A low altitude fusion management platform and method thereof

Abstract

The invention discloses a low-altitude fusion management platform and a method thereof, belonging to the technical field of low-altitude management. The invention selects drones that meet the requirements of receiving the tasks to be performed as preferred drones based on real-time fusion data, and then calculates the flight risk value and efficiency value of the corresponding preferred drones going to the execution location of the tasks to be performed, fully considering the flight risk and arrival efficiency of the drones going to the new tasks, achieving an optimized scheduling strategy, and ensuring that the drones scheduled to perform the tasks to be performed have sufficient safety and efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of low-altitude management, and in particular to a low-altitude fusion management platform and a method thereof. Background Art

[0002] Low-altitude management platforms play a vital role in the scheduling and allocation of flight missions for drones.

[0003] When scheduling and allocating flight missions for drones, low-altitude management platforms in the existing technology usually schedule drones to perform new flight missions based on the drone status. They do not consider evaluating the risks of drones going to perform flight missions through multiple data sources, nor do they evaluate the efficiency of the scheduled drones going to perform flight missions. Therefore, the safety and efficiency of the scheduled drones going to perform flight missions cannot be guaranteed.

[0004] Therefore, in order to solve the technical problems existing in the prior art, the present invention provides a low-altitude fusion management platform and method thereof. Summary of the invention

[0005] In order to solve the technical problems existing in the prior art, the present invention provides a low-altitude fusion management platform, including:

[0006] The data acquisition module is used to acquire the task data of the tasks to be executed and the tasks currently being executed, and is provided with a UAV communication interface, an ATC communication interface and a GIS communication interface; the UAV communication interface is used to acquire UAV data; the ATC communication interface is used to acquire airspace data; and the GIS communication interface acquires building data;

[0007] A data fusion module is used to fuse the drone data, airspace data and building data using a Kalman filter algorithm to obtain real-time fused data, wherein the real-time fused data represents the drone data currently corresponding to each drone, the task data corresponding to the currently executed task, and the airspace data and building data of the current airspace;

[0008] The scheduling control module includes: a VP relationship establishment module, a screening module, a risk value calculation module, an efficiency value calculation module and an execution module;

[0009] The VP relationship establishment module is used to establish a mapping relationship between the flight speed V and the power consumption rate P of the drone;

[0010] The screening module is used to select a UAV that meets the requirements of receiving the task to be performed as a preferred UAV according to the real-time fusion data;

[0011] The risk value calculation module is used to calculate the flight risk value F of each preferred UAV to the execution location of the task to be executed according to the real-time fusion data;

[0012] The efficiency value calculation module is used to calculate the efficiency value X of each preferred UAV reaching the execution position of the task to be executed according to the real-time fusion data;

[0013] The execution module is used to calculate the corresponding scheduling fitness value Fit according to the flight risk value and efficiency value of each preferred UAV, and select the best preferred UAV to execute the task to be executed according to the scheduling fitness value.

[0014] Furthermore, the task data includes: execution location and estimated power consumption; the drone data includes real-time location, real-time power and progress percentage of the current task; the airspace data includes the maximum flight altitude of the drone in each low-altitude airspace; the building data includes building location and building height.

[0015] Furthermore, the screening module includes:

[0016] The minimum estimated power consumption calculation module is used to calculate the minimum estimated power consumption of each drone after completing the task to be performed and returning. , specifically:

[0017]

[0018] in, Indicates the return distance from the execution location of the task to be executed; if the progress percentage of the current execution task corresponding to the drone is 100%, then Indicates the distance from the corresponding real-time position of the corresponding drone to the execution position of the task to be executed; if the progress percentage of the current execution task corresponding to the drone is less than 100%, then Indicates the distance of the corresponding UAV from the execution position of the corresponding currently executed task to the execution position of the task to be executed; Indicates the preset minimum flight speed; express The corresponding power consumption rate; Indicates the estimated power consumption of the task to be executed;

