Unmanned aerial vehicle flight control method and device and medium

Abstract

The invention provides an unmanned aerial vehicle flight control method and device and a medium, and relates to the technical field of unmanned aerial vehicles. The method comprises the following steps: dividing a local flight space of an unmanned aerial vehicle into a preset number of cubic spaces with preset scales; assuming that the unmanned aerial vehicle is located in each cubic space, obtaining a first cubic space in which communication signals between the unmanned aerial vehicle and a base station are optimal in the local flight space; and controlling the flight path of the unmanned aerial vehicle according to the first cubic space. The local space of the flight of the unmanned aerial vehicle is divided into the cubic space, the cubic space with the optimal communication signal between the unmanned aerial vehicle and the base station is obtained to serve as the basis for controlling the flight path of the unmanned aerial vehicle, it is ensured that the unmanned aerial vehicle always keeps good communication with the base station in the flight process, and the flight safety of the unmanned aerial vehicle is improved.

Description

Technical Field

[0001] This application relates at least to the field of drone technology, and particularly to a method, device, and medium for controlling the flight of a drone. Background Art

[0002] With the advent of the low-altitude economy era, the flight safety of drones has become a key topic of concern in the industry. Ground-to-air coverage base stations are an important means of monitoring the flight safety of drones. During flight, drones may encounter problems with weak communication signals with base stations, posing a great potential hazard to flight safety. Summary of the Invention

[0003] In view of the above deficiencies, this application provides a method, device, and medium for controlling the flight of a drone to solve the following technical problem: how to optimize the flight position of the drone to ensure the communication signal strength between the drone and the base station.

[0004] In a first aspect, this application provides a method for controlling the flight of a drone, the method including:

[0005] Dividing the local flight space of the drone into a preset number of cube spaces of a preset scale;

[0006] Assuming that the drone is located in each of the cube spaces, obtaining a first cube space in the local flight space where the communication signal between the drone and the base station is optimal;

[0007] Controlling the flight path of the drone according to the first cube space.

[0008] Further, assuming that the drone is located in each of the cube spaces, obtaining a first cube space in the local flight space where the communication signal between the drone and the base station is optimal specifically includes:

[0009] Assuming that the drone is located at the central position of each of the cube spaces, respectively obtaining the uplink signal level distribution of the signal received by the base station from the drone and the downlink signal level distribution of the signal received by the drone from the base station in the local flight space according to the uplink signal level model and the downlink signal level model, and obtaining the central position of the first cube space where the communication signal between the drone and the base station is optimal according to the uplink signal level distribution and the downlink signal level distribution.

[0010] Further, the method further includes:

[0011] Obtaining an uplink signal level model and a downlink signal level model obtained through pre-training;

[0012] The uplink signal level model is used to estimate the uplink signal level of the signal received by the base station from the drone according to the positions and parameters of the drone and the base station;

[0013] The downlink signal level model is used to estimate the downlink signal level of the signal received by the UAV from the base station according to the positions and parameters of the UAV and the base station.

[0014] Further, where:

[0015] The local flight space of the UAV is divided into a preset number of cube spaces with a preset scale, specifically including:

[0016] During the flight of the UAV, obtain the first downlink signal level of the signal received by the UAV from the first base station currently connected, or the first uplink signal level of the signal currently received by the first base station from the UAV. If the first downlink signal level is lower than the first threshold or the first uplink signal level is lower than the second threshold, obtain the first local flight space centered on the current position of the UAV, and divide the first local flight space into a preset number of cube spaces with a preset scale, or

[0017] In the flight plan of the UAV, if the positions and parameters of all base stations passed by the UAV during flight remain unchanged, divide the entire flight space of the UAV from the takeoff position to the end position into multiple second local flight spaces, and divide each second local flight space into a preset number of cube spaces with a preset scale;

[0018] Control the flight path of the UAV according to the first cube space, specifically including:

[0019] During the flight of the UAV, use the central position of the first cube space as the starting point of the subsequent flight path of the UAV, or

[0020] In the flight plan of the UAV, connect the central positions of the first cube spaces of each second local flight space to form the flight path of the UAV.

[0021] Further, obtaining the first downlink signal level of the signal received by the UAV from the first base station currently connected, or the first uplink signal level of the signal currently received by the first base station from the UAV, specifically includes:

[0022] Obtain the true level of the signal received by the UAV from the first base station currently connected to obtain the first downlink signal level; or

[0023] Input the current position of the UAV, the current first signal transmission parameter of the UAV, the position of the first base station currently connected to the UAV, and the receiving working parameters of the first cell served by the first base station for the UAV into the uplink signal level model to obtain the first uplink signal level.

[0024] Further, obtain a first local flight space centered on the current position of the drone, and divide the first local flight space into a preset number of cube spaces of a preset scale, specifically including:

[0025] Obtain a central cube space with a preset scale of r*r*r centered on the current position of the drone, and expand outward from the central cube space to obtain n - 1 adjacent cube spaces with a preset scale of r*r*r. The preset number n can divide the first local flight space with a total scale of R1*R2*R3 using cube spaces of r*r*r.

