Unmanned aerial vehicle and helicopter operation conflict resolution method and device and storage medium

Abstract

The invention aims to provide an unmanned aerial vehicle and helicopter operation conflict resolution method and device, and a storage medium. The method comprises the following steps: constructing an operation unmanned aerial vehicle group and determining an obstacle avoidance priority of each unmanned aerial vehicle in the operation unmanned aerial vehicle group; determining a conflict resolution airspace; a conflict detection step: sequentially judging whether each unmanned aerial vehicle in the running unmanned aerial vehicle group conflicts with the target helicopter based on the obstacle avoidance priority, and determining the unmanned aerial vehicles in a conflict state; a release step: setting the target helicopter as an obstacle, and sequentially performing path planning on the unmanned aerial vehicles in the conflict state according to the obstacle avoidance priorities of the unmanned aerial vehicles in the conflict state; and setting a time interval, re-determining the related information of the running unmanned aerial vehicle group and the related information of the target helicopter, and repeating the conflict detection step and the release step until all the running unmanned aerial vehicles leave the conflict release airspace. Calculation is simple and fast, and important technical support is provided for unmanned aerial vehicle conflict solution.

Description

Technical Field

[0001] The present application relates to the field of UAV technology, and in particular to a method, device and storage medium for resolving operational conflicts between UAVs and helicopters. Background Art

[0002] With the development of vertical take-off and landing aircraft manufacturing technology and low-altitude logistics industry, drones and helicopters as new means of urban air transportation have gradually become an important way to relieve the pressure of ground transportation. The light weight and strong maneuverability of drones make them play an important role in the "last mile" of logistics transportation. As the scale of drone operations gradually increases, it also brings huge challenges to the flight safety of existing helicopters in cities.

[0003] There are many people in urban areas and the airspace conditions are complex. As the number of drones increases, the safety of urban air traffic operations is gradually threatened. At the same time, as the scale of urban air traffic operations gradually increases, human-involved control cannot meet the future needs of efficient operation. With the development of artificial intelligence technology, the development of autonomous conflict identification and resolution technology between drones and helicopters is an important means to achieve coordinated management of urban air traffic and improve the autonomous operation of urban air traffic. In the existing methods, drone swarms cannot adaptively select flight paths according to the position of helicopters, and are prone to collisions with helicopters. Human control is also required, and the path selection is inappropriate. Drones and helicopters cannot be operated efficiently at the same time in the same airspace. Summary of the invention

[0004] One purpose of the present application is to provide a method, device and storage medium for resolving conflicts between the operations of drones and helicopters, so as to solve the problems in the prior art that a drone swarm cannot adaptively select a flight path according to the position of a helicopter, is prone to collision with a helicopter, and cannot efficiently operate drones and helicopters simultaneously in the same airspace.

[0005] According to one aspect of the present application, a method for resolving conflicts between a drone and a helicopter is provided, the method comprising: Build a swarm of operating drones and determine the obstacle avoidance priority of each drone in the swarm; Determine the conflict resolution airspace, obtain relevant information about the drone group operating in the conflict resolution airspace at the same time and relevant information about the target helicopter that needs to be avoided; Perform conflict detection steps: based on the obstacle avoidance priority, determine whether each drone in the running drone group conflicts with the target helicopter according to the relevant information of the running drone group and the relevant information of the target helicopter, and determine the drones in conflict; Perform the release step: set the target helicopter as an obstacle, and plan the paths of the UAVs in conflict according to their obstacle avoidance priorities; A time interval is set, relevant information of the operating drone group and relevant information of the target helicopter are re-determined, and the conflict detection step and the conflict resolution step are repeated until all operating drones leave the conflict resolution airspace.

[0006] Optionally, judging whether each drone in the running drone group conflicts with the target helicopter based on the obstacle avoidance priority in turn according to the relevant information of the running drone group and the relevant information of the target helicopter includes: Determine the critical angle and the top angle of the space speed obstacle cone when each UAV in the UAV group will collide with the target helicopter according to the relevant information of the operating UAV group and the relevant information of the target helicopter; Based on the obstacle avoidance priority, it is determined in turn whether the spatial speed obstacle cone vertex angle between the running UAV and the target helicopter is greater than the corresponding critical angle. If not, it is determined that the running UAV and the target helicopter will collide.

