Method for calculating maximum flight speed and flight time of unmanned aerial vehicle and flight control method

Abstract

The problems that when the flight speed of an unmanned aerial vehicle is optimized in the prior art, noise and vibration influences are ignored, so that the robustness of the flight speed in a real and complex environment is insufficient, and an existing noise and vibration control method may cause that noise or vibration exceeds the standard under a local working condition are solved. The invention provides an unmanned aerial vehicle maximum flight speed and flight time calculation method and a flight control method. According to the method, factors such as noise intensity and vibration acceleration are fully integrated, an acoustic radiation model and a vibration influence model are respectively established, the two models are used for solving an acoustic limiting speed and a vibration limiting speed, and a small value is selected as the maximum flight speed of the unmanned aerial vehicle. And calculating the actual maximum flight speed of the unmanned aerial vehicle by combining the wind speed and the wind angle of the unmanned aerial vehicle operation area. When the unmanned aerial vehicle flies at the actual maximum flight speed obtained through the method, the flight stability can be kept, the working efficiency can be guaranteed, noise and vibration generated by flight can be prevented from exceeding the standard, and the adverse effect of the noise and vibration on the performance of the unmanned aerial vehicle is avoided.

Description

Technical Field

[0001] The present invention relates to the field of control or regulation systems for non-electrical variables, and in particular to a method for calculating the maximum flight speed and flight time of an unmanned aerial vehicle (UAV) and a flight control method. Background Art

[0002] As an efficient and flexible flight platform, drones are increasingly used in a variety of fields, including agricultural monitoring, environmental protection, and logistics and transportation. Optimizing their flight performance is directly related to the efficiency and reliability of mission execution. The flight speed of a drone is a key factor affecting its flight performance. A flight speed that is too low will extend operating time and increase energy consumption; a flight speed that is too high will induce stronger aerodynamic noise and structural vibration, reducing the accuracy of onboard sensors, communication distance, and structural life. Specifically, the coupling relationship between flight speed, noise, and vibration, and their impact on drone flight performance, is mainly reflected in the following aspects:

[0003] 1. Noise interference:

[0004] The noise generated by drones in operation primarily consists of propeller-vortex interaction noise caused by propeller rotation and aerodynamic noise generated by the drone's motion. This noise can interfere with the effective signals of onboard sensors (such as acoustic monitoring equipment), affecting data acquisition accuracy. It can also affect the quality of communication between the drone and ground stations, and even violate environmental regulations in the area where the drone operates. Therefore, noise has become a significant factor limiting drone flight efficiency in high-precision monitoring missions requiring hovering near the ground or low-speed cruising.

[0005] 2. Vibration impact:

[0006] When a drone is operating, vibrations caused by the drone's power system (such as motors and propellers) or external airflow can increase feedback errors in the flight control system, leading to deviations in the flight trajectory. Long-term vibrations can also accelerate mechanical fatigue and even cause permanent damage to key components.

[0007] 3. Dynamic coupling effect:

[0008] Existing research indicates that noise and vibration often exhibit a nonlinear coupling relationship with flight speed. For example, high-speed flight can exacerbate propeller vortex vibration, while reduced speed can reduce the aircraft's wind resistance, creating a performance optimization paradox of "speeding up and exceeding the limit" or "speeding down and losing stability."

[0009] However, current optimization of UAV performance ignores the aforementioned aspects, especially the dynamic coupling effect mentioned above, resulting in the following limitations of current optimization schemes:

[0010] 1. When it comes to optimizing flight speed, mainstream research focuses on increasing flight speed or extending flight time, often ignoring the coupling relationship between noise, vibration, and flight speed. This results in the resulting flight speed being insufficiently robust in real, complex environments.

[0011] 2. Regarding noise and vibration control, existing technologies focus on eliminating noise sources such as low-noise propellers and designing vibration suppression devices such as vibration-damping structures. Once the design is completed, the noise and vibration suppression effect is fixed, which may cause noise or vibration to exceed the standard under local operating conditions, thereby affecting the performance of the drone. Summary of the Invention

[0012] In order to overcome the technical problems that the existing optimization of UAV flight speed ignores the influence of noise and vibration, resulting in insufficient robustness of flight speed in real complex environments, and the existing noise and vibration control methods cannot dynamically adjust the suppression effect, which may lead to excessive noise or vibration under local working conditions, the present invention proposes a method for calculating the maximum flight speed of UAV.