[0026] Further, assume that the drone is located at the central position of each of the cube spaces. Respectively, according to the uplink signal level model and the downlink signal level model, obtain the uplink signal level distribution of the signal received by the base station from the drone in the local flight space and the downlink signal level distribution of the signal received by the drone from the base station. According to the uplink signal level distribution and the downlink signal level distribution, obtain the central position of the first cube space with the optimal communication signal between the drone and the base station, specifically including:

[0027] Obtain the second base station that the drone is most likely to connect to and the second cell served by the second base station at the central position of each of the cube spaces;

[0028] Input the central position of each of the cube spaces, the second signal reception parameters of the drone, the position of the second base station, and the transmission working parameters of the second cell into the downlink signal level model to obtain the second downlink signal level;

[0029] Input the central position of each of the cube spaces, the second signal transmission parameters of the drone, the position of the second base station, and the reception working parameters of the second cell into the uplink signal level model to obtain the second uplink signal level;

[0030] Select the central position of a certain cube space with the optimal second downlink signal level and second uplink signal level as the central position of the first cube space.

[0031] Further, assume that the drone is located at the central position of each of the cube spaces. Respectively, according to the uplink signal level model and the downlink signal level model, obtain the uplink signal level distribution of the signal received by the base station from the drone in the local flight space and the downlink signal level distribution of the signal received by the drone from the base station. According to the uplink signal level distribution and the downlink signal level distribution, obtain the central position of the first cube space with the optimal communication signal between the drone and the base station, specifically including:

[0032] Obtain the central position of each of the cube spaces, the second base station to which the drone is most likely to connect, and the second cell served by the second base station for the drone;

[0033] Input the central position of each cube space, the current first signal reception parameter or first signal transmission parameter of the drone, the position of the second base station, and the transmission working parameters or reception working parameters of the second cell into the downlink signal level model or uplink signal level model to obtain the second downlink signal level or second uplink signal level;

[0034] Select a number of third base stations among the second base stations where the second downlink signal level is greater than the third threshold or the second uplink signal level is greater than the fourth threshold, and obtain the third cell served by the third base station for the drone and the central position of the second cube space corresponding to the third base station;

[0035] Input the central position of each second cube space, the adjustable third signal transmission parameter or third signal reception parameter of the drone, the position of the third base station, and the reception working parameters or transmission working parameters of the third cell into the uplink signal level model or downlink signal level model to obtain the optimal third uplink signal level or third downlink signal level of the central position of each second cube space;

[0036] Select the optimal fourth uplink signal level or fourth downlink signal level from a number of third uplink signal levels or third downlink signal levels, and select the central position of the cube space corresponding to the fourth uplink signal level or fourth downlink signal level as the central position of the first cube space.

[0037] In a second aspect, the present application provides a drone flight control device, and the device includes:

[0038] A division unit for dividing the local flight space of the drone into a preset number of cube spaces of a preset scale;

[0039] A prediction unit connected to the division unit for assuming that the drone is located in each of the cube spaces and obtaining the first cube space in the local flight space where the communication signal between the drone and the base station is optimal;

[0040] A control unit connected to the prediction unit for controlling the flight path of the drone according to the first cube space.

[0041] In a third aspect, the present application provides a computer-readable storage medium, and a computer program is stored in the computer-readable storage medium. When the computer program is run by a processor, the above-mentioned drone flight control method is implemented.

[0042] The present application provides a method, apparatus and medium for controlling the flight of a drone. A cubic space is divided in the local space where the drone flies, and the cubic space with the optimal communication signal between the drone and the base station is obtained as the basis for controlling the flight path of the drone, ensuring that the drone always maintains good communication with the base station during flight and improving the flight safety of the drone. Description of the Drawings

[0043] Figure 1 is a flowchart of a method for controlling the flight of a drone according to an embodiment of the present application;

[0044] Figure 2 is a schematic structural diagram of an apparatus for controlling the flight of a drone according to an embodiment of the present application;

[0045] Figure 3 is a flowchart of another method for controlling the flight of a drone according to an embodiment of the present application;

[0046] Figure 4 is a schematic structural diagram of another apparatus for controlling the flight of a drone according to an embodiment of the present application. Detailed Embodiments

[0047] To enable those skilled in the art to better understand the technical solutions of the present application, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

[0048] It can be understood that the specific embodiments and drawings described herein are only used to explain the present application, rather than limiting the present application.

[0049] It can be understood that, without conflict, the various embodiments and features in the embodiments of the present application can be combined with each other.

[0050] It can be understood that, for the convenience of description, only the parts related to the present application are shown in the drawings of the present application, and the parts unrelated to the present application are not shown in the drawings.

[0051] It can be understood that each module and unit involved in the embodiments of the present application may correspond to only one physical structure, or may be composed of multiple physical structures, or multiple modules and units may also be integrated into one physical structure.

[0052] It can be understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of the present application may occur in a different order from that marked in the drawings.

[0053] It can be understood that in the flowcharts and block diagrams of the present application, the possible system architectures, functions, and operations of the systems, devices, equipment, and methods according to the various embodiments of the present application are shown. Among them, each block in the flowchart or block diagram may represent a module, unit, program segment, or code, which contains executable instructions for implementing the specified function. Moreover, each block or combination of blocks in the block diagram and flowchart can be implemented by a hardware-based device for implementing the specified function, or by a combination of hardware and computer instructions.

