A method, medium and device for online path planning of fixed-wing UAV cluster

Abstract

The present invention relates to the technical field of unmanned aerial vehicle path planning, and provides a method, medium and device for online path planning of a fixed-wing unmanned aerial vehicle cluster, the method comprising: S1, obtaining fixed-wing unmanned aerial vehicle cluster information, no-fly zones and electronic fences; S2, calculating the flight safety distance based on the fixed-wing unmanned aerial vehicle cluster information; S3, obtaining the flight segments that need to be planned online according to environmental changes using the flight safety distance and the no-fly zone; S4, performing online path planning on the flight segments that need to be planned online based on the flight safety distance to form a new route; S5, correcting the new route, and judging whether the online path planning task is completed according to the correction result, and adjusting the formation spacing or formation formation if it is not completed, and returning to S2. The present invention can solve the problem that the fixed-wing unmanned aerial vehicle cluster needs to complete the secondary route planning online within a limited time on the airborne end when the fixed-wing unmanned aerial vehicle cluster flies in formation in a designated airspace and there are environmental changes such as the generation of a new no-fly zone.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) path planning, and in particular to a method, medium and device for online path planning of a fixed-wing UAV cluster. Background Art

[0002] Drones are widely used in civil and military fields due to their flexible, convenient and fast operation. Path planning is an important part of the drone mission, which requires the drone to fly from the starting point to the end point along a certain path while avoiding obstacles.

[0003] Traditional fixed-wing UAV path planning methods mainly rely on pre-set waypoints and route planning algorithms. These methods are often unable to adapt to complex and changing flight environments and have limited ability to handle dynamic obstacles. In addition, traditional methods usually ignore the dynamic performance and maneuverability of UAVs and cannot perform flexible path planning for different mission requirements.

[0004] In order to overcome these challenges, some new path planning technologies have emerged in recent years, such as methods based on genetic algorithms, artificial neural networks, and reinforcement learning. These technologies take advantage of big data analysis and machine learning and can 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] When a fixed-wing UAV swarm is deployed in actual scenarios to perform specific tasks such as post-earthquake rescue, it needs to fly in a designated airspace and adaptively handle the impact of dynamic obstacles and environmental changes on the route and airway online within a limited time on the airborne end. When a fixed-wing UAV swarm flies in a designated airspace, generating a new route in real time to avoid obstacles when the environment changes is an important factor that needs to be considered, and existing methods do not respond appropriately to this factor. Summary of the invention

[0006] The present invention aims to provide a method, medium and device for online path planning of a fixed-wing UAV cluster, so as to solve the problem that the fixed-wing UAV cluster needs to complete secondary route planning online within a limited time on the airborne end when the fixed-wing UAV cluster flies in formation in a designated airspace and there are environmental changes such as the emergence of a new no-fly zone.

[0007] The present invention provides a fixed-wing UAV cluster online path planning method, comprising the following steps:

[0008] S1, obtain fixed-wing UAV cluster information, no-fly zones and electronic fences;

[0009] S2, based on the fixed-wing UAV cluster information, calculates the flight safety distance of the fixed-wing UAV cluster;

[0010] S3, based on environmental changes, uses the flight safety distance and no-fly zones of the fixed-wing UAV cluster to obtain the flight segments that need to be planned online;

[0011] S4, based on the flight safety distance of the fixed-wing UAV cluster, online path planning is performed for the flight segments that need online planning to form a new route;

[0012] S5, based on the requirements of fixed-wing UAVs and fixed-wing UAV clusters, no-fly zones and electronic fences, correct the new route, and determine whether the fixed-wing UAV cluster online path planning task is completed based on the correction results:

[0013] If the fixed-wing UAV cluster online path planning task has been completed, the fixed-wing UAV cluster online path planning process ends;

[0014] If the online path planning task of the fixed-wing UAV cluster is not completed, the formation spacing or formation of the fixed-wing UAV cluster is adjusted, and the process returns to step S2.

[0015] Furthermore, in step S1, obtaining fixed-wing UAV cluster information includes:

[0016] Get the number of fixed-wing UAVs in a fixed-wing UAV cluster, the formation and formation spacing of the fixed-wing UAV cluster;

[0017] The drone in the middle of the fixed-wing drone cluster is set as the leader, and the other drones are set as wingmen, and the location information of the leader is obtained.

[0018] Further, in step S2, based on the fixed-wing UAV cluster information, calculating the flight safety distance of the fixed-wing UAV cluster includes:

[0019] Taking the flight route of the leader in the fixed-wing UAV cluster as the main route, the distance X1 from the fixed-wing UAV farthest from the main route to the main route is calculated according to the formation and formation spacing of the fixed-wing UAV cluster;

[0020] Set the safety redundancy distance X2 of the fixed-wing UAV cluster;

[0021] Calculate the safe flight distance X=X1+X2 of the fixed-wing UAV cluster.

