UAV flight conflict risk detection method, device, electronic equipment and medium

Abstract

The present application provides a detection method, device, electronic device and medium for the risk of conflict in the flight of unmanned aerial vehicles. The detection method includes: obtaining the model of the unmanned aerial vehicle, constructing a three-dimensional space protection zone centered on the unmanned aerial vehicle; coloring the spatial grid where the unmanned aerial vehicle is located in the three-dimensional space protection zone, and coloring each protection zone according to the preset mark and the corresponding coloring value to obtain the color scale of each protection zone; detecting the largest protection zone in the spatial area as the current area, and obtaining the detection result of the current area. If the detection result indicates that there is no conflict risk in the current area, it is determined that there is no conflict risk during the flight of the unmanned aerial vehicle. The technical solution provided by the present application can avoid the technical transformation of the radar equipment, improve the applicability of the detection of the risk of conflict in the flight of unmanned aerial vehicles, and can warn of the risk of conflict such as the flight restricted area in advance through the preset mark, effectively curb the behavior of accidentally breaking into the flight restricted area, and ensure the safety of the flight restricted area.

Description

Technical Field

[0001] The present application relates to the field of drone technology, and in particular to a method, device, electronic equipment and medium for detecting the risk of drone flight conflict. Background Art

[0002] As the leading industry of the low-altitude economy, drones are continuously expanding their application industries and fields, which will bring strong impetus to the development of the low-altitude economy. However, with the widespread application of drones, compliance flight and safety issues have attracted much attention. Therefore, the algorithm that monitors the conflict risk between drones and airspace boundaries, flight restricted areas, obstacles and other aircraft during flight according to the flight trajectory of drones in real time is the key technology to solve the compliance and safety of drone flights.

[0003] At present, the main way to detect conflict risks is to install airborne radars on drones. However, this method requires adding radar equipment to the drone equipment and performing corresponding technical modifications. The application threshold is high, resulting in a small scope of application for drone flight conflict risk detection. Therefore, how to detect drone flight conflict risks has become an urgent problem to be solved. Summary of the invention

[0004] In view of this, the purpose of the present application is to provide a method, device, electronic device and medium for detecting the risk of conflict in UAV flight. The method can create a three-dimensional space protection zone, and color the spatial grid where the UAV is located in the three-dimensional space protection zone and each protection zone, so that the area formed by the spatial grid where the UAV is located and the grid where the conflict risk represented by the preset mark is located has a larger color scale, thereby determining whether the flight area has a conflict risk through the color scale, avoiding the technical transformation of adding radar equipment, improving the applicability of UAV flight conflict risk detection, and through the preset marks, early warning of conflict risks such as flight restricted areas can be given, effectively curbing the behavior of unintentionally breaking into the flight restricted area, and ensuring the safety of the flight restricted area.

[0005] This application mainly includes the following aspects:

[0006] In a first aspect, an embodiment of the present application provides a method for detecting a risk of a UAV flight conflict, the detection method comprising:

[0007] Get the model of the drone;

[0008] Based on the model of the drone, a three-dimensional space protection zone centered on the drone is constructed; wherein the three-dimensional space protection zone of the drone includes a space grid where the drone is located and a plurality of gradually increasing space protection zones centered on the space grid;

[0009] Color the spatial grid where the drone is located, and color each protected area according to the preset mark and the color value corresponding to each preset mark to obtain the color scale of each protected area;

[0010] Based on the color scale of each protected area, the largest protected area in the spatial area is used as the current area for detection to obtain the detection result of the current area. If the detection result of the current area indicates that there is no conflict risk in the current area, it is determined that there is no conflict risk during the flight of the UAV.

[0011] Furthermore, the step of constructing a three-dimensional space protection zone centered on the drone based on the model of the drone includes:

[0012] Based on the model of the drone, in a first mapping relationship between the preset model and the unit safety ceiling, determine the unit safety ceiling corresponding to the model of the drone, and in a second mapping relationship between the preset model and the unit safety moving distance, determine the unit safety moving distance corresponding to the model of the drone;

[0013] Determining the vertical space layering code of the UAV based on the unit safety ceiling corresponding to the model of the UAV;

[0014] Determining a horizontal grid level of the drone based on a unit safe movement distance corresponding to the model of the drone;

[0015] Obtain the current longitude and latitude of the drone, and determine the code of the horizontal grid of the drone based on the longitude and latitude and the horizontal grid level of the drone;

[0016] Based on the coding of the horizontal grid of the UAV and the vertical spatial layered coding of the UAV, a three-dimensional spatial protection zone centered on the UAV is obtained.

[0017] Furthermore, the step of determining the vertical space layered coding of the UAV based on the unit safety ceiling corresponding to the model of the UAV includes:

[0018] Determine the product of the unit safety ceiling corresponding to the model of the UAV and the first preset multiple as the first parameter;

[0019] In a third mapping relationship between a preset first range and an altitude level, determining a target altitude level corresponding to the preset first range where the first parameter is located;

[0020] The current altitude of the UAV is obtained, and the vertical spatial layered coding of the UAV is determined based on the target altitude level and the current altitude.

[0021] Furthermore, the step of determining the horizontal grid level of the drone based on the unit safe moving distance corresponding to the model of the drone includes:

[0022] The product of the unit safe moving distance corresponding to the model of the UAV and the second preset multiple is determined as the second parameter;

[0023] In a fourth mapping relationship between a preset second range and a horizontal grid level, determining a target horizontal grid level corresponding to the preset second range where the second parameter is located;

[0024] The target horizontal grid level is determined as the horizontal grid level of the UAV.