[0013] Based on the method for calculating the maximum flight speed of a UAV proposed in the present invention, the present invention further proposes a method for calculating the flight time of a UAV and a method for controlling the flight of a UAV for path planning.

[0014] The technical solution of the present invention is:

[0015] The method for calculating the maximum flight speed of a UAV is special in that it includes the following steps:

[0016] Step 1: Establish acoustic radiation model and vibration impact model;

[0017] The acoustic radiation model is:

[0018] ;

[0019] The vibration impact model is:

[0020] ;

[0021] Where, is the acoustic radiation value; is the noise propagation coefficient, is the blade-vortex interaction noise coefficient, is the aerodynamic noise coupling coefficient; is the flight speed of the drone; is the propeller speed, , is the thrust coefficient; is the propeller radius; is the mechanical vibration cost item; is the vibration frequency of the drone, ; is the vibration acceleration of the drone, ; is the vibration sensitivity coefficient, Indicates the vibration frequency of the drone Sensitivity to vibration effects, Indicates the vibration acceleration of the drone sensitivity to vibration effects; is the vibration characteristic coefficient, Indicates the vibration frequency of the drone The flight speed of the drone The relationship coefficient between Indicates the vibration acceleration of the drone The flight speed of the drone The relationship coefficient between

[0022] Step 2: Obtain drone operation data and environmental data;

[0023] The UAV operation data includes propeller radius , noise propagation coefficient , vibration sensitivity coefficient , thrust coefficient , vibration characteristic coefficient and maximum vibration threshold ; Noise propagation coefficient , vibration characteristic coefficient Obtained through wind tunnel experiments; thrust coefficient Based on actual flight test; vibration sensitivity coefficient Obtained through numerical simulation; maximum vibration threshold Obtained through vibration testing;

[0024] The environmental data includes a maximum acoustic threshold , wind speed Zephyr Corner ; Maximum acoustic threshold Determined according to the environmental protection regulations of the area where the drone is operating; wind speed Obtained by placing wind speed measurement points in the UAV operation area; wind angle Obtained through path planning software;

[0025] Step 3: Calculate the acoustic limit speed and vibration limit speed;

[0026] Substituting the UAV operation data and environmental data obtained in step 2 into the acoustic radiation model and vibration impact model to obtain the acoustic limit speed and vibration limit speed;

[0027] Step 4: Calculate the maximum flight speed:

[0028] Select the smaller value from the acoustic limit speed and the vibration limit speed as the maximum flight speed ;

[0029] Step 5: Calculate the actual maximum flight speed:

[0030] The maximum flight speed obtained from step 4 , wind speed obtained in step 3 Zephyr Corner , calculate the actual maximum flight speed .

[0031] Furthermore, in step 2, the UAV path is first divided into multiple sub-paths, and then the UAV operation data and the environmental data under each sub-path are obtained; accordingly, in step 3, the local acoustic limit speed and the local vibration limit speed of each sub-path are calculated; in step 4, for each sub-path, the smaller value is selected from its local acoustic limit speed and local vibration limit speed as the local maximum flight speed of each sub-path; in step 5, the local maximum flight speed of each sub-path, the wind speed and wind angle of each sub-path are used to calculate the local actual maximum flight speed of each sub-path.

[0032] Furthermore, before step 1, the drone path is divided into multiple sub-paths, and then for each sub-path, the method of steps 1-5 is used to solve the local actual maximum flight speed of each sub-path.

[0033] Furthermore, the length of each subpath Use the following formula to calculate:

[0034]

[0035] Where, is the reference segment length; The length of the reference segment Divide the time The average distance between obstacles near the segment path is obtained through the 3D map; The safe distance of the drone is the minimum distance between the drone and obstacles during flight. is the correction factor, ranging from 0 to 1.

[0036] The present invention also proposes a method for calculating the flight time of a UAV for path planning, which is special in that it includes the following steps:

[0037] Step 1): Use the above-mentioned UAV maximum flight speed calculation method to calculate the local actual maximum flight speed of each subpath;

[0038] Step 2): Calculate flight time ;

[0039]

[0040] Where, For the The local actual maximum flight speed of the segment path; is the total number of subpaths; is an empirical parameter with a value of [0,1]; is the average distance between obstacles in the UAV's total path.

[0041] The present invention also proposes a UAV flight control method oriented to path planning, which is special in that it includes the following steps:

[0042] Step 1: Using the above-mentioned method for calculating the maximum flight speed of the UAV, calculate the local actual maximum flight speed of the UAV in each sub-path, and store the sub-path and the local actual maximum flight speed in correspondence;

[0043] Step 2: The flight control system controls the UAV according to the local actual maximum flight speed of each sub-path calculated in step 1.