[0022] Furthermore, in step S3, according to environmental changes, the flight safety distance and no-fly zone of the fixed-wing UAV cluster are used to obtain the flight segments that need to be planned online, including:

[0023] Get the waypoints of the current main flight route of the leader aircraft in the fixed-wing UAV cluster, and use the current position of the leader aircraft in the fixed-wing UAV cluster as a waypoint;

[0024] Add the flight safety distance of fixed-wing drone clusters to the radius of all no-fly zones.

[0025] Check in turn whether each flight segment in the main route has passed through all no-fly zones;

[0026] The flight segments passing through the no-fly zones are considered as the flight segments that need to be planned online.

[0027] Furthermore, in step S4, based on the flight safety distance of the fixed-wing UAV cluster, online path planning is performed for the flight segments that need online planning, and the formation of a new route includes:

[0028] The first and last waypoints of the flight segment to be planned online are used as the starting and ending points. Based on the flight performance of the fixed-wing UAV itself, the improved fast random tree algorithm RRT* is used to generate the flight segment that avoids the no-fly zone.

[0029] The flight segments that avoid no-fly zones and the flight segments that do not require online planning are spliced ​​into a new route.

[0030] Furthermore, in step S5, the new route is corrected through the following four aspects:

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

[0032] Check whether each waypoint in the new route is within the electronic fence;

[0033] Correct whether each segment in the new route meets the turning radius requirements of the fixed-wing UAV;

[0034] Check whether the new route meets the minimum requirements for formation control of fixed-wing UAV clusters;

[0035] When all of the above four aspects are met, the fixed-wing UAV cluster online path planning task has been completed, and the fixed-wing UAV cluster online path planning process ends.

[0036] Further, in step S5, adjusting the formation spacing or formation of the fixed-wing UAV cluster includes:

[0037] Adjust the formation by first adjusting the formation spacing and then adjusting the formation formation;

[0038] The formation spacing of the fixed-wing UAV cluster is adjusted in each iteration. The formation spacing is reduced in turn according to the set ratio of the original formation spacing, and the new formation spacing is not less than the minimum formation spacing;

[0039] When the formation spacing of the previous iteration is the minimum formation spacing, the formation of the fixed-wing UAV cluster is adjusted. When the formation of this iteration changes, the formation spacing is reset to the original formation spacing.

[0040] Furthermore, the formation is adjusted to a horizontal straight line formation, a circular formation, a triangle formation and a vertical straight line formation.

[0041] The present invention also provides a computer terminal storage medium storing computer terminal executable instructions, wherein the computer terminal executable instructions are used to execute the above-mentioned fixed-wing UAV cluster online path planning method.

[0042] The present invention also provides a computing device, comprising:

[0043] 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, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned fixed-wing UAV cluster online path planning method.

[0044] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0045] The present invention provides an online path planning method for a fixed-wing UAV cluster, which is reasonably designed, safe and efficient, and can collaboratively and quickly solve the problem that the fixed-wing UAV cluster needs to complete secondary route planning online within a limited time on the airborne end when the fixed-wing UAV cluster flies in formation in a designated airspace and there are environmental changes such as the emergence of a new no-fly zone. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 The present invention is a flowchart of a fixed-wing UAV cluster online path planning method according to an embodiment of the present invention.

[0047] Figure 2 Schematic diagram of an existing basic route in an embodiment of the present invention.

[0048] Figure 3 Schematic diagram of flight safety distance calculation in an embodiment of the present invention.

[0049] Figure 4 It is a schematic diagram of a flight segment in an existing basic route that passes through a no-fly zone and needs to be replanned in an embodiment of the present invention.

[0050] Figure 5 The figure is a schematic diagram of generating a new route based on the improved fast random tree algorithm in an embodiment of the present invention.

[0051] Figure 6 This is a schematic diagram of the route finally generated in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0053] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] like Figure 1 As shown, this embodiment proposes an online path planning method for a fixed-wing UAV cluster, comprising the following steps:

[0055] S1, such as Figure 2 As shown, fixed-wing UAV cluster information, no-fly zones and electronic fences are obtained; wherein, obtaining fixed-wing UAV cluster information includes:

[0056] Get the number of fixed-wing UAVs in a fixed-wing UAV cluster, the formation and formation spacing of the fixed-wing UAV cluster;

[0057] The UAV in the middle of the fixed-wing UAV cluster is set as the leader, and the other UAVs are set as wingmen, and the position information of the leader is obtained, and the position information includes longitude, latitude, altitude, etc.