[0025] Furthermore, the step of determining the coding of the horizontal grid of the drone based on the longitude and latitude and the horizontal grid level of the drone includes:

[0026] Substitute the latitude and longitude and the horizontal grid level of the drone into the base grid code algorithm of the Beidou grid location code to obtain the code of the base grid where the drone is located, use the base grid as the current protection zone, and initialize the current order;

[0027] Substituting the code of the current protection zone into the protection zone algorithm of the Beidou grid location code, the code of the next-order protection zone of the UAV is obtained; wherein the code of the next-order protection zone is a set of codes corresponding to each grid adjacent to the current protection zone;

[0028] Add one to the current order to obtain a preset order, and determine whether the current order reaches the preset order;

[0029] If not, the next-order protection zone is used as the current protection zone, and the code of the current protection zone is substituted into the protection zone algorithm of the Beidou grid location code to obtain the code of the next-order protection zone of the drone;

[0030] If reached, the code of the horizontal grid of the UAV is obtained.

[0031] Furthermore, the step of performing detection on the largest protection zone in the spatial region as the current region to obtain the detection result of the current region includes:

[0032] Taking the largest protected area in the spatial region as the current region, determining whether the color level of the current region is greater than a preset color level;

[0033] If it is greater, the conflict risk in the current area is determined as the detection result of the current area;

[0034] If it is not greater than, then it is determined that there is no conflict risk in the current area as the detection result of the current area.

[0035] Furthermore, the detection method also includes:

[0036] If the detection result of the current area indicates that there is a conflict risk in the current area, the protection zone of the next spatial area of ​​the current area is updated to the current area in the order of the spatial areas from large to small to continue the detection;

[0037] Until the protected area with the smallest spatial area is traversed, if the obtained detection result still indicates that there is a conflict risk, then in the fifth mapping relationship between the preset color level and the conflict risk level, determine the target conflict risk level corresponding to the color level of the protected area with the smallest spatial area;

[0038] In a sixth mapping relationship between preset conflict risk levels and risk avoidance measures, the risk avoidance measures corresponding to the target conflict risk level are determined.

[0039] In a second aspect, an embodiment of the present application further provides a device for detecting a risk of a flight conflict between unmanned aerial vehicles, the detection device comprising:

[0040] The acquisition module is used to obtain the model of the drone;

[0041] A construction module, for constructing a three-dimensional space protection zone centered on the drone based on the model of the drone; wherein the three-dimensional space protection zone of the drone includes a space grid where the drone is located and a plurality of gradually increasing space protection zones centered on the space grid;

[0042] A coloring module is used to color the spatial grid where the drone is located, and to color each protected area according to a preset mark and a coloring value corresponding to each preset mark, so as to obtain a color scale for each protected area;

[0043] The detection module is used to detect the largest protection area in the spatial area as the current area based on the color scale of each protection area, and obtain the detection result of the current area. If the detection result of the current area indicates that there is no conflict risk in the current area, it is determined that there is no conflict risk during the flight of the UAV.

[0044] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the method for detecting the risk of drone flight conflict as described above are performed.

[0045] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method for detecting the risk of drone flight conflict as described above are executed.

[0046] The embodiments of the present application provide a method, device, electronic device and storage medium for detecting the risk of conflict in the flight of a drone. The detection method comprises: obtaining the model of the drone; based on the model of the drone, constructing a three-dimensional spatial protection zone centered on the drone; wherein the three-dimensional spatial protection zone of the drone comprises a spatial grid where the drone is located and a plurality of gradually increasing spatial protection zones centered on the spatial grid; coloring the spatial grid where the drone is located, and coloring each protection zone according to a preset mark and a coloring value corresponding to each preset mark to obtain a color scale of each protection zone; based on the color scale of each protection zone, performing detection from the protection zone with the largest spatial area as the current area to obtain a detection result of the current area; if the detection result of the current area indicates that there is no conflict risk in the current area, then determining that there is no conflict risk during the flight of the drone.

[0047] In this way, the technical solution provided by the present application can be used to create a three-dimensional space protection zone, and the space grid where the drone is located in the three-dimensional space protection zone and each protection zone can be colored, so that the area formed by the space grid where the drone is located and the grid where the conflict risk represented by the preset mark is located has a larger color scale, thereby determining whether the flight area has a conflict risk through the color scale, avoiding the need to increase the technical transformation of radar equipment, and improving the applicability of drone flight conflict risk detection. In addition, through preset marks, conflict risks such as flight restricted areas can be warned in advance, effectively curbing unintentional intrusions into flight restricted areas and ensuring the safety of flight restricted areas.

[0048] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 A flow chart of a method for detecting a risk of a UAV flight conflict provided by an embodiment of the present application is shown;

[0051] Figure 2A flowchart of a method for constructing a three-dimensional space protection zone provided in an embodiment of the present application;

[0052] Figure 3 A schematic diagram of the structure of a device for detecting the risk of a flight conflict between unmanned aerial vehicles provided in an embodiment of the present application is shown;

[0053] Figure 4 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0054] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art, under the guidance of the content of the present application, can add one or more other operations to the flowchart, or remove one or more operations from the flowchart.

[0055] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0056] In order to enable those skilled in the art to use the contents of this application, the following implementation methods are provided in combination with a specific application scenario, “Detection of UAV flight conflict risks”. For those skilled in the art, the general principles defined herein can be applied to other embodiments and application scenarios without departing from the spirit and scope of this application.

[0057] The following methods, devices, electronic devices or computer-readable storage media of the embodiments of the present application can be applied to any scenario where the risk of drone flight conflict needs to be detected. The embodiments of the present application are not limited to specific application scenarios. Any solution using a drone flight conflict risk detection method, device, electronic device and storage medium provided in the embodiments of the present application is within the protection scope of the present application.

