path length, and select the candidate path with the shortest path length as the planned path. The path extension module is used to extend the planned path to obtain the final path when the sum of the length of the planned path and the remaining path length of the UAV is less than the remaining mission path length of the target; otherwise, the planned path is used as the final path.

[0092] The UAV path planning device based on cooperative intersection points provided in this embodiment of the invention produces the same technical effects as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in this embodiment can be referred to the corresponding content in the aforementioned method embodiment, and will not be repeated here.

[0093] Furthermore, this application also provides a computer-readable storage medium and an electronic device. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the UAV path planning method based on cooperative intersection points as described in any of the preceding claims. The electronic device includes a memory and a processor, wherein the memory may be a computer-readable storage medium, and the processor, when executed, is capable of implementing the UAV path planning method based on cooperative intersection points as described in any of the preceding claims.

[0094] Furthermore, in some embodiments, the processor may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits packaged with the same or different functions, including combinations of one or more central processing units, microprocessors, digital processing chips, graphics processors, and various control chips. The processor is the control core of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in memory and calls data stored in said memory to perform various functions of the electronic device and process data.

[0095] Any content or technical means not mentioned in the embodiments of this invention can be obtained by referring to the prior art. This disclosure does not limit the scope of the invention and therefore will not be elaborated further.

[0096] The embodiments of the present invention have been described in detail above, and the principles and implementation methods of the present invention have been explained. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of the present invention. Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, computer software program products, or electronic devices, etc. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] It should be noted that the word "comprising" does not exclude the presence of components or steps not listed in the claims. The words "a" or "an" preceding a component do not exclude the presence of a plurality of such components. This invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer.

[0098] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0099] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for UAV path planning based on cooperative intersection points, characterized in that, Includes the following steps: S1. Obtain the drone pose, target pose, future mission type, drone remaining path length, and target remaining mission path length; S2. Determine the center of the UAV circle based on the UAV pose and preset turning radius; determine the optimal mission heading based on the future mission type; and determine the cooperative rendezvous distance based on the target pose, and determine the center of the cooperative rendezvous point circle based on the cooperative rendezvous distance. S3. Iterate through the UAV circle and cooperative intersection circle under each optimal mission flight direction, generate path points using the turn-straight-turn strategy and the turn-turn-turn strategy, calculate the path length, and select the candidate path with the shortest path length as the planned path. S4. When the sum of the length of the planned path and the remaining path length of the UAV is less than the remaining mission path length of the target, the planned path is extended to obtain the final path; otherwise, the planned path is used as the final path.

2. The UAV path planning method based on cooperative intersection points as described in claim 1, characterized in that, In S2, determining the optimal mission heading based on the future mission type includes: When the future task type is a classification task, the diagonal direction of the target is calculated based on the length and width of the target corresponding to the target pose, and the four headings corresponding to the diagonal direction are taken as the optimal task headings. When the future task type is a job execution or detection task, determine whether the distance between the UAV and the target is less than a preset proximity threshold; if so, directly take the UAV's flight path from the UAV circle to the target as the optimal task flight path; otherwise, first determine the cooperative rendezvous circle away from the target, and take the flight path from the UAV to the target sequentially through the UAV circle and the cooperative rendezvous circle as the optimal task flight path.

3. The UAV path planning method based on cooperative intersection points as described in claim 1, characterized in that, In S3, the direct-to-direct strategy and the direct-to-direct-to strategy are executed sequentially. When the direct-to-direct-to strategy is not feasible, the direct-to-direct-to-direct-to strategy is executed directly.

4. The UAV path planning method based on cooperative intersection points as described in claim 1 or 3, characterized in that, When the distance between the center of the UAV circle and the center of the cooperative intersection point is greater than n times the minimum turning radius, or when the UAV circle and the cooperative intersection circle have the same direction of rotation, the straight-turn strategy is feasible. The "turn-turn-turn" strategy is feasible when the distance between the center of the UAV circle and the center of the cooperative rendezvous point circle is less than n times the minimum turning radius and the UAV circle and the cooperative rendezvous circle have the same direction of rotation. When the distance between the center of the drone and the center of the cooperative rendezvous point is equal to n times the minimum turning radius, the selection is made based on planning requirements, including prioritizing planning efficiency by choosing a straight-turn strategy and prioritizing spatial fault tolerance by choosing a turn-turn-turn strategy. n is an integer greater than 0.

5. The UAV path planning method based on cooperative intersection points as described in claim 1 or 3, characterized in that, In S3, the execution process of the straight-to-straight strategy and the turn-to-turn-to-turn strategy includes: Coordinate transformation is performed with the center of the UAV as the origin; Based on the distance between the center of the UAV circle and the center of the cooperative rendezvous circle, and the preset turning radius, the coordinates of the first entry point of the UAV flying towards the cooperative rendezvous circle and the coordinates of the second entry point of the UAV entering the cooperative rendezvous circle are calculated using geometric relationships. Based on the coordinates of the first entry point and the second entry point, the arc length and the line segment length are accumulated to obtain the path length of the candidate path; If the path length of the current candidate path is the optimal length in the current iteration, then perform the inverse coordinate transformation and save the current optimal path; otherwise, exit and continue the iteration.

6. The UAV path planning method based on cooperative intersection points as described in claim 1, characterized in that, In S4, the process of extending the planned path includes: Determine whether the current distance between the drone and the target is greater than a preset distance threshold; If the value is greater than the target circle, a new first UAV circle is planned outside the target circle corresponding to the target. The planned path is extended by using the extra turning arc length generated by the first UAV circle and the increased flight distance during the flight to the cooperative rendezvous circle. If the value is not greater than the target value, remove all path points in the planned path except for the current location of the UAV, and plan a new second UAV circle inside the target circle corresponding to the target. Use the extra turning arc length generated by the second UAV circle and the increased flight distance during the flight to the cooperative rendezvous circle to extend the planned path.

7. The UAV path planning method based on cooperative intersection points as described in claim 6, characterized in that, The preset distance threshold is the sum of the distance between the center of the cooperative rendezvous point and the target, and m times the minimum turning radius of the UAV, where m is an integer greater than 0.

8. A UAV path planning device based on cooperative intersection points, characterized in that, The method for implementing UAV path planning based on cooperative intersection points as described in any one of claims 1 to 7 includes: The information acquisition module is used to acquire the UAV pose, target pose, future mission type, UAV remaining path length, and target remaining mission path length. An initialization module is used to determine the center of the UAV circle based on the UAV pose and a preset turning radius; determine the optimal mission heading based on the future mission type; and determine the cooperative rendezvous distance based on the target pose, and determine the center of the cooperative rendezvous point circle based on the cooperative rendezvous distance. The path planning module is used to traverse and iterate the UAV circle and cooperative rendezvous circle under each optimal mission flight direction, generate path points using the turn-straight-turn strategy and the turn-turn-turn strategy, calculate the path length, and select the candidate path with the shortest path length as the planned path. The path extension module is used to extend the planned path to obtain the final path when the sum of the length of the planned path and the remaining path length of the UAV is less than the remaining mission path length of the target; otherwise, the planned path is used as the final path.

9. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the UAV path planning method based on cooperative intersection points as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the UAV path planning method based on cooperative intersection points as described in any one of claims 1 to 7.

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