[0007] Optionally, determining the critical angle and the top angle of the space speed obstacle cone when each drone in the drone group will collide with the target helicopter according to the relevant information of the running unmanned cluster and the relevant information of the target helicopter, including: Determine the critical angle at which each drone will collide with the target helicopter based on the position of the operating drone group and the position of the target helicopter; Determine the relative speed and relative displacement between each UAV and the helicopter according to the position and speed of the operating UAV group and the position and speed of the target helicopter; The space velocity obstacle cone vertex angle formed between each UAV and the target helicopter is determined according to the relative speed and relative displacement.

[0008] Optionally, determining a critical angle at which each drone will collide with the target helicopter according to the position of the operating drone group and the position of the target helicopter includes: Determine the radiation radius of each drone in the operating drone group and the radiation radius of the target helicopter; Determine the relative distance between each UAV and the target helicopter based on the position of the operating UAV group and the position of the target helicopter; The critical angle at which each UAV will collide with the target helicopter is determined according to the radiation radius of each UAV, the radiation radius of the target helicopter and the relative distance.

[0009] Optionally, the critical angle satisfies the following formula: ,in, is the critical angle, , R1 is the radiation radius of the UAV, R2 is the radiation radius of the target helicopter, and D is the relative distance between the UAV and the target helicopter.

[0010] Optionally, the space velocity barrier cone vertex angle satisfies the following formula: , in, is the space velocity obstacle cone apex angle, represents the relative speed between the UAV and the target helicopter, Indicates the position of the drone at any time. Indicates the position of the target helicopter at any time.

[0011] Optionally, path planning is performed for the UAVs in conflict within the conflict resolution airspace in sequence according to the obstacle avoidance priorities of the UAVs in conflict, including: Obtain the obstacle avoidance priority of the UAVs in conflict state, and use the A-star algorithm to plan the paths of the UAVs in conflict state in the conflict resolution airspace.

[0012] Optionally, the conflict resolution airspace includes a square structured airspace, and the A-star algorithm includes the following steps: Step 1: rasterize the square structured airspace, and define the total cost function according to the actual cost between the current node and the starting point and the estimated cost between the current node and the target node; Step 2, construct an unsearched node list and a searched node list, load the starting point into the unsearched node list, and the searched node list is initially empty; Step 3, traverse the grid nodes around the starting point coordinates, calculate the actual cost from the starting point to the target node, and the estimated cost from the target node to the end point; determine whether there is a node in the unsearched node list based on the calculation results. If not, the conflict resolution fails. If so, continue to determine whether the current node in the unsearched node list is the end point. If so, return the path of the drone; Step 4, traverse the adjacent nodes of the current node, determine whether the adjacent nodes are in the searched node list, if not, update the available adjacent nodes around the current node and put the available adjacent nodes into the unsearched node list, if yes, calculate the corresponding total cost, compare the calculated total cost with the total cost corresponding to the current node, if better, replace it, and replace the total cost function; Step 5, return to step 3 to continue processing the adjacent points of the points around the current node until it extends to the target node or the searched node list is empty. When the searched node list is not empty, return to step 3 and connect the nodes in the searched node list in sequence to generate a new path for the drone.

[0013] According to another aspect of the present application, a device for resolving conflicts between a drone and a helicopter is provided, the device comprising: one or more processors; and A memory storing computer readable instructions, which, when executed, cause the processor to perform the operations of the method as described above.

[0014] According to another aspect of the present application, a computer-readable medium is provided, on which computer-readable instructions are stored. The computer-readable instructions can be executed by a processor to implement the method described above.