[0058] Based on this, the present application proposes a detection method, device, electronic device and storage medium for the risk of conflict in UAV flight. The detection method includes: obtaining the model of the UAV; based on the model of the UAV, constructing a three-dimensional spatial protection zone centered on the UAV; wherein the three-dimensional spatial protection zone of the UAV includes a spatial grid where the UAV is located and a plurality of gradually increasing spatial protection zones centered on the spatial grid; coloring the spatial grid where the UAV is located, and coloring each protection zone according to a preset mark and a coloring value corresponding to each preset mark to obtain a color scale of each protection zone; based on the color scale of each protection zone, performing detection from the largest protection zone in the spatial zone as the current zone to obtain a detection result of the current zone, and if the detection result of the current zone indicates that there is no conflict risk in the current zone, then it is determined that there is no conflict risk during the flight of the UAV.

[0059] In this way, the technical solution provided by the present application can be used to create a three-dimensional space protection zone, and the space grid where the drone is located in the three-dimensional space protection zone and each protection zone can be colored, so that the area formed by the space grid where the drone is located and the grid where the conflict risk represented by the preset mark is located has a larger color scale, thereby determining whether the flight area has a conflict risk through the color scale, avoiding the need to increase the technical transformation of radar equipment, and improving the applicability of drone flight conflict risk detection. In addition, through preset marks, conflict risks such as flight restricted areas can be warned in advance, effectively curbing unintentional intrusions into flight restricted areas and ensuring the safety of flight restricted areas.

[0060] To facilitate understanding of the embodiments of the present application, a method for detecting the risk of a drone flight conflict disclosed in the embodiments of the present application is first introduced in detail.

[0061] See also Figure 1 , Figure 1 A flow chart of a method for detecting a risk of a UAV flight conflict provided in an embodiment of the present application is shown in FIG. Figure 1 As shown in , the detection methods include:

[0062] S101. Obtain the model of the drone;

[0063] In this step, there are many types of drones on the market, and it is necessary to build a three-dimensional space protection zone suitable for the type of drone according to the type of drone. The three-dimensional space protection zone is mainly constructed by gridding the three-dimensional space through spatial gridding technology. The conflict detection objects such as airspace, flight restricted areas, obstacles, etc. in the three-dimensional space can also be semi-permanently marked in the spatial grid. At the same time, all moving drones and other aircraft are dynamically marked, and finally real-time conflict detection calculations are completed through specific algorithms.

[0064] S102, based on the model of the UAV, constructing a three-dimensional space protection zone centered on the UAV;

[0065] In this step, the three-dimensional space protection zone of the UAV includes the space grid where the UAV is located and a plurality of gradually increasing space protection zones centered on the space grid.

[0066] Here, each protected area has a corresponding horizontal grid level and a three-dimensional space vertical layering, and the horizontal grid level and the three-dimensional space vertical layering decrease as the spatial area of ​​the corresponding protected area gradually increases.

[0067] As an example, the spatial gridding standard can be divided into L1~L6, 6 different horizontal grid levels with the help of Beidou grid location code (GB / T39409-2020); the altitude layer is divided into H1~H3, 3 different three-dimensional space vertical layers, and the matching relationship is L1 and L2 corresponding to H1 altitude layer, L3 and L4 corresponding to H2 altitude layer, L5 and L6 corresponding to H3 altitude layer, forming three-dimensional space grids respectively. For example, L1 corresponds to 55.66km×55.66km grid, L2 corresponds to 27.83km×18.55km grid, L3 corresponds to 1.85km×1.85km grid, L4 corresponds to 123.69m×123.69m grid, L5 corresponds to 61.84m×61.84m grid, and L6 corresponds to 7.73m×7.73m grid; H1 corresponds to 30km altitude layer, H2 corresponds to 120m altitude layer, and H3 corresponds to 30m altitude layer.

[0068] Please note that Figure 2 , Figure 2 A flowchart of a method for constructing a three-dimensional space protection zone provided in an embodiment of the present application is shown in FIG. Figure 2 As shown in the figure, based on the model of the drone, the steps of constructing a three-dimensional space protection zone centered on the drone include:

[0069] S1021. Based on the model of the drone, determine the unit safety ceiling corresponding to the model of the drone in a preset first mapping relationship between the model and the unit safety ceiling, and determine the unit safety moving distance corresponding to the model of the drone in a preset second mapping relationship between the model and the unit safety moving distance;

[0070] In this step, the first mapping relationship and the second mapping relationship can be established in advance based on experience and experimental data, and the safety ceiling per unit time of each type of drone in the first mapping relationship and its corresponding type of drone can be calculated. (i.e. unit safety ceiling), determine the corresponding model of the drone , and then according to The vertical stratification of the three-dimensional space is completed. Through the safe moving distance per unit time ρ (i.e., unit safe moving distance) of each type of drone in the second mapping relationship and its corresponding type of drone, the ρ corresponding to the type of drone is determined, and then the horizontal grid level applicable to the type of drone is determined according to ρ.

[0071] S1022, determining a vertical space hierarchical coding of the UAV based on a unit safety ceiling corresponding to the model of the UAV;

[0072] It should be noted that the steps for determining the vertical space layer coding of the UAV based on the unit safety ceiling corresponding to the UAV model include:

[0073] S10221. Determine the product of the unit safety ceiling corresponding to the model of the UAV and a first preset multiple as a first parameter;

[0074] In this step, according to the unit safety ceiling , determine which altitude layer in the vertical stratification of the three-dimensional space the drone's current altitude belongs to. When the altitude layers in the vertical stratification of the three-dimensional space are divided into three layers, the specific formula is as follows:

[0075]

[0076] in, is the first preset multiple, It can be 10, is the first parameter, It is the altitude layer to which the current UAV altitude belongs in the vertical stratification of the three-dimensional space.