[0054] It can be understood that the modules and units involved in the embodiments of the present application can be implemented in software or in hardware. For example, the modules and units can be located in the processor.

[0055] Embodiment 1:

[0056] As Figure 1 shown, the present application provides a method for controlling the flight of a drone, and the method includes:

[0057] S1. Divide the local flight space of the drone into a preset number of cube spaces with a preset scale;

[0058] S2. Assume that the drone is located in each of the cube spaces, and obtain the first cube space in the local flight space where the communication signal between the drone and the base station is optimal;

[0059] S3. Control the flight path of the drone according to the first cube space.

[0060] In this embodiment, the method divides cube spaces in the local space where the drone flies, obtains the cube space with the optimal communication signal between the drone and the base station, and uses it as the basis for controlling the flight path of the drone, ensuring that the drone always maintains good communication with the base station during flight and improving the flight safety of the drone. As Figure 1 shown, the method corresponds to being applied to the device as Figure 2 shown.

[0061] In one embodiment, S2. Assume that the drone is located in each of the cube spaces, and obtain the first cube space in the local flight space where the communication signal between the drone and the base station is optimal, specifically including:

[0062] Assume that the drone is located at the center position of each of the cube spaces, respectively obtain the uplink signal level distribution of the signal received by the base station from the drone in the local flight space and the downlink signal level distribution of the signal received by the drone from the base station according to the uplink signal level model and the downlink signal level model, and obtain the center position of the first cube space with the optimal communication signal between the drone and the base station according to the uplink signal level distribution and the downlink signal level distribution.

[0063] In this embodiment, a drone flight control method as shown in Figure 3 and a drone flight control device as shown in Figure 4 are specifically provided. Particularly for the problem that when the uplink signal transmitted by the drone may be very weak when reaching the base station due to abnormal conditions during flight, resulting in the ground being unable to monitor the drone's state, the drone cannot timely grasp the situation of the base station receiving the signal, and thus it is difficult to adjust the position in time to enhance the ability of the base station to receive the signal. By directly using the wireless data on the base station side for modeling, the flight problem in the case of weak uplink signals of the drone can be solved. The base station refers to a cellular network base station on the ground that has air coverage and ensures the flight of the drone. For example, a 5G (5th Generation Mobile Communication Technology)-A (Advanced, evolution and enhancement) / 6G (6th Generation Mobile Communication Technology) base station. Among them, the downlink signal refers to the signal transmitted by the base station received by the drone, and the uplink signal refers to the signal transmitted by the drone received by the base station. In order to synchronously ensure the strength of the uplink signal and the downlink signal, this embodiment uses an uplink signal level model and a downlink signal level model to respectively predict the uplink signal and downlink signal strengths at multiple position points in the local space, and obtains the position point with the optimal communication signal between the drone and the base station by synthesizing the uplink signal strength and the downlink signal strength.

[0064] The method includes the following steps:

[0065] Step S01: The drone collects the base station downlink signal information in the flight space and establishes a downlink signal level model;

[0066] Step S02: The base station receives the drone uplink signal information and establishes an uplink signal level model;

[0067] Step S03: During the flight of the drone, estimate the base station received signal level according to the uplink signal level model. If certain conditions are met, estimate the downlink signal level in the space around the drone;

[0068] Step S04: Determine the optimal position of the drone signal according to the downlink signal level in the surrounding space, and reset the flight path with the optimal position signal as the next starting point of the flight path.

[0069] The device includes the following modules:

[0070] Acquisition module 01, used to collect the base station downlink signal information and uplink signal information in the flight space;

[0071] The training module 02, connected to the acquisition module 01, is used to establish a downlink signal level model and an uplink signal level model according to the acquired downlink signal information and uplink signal information;

[0072] The estimation module 03, connected to the training module, is used to estimate the uplink signal level received by the base station according to the uplink signal information and estimate the downlink signal level in the space around the UAV according to the current position;

[0073] The decision module 04, connected to the estimation module 03, is used to determine the optimal position of the UAV signal according to the downlink signal level in the surrounding space, and reset the flight path with the optimal signal position as the next starting point of the flight path.

[0074] In one embodiment, the method further includes:

[0075] Obtain the pre-trained uplink signal level model and downlink signal level model;

[0076] The uplink signal level model is used to estimate the uplink signal level of the signal received by the base station from the UAV according to the positions and parameters of the UAV and the base station;

[0077] The downlink signal level model is used to estimate the downlink signal level of the signal received by the UAV from the base station according to the positions and parameters of the UAV and the base station.

[0078] In this embodiment, the uplink signal level model and the downlink signal level model are obtained by pre-collecting data for training. The specific training model used can be one of various existing machine learning algorithms. The trained model can estimate the uplink signal level of the signal received by the base station from the UAV and the downlink signal level of the signal received by the UAV from the base station according to the positions and parameters of the UAV and the base station. The training process is described in detail as follows:

[0079] Step S01: The UAV collects the downlink signal information of the base station in the flight space and establishes a downlink signal level model, which specifically includes:

[0080] Pre-plan the flight space of the UAV;

[0081] The UAV collects the downlink signal information of the base station at different heights and longitude and latitude positions in the flight space;

[0082] The downlink signal information includes, but is not limited to, the serving cell identifier ECI (E-UTRAN Cell Identifier, evolved universal terrestrial radio access network cell identifier) and the signal level strength RSRP (Reference Signal Received Power);

[0083] In addition, the drone also collects the longitude, latitude, and altitude of the location where the current received downlink signal is located;

[0084] The drone sends the collected downlink signal information data to the server;

[0085] The server uses the serving cell identifier ECI and the signal level strength RSRP of the signal as the targets, and the drone's longitude, latitude, and altitude as features, and trains this data using the K-Nearest Neighbor (KNN) algorithm to obtain the downlink signal level model of the drone's flight space;

[0086] Load the downlink signal level model into the drone's calculation module.