[0015] Compared with the prior art, the present application constructs a group of running drones and determines the obstacle avoidance priority of each drone in the group; determines the conflict relief airspace, obtains the relevant information of the group of running drones at the same time in the conflict relief airspace and the relevant information of the target helicopter to be avoided; performs a conflict detection step: based on the obstacle avoidance priority, judges whether each drone in the group of running drones conflicts with the target helicopter in turn according to the relevant information of the group of running drones and the relevant information of the target helicopter, and determines the drone in the conflict state; performs a relief step: sets the target helicopter as an obstacle, and plans the path of the drone in the conflict state in turn according to the obstacle avoidance priority of the drone in the conflict state; sets a time interval, re-determines the relevant information of the group of running drones and the relevant information of the target helicopter, and repeats the conflict detection step and relief step until all running drones leave the conflict relief airspace. Thus, the drone group can adaptively select the flight path according to the position of the helicopter to avoid collision with the helicopter, and the calculation is simple and fast, providing important technical support for the resolution of drone conflicts. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings: Figure 1 A schematic flow chart of a method for resolving conflicts between a UAV and a helicopter according to one aspect of the present application is shown; Figure 2 A flow chart of a method for resolving conflicts between drones and helicopters in an urban scenario in one embodiment of the present application is shown; Figure 3 A schematic diagram showing key parameters of the speed obstacle method during the operation of a UAV and a target helicopter in one embodiment of the present application is shown; Figure 4 A schematic diagram showing a predetermined route of a single UAV in one embodiment of the present application is shown; Figure 5A schematic diagram showing a drone path regenerated by a single drone for conflict resolution between a target helicopter and an obstacle in one embodiment of the present application.

[0017] The same or similar reference numerals in the drawings represent the same or similar components. DETAILED DESCRIPTION

[0018] The present application is described in further detail below in conjunction with the accompanying drawings.

[0019] In a typical configuration of the present application, the terminal, the device of the service network and the trusted party all include one or more processors (eg, a central processing unit (CPU)), an input / output interface, a network interface and a memory.

[0020] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0021] Computer readable media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, Phase-Change RAM (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of random access memory (RAM), Read-Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Flash memory or other memory technology, Compact Disc Read-Only Memory (CD-ROM), Digital Versatile Disk (DVD) or other optical storage, cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. According to the definition in this article, computer-readable media does not include non-transitory media such as modulated data signals and carrier waves.

[0022] Figure 1 A schematic flow chart of a method for resolving conflicts between a UAV and a helicopter according to one aspect of the present application is shown. The method comprises: steps S11 to S15, wherein: Step S11, constructing a group of running drones and determining the obstacle avoidance priority of each drone in the group of running drones; Here, the method described in this application can be used to solve the problem of conflict detection and resolution between drones and helicopters in urban scenes. First, the initialization module is performed to construct a group of running drones UAVs and the obstacle avoidance priority is ,in, Indicates the obstacle avoidance priority of the nth drone in the drone group. Then, the obstacle avoidance priority is used to detect conflicts between all drones in the drone group and helicopters and to free the drones that may conflict.

[0023] Step S12, determine the conflict resolution airspace, obtain relevant information of the drone group operating at the same time in the conflict resolution airspace and relevant information of the target helicopter to be avoided; here, set the conflict resolution airspace The conflict resolution airspace is an area within a certain space range, that is, a space that is not occupied by obstacles and maneuvers within this airspace will not increase the probability of conflict with helicopters. In the embodiment of the present application, a square structured airspace with a side length of 100 meters is set as the test area, that is, as the conflict resolution airspace ; The relevant information of the drone group includes the initial position and initial speed of the drone group, and the relevant information of the target helicopter includes the initial position and initial speed. Set the initial position of the drone group to And the initial velocity is , and the initial position of the target helicopter to be avoided is And the initial velocity is .

[0024] Step S13, a conflict detection step is performed: based on the obstacle avoidance priority, it is determined in turn according to the relevant information of the running drone group and the relevant information of the target helicopter whether each drone in the running drone group conflicts with the target helicopter, and the drone in a conflict state is determined; here, conflict detection is performed, and based on the obstacle avoidance priority, it is determined in turn whether each drone in the drone group conflicts with the target helicopter. The judgment is made based on the acquired relevant information of the drone group and the relevant information of the target helicopter, specifically, it is determined based on the position and speed of each drone in the drone group and the position and speed of the target helicopter whether a conflict will occur between the drone and the target helicopter.

[0025] Step S14, a release step is performed: the target helicopter is set as an obstacle, and paths are planned for the UAVs in conflict according to the obstacle avoidance priorities of the UAVs in conflict; here, when there are UAVs in the UAV group that will conflict with the target helicopter, that is, there are UAVs in conflict, the target helicopter is set as an obstacle, obstacle avoidance is performed on these UAVs in conflict, and new paths are planned for the UAVs in conflict in order according to the obstacle avoidance priorities to avoid the target helicopter.