[0077] S10222. Determine, in a third mapping relationship between a preset first range and an altitude level, a target altitude level corresponding to the preset first range where the first parameter is located;

[0078] In this step, the third mapping relationship has a height level corresponding to each preset first range. As an example, when the first parameter exist The target height level is H3; when the first parameter is within the preset first range, the target height level is H3; exist The target height level is H2. When the first parameter is within the preset first range, exist The target height level is H1; when the first parameter is within the preset first range, the target height level is H1; If it is not within any of the above preset first ranges, the target height level is H1.

[0079] S10223. Obtain the current altitude of the UAV, and determine the vertical spatial layered coding of the UAV based on the target altitude level and the current altitude.

[0080] In this step, the function The value range is always equal to H1, H2 or H3, and finally according to the function The result and the altitude of the drone are used to obtain the code of the base layer BS where the drone is located, that is, the code of the altitude layer where the drone is located; for example, H1 corresponds to the 30km altitude layer, H2 corresponds to the 120m altitude layer, and H3 corresponds to the 30m altitude layer. The target drone is flying at an altitude of 100m. The function result is H3, then the altitude layer where the target UAV is located is numbered (100m / 30Km) (100m / 120m) (100m / 30m) = 003. The upper and lower layer codes are calculated based on the code BS, that is, the upper layer code US is 004 and the lower layer code DS is 002. The set of the base layer code BS, the upper layer code US of BS and the lower layer code DS of BS constitutes the vertical space layered code of the UAV.

[0081] S1023, determining the horizontal grid level of the drone based on the unit safe moving distance corresponding to the model of the drone;

[0082] It should be noted that the steps of determining the horizontal grid level of a drone based on the unit safe moving distance corresponding to the model of the drone include:

[0083] S10231. Determine the product of the unit safe moving distance corresponding to the model of the UAV and the second preset multiple as the second parameter;

[0084] In this step, the horizontal grid level applicable to the UAV is determined according to the unit safe moving distance ρ. When the horizontal grid level is divided into 6 levels, the specific formula is as follows:

[0085]

[0086] in, is the second preset multiple, It can be 10, is the second parameter, The horizontal grid level applicable to the drone.

[0087] S10232. Determine, in a fourth mapping relationship between a preset second range and a horizontal grid level, a target horizontal grid level corresponding to the preset second range where the second parameter is located;

[0088] In this step, the fourth mapping relationship has a horizontal grid level corresponding to each preset second range; if there are 6 horizontal grid levels, then the function The value range is always equal to L1, L2, L3, L4, L5 or L6, and finally through the function The value of can determine the horizontal grid level applicable to the UAV.

[0089] S10233. Determine the target horizontal grid level as the horizontal grid level of the UAV.

[0090] S1024, obtaining the longitude and latitude of the current location of the drone, and determining the code of the horizontal grid of the drone based on the longitude and latitude and the horizontal grid level of the drone;

[0091] In this step, assuming that there are 6 levels of horizontal grids and the corresponding protection zone is the second order, first, based on the current longitude and latitude of the UAV and the horizontal grid level of the UAV, determine the code of the base grid where the UAV is located, and then determine the first-order protection zone of the UAV through the code of the base grid where the UAV is located. Finally, based on the first-order protection zone of the UAV, determine the second-order protection zone of the UAV, that is, obtain the code of the horizontal grid of the UAV.

[0092] It should be noted that the steps of determining the coding of the horizontal grid of the drone based on the longitude and latitude and the horizontal grid level of the drone include:

[0093] S10241, substituting the latitude and longitude and the horizontal grid level of the drone into the base grid code algorithm of the Beidou grid location code, obtaining the code of the base grid where the drone is located, taking the base grid as the current protection zone, and initializing the current order;

[0094] In this step, according to the function The applicable horizontal grid level and the horizontal position of the UAV are determined by the calculation results (longitude and latitude), determine the code of the base grid where the drone is located, e.g. = L6, the coding calculation formula of the base grid where the drone is located is as follows:

[0095]

[0096] in, The longitude and latitude of the current location of the drone; To determine the level of horizontal grid level applicable to the UAV, when = L6, then is 6; ~ It is the base grid code algorithm of Beidou grid location code (GB / T39409-2020 standard algorithm); The code for the base grid where the drone is located.

[0097] As an example, if the current latitude and longitude of the drone is 39°59′35.38″N, 116°18′45.37″N, =6, then the final calculation result, that is, the code of the base grid where the UAV is located is: N50J47539B8225.

[0098] S10242, substituting the code of the current protection zone into the protection zone algorithm of the Beidou grid location code to obtain the code of the next-order protection zone of the UAV;

[0099] In this step, the code of the next-order protection zone is the set of codes corresponding to each grid adjacent to the current protection zone. The specific formula is as follows:

[0100]

[0101] in, is the code of the first-order protected area; The protection zone algorithm for the Beidou grid location code can be calculated The code of each adjacent grid in the eight directions of the indicated base grid, namely, front, back, left, right, left front, right front, left back and right back, so is the set of eight codes.

[0102] S10243, adding one to the current order to obtain a preset order, and determining whether the current order reaches the preset order;

[0103] In this step, the horizontal grid level has a corresponding order of the protection zone, and the order is set to the preset order. When calculating the code of the base grid, the current order is initialized. Each time a code set of a protection zone is obtained, the current order is increased by one to determine whether the current order reaches the preset order. If not, continue to determine the code of the next protection zone. If it is reached, the code of the horizontal grid of the UAV is obtained.

