Shape-based fixed-wing unmanned aerial vehicle online path planning method, medium and device

Abstract

The present application relates to the technical field of unmanned aerial vehicle path planning, and provides a fixed-wing unmanned aerial vehicle online path planning method based on fitting, a medium and a device, the method comprising the following steps: S1, obtaining a new no-fly zone and fitting it into a circle to generate a new existing basic flight path; S2, obtaining a re-planned flight section in the new existing basic flight path that passes through the new no-fly zone fitting circle; S3, re-planning the flight path in each re-planned flight section; S4, generating a new flight path through splicing and optimization and correction; S5, judging whether the fixed-wing unmanned aerial vehicle online path planning task is completed, if not, returning to step S3. The present application is reasonable and efficient, can effectively utilize the inherent characteristics of the fixed-wing unmanned aerial vehicle, and solve the problem that the fixed-wing unmanned aerial vehicle needs to complete secondary flight path re-planning within a limited time on the airborne end when there is an environmental change such as the generation of a new no-fly zone.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) path planning technology, and more specifically, to a method, medium, and device for online path planning of fixed-wing UAVs based on shape mimicry. Background Technology

[0002] Unmanned aerial vehicles (UAVs) are characterized by their flexibility, convenience, and speed, and are widely used in both civilian and military fields. Path planning is a crucial aspect of UAV mission execution, requiring the UAV to fly from a starting point to a destination along a specific path while avoiding obstacles.

[0003] Traditional path planning methods for fixed-wing UAVs primarily rely on pre-defined waypoints and route planning algorithms. These methods often fail to adapt to complex and ever-changing flight environments and have limited ability to handle dynamic obstacles. Furthermore, traditional methods typically ignore the dynamic performance and maneuverability of UAVs, making it impossible to provide flexible path planning for different mission requirements.

[0004] To overcome these challenges, new path planning techniques have emerged in recent years, such as those based on genetic algorithms, artificial neural networks, and reinforcement learning. These techniques leverage the advantages of big data analytics and machine learning to better handle path planning problems in complex environments. However, these methods still have some limitations in practical applications, including high computational complexity, large training data requirements, and poor real-time performance.

[0005] Therefore, a novel path planning method for fixed-wing unmanned aerial vehicles (UAVs) is needed to overcome the limitations of traditional methods and existing technologies. This method should enable efficient, safe, and flexible path planning in complex and ever-changing environments, while considering the dynamic performance and maneuverability of the UAV. Furthermore, the method should be real-time, adaptable to different mission requirements, and able to adaptively handle dynamic obstacles and environmental changes.

[0006] In real-world scenarios, fixed-wing UAVs deployed for specific tasks such as earthquake relief need to adaptively handle the impact of dynamic obstacles and environmental changes on their flight paths within a limited timeframe on the onboard device. Real-time generation of new flight paths to avoid obstacles when the environment changes is a crucial factor that needs to be considered, and existing methods do not adequately address this factor. Summary of the Invention

[0007] This invention aims to provide a shape-mimicking-based online path planning method for fixed-wing UAVs, in order to solve the problem that fixed-wing UAVs need to complete secondary route replanning online within a limited time on the airborne terminal when environmental changes occur, such as the emergence of new no-fly zones.

[0008] This invention provides an online path planning method for a fixed-wing unmanned aerial vehicle based on shape mimicry, comprising the following steps:

[0009] S1, obtain the new no-fly zone and fit it into a circle to generate a new existing basic route;

[0010] S2, obtain the replanned flight segments that fit a circle through the new no-fly zone in the new existing basic routes;

[0011] S3 involves replanning routes within each replanned flight segment;

[0012] S4 generates and corrects new routes through splicing and optimization;

[0013] S5, determine whether the online path planning task of the fixed-wing UAV is completed. If not, return to step S3.

[0014] Furthermore, in step S1, obtaining the new no-fly zone and fitting it into a circle to generate a new existing basic route includes:

[0015] Acquire new no-fly zones;

[0016] By fitting the minimum circumcircle of the new no-fly zone, the center point and radius of the minimum circumcircle are obtained;

[0017] Obtain waypoints for existing basic routes, and also include the current location of the fixed-wing UAV as a waypoint;

[0018] Based on the minimum circumcircle of the new no-fly zone, delete the waypoints in the existing basic routes that fall within the minimum circumcircle of the new no-fly zone, and combine the remaining waypoints to form new existing basic routes.