[0026] Step S15, set a time interval, re-determine the relevant information of the running drone group and the relevant information of the target helicopter, repeat the conflict detection step and the conflict resolution step until all running drones leave the conflict resolution airspace. Here, set a time interval T, update the relevant information of the drone group and the relevant information of the target helicopter, and use the positioning device to update the position L of the drone group and the position of the target helicopter. , and the speed of the drone group at this time If there are still UAVs in the conflict resolution fixed airspace, the conflict detection step of step S13 and the conflict resolution step of step S14 are returned until all UAVs leave the conflict resolution airspace. The time interval is set to perform conflict detection on the positions of UAVs and helicopters at regular intervals, such as once every 10 seconds or once every 5 seconds.

[0027] Figure 2 A flow chart of a method for resolving conflicts between drones and helicopters in an urban scenario in one embodiment of the present application is shown, including: inputting into the system the obstacle avoidance priority, initial position, initial speed of the drone swarm, and the initial position, initial speed and other related information of the helicopter; judging in turn whether a conflict occurs between the drones and helicopters according to the priority order using the speed obstacle method; setting the helicopter as an obstacle to plan the path of the drone swarm in turn according to the conflict detection result and the priority order; setting a time interval, obtaining the positions of the drones and helicopters using the positioning system, and repeating the above steps of detecting and resolving conflicts between the drones.

[0028] In some embodiments of the present application, in step S13, the critical angle and the space speed obstacle cone vertex angle when each drone in the running drone group and the target helicopter will collide are determined according to the relevant information of the running drone cluster and the relevant information of the target helicopter; based on the obstacle avoidance priority, it is judged in turn whether the space speed obstacle cone vertex angle between the running drone and the target helicopter is greater than the corresponding critical angle, if not, it is determined that the running drone and the target helicopter will collide. Here, the relevant information of the running drone cluster includes the speed and position of each drone in the cluster at any time, and the relevant information of the target helicopter includes the speed and position of the target helicopter at any time, and then the space speed obstacle cone vertex angle and the critical angle when the conflict occurs between each drone and the target helicopter corresponding to the same time are calculated, and the space speed obstacle angle and the corresponding critical angle between the drone and the target helicopter are compared in order according to the obstacle avoidance priority. When the space speed obstacle angle is greater than the critical angle, it means that the target helicopter is not a threat to the drone, and when it is less than the critical angle, the target helicopter is a threat to the drone, and it is necessary to plan the path of the drone to resolve the conflict.

[0029] In the above embodiment, the critical angle when each drone and the target helicopter collide is determined according to the position of the running drone group and the position of the target helicopter; the relative speed and relative displacement between each drone and the helicopter are determined according to the position and speed of the running drone group and the position and speed of the target helicopter; the space speed obstacle cone vertex angle formed between each drone and the target helicopter is determined according to the relative speed and relative displacement. Here, when calculating the critical angle, the position of the running drone group at any time and the position of the target helicopter at the same time are obtained, and then the relative position between the drone and the target helicopter is calculated, and then the critical angle between the drone and the target helicopter can be obtained by combining the radiation radius of the drone and the target helicopter. And according to the speed and position in the relevant information of the drone and the speed and position in the relevant information of the target helicopter, the relative speed and relative displacement between the drone and the target helicopter can be calculated, and then the space speed obstacle cone vertex angle is calculated; wherein, the space speed obstacle cone vertex angle is the angle between the relative displacement vector and the relative speed vector between the target helicopter and the drone.

[0030] Specifically, when calculating the critical angle, the radiation radius of each drone in the operating drone group and the radiation radius of the target helicopter are determined; the relative distance between each drone and the target helicopter is determined according to the position of the operating drone group and the position of the target helicopter; the critical angle when each drone and the target helicopter collide is determined according to the radiation radius of each drone, the radiation radius of the target helicopter and the relative distance. The critical angle satisfies the following formula: ,in, is the critical angle, , R1 is the radiation radius of the UAV, R2 is the radiation radius of the target helicopter, and D is the relative distance between the UAV and the target helicopter.

[0031] Set the horizontal length of one side of the drone to , then the maximum horizontal size is The radius of the circumscribed sphere is , that is, the radiation radius of the drone is , set the horizontal dimension length of one side of the target helicopter to , the maximum horizontal size of the target helicopter is The radius of the circumscribed sphere is , that is, the radiation radius of the target helicopter is . For the UAV and the target helicopter, the speed at any time is and , the positions of the UAV and the target helicopter at any time are and , then the speed of the drone is: ; in, is the angle formed by the drone speed and the xy plane, It is the angle between the UAV speed and the x-axis after being projected onto the xy plane.