[0087] Step S02: The base station receives the drone's uplink signal information and establishes an uplink signal level model, specifically including:

[0088] While the drone collects the base station's downlink signal, it also transmits an uplink signal to the base station, and the base station receives the drone's uplink signal information;

[0089] The uplink signal information includes, but is not limited to, the signal level strength RSRP received by the base station;

[0090] In addition, the drone also collects the uplink signal transmission power, longitude, latitude, and altitude of the uplink signal transmission location where it is currently located;

[0091] The base station and the drone send the collected uplink signal information data to the server;

[0092] Associate the uplink signal information data with the cell engineering parameter data to obtain a training data set;

[0093] The cell engineering parameter data includes, but is not limited to, the azimuth angle of the serving cell, the site height, the antenna tilt angle, the cell longitude and latitude, etc.;

[0094] In the training data set, use the signal level strength RSRP of the base station receiving the uplink signal as the target, and the uplink signal transmission power, uplink signal transmission longitude, latitude, transmission height, and cell engineering parameters as features, and use machine learning algorithms to train the uplink signal level model;

[0095] Machine learning algorithms include, but are not limited to, K-Nearest Neighbor, Support Vector Machine, Random Forest, Gradient Boosting Decision Tree, and Deep Learning Model, etc. The specific steps in the training process are not limited in this embodiment;

[0096] Load the uplink signal level model into the drone's calculation module.

[0097] In one embodiment, where:

[0098] S1. Divide the local flight space of the drone into a preset number of cube spaces of a preset scale, specifically including:

[0099] During the flight of the drone, obtain the first downlink signal level of the signal received by the drone from the first base station currently connected, or the first uplink signal level of the signal currently received by the first base station from the drone. If the first downlink signal level is lower than the first threshold or the first uplink signal level is lower than the second threshold, obtain the first local flight space centered on the current position of the drone, and divide the first local flight space into a preset number of cube spaces of a preset scale, or

[0100] In the flight plan of the drone, if the positions and parameters of all base stations passed by the drone during flight remain unchanged, divide the entire flight space of the drone from the takeoff position to the end position into multiple second local flight spaces, and divide each second local flight space into a preset number of cube spaces of a preset scale;

[0101] S3. Control the flight path of the drone according to the first cube space, specifically including:

[0102] During the flight of the drone, use the central position of the first cube space as the starting point of the subsequent flight path of the drone, or

[0103] In the flight plan of the drone, connect the central positions of the first cube spaces of each second local flight space to form the flight path of the drone.

[0104] In this embodiment, there are two specific ways to control the flight path of the drone. One is to perform path planning, and the other is to adjust the path in real time during flight. The way of planning the path can be applied on the premise that the parameters of the base stations during flight are known and these parameters will not change during flight. According to the uplink signal level model and the downlink signal level model, calculate all the optimal position points in the flight route to form the flight path with the best signal. The way of adjusting the path in real time has stronger adaptability and can adjust the flight path according to the real-time signal transmission and reception situation during flight.

[0105] In an implementation manner, obtaining the first downlink signal level of the signal received by the drone from the first base station currently connected, or the first uplink signal level of the signal currently received by the first base station from the drone, specifically includes:

[0106] Obtain the real level of the signal received by the drone from the first base station currently connected to obtain the first downlink signal level; or

[0107] Input the current position of the drone, the current first signal transmission parameters of the drone, the position of the first base station currently connected to the drone, and the receiving engineering parameters of the first cell served by the first base station for the drone into the uplink signal level model to obtain the first uplink signal level.

[0108] In this embodiment, when the uplink signal level model and the downlink signal level model are loaded in the drone and the drone adjusts the path in real time according to the communication signal transceiver situation, the drone can know the true level of the received signal by itself, but it is necessary to use the model to predict the level of the signal received by the base station from the drone. The cell engineering parameters of the base station can be sent to the drone at each adjustment or its adjustment plan can be sent to the drone in advance.

[0109] In an implementation manner, obtain a first local flight space centered on the current position of the drone, and divide the first local flight space into a preset number of cube spaces with a preset scale, specifically including:

[0110] Obtain a central cube space with a preset scale of r*r*r centered on the current position of the drone, and expand outward from the central cube space to obtain n - 1 adjacent cube spaces with a preset scale of r*r*r. The preset number n can use cube spaces with a scale of r*r*r to divide the first local flight space with a total scale of R1*R2*R3.