[0058] S2, such as Figure 3 As shown in the figure, based on the fixed-wing UAV cluster information, the flight safety distance of the fixed-wing UAV cluster is calculated:

[0059] Taking the flight route of the leader in the fixed-wing UAV cluster as the main route, the distance X1 from the fixed-wing UAV farthest from the main route to the main route is calculated according to the formation and formation spacing of the fixed-wing UAV cluster;

[0060] Set the safety redundancy distance X2 of the fixed-wing UAV cluster (set as needed, such as 50M);

[0061] Calculate the safe flight distance X=X1+X2 of the fixed-wing UAV cluster.

[0062] S3, such as Figure 4As shown, according to environmental changes (for example, if there is a new no-fly zone), the flight safety distance and no-fly zone of the fixed-wing drone cluster are used to obtain the flight segments that need to be planned online:

[0063] Get the waypoints of the current main flight route of the leader aircraft in the fixed-wing UAV cluster, and use the current position of the leader aircraft in the fixed-wing UAV cluster as a waypoint;

[0064] Add the flight safety distance of fixed-wing drone clusters to the radius of all no-fly zones.

[0065] Check in turn whether each flight segment in the main route has passed through all no-fly zones;

[0066] The flight segments passing through the no-fly zones are considered as the flight segments that need to be planned online.

[0067] S4, such as Figure 5 As shown in the figure, based on the flight safety distance of the fixed-wing UAV cluster, online path planning is performed for the flight segments that need online planning to form a new route:

[0068] The first and last waypoints of the flight segment to be planned online are used as the starting point and the ending point, and based on the flight performance of the fixed-wing UAV itself, the improved fast random tree algorithm RRT* is used to generate a flight segment that avoids the no-fly zone; wherein the improved fast random tree algorithm RRT* is a prior art and will not be described in detail here;

[0069] The flight segments that avoid no-fly zones and the flight segments that do not require online planning are spliced ​​into a new route.

[0070] S5, such as Figure 6 As shown, based on the requirements of fixed-wing UAVs and fixed-wing UAV clusters, no-fly zones and electronic fences, the new route is corrected, and the online path planning task of the fixed-wing UAV cluster is judged based on the correction results:

[0071] If the fixed-wing UAV cluster online path planning task has been completed, the fixed-wing UAV cluster online path planning process ends;

[0072] If the online path planning task of the fixed-wing UAV cluster is not completed, the formation spacing or formation of the fixed-wing UAV cluster is adjusted, and the process returns to step S2.

[0073] In this embodiment, the new route is corrected through the following four aspects, and whether the fixed-wing UAV cluster online path planning task is completed is judged according to the correction result:

[0074] Check whether each waypoint in the new route is within the no-fly zone;

[0075] Check whether each waypoint in the new route is within the electronic fence;

[0076] Correct whether each segment in the new route meets the turning radius requirements of the fixed-wing UAV;

[0077] Check whether the new route meets the minimum requirements for formation control of fixed-wing UAV clusters;

[0078] When all of the above four aspects are met, the fixed-wing UAV cluster online path planning task has been completed, and the fixed-wing UAV cluster online path planning process ends;

[0079] Otherwise, if the online path planning task of the fixed-wing UAV cluster is not completed, the formation spacing or formation of the fixed-wing UAV cluster is adjusted, and the process returns to step S2:

[0080] Adjust the formation by first adjusting the formation spacing and then adjusting the formation formation;

[0081] Each iteration adjusts the formation spacing of the fixed-wing UAV cluster. The formation spacing is reduced in sequence according to the set ratio of the original formation spacing (which can be set as needed, such as 10%), and the new formation spacing is not less than the minimum formation spacing (which can be set as needed, such as 150M).

[0082] When the formation spacing of the previous iteration is the minimum formation spacing, the formation of the fixed-wing UAV cluster is adjusted. The formation formation is adjusted according to the horizontal formation, circular formation, triangle formation, and vertical formation. When the formation formation of this iteration changes, the formation spacing is reset to the original formation spacing.

[0083] In addition, in some embodiments, a computer terminal storage medium is provided, which stores computer terminal executable instructions, and the computer terminal executable instructions are used to execute the fixed-wing UAV cluster online path planning method as described in the above 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 memories, such as memory cards, ROMs, or RAMs. Computer storage media can also be distributed on network-connected computer systems, such as application stores.

[0084] In addition, in some embodiments, a computing device is proposed, comprising: at least one processor; and a memory in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the fixed-wing UAV cluster online path planning method as described in the above embodiment. Examples of computing devices include PCs, tablet computers, smart phones, or PDAs.