[0032] The speed of the target helicopter is: ; set up It is the combined radiation radius of the target helicopter and the UAV, that is, the conflict area of ​​the UAV is transferred to the target helicopter to form a comprehensive protection area. Once the protection area is breached, a conflict will occur.

[0033] Relative speed of drone and helicopter , ; The distance between the drone and the helicopter is for: , Calculate the critical angle : , that is, it takes into account the relative position vector of the UAV and the manned aircraft and the angle formed by the UAV and the outer tangent of the comprehensive radiation radius, representing an indicator of the area that needs to be avoided for UAV conflict resolution.

[0034] Figure 3 The key parameter diagram of the speed obstacle method during the operation of the UAV and the target helicopter is shown in the figure. The radiation radius of the UAV R1 and the radiation radius of the target helicopter R2 are converted into a combined obstacle area with the target helicopter as the theme. The calculation method is: ; The cone area is the obstacle space of the current relative position of the target helicopter and the UAV. By comparing this space with the relative speed between the target helicopter and the UAV, it is possible to determine whether there is a conflict risk in the current operation state; the current speed of the UAV and the helicopter is and , is the relative speed between the UAV and the target helicopter.

[0035] Continuing with the above embodiment, the space velocity barrier cone vertex angle satisfies the following formula: , in, is the space velocity obstacle cone apex angle, represents the relative speed between the UAV and the target helicopter, Indicates the position of the drone at any time. Indicates the position of the target helicopter at any time.

[0036] like , then the helicopter poses no threat to the drone. , then the helicopter poses a threat to the drone, and it is necessary to plan the path for the drone to resolve the conflict.

[0037] In some embodiments of the present application, in step S14, the obstacle avoidance priority of the UAV in the conflict state is obtained, and the A-star algorithm is used in turn to plan the path of the UAV in the conflict state in the conflict resolution airspace. Here, according to the obstacle avoidance priority order, the speed obstacle method is used to determine whether the UAV and the target helicopter conflict in turn, and then according to the conflict detection result and the obstacle avoidance priority order, the target helicopter is set as an obstacle to plan the path of the UAV group in turn. For the UAV in the conflict state, the A-star algorithm can be used for path planning, and the following steps are performed to resolve the conflict: The conflict resolution airspace includes a square structured airspace, and the A-star algorithm includes the following steps: Step 1: Rasterize the square structured airspace and define the total cost function based on the actual cost between the current node and the starting point and the estimated cost between the current node and the target node. The side length of each cube in the rasterized airspace is 1 meter, and the starting point coordinates of the current conflict resolution drone are , define the total cost function for: , In the formula, For the current node The actual cost of the starting point, The distance between the current node and the target node The estimated cost of , ; Step 2: Build an unsearched node list (open list) and a searched node list (close list), load the starting point into the unsearched node list, and the searched node list is initially empty; Step 3, traverse the grid nodes around the starting point coordinates, calculate the actual cost from the starting point to the target node, and the estimated cost from the target node to the end point respectively; determine whether there is a node in the unsearched node list based on the calculation results, specifically put the target node into the unsearched node list, remove the node corresponding to the minimum value of the sum of the actual cost and the estimated cost in the unsearched node list, and move it into the searched node list. If there is no node in the unsearched node list, the conflict resolution fails. If the current node in the unsearched node list is the end point, return the path; Step 4, traverse the adjacent nodes of the current node, ignoring the nodes in the searched node list and the nodes occupied by obstacles, and determine whether the adjacent nodes are in the searched node list. If not, update the available adjacent nodes around the current node and put the available adjacent nodes into the unsearched node list. If yes, calculate the corresponding total cost, compare the calculated total cost with the total cost corresponding to the current node, and replace it if it is better, and replace the total cost function; Step 5, return to step 3 to continue processing the adjacent points of the points around the current node until it extends to the target node or the searched node list is empty. When the searched node list is not empty, return to step 3 and connect the nodes in the searched node list in sequence to generate a new path for the drone.