[0019] The judgment module judges whether the corresponding drone meets the requirements for receiving the task to be performed according to the minimum estimated power consumption, specifically:

[0020] If the progress percentage of the current execution task corresponding to the drone is 100%, the first preset rule is used for judgment. The first rule is: if the progress percentage of the current execution task corresponding to the drone is 100%, the first preset rule is used for judgment. ,in, Indicates the real-time power of the corresponding drone. Indicates the preset safety power level, and the corresponding drone is qualified to receive the task to be executed;

[0021] If the progress percentage of the currently executed task corresponding to the drone is less than 100%, the second preset rule is used for judgment, and the second rule is:

[0022]

[0023] If satisfied , then the corresponding second drone meets the requirements for receiving the task to be performed;

[0024] in, Indicates the estimated remaining power of the corresponding drone after completing the corresponding current mission. Indicates the progress percentage of the current mission executed by the drone. Indicates the estimated power consumption of the current mission executed by the drone.

[0025] Furthermore, the risk value calculation module includes:

[0026] A plane path acquisition module is used to acquire the plane path of each preferred UAV to the execution position of the task to be executed, and the plane path is a path without considering the altitude;

[0027] An airspace statistics module is used to obtain the low-altitude airspace traversed by the plane path, that is, the low-altitude airspace that the preferred UAV corresponding to the plane path needs to traverse in the process of going to the execution position of the task to be executed;

[0028] The obstacle avoidance statistics module is used to count the number of buildings that the preferred drone corresponding to the planar path needs to avoid according to the building heights of each building passed by the planar path and the maximum flight heights of the preferred drones corresponding to each low-altitude airspace passed by the planar path;

[0029] The first calculation module is used to calculate the flight risk value of each preferred UAV to the execution location of the task to be executed, specifically:

[0030] F

[0031] in, represents the preset risk factor, and J represents the number of buildings that the corresponding optimal drone needs to avoid.

[0032] Furthermore, the obstacle avoidance statistics module counts the number of buildings that the preferred drone corresponding to the planar path needs to avoid, specifically:

[0033] If the building height of the building passed by the plane path in the low-altitude airspace currently traversed is greater than the maximum flight height of the preferred UAV of the plane path in the low-altitude airspace currently traversed, then the building will be used as the obstacle avoidance building of the plane path, and the number of obstacle avoidance buildings in the low-altitude airspace that the plane path needs to traverse will be counted as the number of buildings that the preferred UAV corresponding to the plane path needs to avoid.

[0034] Furthermore, the efficiency value calculation module includes:

[0035] The maximum speed acquisition module is used to evaluate the maximum speed that can be set for each preferred drone. ;

[0036] The time calculation module is used to calculate the time T for each preferred UAV to arrive at the execution location of the task to be executed, specifically:

[0037]

[0038] Wherein, t represents the time when the corresponding preferred UAV starts to go to the execution location of the task to be executed. If the progress percentage of the current execution task corresponding to the UAV is 100%, then Indicates the distance from the corresponding real-time position of the corresponding drone to the execution position of the task to be executed. If the progress percentage of the current execution task corresponding to the drone is less than 100%, then Indicates the distance of the corresponding UAV from the execution position of the corresponding currently executed task to the execution position of the task to be executed;

[0039] The second calculation module is used to calculate the efficiency value X of each preferred drone, specifically:

[0040]

[0041] in, Indicates the preset efficiency factor.

[0042] Furthermore, the maximum speed that can be set for each preferred drone is evaluated. , specifically:

[0043] If the progress percentage of the currently executed task corresponding to the preferred drone is 100%, then And meet The current settable speed In the above example, select the maximum value as the maximum speed that can be set for the corresponding preferred drone. , Indicates the real-time power of the corresponding drone;

[0044] If the progress percentage of the currently executed task corresponding to the preferred drone is less than 100%, then , The current settable speed In the above example, select the maximum value as the maximum speed that can be set for the corresponding preferred drone. , Indicates the estimated remaining power of the corresponding drone after completing the corresponding current mission;

[0045] represents the return distance from the execution location of the task to be executed, represents the estimated power consumption of the task to be executed, Indicates the preset safety power level.