[0044] Beneficial effects of the present invention:

[0045] The proposed method for calculating the maximum flight speed of a drone fully integrates factors such as noise intensity and vibration acceleration, establishing an acoustic radiation model and a vibration impact model. These models are used to solve for the acoustic and vibration limiting speeds, respectively. The smaller of these values ​​is selected as the drone's maximum flight speed. The actual maximum flight speed is then calculated based on the wind speed and wind angle in the drone's operating area. When a drone flies at the actual maximum flight speed determined by this method, it not only maintains flight stability and ensures operational efficiency, but also prevents excessive noise and vibration from exceeding flight standards, thus avoiding the adverse effects of noise and vibration on drone performance.

[0046] 2. The dynamic relationship among noise, vibration, and flight speed is difficult to describe with a single model. The present invention indirectly balances the constraints of noise and vibration on flight speed by “taking the minimum value,” avoiding the complexity of direct coupling modeling. This makes the established model simple, the calculation process simple, and the parameters required by the model easy to obtain or estimate. It can quickly and accurately provide an optimized actual maximum flight speed solution for the UAV’s flight mission, thereby improving flight stability, work efficiency, safety, and mission completion quality, and providing reliable technical support for the application of UAVs in noise-sensitive and high-precision mission environments.

[0047] 3. The method for calculating the maximum flight speed of a drone proposed in this invention further considers the impact of obstacles, divides the total path of the drone into multiple sub-paths, and calculates the local actual maximum flight speed that better matches the sub-path planning on each sub-path. This ensures that the drone can take into account flight stability, safety, and mission completion quality on each sub-path, providing a more accurate basis for more precise path planning, time planning, battery management, and maintenance of drone missions.

[0048] 4. The UAV flight control method proposed in the present invention calculates the local actual maximum flight speed of the UAV under each sub-path, and accurately controls the flight of the UAV based on the local actual maximum flight speed, thereby ensuring the flight stability, mission execution efficiency, safety and mission completion quality of the UAV. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 The present invention is a flowchart of a method for calculating the maximum flight speed of a UAV.

[0050] Figure 2 This is a flow chart of the method for calculating the maximum flight speed of a UAV for path planning according to the present invention.

[0051] Figure 3 This is a flow chart of the method for calculating the flight time of a UAV for path planning according to the present invention.

[0052] Figure 4 This is a flow chart of the UAV flight control method for path planning of the present invention. DETAILED DESCRIPTION

[0053] The present invention will be further described below in conjunction with the accompanying drawings.

[0054] Reference Figure 1 The method for calculating the maximum flight speed of a drone provided by the present invention comprises the following steps:

[0055] Step 1: Establish acoustic radiation model and vibration impact model;

[0056] The acoustic radiation model established in this step is:

[0057] ;

[0058] in, is the acoustic radiation value; is the noise propagation coefficient, Characterize the blade-vortex interaction noise coefficient; Characterize the aerodynamic noise coupling coefficient; is the flight speed of the drone; is the propeller speed, , is the thrust coefficient; is the propeller radius; represents the vortex noise generated by the propeller rotation; Represents the aerodynamic noise generated by drone flight.

[0059] The vibration impact model established in this step is:

[0060] ;

[0061] in, is the mechanical vibration cost item; is the vibration frequency of the drone, ; is the vibration acceleration of the drone, ; is the flight speed of the drone; is the vibration sensitivity coefficient, Indicates the vibration frequency of the drone Sensitivity to vibration effects, Indicates the vibration acceleration of the drone sensitivity to vibration effects; is the vibration characteristic coefficient, Indicates the vibration frequency of the drone The flight speed of the drone The relationship coefficient between Indicates the vibration acceleration of the drone The flight speed of the drone The relationship coefficient between It represents the dominant term of elastic potential energy, which is related to the square of the UAV vibration frequency and reflects the periodic elastic potential energy stored in the UAV's mechanical system (including the main frame of the UAV fuselage, rotors, motors and other components on the vibration transmission path); It represents the dominant term of inertia force, which is related to the vibration acceleration of the UAV and reflects the instantaneous impact of the mass inertia force on the main frame structure of the UAV fuselage.