[0019] Furthermore, in step S2, obtaining the replanned flight segments that fit a circle through the new no-fly zone in the new existing basic route includes:

[0020] The route between any two points in the new existing basic air route is considered as a single air segment.

[0021] Check in turn whether each flight segment has passed through the minimum circumcircle of the new no-fly zone;

[0022] The flight segment that passes through the smallest outer circle of the new no-fly zone will be designated as a replanned flight segment.

[0023] Furthermore, in step S3, within each replanned segment, the replanned route includes:

[0024] Within each replanned flight segment, find the chord length X of the smallest circumcircle of the replanned flight segment passing through the new no-fly zone, and the two waypoints on the replanned flight segment that are Y = X / 2 from the smallest circumcircle of the new no-fly zone;

[0025] Using these two waypoints as the starting and ending points, and based on the flight performance of the fixed-wing UAV itself, an improved fast random tree algorithm (RRT*) is used to generate a route that avoids the new no-fly zone.

[0026] Furthermore, in step S4, a new route is generated and corrected through splicing and optimization, including:

[0027] Optimize the route generated in step S3: In the route generated in step S3, starting from the starting point, compare the waypoints with subsequent waypoints to see if they pass through the minimum outer circle of the new no-fly zone. If they do not pass through the minimum outer circle of the new no-fly zone, and the straight-line distance between waypoints is less than the distance of the segment before replanning and meets the turning radius requirements of the fixed-wing UAV, then delete the intermediate waypoints until the optimization is completed.

[0028] The optimized route generated in step S3 is combined with the segments of the existing basic route that do not need to be replanned to form a new route.

[0029] The new route is corrected to ensure that each waypoint meets the requirements, and each segment of the new route meets the requirements.

[0030] Furthermore, in step S4, correcting whether each waypoint in the new route meets the requirements includes:

[0031] Correct whether each waypoint in the new route is within a no-fly zone;

[0032] And whether each waypoint in the new route meets the waypoint flight altitude requirements.

[0033] Furthermore, in step S4, correcting whether each segment of the new route meets the requirements includes:

[0034] Correct whether each segment of the new route meets the turning radius requirements of the fixed-wing UAV;

[0035] And to correct whether each segment of the new route passes through a no-fly zone.

[0036] Furthermore, in step S5, determining whether the online path planning task for the fixed-wing UAV has been completed includes:

[0037] Based on the correction results of the new route in step S4, determine whether the online path planning task of the fixed-wing UAV is completed; if the correction results do not meet the requirements, return to step S3; otherwise, end the online path planning process of the fixed-wing UAV.

[0038] The present invention also provides a computer terminal storage medium storing computer terminal executable instructions, which are used to execute the above-described shape-based fixed-wing UAV online path planning method.

[0039] The present invention also provides a computing device, comprising:

[0040] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the above-described shape-based fixed-wing UAV online path planning method.

[0041] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0042] This invention is rationally designed and highly efficient. It can effectively utilize the inherent characteristics of fixed-wing UAVs to solve the problem that fixed-wing UAVs need to complete secondary route replanning online within a limited time on the airborne terminal when environmental changes occur, such as the emergence of new no-fly zones. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart of the online path planning method for a fixed-wing UAV based on shape mimicry, as described in an embodiment of the present invention.

[0045] Figure 2 This is a schematic diagram of a new no-fly zone in an embodiment of the present invention, fitted into a circle, and generating a new existing basic air route.

[0046] Figure 3 This is a schematic diagram illustrating the examination of the smallest circumcircle of a new existing basic airway passing through a new no-fly zone in an embodiment of the present invention.

[0047] Figure 4 This is a schematic diagram illustrating the determination of the start and end points of the improved fast random tree algorithm in the replanning flight segment according to an embodiment of the present invention.

[0048] Figure 5 This is a schematic diagram illustrating the generation of new routes based on the improved fast random tree algorithm in an embodiment of the present invention.

[0049] Figure 6 This is a schematic diagram illustrating the optimization and replanning of flight segments in an embodiment of the present invention.