[0046] Furthermore, the execution module calculates the corresponding scheduling fitness value Fit according to the flight risk value and efficiency value of each preferred UAV, and selects the best preferred UAV to execute the task to be executed according to the scheduling fitness value, specifically:

[0047]

[0048] in, represents the preset risk weight, Indicates the preset efficiency weight;

[0049] The maximum value is taken, and the corresponding preferred drone is the best preferred drone to perform the task to be performed.

[0050] The present invention also provides a low-altitude fusion management method, comprising the following steps:

[0051] Obtain mission data, drone data, airspace data, and building data for pending and currently executed missions;

[0052] The UAV data, airspace data and building data are fused by using a Kalman filter algorithm to obtain real-time fused data, wherein the real-time fused data represents the UAV data currently corresponding to each UAV, the task data corresponding to the currently executed task, and the airspace data and building data of the current airspace;

[0053] Establish a mapping relationship between the UAV's flight speed V and power consumption rate P;

[0054] Selecting a UAV that meets the requirements of receiving the task to be performed as a preferred UAV according to the real-time fusion data;

[0055] Calculate the flight risk value F of each preferred UAV to the execution location of the task to be executed according to the real-time fusion data;

[0056] Calculate the efficiency value X of each preferred UAV reaching the execution position of the task to be executed according to the real-time fusion data;

[0057] The corresponding scheduling fitness value Fit is calculated according to the flight risk value and efficiency value of each preferred UAV, and the best preferred UAV is selected according to the scheduling fitness value to execute the task to be executed.

[0058] Furthermore, the corresponding scheduling fitness value Fit is calculated according to the flight risk value and efficiency value of each preferred UAV, and the best preferred UAV is selected to perform the task to be performed according to the scheduling fitness value, specifically:

[0059]

[0060] in, represents the preset risk weight, represents the preset efficiency weight; the maximum value is taken from them, and the corresponding preferred drone is the best preferred drone to perform the task to be performed.

[0061] Compared with the prior art, the present invention has the following beneficial effects:

[0062] The present invention selects drones that meet the requirements of receiving the tasks to be performed as preferred drones based on real-time fusion data, and then calculates the flight risk value and efficiency value of the corresponding preferred drones to the execution location of the tasks to be performed, fully considering the flight risk and arrival efficiency of the drones to the new tasks, achieving an optimized scheduling strategy, and ensuring that the drones scheduled to perform the tasks to be performed have sufficient safety and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0064] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0065] Figure 1 It is a structural block diagram of the low-altitude fusion management platform of the present invention;

[0066] Figure 2 It is a structural block diagram of the dispatching control module of the low-altitude fusion management platform of the present invention;

[0067] Figure 3 It is a structural block diagram of the screening module of the low-altitude fusion management platform of the present invention;

[0068] Figure 4 It is a structural block diagram of a risk value calculation module of the low-altitude fusion management platform of the present invention;

[0069] Figure 5 It is a structural block diagram of the efficiency value calculation module of the low-altitude fusion management platform of the present invention. DETAILED DESCRIPTION

[0070] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0072] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0073] See also Figure 1 As shown, the present invention provides a low-altitude fusion management platform, comprising:

[0074] Data acquisition module, data fusion module, scheduling control module, and a central processing unit connected to the above modules.

[0075] The data acquisition module is used to obtain task data of tasks to be executed and currently executed tasks, and is provided with a UAV communication interface, an air traffic control communication interface and a GIS communication interface.

[0076] The data acquisition module communicates with each drone through the drone communication interface to acquire drone data;

[0077] The data acquisition module communicates with the air traffic control department through the air traffic control communication interface to acquire airspace data.

[0078] The data acquisition module communicates with the GIS system through the GIS communication interface to acquire building data.