[0038] Figure 4 The figure shows a schematic diagram of the planned route of a single drone. Figure 5 Schematic diagram of the regenerated drone path for a single drone to resolve the conflict between the target helicopter and obstacles; the black obstacles are ground building obstacles. Since the target helicopter and the drone are operating in the same airspace, the drone track is changed through collision detection and the A-star algorithm.

[0039] The method described in this application constructs a conflict detection and resolution model for drones and helicopters based on the speed barrier method combined with the A-star algorithm. By analyzing the speed trend of the drone group, the drones that need to be resolved from the conflict are judged, and then they are resolved in sequence according to priority, thereby achieving conflict resolution between drones and helicopters. The calculation is simple and fast, providing technical support for the intelligent operation of urban air traffic.

[0040] In addition, an embodiment of the present application also provides a computer-readable medium on which computer-readable instructions are stored. The computer-readable instructions can be executed by a processor to implement the aforementioned method for resolving conflicts between drones and helicopters.

[0041] In one embodiment of the present application, a device for resolving conflicts between a drone and a helicopter is also provided, the device comprising: one or more processors; and A memory storing computer readable instructions, which, when executed, cause the processor to perform the operations of the method as described above.

[0042] For example, the computer readable instructions, when executed, cause the one or more processors to: Build a swarm of operating drones and determine the obstacle avoidance priority of each drone in the swarm; Determine the conflict resolution airspace, obtain relevant information about the drone group operating in the conflict resolution airspace at the same time and relevant information about the target helicopter that needs to be avoided; Perform conflict detection steps: based on the obstacle avoidance priority, determine whether each drone in the running drone group conflicts with the target helicopter according to the relevant information of the running drone group and the relevant information of the target helicopter, and determine the drones in conflict; Perform the release step: set the target helicopter as an obstacle, and plan the paths of the UAVs in conflict according to their obstacle avoidance priorities; A time interval is set, relevant information of the operating drone group and relevant information of the target helicopter are re-determined, and the conflict detection step and the conflict resolution step are repeated until all operating drones leave the conflict resolution airspace.

[0043] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

[0044] It should be noted that the present application can be implemented in software and / or a combination of software and hardware, for example, it can be implemented using an application-specific integrated circuit (ASIC), a general-purpose computer or any other similar hardware device. In one embodiment, the software program of the present application can be executed by a processor to implement the steps or functions described above. Similarly, the software program of the present application (including related data structures) can be stored in a computer-readable recording medium, for example, a RAM memory, a magnetic or optical drive or a floppy disk and the like. In addition, some steps or functions of the present application can be implemented using hardware, for example, as a circuit that cooperates with a processor to perform various steps or functions.

[0045] In addition, a part of the present application may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present application through the operation of the computer. The program instruction for calling the method of the present application may be stored in a fixed or removable recording medium, and / or transmitted through a data stream in a broadcast or other signal-bearing medium, and / or stored in a working memory of a computer device that runs according to the program instruction. Here, according to an embodiment of the present application, a device is included, the device including a memory for storing computer program instructions and a processor for executing program instructions, wherein, when the computer program instruction is executed by the processor, the device is triggered to run the method and / or technical solution based on the aforementioned multiple embodiments according to the present application.

[0046] It is obvious to those skilled in the art that the present application is not limited to the details of the exemplary embodiments described above, and that the present application can be implemented in other specific forms without departing from the spirit or essential features of the present application. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present application is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present application. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural.

Claims

1. A method for resolving conflicts between unmanned aerial vehicles and helicopters, characterized in that: The method comprises: Build a swarm of operating drones and determine the obstacle avoidance priority of each drone in the swarm; Determine the conflict resolution airspace, obtain relevant information about the drone group operating in the conflict resolution airspace at the same time and relevant information about the target helicopter that needs to be avoided; Perform conflict detection steps: based on the obstacle avoidance priority, determine whether each drone in the running drone group conflicts with the target helicopter according to the relevant information of the running drone group and the relevant information of the target helicopter, and determine the drones in conflict; Perform the release step: set the target helicopter as an obstacle, and plan the paths of the UAVs in conflict according to their obstacle avoidance priorities; A time interval is set, and relevant information of the operating drone group and relevant information of the target helicopter are re-determined, and the conflict detection step and the conflict resolution step are repeated until all the operating drones leave the conflict resolution airspace.