[0104] S10244. If not, the next-order protection zone is used as the current protection zone, and the code of the current protection zone is further substituted into the protection zone algorithm of the Beidou grid location code to obtain the code of the next-order protection zone of the UAV;

[0105] As an example, if the preset order is two, the code of the first-order protection zone is obtained After that, Substituting into the protection zone algorithm of the Beidou grid location code, the formula is as follows:

[0106]

[0107] in, The input parameters are eight codes of the first-order protection zone. It is the set of codes of each grid adjacent to the periphery of the first-order protection zone, that is, the code of the second-order protection zone.

[0108] S10245. If reached, the code of the horizontal grid of the UAV is obtained.

[0109] In this step, if the preset order is two, the final coded representation of the second-order protection zone forms a 5×5 horizontal protection zone of 25 horizontal grids, i.e., a grid of the second-order protection zone centered on the base grid (the first-order protection zone includes 9 grids including the base grid and 16 grids adjacent to the first-order protection zone), and the first-order protection zone includes 9 grids including the base grid, including 1 base grid and 8 grids adjacent to the base grid (i.e., grids in eight directions).

[0110] S1025. Based on the coding of the horizontal grid of the UAV and the vertical spatial layered coding of the UAV, a three-dimensional spatial protection zone centered on the UAV is obtained.

[0111] In this step, the spatial set of the protected area is determined through the horizontal grid coding and vertical spatial layered coding of the drone. The specific formula is as follows:

[0112]

[0113] Here, if the preset order is two, then substituting the horizontal protection zone coding and the vertical space layered coding into the above formula, a three-dimensional space protection zone with 25 space grids in each layer and a total of 75 space grids can be obtained.

[0114] S103, coloring the spatial grid where the UAV is located, and coloring each protected area according to a preset mark and a coloring value corresponding to each preset mark, to obtain a color scale for each protected area;

[0115] In this step, the spatial grids are colored according to the drone protection area, and the coloring order is gradually upward. For example, the protection area contains a certain horizontal 6-level and vertical 3-level grid, namely L6H3. For example, the spatial grid code where the current drone is located is specifically N50J47539B8225-003, representing the L6H3 level grid, and then gradually upward as follows: L5H3 code is: N50J47539B82-003, L4H2 code is: N50J47539B8-00, L3H2 code is: N50J47539-00, L2H1 code is: N50J475-0, The L1H1 code is: N50J47-0; that is, start coloring from the spatial grid where the drone is located, dynamically mark the drone, and then color the first-order protection zone with the spatial grid where the drone is located as the center, and then color the second-order protection zone, and gradually expand the coloring area. Repeat the above work 25 times and remove duplicates (the spatial grid of each protection zone must be colored, so the 25 spatial grids of the second-order protection zone must be repeated 25 times. Because the protection zones are all inclusion relationships, it is necessary to remove duplicates from the repeatedly colored spatial grids to ensure that each spatial grid is colored once), and obtain the color scale of each spatial grid.

[0116] Here, different marks and corresponding coloring values ​​can be pre-set according to different conflict risks such as flight restricted areas and obstacles, and the space grids where they are located are colored according to the preset coloring values ​​to distinguish different conflict risks; for example, the space grids without conflict risks (i.e., no pre-marks and dynamic marks) are colored off-white or white, and the space grids with conflict risks are colored with the color corresponding to the preset marks. Pre-marks can be fixed obstacles, flight restricted areas and other conflict risks, and dynamic marks can be dynamic conflict risks such as other aircraft. Other aircraft mark and color the space grids where they are located to notify surrounding aircraft of their own location and avoid conflict risks.

[0117] S104. Based on the color scale of each protected area, the largest protected area in the spatial area is used as the current area for detection to obtain a detection result of the current area. If the detection result of the current area indicates that there is no conflict risk in the current area, it is determined that there is no conflict risk during the flight of the UAV.

[0118] It should be noted that the steps of performing detection from the largest protected area in the spatial area as the current area and obtaining the detection result of the current area include:

[0119] S1041, taking the largest protected area in the spatial region as the current region, and determining whether the color level of the current region is greater than a preset color level;

[0120] In this step, the largest protection zone in the spatial area is taken as the current area for detection. For example, if the second-order protection zone is the largest protection zone, then starting from the second-order protection zone, determine whether the color level of each spatial grid in the second-order protection zone is greater than the corresponding preset color level. If it is greater, it means that the second-order protection zone has a conflict risk. If not, it means that the second-order protection zone does not have a conflict risk.

[0121] S1042: If it is greater than, determining that there is a conflict risk in the current area as the detection result of the current area;

[0122] S1043: If it is not greater than, determining that there is no conflict risk in the current area as the detection result of the current area.

[0123] In step S104, the color level of the spatial grid where the drone is located is used to determine the space contained in the grid from large to small. The specific order is L1H1, L2H1, L3H2, L4H2, L5H3 to L6H3. The entire judgment process will stop when no conflict risk is found. For example, when it is determined that the L3H2 level is risk-free, the judgment process will not continue to check downward, because the judgment is performed step by step from large to small spatial areas. If there is no conflict risk in the large spatial area, it means that there will be no conflict risk in the small spatial area, and there is no need for detection.

[0124] It should be noted that the detection method also includes:

[0125] 1. If the detection result of the current area indicates that there is a conflict risk in the current area, the protection zone of the next spatial area of ​​the current area is updated to the current area in the order of the spatial areas from large to small to continue the detection;

[0126] 2. until the protected area with the smallest spatial area is traversed, if the obtained detection result still indicates that there is a conflict risk, then in the fifth mapping relationship between the preset color level and the conflict risk level, determine the target conflict risk level corresponding to the color level of the protected area with the smallest spatial area;

[0127] 3. In the sixth mapping relationship between the preset conflict risk levels and the risk avoidance measures, the risk avoidance measures corresponding to the target conflict risk level are determined.