[0050] Figure 7 This is a schematic diagram of the final generated flight path in an embodiment of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0052] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0053] Example

[0054] like Figure 1 As shown, this embodiment proposes an online path planning method for a fixed-wing unmanned aerial vehicle (UAV) based on shape mimicry, including the following steps:

[0055] S1, as Figure 2 As shown, a new no-fly zone is obtained and fitted into a circle to generate a new existing basic route:

[0056] Acquire new no-fly zones;

[0057] By fitting the minimum circumcircle of the new no-fly zone, the center point and radius of the minimum circumcircle are obtained;

[0058] Obtain waypoints for existing basic routes, and also include the current location of the fixed-wing UAV as a waypoint;

[0059] Based on the minimum circumcircle of the new no-fly zone, delete the waypoints in the existing basic routes that fall within the minimum circumcircle of the new no-fly zone, and combine the remaining waypoints to form new existing basic routes.

[0060] S2, as Figure 3 As shown, the replanned flight segments that fit a circle through the new no-fly zone in the new existing basic routes are obtained:

[0061] The route between any two points in the new existing basic air route is considered as a single air segment.

[0062] Check in turn whether each flight segment has passed through the minimum circumcircle of the new no-fly zone;

[0063] The flight segment that passes through the smallest outer circle of the new no-fly zone will be designated as a replanned flight segment.

[0064] S3, as Figure 4 As shown, within each replanned segment, the replanned route is:

[0065] Within each replanned flight segment, find the chord length X of the smallest circumcircle of the replanned flight segment passing through the new no-fly zone, and the two waypoints on the replanned flight segment that are Y = X / 2 from the smallest circumcircle of the new no-fly zone;

[0066] Use these two waypoints as the starting and ending points, such as Figure 5 As shown, based on the flight performance of the fixed-wing UAV itself, an improved Fast Random Tree Algorithm (RRT*) is used to generate routes that avoid new no-fly zones. The improved RRT* algorithm is existing technology and will not be described in detail here.

[0067] S4 generates and corrects new routes through splicing and optimization:

[0068] Optimize the route generated in step S3: In the route generated in step S3, starting from the starting point, sequentially compare whether each waypoint passes through the minimum outer circle of the new no-fly zone. If it does not pass through the minimum outer circle of the new no-fly zone, and the straight-line distance between waypoints is less than the distance of the segment before replanning and meets the turning radius requirements of the fixed-wing UAV, then delete the intermediate waypoints until optimization is complete; Figure 6 As shown, for the replanned flight segment between waypoint 6 and waypoint 10, waypoint 6 and waypoint 8, and waypoint 9 and waypoint 10 pass through no-fly zones and will not be optimized; waypoint 7 and waypoint 9 and waypoint 10 pass through no-fly zones and will not be optimized; waypoint 8 and waypoint 10 do not pass through no-fly zones, the distance from waypoint 8 to waypoint 9 to waypoint 10 is less than the straight-line distance from waypoint 8 to waypoint 9, and meets the single-aircraft performance requirements such as turning radius, so optimization will be performed, that is, waypoint 9 will be deleted, and waypoint 8 and waypoint 10 will be directly connected.

[0069] The optimized route generated in step S3 is then combined with segments of the existing basic route that do not require replanning to form a new route, such as... Figure 7 As shown;

[0070] The new route is corrected to ensure that each waypoint meets the requirements: whether each waypoint is within a no-fly zone; and whether each waypoint meets the individual aircraft performance requirements, such as flight altitude.

[0071] And to correct whether each segment of the new route meets the requirements: whether each segment of the new route meets the turning radius and single-unit performance requirements of the fixed-wing UAV itself; and whether each segment of the new route passes through no-fly zones.

[0072] S5, Determine whether the online path planning task of the fixed-wing UAV is completed: Based on the correction results of the new route in step S4, determine whether the online path planning task of the fixed-wing UAV is completed; if the correction results do not meet the requirements, continue to return to step S3, otherwise end the process of online path planning of the fixed-wing UAV.

[0073] Furthermore, in some embodiments, a computer terminal storage medium is proposed, storing computer terminal executable instructions for executing the shape-based fixed-wing UAV online path planning method described in the preceding embodiments. Examples of computer storage media include magnetic storage media (e.g., floppy disks, hard disks, etc.), optical recording media (e.g., CD-ROMs, DVDs, etc.), or memory such as memory cards, ROMs, or RAMs. The computer storage medium can also be distributed across a network-connected computer system, for example, as an application store.

[0074] Furthermore, in some embodiments, a computing device is proposed, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the shape-based fixed-wing UAV online path planning method as described in the foregoing embodiments. Examples of computing devices include PCs, tablets, smartphones, or PDAs.