[0111] In this embodiment, during the flight of the drone, the uplink signal transmission power, the uplink signal transmission longitude and latitude, and the launch height at the current position are associated with the cell engineering parameters to form features, and the estimated base station received uplink signal level is obtained by inputting into the uplink signal level model; if the estimated uplink signal level meets certain conditions, such as being lower than a certain threshold, the drone estimates the downlink signal level of the surrounding space; taking the current position of the drone as the center position of a cube with a size of r*r*r, 26 cubes with a size of r*r*r in the surrounding space are established with this cube as the center; calculate the downlink signal level and the serving cell at the center positions of the 26 cubes; input the longitude, latitude and height of each center position into the downlink signal level model to output the estimated downlink signal level and the serving cell at this position. In this embodiment, the flight position of the drone is adjusted in real time during the flight of the drone. Each local flight space is a cube with R1 = R2 = R3, which can be imagined as a Rubik's Cube with a size of 3*3*3. The current position of the drone is the central cube of the Rubik's Cube. There are 26 small cubes around this central cube. It can also be other numbers, such as a Rubik's Cube with a size of 5*5*5, then there are 5*5*5 - 1 = 124 surrounding cubes.

[0112] In one embodiment, assuming that the UAV is located at the center position of each of the cube spaces, the uplink signal level distribution of the signals received by the base station from the UAV in the local flight space and the downlink signal level distribution of the signals received by the UAV from the base station are obtained respectively according to the uplink signal level model and the downlink signal level model. According to the uplink signal level distribution and the downlink signal level distribution, obtaining the center position of the first cube space with the optimal communication signal between the UAV and the base station specifically includes:

[0113] Obtain the second base station that the UAV is most likely to connect to and the second cell served by the second base station for the UAV at the center position of each of the cube spaces;

[0114] Input the center position of each of the cube spaces, the second signal reception parameters of the UAV, the position of the second base station, and the transmission working parameters of the second cell into the downlink signal level model to obtain the second downlink signal level;

[0115] Input the center position of each of the cube spaces, the second signal transmission parameters of the UAV, the position of the second base station, and the reception working parameters of the second cell into the uplink signal level model to obtain the second uplink signal level;

[0116] Select the center position of a certain cube space with the optimal second downlink signal level and second uplink signal level as the center position of the first cube space.

[0117] In this embodiment, the uplink signal strength and downlink signal strength of each cube space in the current local flight space can be directly predicted through the uplink signal level model and the downlink signal level model, and an optimal position is obtained by combining the two as the starting point for subsequent flight.

[0118] In one embodiment, assuming that the UAV is located at the center position of each of the cube spaces, the uplink signal level distribution of the signals received by the base station from the UAV in the local flight space and the downlink signal level distribution of the signals received by the UAV from the base station are obtained respectively according to the uplink signal level model and the downlink signal level model. According to the uplink signal level distribution and the downlink signal level distribution, obtaining the center position of the first cube space with the optimal communication signal between the UAV and the base station specifically includes:

[0119] Obtain the second base station that the UAV is most likely to connect to and the second cell served by the second base station for the UAV at the center position of each of the cube spaces;

[0120] Input the central position of each of the cube spaces, the current first signal reception parameter or first signal transmission parameter of the drone, as well as the position of the second base station and the transmission working parameters or reception working parameters of the second cell into the downlink signal level model or the uplink signal level model to obtain the second downlink signal level or the second uplink signal level;

[0121] Select several third base stations in the second base station where the second downlink signal level is greater than the third threshold or the second uplink signal level is greater than the fourth threshold, and obtain the third cell served by the third base station for the drone and the central position of the second cube space corresponding to the third base station;

[0122] Input the central position of each second cube space, the adjustable third signal transmission parameter or third signal reception parameter of the drone, as well as the position of the third base station and the reception working parameters or transmission working parameters of the third cell into the uplink signal level model or the downlink signal level model to obtain the optimal third uplink signal level or third downlink signal level for the central position of each second cube space;

[0123] Select the optimal fourth uplink signal level or fourth downlink signal level from several third uplink signal levels or third downlink signal levels, and select the central position of the cube space corresponding to the fourth uplink signal level or fourth downlink signal level as the central position of the first cube space.

[0124] In this embodiment, at each surrounding space point, adjust the uplink signal transmission power according to the estimated downlink signal level; take the estimated uplink signal transmission power, the longitude and latitude of the central position, the height of the central position, and the cell working parameters of each central position as features, and input them into the uplink signal level model to obtain the estimated base station received uplink signal level value of the surrounding space; select the central point position corresponding to the optimal uplink signal level as the starting point of the subsequent flight path according to certain conditions, and reset the drone's flight path. According to the mutual relationship between the uplink and downlink signal levels, vice versa. It can be understood that the signal transmission and reception between the drone and the base station are relative, and the model and the output results are also relative. For example, if the reception parameter of the drone is input into the model, the transmission working parameter of the base station is correspondingly input into the model. This model is the downlink signal level model, and the output is the downlink signal level, and vice versa. The understanding of the word "or" in the text of this application is based on not violating the basic technical logic, and these technical logics are self-evident to those skilled in the art.

[0125] In this embodiment, it further includes: obtaining the spatial coordinates of the center position of each cubic space, and the base station coordinates of all base stations within a preset range centered on the center position of each cubic space; obtaining the base station with the shortest distance between the spatial coordinates and the base station coordinates as the second base station, and obtaining the cell corresponding to the direction of the second base station towards the center position of the corresponding cubic space as the second cell. Both the received engineering parameters and the transmitted engineering parameters belong to the cell engineering parameters.