[0062] Step 2: Obtain drone operation data and environmental data;

[0063] The drone operation data that needs to be obtained in this step include:

[0064] Propeller radius , refers to the distance from the center axis of the drone's propeller to the farthest end of the propeller blade, in meters;

[0065] Noise propagation coefficient ,in, Characterizes the propeller-vortex interaction noise coefficient, which is the relationship coefficient between the propeller vortex noise and the UAV flight state; Characterizes the aerodynamic noise coupling coefficient, which is the coefficient of the relationship between aerodynamic noise and the flight speed of the UAV; and It can be obtained through wind tunnel experiments, measuring the noise data at different propeller speeds and wind speeds, and then fitting the noise data to obtain and ; and All are dimensionless quantities;

[0066] Vibration sensitivity coefficient , can be obtained through numerical simulation. A three-dimensional model of the UAV is established in simulation software (such as ANSYS), and simulation data of frequency response and acceleration response are obtained. The simulation data are fitted to obtain and ; and All are dimensionless quantities;

[0067] thrust coefficient , refers to the flight speed of the drone and propeller speed The ratio of the propeller speed of the UAV at different flight speeds can be obtained based on actual flight tests, and the obtained data can be fitted to obtain ; is a dimensionless quantity;

[0068] Vibration characteristic coefficient , which can be obtained through wind tunnel experiments, measuring the vibration frequency and vibration acceleration of the drone under different wind speeds, and fitting the measured data to obtain and ; and All are dimensionless quantities;

[0069] Maximum vibration threshold , refers to the maximum vibration level that the drone can tolerate during flight. Exceeding this threshold may cause damage to the drone structure or affect the drone's flight stability; Maximum vibration threshold Vibration testing can be performed on a test drone with the same structural parameters as the drone to be used for the mission.

[0070] The environmental data that needs to be obtained in this step include:

[0071] Maximum acoustic threshold , refers to the maximum noise level allowed during drone flight. Exceeding this threshold may violate relevant noise regulations; The value is determined according to the environmental protection regulations of the area where the drone is operating;

[0072] wind speed , refers to the horizontal speed of air flow, which can be collected by wind speed measurement points arranged in the UAV operation area, and the unit is meters per second; when there are multiple wind speed measurement points arranged in the UAV operation area, the average wind speed collected by each wind speed measurement point is taken as the wind speed ;

[0073] Wind Corner , refers to the angle between the ground speed vector and the wind speed vector in the UAV navigation speed triangle, that is, the angle between the track line and the wind direction line. The wind angle ranges from 0 to ±180°, and the unit is degree; wind angle It can be obtained by calculation and processing based on the ground speed vector and wind speed vector through path planning software.

[0074] Step 3: Calculate the acoustic limit speed and vibration limit speed;

[0075] According to the acoustic radiation model established in step 1 and the UAV operation data and environmental data obtained in step 2, the acoustic limit speed is obtained. for:

[0076] ;

[0077] According to the vibration impact model established in step 1 and the UAV operation data obtained in step 2, the vibration limit speed is obtained. for:

[0078] .

[0079] Step 4: Calculate the maximum flight speed of the drone;

[0080] Use the following formula to calculate the maximum flight speed of the drone :

[0081] .

[0082] Step 5: Calculate the actual maximum flight speed of the drone;

[0083] Based on the maximum flight speed of the drone , combined with the wind speed in the drone operation area Zephyr Corner , use the following formula to calculate the actual maximum flight speed of the drone :

[0084] .

[0085] The above is the basic technical solution of the present invention. On this basis, in order to further improve the dynamic adaptability of the present invention to the real-time environment, the present invention also proposes a method for calculating the maximum flight speed of a UAV for path planning. Figure 2 , this method first divides the total path of the UAV into multiple sub-paths, and then uses the method of steps 1-5 above to calculate the local actual maximum flight speed of each sub-path. Alternatively, the total path of the UAV can be divided into multiple sub-paths in the above step 2, and the UAV operation data and the environmental data under each sub-path are obtained, and substituted into the model established in step 1 to solve the local acoustic limit speed and local vibration limit speed of each sub-path, and select the smaller value as the maximum flight speed of each sub-path, and then calculate the local actual maximum flight speed of each sub-path in combination with the wind speed and wind angle of the sub-path. Preferably, considering that the wind speed changes more significantly in areas with dense obstacles, the influence of obstacles can be considered when dividing sub-paths, so that the calculated local actual maximum flight speed of each sub-path is more accurate, which can provide a more accurate basis for estimating the total flight time, mission planning, safety, battery management and maintenance, etc. Specifically, when considering the influence of obstacles, the sub-path length Calculate according to the following formula:

[0086]

[0087] Where, The default segment length is 100 meters, which can be set according to the actual flight control requirements. The smaller the value, the higher the flight control accuracy); The length of the reference segment Divide the time The average distance between obstacles near the segment path, Available through 3D maps; The safe distance of the drone is the minimum distance between the drone and obstacles during flight, usually half of the drone's wheelbase. is the correction factor, ranging from 0 to 1.