[0079] The data fusion module is used to use the Kalman filtering algorithm to fuse the drone data, airspace data and building data to obtain real-time fused data. The real-time fused data represents the drone data currently corresponding to each drone, the corresponding task data of the currently executed task, and the airspace data and building data of the current airspace.

[0080] The task data includes: an execution location and an estimated power consumption for execution; the estimated power consumption for execution is the estimated power consumption for completing the task after the drone reaches the execution location for executing the task.

[0081] The drone data includes real-time location, real-time battery level and progress percentage of the current mission.

[0082] The airspace data includes the maximum flight altitude of the UAV in each low-altitude airspace.

[0083] The building data includes building location and building height.

[0084] See also Figure 2 As shown, the scheduling control module includes: a VP relationship establishment module, a screening module, a risk value calculation module, an efficiency value calculation module and an execution module.

[0085] The VP relationship establishment module is used to establish the mapping relationship between the UAV's flight speed V and the power consumption rate P. Specifically, the UAV's historical flight speed, the corresponding historical flight time, and the corresponding historical power consumption are used as training data. After training the deep learning model, the mapping relationship between the UAV's flight speed and the power consumption rate is obtained. The power consumption rate of this solution is the ratio of power consumption to the corresponding flight time.

[0086] The screening module is used to select a UAV that meets the requirements of receiving the task to be performed as a preferred UAV based on the real-time fusion data.

[0087] See also Figure 3 As shown, the screening module includes: a minimum estimated power consumption calculation module and a judgment module.

[0088] The minimum estimated power consumption calculation module is used to calculate the minimum estimated power consumption of each drone after completing the task to be performed and returning. , specifically:

[0089]

[0090] in, Indicates the return distance from the execution location of the task to be executed, that is, the distance from the execution location of the task to be executed to the drone dispatch location. If the progress percentage of the current execution task corresponding to the drone is 100%, then Indicates the distance from the corresponding real-time position of the corresponding drone to the execution position of the task to be executed. If the progress percentage of the current execution task corresponding to the drone is less than 100%, then Indicates the distance from the execution location of the corresponding UAV to the execution location of the task to be executed. Indicates the preset minimum flight speed. express The corresponding power consumption rate, Indicates the estimated power consumption of the task to be executed;

[0091] The judgment module judges whether the corresponding drone meets the requirements for receiving the task to be performed according to the minimum estimated power consumption, specifically:

[0092] If the progress percentage of the currently executed task corresponding to the drone is 100%, the first preset rule is used for judgment, and the first rule is:

[0093] If satisfied ,in, Indicates the real-time power of the corresponding drone. Indicates the preset safety power level, and the corresponding drone is qualified to receive the task to be executed;

[0094] If the progress percentage of the currently executed task corresponding to the drone is less than 100%, the second preset rule is used for judgment, and the second rule is:

[0095]

[0096] If satisfied , then the corresponding second drone meets the requirements for receiving the task to be performed;

[0097] in, Indicates the estimated remaining power of the corresponding drone after completing the corresponding current mission. Indicates the progress percentage of the current mission executed by the drone. Indicates the estimated power consumption of the current mission executed by the drone.

[0098] The mapping relationship between the flight speed V and the power consumption rate P established by the VP relationship establishment module is used to obtain the minimum estimated power consumption of the drone after it goes to complete the task to be performed and returns. According to the minimum estimated power consumption and the real-time power of the drone, it is determined whether the drone can still go to perform the task to be performed, thereby ensuring the safety of the task execution and optimizing the scheduling strategy.

[0099] The risk value calculation module is used to calculate the flight risk value F of each preferred UAV to the execution location of the task to be executed based on the real-time fusion data.

[0100] See also Figure 4 As shown, the risk value calculation module includes a plane path acquisition module, a spatial statistics module, an obstacle avoidance statistics module and a first calculation module.

[0101] The planar path acquisition module is used to acquire the planar path of each preferred UAV to the execution location of the task to be executed, and the planar path is a path without considering the altitude.