[0126] In this embodiment, it includes: collecting the downlink signal information of the flight space of the unmanned aerial vehicle (UAV), and establishing a downlink signal level model at the spatial sampling points; collecting the uplink signal information received by the base station, and establishing an uplink signal level model for the base station to receive the uplink signal; estimating whether the transmitted uplink signal level at each position during flight can meet the requirement of the base station receiving level; estimating the downlink signal level at 26 positions around the current position of the UAV; adjusting the uplink transmission power according to the downlink signal levels at the 26 positions, and selecting the position with the optimal estimated uplink reception power as the next starting point of the flight path. A method for ensuring the uplink communication quality of the base station UAV is proposed. By establishing a model, the problem of ensuring the uplink link communication signal when the uplink signal level is lower than the threshold can be solved. The model uses the base station wireless data (cell engineering parameters) for real-time signal strength estimation. At positions where the uplink signal is weak, search for positions with strong uplink signals around and restart the next path, so as to realize the real-time adjustment of the UAV flight path.

[0127] Embodiment 2:

[0128] As Figure 2 shown, the present application provides a UAV flight control device, and the device includes:

[0129] A dividing unit 1, configured to divide the local flight space of the UAV into a preset number of cubic spaces with a preset scale;

[0130] A predicting unit 2, connected to the dividing unit 1, and configured to assume that the UAV is located in each of the cubic spaces, and obtain a first cubic space with the optimal communication signal between the UAV and the base station in the local flight space;

[0131] A control unit 3, connected to the predicting unit 2, and configured to control the flight path of the UAV according to the first cubic space.

[0132] In an implementation manner, the predicting unit 2 is specifically configured to:

[0133] Assume that the UAV is located at the center position of each of the cube spaces. According to the uplink signal level model and the downlink signal level model respectively, obtain the uplink signal level distribution of the signal received by the base station from the UAV in the local flight space and the downlink signal level distribution of the signal received by the UAV from the base station. According to the uplink signal level distribution and the downlink signal level distribution, obtain the center position of the first cube space where the communication signal between the UAV and the base station is optimal.

[0134] In one embodiment, the device further includes a model unit, which is used for:

[0135] Obtain the pre-trained uplink signal level model and downlink signal level model;

[0136] The uplink signal level model is used to estimate the uplink signal level of the signal received by the base station from the UAV according to the positions and parameters of the UAV and the base station;

[0137] The downlink signal level model is used to estimate the downlink signal level of the signal received by the UAV from the base station according to the positions and parameters of the UAV and the base station.

[0138] In one embodiment, where:

[0139] The partitioning unit 1 specifically includes:

[0140] The real-time partitioning unit is used to, during the flight of the UAV, obtain the first downlink signal level of the signal received by the UAV from the first base station currently connected, or the first uplink signal level of the signal currently received by the first base station from the UAV. If the first downlink signal level is lower than the first threshold or the first uplink signal level is lower than the second threshold, obtain the first local flight space centered on the current position of the UAV, and divide the first local flight space into a preset number of cube spaces with a preset scale, or

[0141] The planning and partitioning unit is used to, in the flight plan of the UAV, if the positions and parameters of all the base stations passed by the UAV during the flight remain unchanged, divide the entire flight space of the UAV from the take-off position to the end position into multiple second local flight spaces, and divide each second local flight space into a preset number of cube spaces with a preset scale;

[0142] The control unit 3 specifically includes:

[0143] The path reset unit is connected to the real-time partitioning unit through the prediction unit, and is used to, during the flight of the UAV, use the center position of the first cube space as the starting point of the subsequent flight path of the UAV, or

[0144] The path planning unit is connected to the planning division unit through the prediction unit and is used to connect the central positions of the first cube spaces of each second local flight space in the flight plan of the UAV to form the flight path of the UAV.

[0145] In one embodiment, the real-time division unit includes a signal level acquisition unit, specifically including:

[0146] The real level acquisition unit is used to acquire the real level of the signal received by the UAV from the currently connected first base station to obtain the first downlink signal level; or,

[0147] The estimated level acquisition unit is used to input the current position of the UAV, the current first signal transmission parameters of the UAV, the position of the currently connected first base station of the UAV, and the receiving working parameters of the first cell served by the first base station for the UAV into the uplink signal level model to obtain the first uplink signal level.

[0148] In one embodiment, the real-time division unit includes a surrounding space division unit, which is specifically used for:

[0149] Taking the current position of the UAV as the center, a central cube space with a preset scale of r*r*r is obtained. Expanding outward with the central cube space as the center, n-1 adjacent cube spaces with a preset scale of r*r*r are obtained. The preset number n can divide the first local flight space with a total scale of R1*R2*R3 using cube spaces with a scale of r*r*r.