[0088] Reference Figure 3 The present invention also provides a method for calculating the flight time of a UAV for path planning. The method for calculating the maximum flight speed of a UAV for path planning provided by the present invention is first used to calculate the local actual maximum flight speed of each sub-path. Then, the local flight time of the UAV in each sub-path is calculated, and then the total flight time of the UAV is obtained. The calculation formula is as follows:

[0089]

[0090] Where, For the The local actual maximum flight speed of the segment path; is the total number of subpaths, is an empirical parameter with a value of [0,1]; is the average distance between all obstacles in the vicinity of the total path of the UAV; is the correction factor; is the sum of the local flight times of all subpaths.

[0091] Reference Figure 4 The present invention also provides a path planning-oriented UAV flight control method, which first uses the path planning-oriented UAV maximum flight speed calculation method provided by the present invention to calculate the local actual maximum flight speed of each sub-path and store it corresponding to the sub-path. Then, during the flight, the flight control system calls the pre-stored local actual maximum flight speed according to the sub-path position of the UAV during flight to realize the flight control of the UAV.

[0092] In order to make the solution of the present invention easier to understand, it is further described in detail below with reference to specific embodiments.

[0093] Example 1:

[0094] In an urban environment, a drone is tasked with delivering cargo. This mission requires the drone to fly at an optimized speed within the urban area, ensuring both flight stability and environmental noise impact. To reduce noise interference in residential areas and increase the drone's lifespan, this embodiment applies the present invention's maximum drone flight speed calculation method to optimize the drone's flight speed.

[0095] The calculation method of the maximum flight speed of the UAV in this embodiment is:

[0096] Step 1: Obtain drone operation data and environmental data;

[0097] Propeller radius: R=0.5 m; Noise propagation coefficient: =1.2, =0.8; vibration sensitivity coefficient: =0.5, =0.3; thrust coefficient: =0.8; vibration characteristic coefficient: =1, =0.1; Maximum vibration threshold: =35; Maximum acoustic threshold: =60, wind speed: 0.5m / s.

[0098] Step 2: Calculate the acoustic limit speed and vibration limit speed;

[0099] Substitute the UAV operation data and environmental data obtained in step 1 into the acoustic radiation model and vibration impact model established by the present invention to obtain the acoustic limit speed and vibration limit speed They are:

[0100] ;

[0101] .

[0102] Step 3: Calculate the maximum speed of the drone ;

[0103] .

[0104] Step 4: Calculate the actual maximum speed of the drone ;

[0105] Assumed wind angle is 180°, .

[0106] Therefore, the UAV is on the path of performing the cargo delivery mission. As the maximum flight speed, it can ensure that the noise and vibration generated during flight will not exceed the standard.

[0107] Example 2:

[0108] This embodiment is based on the embodiment 1, and divides the total path of the embodiment 1 into multiple sub-paths, and further calculates the UAV flight time.

[0109] Assuming the total path length is 3000m, the benchmark segment length When dividing, the average distance between obstacles near each sub-path is equal. =50m, correction factor =0.8, =20m, then the length of each sub-path for:

[0110] .

[0111] In practice, the maximum acoustic threshold and maximum vibration threshold of different sub-paths may be different, and the local maximum flight speed calculated using the method of the present invention may be different. In order to facilitate calculation, this embodiment assumes that the local maximum flight speed of each sub-path is the same as that calculated in Example 1. , Taking 0.6, when executing the cargo delivery task in Example 1, the flight time of the drone is:

[0112]

[0113] Therefore, the drone needs to complete the cargo delivery task of the embodiment, and the flight time of the drone should be Second.

[0114] Example 3:

[0115] This embodiment is based on Example 2. The local actual maximum flight speed under each sub-path actually calculated in Example 2 is stored in the flight control system in correspondence with the sub-path. The flight control system calls the corresponding local actual maximum flight speed according to the sub-path to perform precise flight control of the UAV, so that the UAV can fly stably under each sub-path and ensure that the maximum acoustic threshold and the maximum vibration threshold are not exceeded, thereby improving adaptability to dynamic environments.