[0102] The airspace statistics module is used to obtain the low-altitude airspace traversed by the plane path, that is, the low-altitude airspace that the preferred UAV corresponding to the plane path needs to traverse in the process of going to the execution location of the task to be performed.

[0103] The obstacle avoidance statistics module is used to count the number of buildings that the preferred drone corresponding to the planar path needs to avoid according to the building heights of each building passed by the planar path and the maximum flight heights of the preferred drones corresponding to each low-altitude airspace passed by the planar path, specifically:

[0104] If the building height of the building passed by the plane path in the low-altitude airspace currently traversed is greater than the maximum flight height of the preferred UAV of the plane path in the low-altitude airspace currently traversed, then the building will be used as the obstacle avoidance building of the plane path, and the number of obstacle avoidance buildings in the low-altitude airspace that the plane path needs to traverse will be counted as the number of buildings that the preferred UAV corresponding to the plane path needs to avoid.

[0105] The first calculation module is used to calculate the flight risk value of each preferred UAV to the execution location of the task to be executed, specifically:

[0106] F

[0107] in, represents the preset risk factor, and J represents the number of buildings that the corresponding optimal drone needs to avoid.

[0108] The following is an example. For example, the plane path of the preferred drone a to the execution location of the task to be executed passes through low-altitude airspace A1 and low-altitude airspace A2. The maximum flight altitude of the drone in low-altitude airspace A1 is H1, and the maximum flight altitude of the drone in low-altitude airspace A2 is H2. The plane path passes through buildings 1 and 2 in low-altitude airspace A1, and passes through building 3 in low-altitude airspace A2. If the building height h1 of building 1 is greater than H1, the building height h2 of building 2 is less than H1, and the building height h3 of building 3 is greater than H3, then in the process of the first execution of drone a to the execution location of the task to be executed, the buildings that need to be avoided are building 1 and building 3, that is, the number of buildings that need to be avoided is 2.

[0109] The efficiency value calculation module is used to calculate the efficiency value X of each preferred UAV reaching the execution position of the task to be executed according to the real-time fusion data.

[0110] See also Figure 5 As shown, the efficiency value calculation module includes a maximum speed acquisition module, a time calculation module and a second calculation module.

[0111] The maximum speed acquisition module is used to evaluate the maximum speed that can be set for each preferred drone. , specifically:

[0112] If the progress percentage of the currently executed task corresponding to the preferred drone is 100%, then And meet The current settable speed In the above example, select the maximum value as the maximum speed that can be set for the corresponding preferred drone. ;

[0113] If the progress percentage of the currently executed task corresponding to the preferred drone is less than 100%, then , The current settable speed In the above example, select the maximum value as the maximum speed that can be set for the corresponding preferred drone. .

[0114] The time calculation module is used to calculate the time T for each preferred UAV to arrive at the execution location of the task to be executed, specifically:

[0115]

[0116] Wherein, t represents the time when the corresponding preferred UAV starts to go to the execution location of the task to be performed.

[0117] The present invention uses the maximum speed that can satisfy a flight speed greater than a preset minimum flight speed and a remaining power greater than a preset safety power after completing the mission equation as the maximum speed that the drone can currently set, so that the drone selected for subsequent scheduling can ensure safety and efficiency when it goes to the execution location of the task to be performed.

[0118] The second calculation module is used to calculate the efficiency value X of each preferred drone, specifically:

[0119]

[0120] in, Indicates the preset efficiency factor.

[0121] The execution module is used to calculate the corresponding scheduling fitness value Fit according to the flight risk value and efficiency value of each preferred UAV, and select the best preferred UAV to execute the task to be executed according to the scheduling fitness value, specifically:

[0122]

[0123] in, represents the preset risk weight, Indicates the preset efficiency weight;

[0124] The maximum value is taken, and the corresponding preferred drone is the best preferred drone to perform the task to be performed.