[0075] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A shape-mimicking online path planning method for fixed-wing unmanned aerial vehicles (UAVs), characterized in that, Includes the following steps: S1, obtain the new no-fly zone and fit it into a circle to generate a new existing basic route; S2, obtain the replanned flight segments that fit a circle through the new no-fly zone in the new existing basic routes; S3 involves replanning routes within each replanned flight segment; S4 generates and corrects new routes through splicing and optimization; S5, determine whether the online path planning task of the fixed-wing UAV has been completed. If not, return to step S3. In step S3, within each replanned segment, the replanned route includes: Within each replanned flight segment, find the chord length X of the smallest circumcircle of the replanned flight segment passing through the new no-fly zone, and the two waypoints on the replanned flight segment that are Y=X / 2 from the smallest circumcircle of the new no-fly zone; Using these two waypoints as the start and end points, and based on the flight performance of the fixed-wing UAV itself, an improved Fast Random Tree algorithm (RRT) is applied. This generates flight routes to avoid the new no-fly zone.

2. The online path planning method for fixed-wing UAVs based on shape mimicry according to claim 1, characterized in that, In step S1, the new no-fly zone is obtained and fitted into a circle to generate a new existing basic route, including: Acquire new no-fly zones; By fitting the minimum circumcircle of the new no-fly zone, the center point and radius of the minimum circumcircle are obtained; Obtain waypoints for existing basic routes, and also include the current location of the fixed-wing UAV as a waypoint; Based on the minimum circumcircle of the new no-fly zone, delete the waypoints in the existing basic routes that fall within the minimum circumcircle of the new no-fly zone, and combine the remaining waypoints to form new existing basic routes.

3. The online path planning method for fixed-wing UAVs based on shape mimicry according to claim 2, characterized in that, In step S2, obtaining the replanned flight segments of the new existing basic routes that fit a circle through the new no-fly zone includes: The route between any two points in the new existing basic air route is considered as a single air segment. Check in turn whether each flight segment has passed through the minimum circumcircle of the new no-fly zone; The flight segment that passes through the smallest outer circle of the new no-fly zone will be designated as a replanned flight segment.

4. The online path planning method for fixed-wing UAVs based on shape mimicry according to claim 3, characterized in that, In step S4, a new route is generated and corrected through splicing and optimization, including: Optimize the route generated in step S3: In the route generated in step S3, starting from the starting point, compare the waypoints with subsequent waypoints to see if they pass through the minimum outer circle of the new no-fly zone. If they do not pass through the minimum outer circle of the new no-fly zone, and the straight-line distance between waypoints is less than the distance of the segment before replanning and meets the turning radius requirements of the fixed-wing UAV, then delete the intermediate waypoints until the optimization is completed. The optimized route generated in step S3 is combined with the segments of the existing basic route that do not need to be replanned to form a new route. The new route is corrected to ensure that each waypoint meets the requirements, and each segment of the new route meets the requirements.

5. The online path planning method for a fixed-wing UAV based on shape mimicry according to claim 4, characterized in that, In step S4, verifying whether each waypoint in the new route meets the requirements includes: Correct whether each waypoint in the new route is within a no-fly zone; And whether each waypoint in the new route meets the waypoint flight altitude requirements.

6. The online path planning method for fixed-wing UAVs based on shape mimicry according to claim 1, characterized in that, In step S4, verifying whether each segment of the new route meets the requirements includes: Correct whether each segment of the new route meets the turning radius requirements of the fixed-wing UAV; And to correct whether each segment of the new route passes through a no-fly zone.

7. The online path planning method for fixed-wing UAVs based on shape mimicry according to claim 1, characterized in that, In step S5, determining whether the online path planning task for the fixed-wing UAV is complete includes: Based on the correction results of the new route in step S4, determine whether the online path planning task of the fixed-wing UAV is completed; if the correction results do not meet the requirements, return to step S3; otherwise, end the online path planning process of the fixed-wing UAV.

8. A computer terminal storage medium storing computer terminal executable instructions, characterized in that, The computer terminal can execute instructions for performing the online path planning method for a fixed-wing unmanned aerial vehicle based on mimicry as described in any one of claims 1-7.

9. A computing device, characterized in that, include: At least one processor; The at least one processor is also connected in communication with a memory, wherein the memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the shape-based fixed-wing UAV online path planning method as described in any one of claims 1-7.

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