2. The method according to claim 1, characterized in that Based on the obstacle avoidance priority, it is determined whether each drone in the running drone group conflicts with the target helicopter according to the relevant information of the running drone group and the relevant information of the target helicopter, including: Determine the critical angle and the top angle of the space speed obstacle cone when each UAV in the UAV group will collide with the target helicopter according to the relevant information of the operating UAV group and the relevant information of the target helicopter; Based on the obstacle avoidance priority, it is determined in turn whether the spatial speed obstacle cone vertex angle between the running UAV and the target helicopter is greater than the corresponding critical angle. If not, it is determined that the running UAV and the target helicopter will collide.

3. The method according to claim 2, characterized in that According to the relevant information of the operating unmanned swarm and the relevant information of the target helicopter, the critical angle and the top angle of the space speed obstacle cone when each UAV in the operating UAV swarm will collide with the target helicopter are determined, including: Determine the critical angle at which each drone will collide with the target helicopter based on the position of the operating drone group and the position of the target helicopter; Determine the relative speed and relative displacement between each UAV and the helicopter according to the position and speed of the operating UAV group and the position and speed of the target helicopter; The space velocity obstacle cone vertex angle formed between each UAV and the target helicopter is determined according to the relative speed and relative displacement.

4. The method according to claim 3, characterized in that The critical angle at which each UAV will collide with the target helicopter is determined based on the position of the UAV group and the position of the target helicopter, including: Determine the radiation radius of each drone in the operating drone group and the radiation radius of the target helicopter; Determine the relative distance between each UAV and the target helicopter based on the position of the operating UAV group and the position of the target helicopter; The critical angle at which each UAV will collide with the target helicopter is determined according to the radiation radius of each UAV, the radiation radius of the target helicopter and the relative distance.

5. The method according to claim 4, characterized in that The critical angle satisfies the following formula: ， in, is the critical angle, , R1 is the radiation radius of the UAV, R2 is the radiation radius of the target helicopter, and D is the relative distance between the UAV and the target helicopter.

6. The method according to claim 3, characterized in that The space velocity obstacle cone vertex angle satisfies the following formula: ， in, is the space velocity obstacle cone apex angle, represents the relative speed between the UAV and the target helicopter, represents the position of the drone at any time. Indicates the position of the target helicopter at any time.

7. The method according to claim 1, characterized in that According to the obstacle avoidance priority of the UAVs in conflict, the paths of the UAVs in conflict resolution airspace are planned in turn, including: Obtain the obstacle avoidance priority of the UAVs in conflict state, and use the A-star algorithm to plan the paths of the UAVs in conflict state in the conflict resolution airspace.

8. The method according to claim 7, characterized in that The conflict resolution airspace includes a square structured airspace, and the A-star algorithm includes the following steps: Step 1: rasterize the square structured airspace, and define the total cost function according to the actual cost between the current node and the starting point and the estimated cost between the current node and the target node; Step 2, construct an unsearched node list and a searched node list, load the starting point into the unsearched node list, and the searched node list is initially empty; Step 3, traverse the grid nodes around the starting point coordinates, calculate the actual cost from the starting point to the target node, and the estimated cost from the target node to the end point; determine whether there is a node in the unsearched node list based on the calculation results. If not, the conflict resolution fails. If so, continue to determine whether the current node in the unsearched node list is the end point. If so, return the path of the drone; Step 4, traverse the adjacent nodes of the current node, determine whether the adjacent nodes are in the searched node list, if not, update the available adjacent nodes around the current node and put the available adjacent nodes into the unsearched node list, if yes, calculate the corresponding total cost, compare the calculated total cost with the total cost corresponding to the current node, if better, replace it, and replace the total cost function; Step 5, return to step 3 to continue processing the adjacent points of the points around the current node until it extends to the target node or the searched node list is empty. When the searched node list is not empty, return to step 3 and connect the nodes in the searched node list in sequence to generate a new path for the drone.

9. A device for resolving conflicts between UAV and helicopter, characterized in that: The device comprises: one or more processors; and A memory storing computer readable instructions which, when executed, cause the processor to perform the operations of the method as claimed in any one of claims 1 to 8.

10. A computer-readable medium having computer-readable instructions stored thereon, wherein the computer-readable instructions can be executed by a processor to implement the method according to any one of claims 1 to 8.

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