[0125] Embodiment 2

[0126] The present invention also provides a low-altitude fusion management method, comprising the following steps:

[0127] S1. Obtaining task data, drone data, airspace data, and building data for tasks to be performed and currently performed;

[0128] S2. Using a Kalman filter algorithm, the drone data, airspace data and building data are fused to obtain real-time fused data, wherein the real-time fused data represents the drone data currently corresponding to each drone, the task data of the corresponding currently executed task, and the airspace data and building data of the current airspace;

[0129] S3, establishing a mapping relationship between the flight speed V of the drone and the power consumption rate P;

[0130] S4. Selecting a UAV that meets the requirements for receiving the task to be performed as a preferred UAV according to the real-time fusion data;

[0131] S5. Calculate the flight risk value F of each preferred UAV to the execution location of the task to be executed according to the real-time fusion data;

[0132] S6. Calculate the efficiency value X of each preferred UAV reaching the execution position of the task to be executed according to the real-time fusion data;

[0133] S7. Calculate the corresponding scheduling fitness value Fit according to the flight risk value and efficiency value of each preferred UAV, and select the best preferred UAV to execute the task to be executed according to the scheduling fitness value.

[0134] It should be noted that the specific method and specific calculation of each step of the above method correspond to the low-altitude fusion management system in Example 1, and will not be repeated here.

[0135] Embodiment 3

[0136] The present invention also provides an electronic device, comprising: a processor, a sending device, an input device, an output device and a memory, the memory is used to store computer program code, the computer program code includes computer instructions, when the processor executes the computer instructions, the electronic device executes a method as any one of the possible implementation methods described above.

[0137] Embodiment 4

[0138] The present invention also provides a computer-readable storage medium, in which a computer program is stored. The computer program includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes a method as described in any possible implementation manner.

[0139] The beneficial effects of the present invention are:

[0140] The present invention selects drones that meet the requirements of receiving the tasks to be performed as preferred drones based on real-time fusion data, and then calculates the flight risk value and efficiency value of the corresponding preferred drones to the execution location of the tasks to be performed, fully considering the flight risk and arrival efficiency of the drones to the new tasks, achieving an optimized scheduling strategy, and ensuring that the drones scheduled to perform the tasks to be performed have sufficient safety and efficiency.

[0141] The present invention performs situation-by-situation calculation and judgment based on the progress percentage of the currently executed task of the preferred UAV, allowing the scheduling strategy to screen from idle UAVs and UAVs that are currently executing heavy tasks, thereby expanding the number of dispatchable UAVs, improving the selectivity of scheduling, ensuring that the best UAV is scheduled, and further ensuring that the UAVs dispatched to execute the tasks to be executed have sufficient safety and efficiency.