[0128] In the above steps 1 to 3, for example, if the L6H3 spatial grid is the smallest protected area, and the color scale value of L6H3 is finally verified, and the detection result is still a risk, then the color scale level corresponding to the color scale value of the spatial grid in the smallest protected area can be determined in the fifth mapping relationship. The color scale level represents the conflict risk level, and the final result is formed. The final result is the level of conflict risk and the location indicated by the spatial grid where the conflict risk is located. According to the conflict risk level in the final result, the corresponding risk avoidance measures are determined in the sixth mapping relationship, such as adjusting the current flight speed and flight direction of the drone to avoid risks.

[0129] In summary, the detection method proposed in this embodiment adds and improves the traditional flight airspace boundary warning and alarm algorithm, and expands the monitoring objects from the airspace boundary to the flight restricted area, the ground, obstacles and other aircraft, which fills the loopholes in flight supervision from a technical level, reduces flight violations, ensures the safety of low-altitude airspace, and improves service supervision capabilities. Among them, the flight restricted area conflict detection added by preset marks advances the judgment of the drone entering the flight restricted area to the warning before the intrusion, which can effectively curb the behavior of unintentionally intruding into the flight restricted area and ensure the safety of the flight restricted area; the added conflict detection between drones and obstacles and other aircraft can timely remind drone operators to correct the flight route through early warning means to avoid flight safety accidents. This embodiment can be applied to the drone service supervision system of the regulatory department, and can also be applied to the operation management system of the competent department or operating unit of the drone industry, providing technical support for the establishment of a low-altitude economic service guarantee and operation management system platform.

[0130] An embodiment of the present application provides a method for detecting the risk of conflict in the flight of an unmanned aerial vehicle, the detection method comprising: obtaining the model of the unmanned aerial vehicle; based on the model of the unmanned aerial vehicle, constructing a three-dimensional spatial protection zone centered on the unmanned aerial vehicle; wherein the three-dimensional spatial protection zone of the unmanned aerial vehicle includes a spatial grid where the unmanned aerial vehicle is located and a plurality of gradually increasing spatial area protection zones centered on the spatial grid; coloring the spatial grid where the unmanned aerial vehicle is located, and coloring each protection zone according to a preset mark and a coloring value corresponding to each preset mark to obtain a color scale of each protection zone; based on the color scale of each protection zone, performing detection from the largest protection zone in the spatial area as the current area to obtain a detection result of the current area, and if the detection result of the current area indicates that there is no conflict risk in the current area, then determining that there is no conflict risk during the flight of the unmanned aerial vehicle.

[0131] In this way, the technical solution provided by the present application can be used to create a three-dimensional space protection zone, and the space grid where the drone is located in the three-dimensional space protection zone and each protection zone can be colored, so that the area formed by the space grid where the drone is located and the grid where the conflict risk represented by the preset mark is located has a larger color scale, thereby determining whether the flight area has a conflict risk through the color scale, avoiding the need to increase the technical transformation of radar equipment, and improving the applicability of drone flight conflict risk detection. In addition, through preset marks, conflict risks such as flight restricted areas can be warned in advance, effectively curbing unintentional intrusions into flight restricted areas and ensuring the safety of flight restricted areas.

[0132] Based on the same inventive concept, an embodiment of the present application also provides a drone flight conflict risk detection device corresponding to the above-mentioned drone flight conflict risk detection method. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0133] See also Figure 3 , Figure 3 A schematic diagram of a detection device for a risk of a UAV flight conflict provided in an embodiment of the present application is shown in FIG. Figure 3 As shown in , the detection device 310 includes:

[0134] An acquisition module 311 is used to acquire the model of the drone;

[0135] A construction module 312 is used to construct a three-dimensional space protection zone centered on the drone based on the model of the drone; wherein the three-dimensional space protection zone of the drone includes a space grid where the drone is located and a plurality of gradually increasing space protection zones centered on the space grid;

[0136] The coloring module 313 is used to color the space grid where the UAV is located, and to color each protected area according to a preset mark and a coloring value corresponding to each preset mark, so as to obtain a color scale of each protected area;

[0137] The detection module 314 is used to detect the largest protection area in the spatial area as the current area based on the color scale of each protection area, and obtain the detection result of the current area. If the detection result of the current area indicates that there is no conflict risk in the current area, it is determined that there is no conflict risk during the flight of the drone.

[0138] Optionally, when the construction module 312 is used to construct a three-dimensional space protection zone centered on the drone based on the model of the drone, the construction module 312 is specifically used to:

[0139] Based on the model of the drone, in a first mapping relationship between the preset model and the unit safety ceiling, determine the unit safety ceiling corresponding to the model of the drone, and in a second mapping relationship between the preset model and the unit safety moving distance, determine the unit safety moving distance corresponding to the model of the drone;

[0140] Determining the vertical space layering code of the UAV based on the unit safety ceiling corresponding to the model of the UAV;

[0141] Determining a horizontal grid level of the drone based on a unit safe movement distance corresponding to the model of the drone;

[0142] Obtain the current longitude and latitude of the drone, and determine the code of the horizontal grid of the drone based on the longitude and latitude and the horizontal grid level of the drone;

[0143] Based on the coding of the horizontal grid of the UAV and the vertical spatial layered coding of the UAV, a three-dimensional spatial protection zone centered on the UAV is obtained.