Claims

1. A method for calculating the maximum flight speed of a UAV, characterized in that: Including steps: Step 1: Establish acoustic radiation model and vibration impact model; The acoustic radiation model is: ； The vibration impact model is: ； Where, is the acoustic radiation value; is the noise propagation coefficient, is the blade-vortex interaction noise coefficient, is the aerodynamic noise coupling coefficient; is the flight speed of the drone; is the propeller speed, , is the thrust coefficient; is the propeller radius; is the mechanical vibration cost item; is the vibration frequency of the drone, ; is the vibration acceleration of the drone, ; is the vibration sensitivity coefficient, Indicates the vibration frequency of the drone Sensitivity to vibration effects, Indicates the vibration acceleration of the drone sensitivity to vibration effects; is the vibration characteristic coefficient, Indicates the vibration frequency of the drone The flight speed of the drone The relationship coefficient between Indicates the vibration acceleration of the drone The flight speed of the drone The relationship coefficient between Step 2: Obtain drone operation data and environmental data; The UAV operation data includes propeller radius , noise propagation coefficient , vibration sensitivity coefficient , thrust coefficient , vibration characteristic coefficient and maximum vibration threshold ; Noise propagation coefficient , vibration characteristic coefficient Obtained through wind tunnel experiments; thrust coefficient Based on actual flight test; vibration sensitivity coefficient Obtained through numerical simulation; maximum vibration threshold Obtained through vibration testing; The environmental data includes a maximum acoustic threshold , wind speed Zephyr Corner ; Maximum acoustic threshold Determined according to the environmental protection regulations of the area where the drone is operating; wind speed Obtained by placing wind speed measurement points in the UAV operation area; wind angle Obtained through path planning software; Step 3: Calculate the acoustic limit speed and vibration limit speed; Substituting the UAV operation data and environmental data obtained in step 2 into the acoustic radiation model and vibration impact model to obtain the acoustic limit speed and vibration limit speed; Step 4: Calculate the maximum flight speed: Select the smaller value from the acoustic limit speed and the vibration limit speed as the maximum flight speed ; Step 5: Calculate the actual maximum flight speed: The maximum flight speed obtained from step 4 , wind speed obtained in step 3 Zephyr Corner , calculate the actual maximum flight speed .

2. The method for calculating the maximum flight speed of a drone according to claim 1, wherein: In step 2, the UAV path is first divided into multiple sub-paths, and then the UAV operation data and the environmental data under each sub-path are obtained; accordingly, in step 3, the local acoustic limit speed and local vibration limit speed of each sub-path are calculated; in step 4, for each sub-path, the smaller value is selected from its local acoustic limit speed and local vibration limit speed as the local maximum flight speed of each sub-path; in step 5, the local maximum flight speed of each sub-path, the wind speed and wind angle of each sub-path are used to calculate the local actual maximum flight speed of each sub-path.

3. The method for calculating the maximum flight speed of a drone according to claim 1, wherein: Before step 1, the UAV path is divided into multiple sub-paths. Then, for each sub-path, the method of steps 1-5 is used to solve the local actual maximum flight speed of each sub-path.

4. The method for calculating the maximum flight speed of a drone according to claim 2 or 3, wherein: The length of each subpath Use the following formula to calculate: Where, is the reference segment length; The length of the reference segment Divide the time The average distance between obstacles near the segment path is obtained through the 3D map; The safe distance of the drone is the minimum distance between the drone and obstacles during flight. is the correction factor, ranging from 0 to 1.

5. A method for calculating the flight time of a UAV for path planning, characterized in that: The following steps are involved: Step 1): Calculate the local actual maximum flight speed of each subpath using the method for calculating the maximum flight speed of the drone described in any one of claims 2 to 4; Step 2): Calculate flight time ; Where, For the The local actual maximum flight speed of the segment path; is the total number of subpaths; is an empirical parameter with a value of [0,1]; is the average distance between obstacles in the UAV's total path.

6. A UAV flight control method for path planning, characterized in that: The following steps are involved: Step 1: using the method for calculating the maximum flight speed of a drone according to any one of claims 2 to 4, calculating the local actual maximum flight speed of the drone in each subpath, and storing the subpaths and the local actual maximum flight speeds in correspondence; Step 2: The flight control system controls the UAV according to the local actual maximum flight speed of each sub-path calculated in step 1.

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