[0142] In the description of the specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0143] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A low-altitude fusion management platform, characterized in that: include: The data acquisition module is used to obtain the task data of the tasks to be executed and the tasks currently being executed, and is provided with a UAV communication interface, an air traffic control communication interface, and a GIS communication interface; The UAV communication interface is used to obtain UAV data; the ATC communication interface is used to obtain airspace data; the GIS communication interface is used to obtain building data; A data fusion module is used to fuse the drone data, airspace data and building data using a Kalman filter algorithm to obtain real-time fused data, wherein the real-time fused data represents the drone data currently corresponding to each drone, the task data corresponding to the currently executed task, and the airspace data and building data of the current airspace; The scheduling control module includes: a VP relationship establishment module, a screening module, a risk value calculation module, an efficiency value calculation module and an execution module; The VP relationship establishment module is used to establish a mapping relationship between the flight speed V and the power consumption rate P of the drone; The screening module is used to select a UAV that meets the requirements of receiving the task to be performed as a preferred UAV according to the real-time fusion data; The risk value calculation module is used to calculate the flight risk value F of each preferred UAV to the execution location of the task to be executed according to the real-time fusion data; The efficiency value calculation module is used to calculate the efficiency value X of each preferred UAV reaching the execution position of the task to be executed according to the real-time fusion data; The execution module is used to calculate the corresponding scheduling fitness value Fit according to the flight risk value and efficiency value of each preferred UAV, and select the best preferred UAV to execute the task to be executed according to the scheduling fitness value; The task data includes: execution location and estimated power consumption; the drone data includes real-time location, real-time power and progress percentage of the current task; the airspace data includes the maximum flight altitude of drones in each low-altitude airspace; the building data includes building location and building height; The risk value calculation module includes: A plane path acquisition module is used to acquire the plane path of each preferred UAV to the execution position of the task to be executed, and the plane path is a path without considering the altitude; An airspace statistics module is used to obtain the low-altitude airspace traversed by the plane path, that is, the low-altitude airspace that the preferred UAV corresponding to the plane path needs to traverse in the process of going to the execution position of the task to be executed; The obstacle avoidance statistics module is used to count the number of buildings that the preferred drone corresponding to the planar path needs to avoid according to the building heights of each building passed by the planar path and the maximum flight heights of the preferred drones corresponding to each low-altitude airspace passed by the planar path; The first calculation module is used to calculate the flight risk value of each preferred UAV to the execution location of the task to be executed, specifically: F ,in, represents the preset risk factor, and J represents the number of buildings that the corresponding optimal drone needs to avoid; The efficiency value calculation module includes: The maximum speed acquisition module is used to evaluate the maximum speed that can be set for each preferred drone. ; The time calculation module is used to calculate the time T for each preferred UAV to arrive at the execution location of the task to be executed. , where t represents the time when the corresponding preferred UAV starts to go to the execution location of the task to be executed. If the progress percentage of the current execution task corresponding to the UAV is 100%, then Indicates the distance from the corresponding real-time position of the corresponding drone to the execution position of the task to be executed. If the progress percentage of the current execution task corresponding to the drone is less than 100%, then Indicates the distance of the corresponding UAV from the execution position of the corresponding currently executed task to the execution position of the task to be executed; The second calculation module is used to calculate the efficiency value X of each preferred drone. ,in, Indicates the preset efficiency factor.

2. The low-altitude fusion management platform according to claim 1 is characterized in that: The screening module comprises: The minimum estimated power consumption calculation module is used to calculate the minimum estimated power consumption of each drone after completing the task to be performed and returning. , specifically: ； in, represents the return distance from the execution location of the task to be executed; Indicates the preset minimum flight speed; express The corresponding power consumption rate; Indicates the estimated power consumption of the task to be executed; The judgment module judges whether the corresponding drone meets the requirements for receiving the task to be performed according to the minimum estimated power consumption, specifically: If the progress percentage of the currently executed task corresponding to the drone is 100%, the first preset rule is used for judgment, and the first preset rule is: If satisfied ,in, Indicates the real-time power of the corresponding drone. Indicates the preset safety power level, and the corresponding drone is qualified to receive the task to be executed; If the progress percentage of the currently executed task corresponding to the drone is less than 100%, the second preset rule is used for judgment, and the second preset rule is: ； If satisfied , then the corresponding second drone meets the requirements for receiving the task to be performed; in, Indicates the estimated remaining power of the corresponding drone after completing the corresponding current mission. Indicates the progress percentage of the current mission executed by the drone. Indicates the estimated power consumption of the current mission executed by the drone.

3. The low-altitude fusion management platform according to claim 1 is characterized in that: The obstacle avoidance statistics module counts the number of buildings that the preferred drone corresponding to the planar path needs to avoid, specifically: If the height of the building passed by the plane path in the low-altitude airspace currently traversed is greater than the maximum flight height of the preferred UAV of the plane path in the low-altitude airspace currently traversed, then the building will be used as the obstacle avoidance building of the plane path, and the number of obstacle avoidance buildings in the low-altitude airspace that the plane path needs to traverse will be counted as the number of buildings that the preferred UAV corresponding to the plane path needs to avoid.