[0150] In one embodiment, the prediction unit 2 specifically includes:

[0151] The base station cell prediction unit is used to obtain the second base station that the UAV is most likely to connect to and the second cell served by the second base station at the central position of each of the cube spaces;

[0152] The downlink level prediction unit is connected to the base station cell prediction unit and is used to input the central position of each of the cube spaces, the second signal reception parameters of the UAV, the position of the second base station, and the transmission working parameters of the second cell into the downlink signal level model to obtain the second downlink signal level;

[0153] The uplink level prediction unit is connected to the base station cell prediction unit and is used to input the central position of each of the cube spaces, the second signal transmission parameters of the UAV, the position of the second base station, and the receiving working parameters of the second cell into the uplink signal level model to obtain the second uplink signal level;

[0154] An optimal selection unit, connected to the downlink level prediction unit and the uplink level prediction unit, is configured to select the central position of a certain cube space with the optimal second downlink signal level and second uplink signal level as the central position of the first cube space.

[0155] In one embodiment, the prediction unit 2 specifically includes:

[0156] A base station cell prediction unit, configured to obtain, at the central position of each cube space, the second base station to which the drone is most likely to connect and the second cell served by the second base station for the drone;

[0157] A first level prediction unit, connected to the base station cell prediction unit, is configured to input the central position of each cube space, the current first signal reception parameter or first signal transmission parameter of the drone, the position of the second base station, and the transmission working parameters or reception working parameters of the second cell into a downlink signal level model or an uplink signal level model to obtain a second downlink signal level or a second uplink signal level;

[0158] A first selection unit, connected to the first level prediction unit, is configured to select a plurality of third base stations in the second base stations where the second downlink signal level is greater than a third threshold or the second uplink signal level is greater than a fourth threshold, and obtain the third cell served by the third base station for the drone and the central position of the second cube space corresponding to the third base station;

[0159] A second level prediction unit, connected to the first selection unit, is configured to input the central position of each second cube space, the adjustable third signal transmission parameter or third signal reception parameter of the drone, the position of the third base station, and the reception working parameters or transmission working parameters of the third cell into an uplink signal level model or a downlink signal level model to obtain the optimal third uplink signal level or third downlink signal level of the central position of each second cube space;

[0160] A second selection unit, connected to the second level prediction unit, is configured to select the optimal fourth uplink signal level or fourth downlink signal level from a plurality of third uplink signal levels or third downlink signal levels, and select the central position of the cube space corresponding to the fourth uplink signal level or fourth downlink signal level as the central position of the first cube space.

[0161] Embodiment 3:

[0162] Embodiment 3 of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is run by a processor, it implements the drone flight control method described in Embodiment 1 or implements the drone flight control device described in Embodiment 2.

[0163] The computer-readable storage medium includes volatile or non-volatile, removable or non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, computer program units, or other data. The computer-readable storage medium includes, but is not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), flash memory, or other memory technologies, CD-ROM (Compact Disc Read-Only Memory), digital versatile discs (DVDs), or other optical disc storage, magnetic cassettes, tapes, magnetic disk storage, or any other medium that can be used to store the desired information and can be accessed by a computer.

[0164] In addition, the present application may further provide a computer device, including a memory and a processor. A computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes the drone flight control method described in Embodiment 1. The computer device may be the drone flight control device described in Embodiment 2.

[0165] Among them, the memory is connected to the processor. The memory may use flash memory, read-only memory, or other memories, and the processor may use a central processing unit or a single-chip microcomputer.

[0166] Embodiments 1-3 of the present application provide a drone flight control method, device, and medium. A cubic space is divided in the local space of the drone flight, and the cubic space with the optimal communication signal between the drone and the base station is obtained as the basis for controlling the flight path of the drone, ensuring that the drone always maintains good communication with the base station during flight and improving the flight safety of the drone.

[0167] It can be understood that the above embodiments are merely exemplary embodiments adopted to illustrate the principle of the present application. However, the present application is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present application, and these modifications and improvements are also regarded as the protection scope of the present application.

Claims

1. A UAV flight control method, characterized in that: The method comprises: Divide the local flight space of the drone into a preset number of cubic spaces of preset sizes; Assuming that the UAV is located in each of the cubic spaces, obtaining a first cubic space in the local flight space where the communication signal between the UAV and the base station is optimal; The flight path of the UAV is controlled according to the first cubic space.

2. The method according to claim 1, characterized in that Assuming that the UAV is located in each of the cubic spaces, obtaining the first cubic space in the local flight space where the UAV has the best communication signal with the base station specifically includes: Assuming that the UAV is located at the center of each of the cubic spaces, the uplink signal level distribution of the base station receiving the signal of the UAV and the downlink signal level distribution of the base station receiving the signal in the local flight space are obtained according to the uplink signal level model and the downlink signal level model respectively. According to the uplink signal level distribution and the downlink signal level distribution, the center position of the first cubic space where the communication signal between the UAV and the base station is optimal is obtained.

3. The method according to claim 2, characterized in that The method further comprises: Obtaining a pre-trained uplink signal level model and a pre-trained downlink signal level model; The uplink signal level model is used to estimate the uplink signal level of the signal received by the base station from the drone according to the locations and parameters of the drone and the base station; The downlink signal level model is used to estimate the downlink signal level of the signal received by the UAV from the base station according to the positions and parameters of the UAV and the base station.