[0085] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A fixed-wing UAV cluster online path planning method, characterized in that: The steps include: S1, obtain fixed-wing UAV cluster information, no-fly zones and electronic fences; S2, based on the fixed-wing UAV cluster information, calculates the flight safety distance of the fixed-wing UAV cluster; S3, based on environmental changes, uses the flight safety distance and no-fly zones of the fixed-wing UAV cluster to obtain the flight segments that need to be planned online; S4, based on the flight safety distance of the fixed-wing UAV cluster, online path planning is performed for the flight segments that need online planning to form a new route; S5, based on the requirements of fixed-wing UAVs and fixed-wing UAV clusters, no-fly zones and electronic fences, correct the new route, and determine whether the fixed-wing UAV cluster online path planning task is completed based on the correction results: If the fixed-wing UAV cluster online path planning task has been completed, the fixed-wing UAV cluster online path planning process ends; If the online path planning task of the fixed-wing UAV cluster is not completed, the formation spacing or formation of the fixed-wing UAV cluster is adjusted, and the process returns to step S2; In step S1, obtaining fixed-wing UAV cluster information includes: Get the number of fixed-wing UAVs in a fixed-wing UAV cluster, the formation and formation spacing of the fixed-wing UAV cluster; Set the drone in the middle of the fixed-wing drone cluster as the leader, and the other drones as wingmen, and obtain the location information of the leader; In step S2, based on the fixed-wing UAV cluster information, calculating the flight safety distance of the fixed-wing UAV cluster includes: Taking the flight route of the leader in the fixed-wing UAV cluster as the main route, the distance X1 from the fixed-wing UAV farthest from the main route to the main route is calculated according to the formation and formation spacing of the fixed-wing UAV cluster; Set the safety redundancy distance X2 of the fixed-wing UAV cluster; Calculate the flight safety distance X=X1+X2 of the fixed-wing UAV cluster; In step S3, according to environmental changes, the flight safety distance and no-fly zone of the fixed-wing UAV cluster are used to obtain the flight segments that need to be planned online, including: Get the waypoints of the current main flight route of the leader aircraft in the fixed-wing UAV cluster, and use the current position of the leader aircraft in the fixed-wing UAV cluster as a waypoint; Add the flight safety distance of fixed-wing drone clusters to the radius of all no-fly zones. Check in turn whether each flight segment in the main route has passed through all no-fly zones; The flight segments passing through the no-fly zones are considered to be the flight segments that need to be planned online; In step S4, based on the flight safety distance of the fixed-wing UAV cluster, online path planning is performed for the flight segments that need online planning, and the new route is formed including: The first and last waypoints of the flight segment to be planned online are used as the starting and ending points. Based on the flight performance of the fixed-wing UAV itself, the improved fast random tree algorithm RRT* is used to generate the flight segment that avoids the no-fly zone. Combine the flight segments that avoid no-fly zones and the flight segments that do not require online planning into a new route; In step S5, the new route is corrected through the following four aspects: Check whether each waypoint in the new route is within the no-fly zone; Check whether each waypoint in the new route is within the electronic fence; Correct whether each segment in the new route meets the turning radius requirements of the fixed-wing UAV; Correct whether the new route meets the minimum requirements for formation control of fixed-wing UAV clusters; When all of the above four aspects are met, the fixed-wing UAV cluster online path planning task has been completed, and the fixed-wing UAV cluster online path planning process ends.

2. The fixed-wing UAV cluster online path planning method according to claim 1 is characterized in that: In step S5, adjusting the formation spacing or formation of the fixed-wing UAV cluster includes: Adjust the formation by first adjusting the formation spacing and then adjusting the formation formation; The formation spacing of the fixed-wing UAV cluster is adjusted in each iteration. The formation spacing is reduced in turn according to the set ratio of the original formation spacing, and the new formation spacing is not less than the minimum formation spacing; When the formation spacing of the previous iteration is the minimum formation spacing, the formation of the fixed-wing UAV cluster is adjusted. When the formation of this iteration changes, the formation spacing is reset to the original formation spacing.

3. The fixed-wing UAV cluster online path planning method according to claim 2 is characterized in that: The formation is adjusted according to horizontal straight line formation, circular formation, triangle formation and vertical straight line formation.

4. A computer terminal storage medium storing computer terminal executable instructions, characterized in that: The computer terminal executable instructions are used to execute the fixed-wing UAV cluster online path planning method as described in any one of claims 1-3.

5. A computing device, characterized in that: include: 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, and the instructions are executed by the at least one processor so that the at least one processor can execute the fixed-wing UAV cluster online path planning method as described in any one of claims 1-3.

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