4. The low-altitude fusion management platform according to claim 1 is characterized in that: The maximum speed that can be set for each preferred drone is evaluated. , specifically: If the progress percentage of the currently executed task corresponding to the preferred drone is 100%, then And meet The current settable speed In the above example, select the maximum value as the maximum speed that can be set for the corresponding preferred drone. , Indicates the real-time power of the corresponding drone; If the progress percentage of the currently executed task corresponding to the preferred drone is less than 100%, then , The current settable speed In the above example, select the maximum value as the maximum speed that can be set for the corresponding preferred drone. , Indicates the estimated remaining power of the corresponding drone after completing the corresponding current mission; represents the return distance from the execution location of the task to be executed, represents the estimated power consumption of the task to be executed, Indicates the preset safety power level.

5. The low-altitude fusion management platform according to claim 1 is characterized in that: The execution module calculates the corresponding scheduling fitness value Fit according to the flight risk value and efficiency value of each preferred UAV, and selects the best preferred UAV to execute the task to be executed according to the scheduling fitness value, specifically: ； in, represents the preset risk weight, Indicates the preset efficiency weight; The maximum value is taken, and the corresponding preferred drone is the best preferred drone to perform the task to be performed.

6. A low-altitude fusion management method, applied to the low-altitude fusion management platform according to any one of claims 1 to 5, characterized in that: The following steps are involved: Obtaining task data, drone data, airspace data and building data of tasks to be executed and currently executed; the task data includes: execution location and estimated power consumption; the drone data includes real-time location, real-time power and progress percentage of the currently executed task; the airspace data includes the maximum flight altitude of drones in each low-altitude airspace; the building data includes building location and building height; The UAV data, airspace data and building data are fused by using a Kalman filter algorithm to obtain real-time fused data, wherein the real-time fused data represents the UAV data currently corresponding to each UAV, the task data corresponding to the currently executed task, and the airspace data and building data of the current airspace; Establish a mapping relationship between the UAV's flight speed V and power consumption rate P; Selecting a UAV that meets the requirements of receiving the task to be performed as a preferred UAV according to the real-time fusion data; Calculate the flight risk value F of each preferred UAV to the execution location of the task to be executed according to the real-time fusion data; Calculate the efficiency value X of each preferred UAV reaching the execution position of the task to be executed according to the real-time fusion data; Calculate the corresponding scheduling fitness value Fit according to the flight risk value and efficiency value of each preferred UAV, and select the best preferred UAV to perform the task to be performed according to the scheduling fitness value; The flight risk value F is calculated as follows: Obtaining a planar path for each preferred UAV to reach the execution location of the task to be executed; Obtaining the low-altitude airspace traversed by the plane path; According to the building heights of the buildings passed by the planar path and the maximum flight heights of the preferred drones corresponding to the low-altitude airspaces passed by the planar path, the number of buildings that the preferred drones corresponding to the planar path need to avoid are counted; Calculate the flight risk value of each preferred UAV to the execution location of the task to be executed, F ,in, represents the preset risk factor, and J represents the number of buildings that the corresponding optimal drone needs to avoid; The calculation method of the efficiency value X is specifically as follows: Evaluate the maximum speed that can be set for each preferred drone ; Calculate the time T for each preferred UAV to arrive at the execution location of the task to be executed, , where t represents the time when the corresponding preferred UAV starts to go to the execution location of the task to be executed. If the progress percentage of the current execution task corresponding to the UAV is 100%, then Indicates the distance from the corresponding real-time position of the corresponding drone to the execution position of the task to be executed. If the progress percentage of the current execution task corresponding to the drone is less than 100%, then Indicates the distance of the corresponding UAV from the execution position of the corresponding currently executed task to the execution position of the task to be executed; Calculate the efficiency value X of each preferred drone, ,in, Indicates the preset efficiency factor.

7. The low-altitude fusion management method according to claim 6, characterized in that: The corresponding scheduling fitness value Fit is calculated according to the flight risk value and efficiency value of each preferred UAV, and the best preferred UAV is selected to perform the task to be performed according to the scheduling fitness value, specifically: ； in, represents the preset risk weight, Indicates the preset efficiency weight; The maximum value is taken, and the corresponding preferred drone is the best preferred drone to perform the task to be performed.

Images