4. The method according to claim 3, characterized in that in: The local flight space of the drone is divided into a preset number of cubic spaces of preset sizes, including: During the flight of the drone, a first downlink signal level of a signal received by the drone from a first base station currently connected, or a first uplink signal level of a signal currently received by the first base station from the drone is obtained; if the first downlink signal level is lower than a first threshold or the first uplink signal level is lower than a second threshold, a first local flight space centered on the current position of the drone is obtained, and the first local flight space is divided into a preset number of cubic spaces of preset sizes, or, In the flight planning of the drone, if the positions and parameters of all base stations passed by the drone during flight remain unchanged, the entire flight space of the drone from the take-off position to the terminal position is divided into a plurality of second local flight spaces, and each second local flight space is divided into a preset number of cubic spaces of preset sizes; Controlling the flight path of the drone according to the first cubic space specifically includes: During the flight of the drone, the center position of the first cubic space is used as the starting point of the subsequent flight path of the drone, or, In the flight planning of the UAV, the center position of the first cubic space of each second local flight space is connected to form the flight path of the UAV.

5. The method according to claim 4, characterized in that Acquiring a first downlink signal level of a signal received by the drone from a first base station to which the drone is currently connected, or a first uplink signal level of a signal received by the first base station from the drone, specifically includes: Obtaining a real level of a signal received by the drone from a first base station currently connected, to obtain a first downlink signal level; or, The current position of the drone and the current first signal transmission parameters of the drone, as well as the position of the first base station to which the drone is currently connected and the receiving parameters of the first cell of the first base station serving the drone are input into the uplink signal level model to obtain the first uplink signal level.

6. The method according to claim 4, characterized in that Acquiring a first local flight space centered on the current position of the drone, and dividing the first local flight space into a preset number of cubic spaces of preset scales, specifically includes: A central cube space with a preset scale of r*r*r is obtained with the current position of the drone as the center, and n-1 adjacent cube spaces with a preset scale of r*r*r are obtained by expanding outward with the central cube space as the center. The preset number n can use the r*r*r cube spaces to divide the first local flight space with a total scale of R1*R2*R3.

7. The method according to any one of claims 2 to 6, characterized in that: Assuming that the UAV is located at the center of each of the cubic spaces, the uplink signal level distribution of the signal received by the base station from the UAV and the downlink signal level distribution of the signal received by the UAV from the base station in the local flight space are obtained according to the uplink signal level model and the downlink signal level model, respectively. According to the uplink signal level distribution and the downlink signal level distribution, the center position of the first cubic space where the communication signal between the UAV and the base station is optimal is obtained, which specifically includes: Acquire, at the center position of each of the cubic spaces, the second base station to which the drone is most likely to be connected and the second cell where the second base station serves the drone; Input the center position of each of the cubic spaces and the second signal receiving parameters of the drone, as well as the position of the second base station and the transmission parameters of the second cell, into a downlink signal level model to obtain a second downlink signal level; Input the center position of each of the cubic spaces and the second signal transmission parameters of the drone, as well as the position of the second base station and the receiving parameters of the second cell, into the uplink signal level model to obtain a second uplink signal level; The center position of a cubic space where the second downlink signal level and the second uplink signal level are optimal is selected as the center position of the first cubic space.

8. The method according to any one of claims 2 to 6, characterized in that: Assuming that the UAV is located at the center of each of the cubic spaces, the uplink signal level distribution of the signal received by the base station from the UAV and the downlink signal level distribution of the signal received by the UAV from the base station in the local flight space are obtained according to the uplink signal level model and the downlink signal level model, respectively. According to the uplink signal level distribution and the downlink signal level distribution, the center position of the first cubic space where the communication signal between the UAV and the base station is optimal is obtained, which specifically includes: Acquire, at the center position of each of the cubic spaces, the second base station to which the drone is most likely to be connected and the second cell where the second base station serves the drone; Input the center position of each of the cubic spaces and the current first signal receiving parameter or first signal transmitting parameter of the drone, as well as the position of the second base station and the transmitting parameter or receiving parameter of the second cell, into a downlink signal level model or an uplink signal level model to obtain a second downlink signal level or a second uplink signal level; Selecting a plurality of third base stations among the second base stations whose second downlink signal level is greater than a third threshold or whose second uplink signal level is greater than a fourth threshold, and obtaining a third cell of the drone served by the third base station and a center position of the second cubic space corresponding to the third base station; Inputting the center position of each second cubic space and the adjustable third signal transmission parameter or third signal reception parameter of the UAV, as well as the position of the third base station and the receiving parameters or transmission parameters of the third cell into the uplink signal level model or the downlink signal level model to obtain the optimal third uplink signal level or third downlink signal level at the center position of each second cubic space; The best fourth uplink signal level or fourth downlink signal level is selected from a plurality of third uplink signal levels or third downlink signal levels, and the center position of the cube space corresponding to the fourth uplink signal level or fourth downlink signal level is selected as the center position of the first cube space.

9. A UAV flight control device, characterized in that: The device comprises: A division unit, used to divide the local flight space of the UAV into a preset number of cubic spaces of preset sizes; A prediction unit connected to the division unit, configured to assume that the UAV is located in each of the cubic spaces, and obtain a first cubic space in the local flight space where the communication signal between the UAV and the base station is optimal; The control unit is connected to the prediction unit and is used to control the flight path of the UAV according to the first cubic space.

10. 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 the processor, the UAV flight control method according to any one of claims 1 to 8 is implemented.

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