[0144] Optionally, when the construction module 312 is used to determine the vertical space layered coding of the UAV based on the unit safety ceiling corresponding to the model of the UAV, the construction module 312 is specifically used to:

[0145] Determine the product of the unit safety ceiling corresponding to the model of the UAV and the first preset multiple as the first parameter;

[0146] In a third mapping relationship between a preset first range and an altitude level, determining a target altitude level corresponding to the preset first range where the first parameter is located;

[0147] The current altitude of the UAV is obtained, and the vertical spatial layered coding of the UAV is determined based on the target altitude level and the current altitude.

[0148] Optionally, when the construction module 312 is used to determine the horizontal grid level of the drone based on the unit safe moving distance corresponding to the model of the drone, the construction module 312 is specifically used to:

[0149] The product of the unit safe moving distance corresponding to the model of the UAV and the second preset multiple is determined as the second parameter;

[0150] In a fourth mapping relationship between a preset second range and a horizontal grid level, determining a target horizontal grid level corresponding to the preset second range where the second parameter is located;

[0151] The target horizontal grid level is determined as the horizontal grid level of the UAV.

[0152] Optionally, when the construction module 312 is used to determine the code of the horizontal grid of the drone based on the longitude and latitude and the horizontal grid level of the drone, the construction module 312 is specifically used to:

[0153] Substitute the latitude and longitude and the horizontal grid level of the drone into the base grid code algorithm of the Beidou grid location code to obtain the code of the base grid where the drone is located, use the base grid as the current protection zone, and initialize the current order;

[0154] Substituting the code of the current protection zone into the protection zone algorithm of the Beidou grid location code, the code of the next-order protection zone of the UAV is obtained; wherein the code of the next-order protection zone is a set of codes corresponding to each grid adjacent to the current protection zone;

[0155] Add one to the current order to obtain a preset order, and determine whether the current order reaches the preset order;

[0156] If not, the next-order protection zone is used as the current protection zone, and the code of the current protection zone is substituted into the protection zone algorithm of the Beidou grid location code to obtain the code of the next-order protection zone of the drone;

[0157] If reached, the code of the horizontal grid of the UAV is obtained.

[0158] Optionally, when the detection module 314 is used to detect the largest protection area in the spatial area as the current area to obtain the detection result of the current area, the detection module 314 is specifically used to:

[0159] Taking the largest protected area in the spatial region as the current region, determining whether the color level of the current region is greater than a preset color level;

[0160] If it is greater, the conflict risk in the current area is determined as the detection result of the current area;

[0161] If it is not greater than, then it is determined that there is no conflict risk in the current area as the detection result of the current area.

[0162] Optionally, the detection module 314 is further used for:

[0163] If the detection result of the current area indicates that there is a conflict risk in the current area, the protection zone of the next spatial area of ​​the current area is updated to the current area in the order of the spatial areas from large to small to continue the detection;

[0164] Until the protected area with the smallest spatial area is traversed, if the obtained detection result still indicates that there is a conflict risk, then in the fifth mapping relationship between the preset color level and the conflict risk level, determine the target conflict risk level corresponding to the color level of the protected area with the smallest spatial area;

[0165] In a sixth mapping relationship between preset conflict risk levels and risk avoidance measures, the risk avoidance measures corresponding to the target conflict risk level are determined.

[0166] An embodiment of the present application provides a detection device for a risk of conflict in flight of a drone, the detection device comprising: an acquisition module for acquiring a model of a drone; a construction module for constructing a three-dimensional spatial protection zone centered on the drone based on the model of the drone; wherein the three-dimensional spatial protection zone of the drone comprises a spatial grid where the drone is located and a plurality of gradually increasing spatial protection zones centered on the spatial grid; a coloring module for coloring the spatial grid where the drone is located, and coloring each protection zone according to a preset mark and a coloring value corresponding to each preset mark to obtain a color scale of each protection zone; a detection module for performing detection from the largest protection zone in the spatial zone as the current zone based on the color scale of each protection zone to obtain a detection result of the current zone; if the detection result of the current zone indicates that there is no conflict risk in the current zone, it is determined that there is no conflict risk during the flight of the drone.

[0167] In this way, the technical solution provided by the present application can be used to create a three-dimensional space protection zone, and the space grid where the drone is located in the three-dimensional space protection zone and each protection zone can be colored, so that the area formed by the space grid where the drone is located and the grid where the conflict risk represented by the preset mark is located has a larger color scale, thereby determining whether the flight area has a conflict risk through the color scale, avoiding the need to increase the technical transformation of radar equipment, and improving the applicability of drone flight conflict risk detection. In addition, through preset marks, conflict risks such as flight restricted areas can be warned in advance, effectively curbing unintentional intrusions into flight restricted areas and ensuring the safety of flight restricted areas.

[0168] See also Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 4 As shown in , the electronic device 400 includes a processor 410 , a memory 420 and a bus 430 .

[0169] The memory 420 stores machine-readable instructions executable by the processor 410. When the electronic device 400 is running, the processor 410 communicates with the memory 420 via the bus 430. When the machine-readable instructions are executed by the processor 410, the above-mentioned Figure 1 to Figure 2The steps of the method for detecting the risk of UAV flight conflict in the method embodiment shown in the figure, and the specific implementation method thereof can be referred to the method embodiment, which will not be described in detail here.

[0170] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figure 1 to Figure 2 The steps of the method for detecting the risk of UAV flight conflict in the method embodiment shown in the figure, and the specific implementation method thereof can be referred to the method embodiment, which will not be described in detail here.

[0171] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0172] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0173] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0174] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0175] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0176] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for detecting the risk of UAV flight conflict, characterized in that: The detection method comprises: Get the model of the drone; Based on the model of the drone, a three-dimensional space protection zone centered on the drone is constructed; wherein the three-dimensional space protection zone of the drone includes a space grid where the drone is located and a plurality of gradually increasing space protection zones centered on the space grid; Color the spatial grid where the drone is located, and color each protected area according to the preset mark and the color value corresponding to each preset mark to obtain the color scale of each protected area; Based on the color scale of each protected area, the largest protected area in the spatial area is used as the current area for detection to obtain the detection result of the current area. If the detection result of the current area indicates that there is no conflict risk in the current area, it is determined that there is no conflict risk during the flight of the UAV; The step of performing detection from the largest protected area in the spatial area as the current area to obtain the detection result of the current area includes: Taking the largest protected area in the spatial region as the current region, determining whether the color level of the current region is greater than a preset color level; If it is greater, the conflict risk in the current area is determined as the detection result of the current area; If it is not greater than, then it is determined that there is no conflict risk in the current area as the detection result of the current area.

2. The detection method according to claim 1, characterized in that: The step of constructing a three-dimensional space protection zone centered on the drone based on the model of the drone includes: Based on the model of the drone, in a first mapping relationship between the preset model and the unit safety ceiling, determine the unit safety ceiling corresponding to the model of the drone, and in a second mapping relationship between the preset model and the unit safety moving distance, determine the unit safety moving distance corresponding to the model of the drone; Determining the vertical space layering code of the UAV based on the unit safety ceiling corresponding to the model of the UAV; Determining a horizontal grid level of the drone based on a unit safe movement distance corresponding to the model of the drone; Obtain the current longitude and latitude of the drone, and determine the code of the horizontal grid of the drone based on the longitude and latitude and the horizontal grid level of the drone; Based on the coding of the horizontal grid of the UAV and the vertical spatial layered coding of the UAV, a three-dimensional spatial protection zone centered on the UAV is obtained.

3. The detection method according to claim 2, characterized in that: The step of determining the vertical space layered coding of the UAV based on the unit safety ceiling corresponding to the model of the UAV comprises: Determine the product of the unit safety ceiling corresponding to the model of the UAV and the first preset multiple as the first parameter; In a third mapping relationship between a preset first range and an altitude level, determining a target altitude level corresponding to the preset first range where the first parameter is located; The current altitude of the UAV is obtained, and the vertical spatial layered coding of the UAV is determined based on the target altitude level and the current altitude.

4. The detection method according to claim 2, characterized in that: The step of determining the horizontal grid level of the drone based on the unit safe moving distance corresponding to the model of the drone comprises: The product of the unit safe moving distance corresponding to the model of the UAV and the second preset multiple is determined as the second parameter; In a fourth mapping relationship between a preset second range and a horizontal grid level, determining a target horizontal grid level corresponding to the preset second range where the second parameter is located; The target horizontal grid level is determined as the horizontal grid level of the UAV.

5. The detection method according to claim 2, characterized in that: The step of determining the coding of the horizontal grid of the drone based on the longitude and latitude and the horizontal grid level of the drone comprises: Substitute the latitude and longitude and the horizontal grid level of the drone into the base grid code algorithm of the Beidou grid location code to obtain the code of the base grid where the drone is located, use the base grid as the current protection zone, and initialize the current order; Substituting the code of the current protection zone into the protection zone algorithm of the Beidou grid location code, the code of the next-order protection zone of the UAV is obtained; wherein the code of the next-order protection zone is a set of codes corresponding to each grid adjacent to the current protection zone; Add one to the current order to obtain a preset order, and determine whether the current order reaches the preset order; If not, the next-order protection zone is used as the current protection zone, and the code of the current protection zone is substituted into the protection zone algorithm of the Beidou grid location code to obtain the code of the next-order protection zone of the drone; If reached, the code of the horizontal grid of the UAV is obtained.

6. The detection method according to claim 1, characterized in that: The detection method further comprises: If the detection result of the current area indicates that there is a conflict risk in the current area, the protection zone of the next spatial area of ​​the current area is updated to the current area in the order of the spatial areas from large to small to continue the detection; Until the protected area with the smallest spatial area is traversed, if the obtained detection result still indicates that there is a conflict risk, then in the fifth mapping relationship between the preset color level and the conflict risk level, determine the target conflict risk level corresponding to the color level of the protected area with the smallest spatial area; In a sixth mapping relationship between preset conflict risk levels and risk avoidance measures, the risk avoidance measures corresponding to the target conflict risk level are determined.

7. A detection device for the risk of UAV flight conflict, characterized in that: The detection device comprises: The acquisition module is used to obtain the model of the drone; A construction module, for constructing a three-dimensional space protection zone centered on the drone based on the model of the drone; wherein the three-dimensional space protection zone of the drone includes a space grid where the drone is located and a plurality of gradually increasing space protection zones centered on the space grid; A coloring module is used to color the spatial grid where the drone is located, and to color each protected area according to a preset mark and a coloring value corresponding to each preset mark, so as to obtain a color scale for each protected area; A detection module is used to detect the largest protected area in the spatial area as the current area based on the color scale of each protected area, and obtain a detection result of the current area. If the detection result of the current area indicates that there is no conflict risk in the current area, it is determined that there is no conflict risk during the flight of the UAV; When the detection module is used to detect the largest protected area in the spatial area as the current area to obtain the detection result of the current area, the detection module is specifically used to: Taking the largest protected area in the spatial region as the current region, determining whether the color level of the current region is greater than a preset color level; If it is greater, the conflict risk in the current area is determined as the detection result of the current area; If it is not greater than, then it is determined that there is no conflict risk in the current area as the detection result of the current area.

8. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the method for detecting the risk of drone flight conflict as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for detecting the risk of flight conflict between unmanned aerial vehicles as described in any one of claims 1 to 6 are executed.

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