Wind-resistant control method and device for roadway unmanned vehicle

Abstract

This application proposes a wind-resistant control method and apparatus for unmanned aerial vehicles (UAVs) operating in a tunnel, comprising: constructing a dynamic model of the UAV running in the tunnel; determining the impact pressure of the UAV at the tunnel entrance based on the operating parameters generated by the UAV during its operation in the tunnel and the basic parameters of the tunnel; determining the desired trajectory of the UAV based on the impact pressure and the dynamic model, the desired trajectory including the desired position and the desired yaw signal; acquiring the current position and current navigation signal of the UAV in the tunnel; generating a yaw command corresponding to adjusting the current navigation signal to the desired yaw signal based on the position error between the desired position and the current position; and adjusting the UAV's operating attitude based on the yaw command. Thus, based on the impact pressure of the UAV at the tunnel entrance, the desired trajectory of the UAV during its operation in the tunnel is determined, thereby generating a yaw command to adjust the UAV's yaw signal, achieving wind-resistant control of the UAV's operating attitude, and ensuring the safety of the UAV when exiting the tunnel.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) technology, and more particularly to a wind-resistant control method, device, electronic equipment, and storage medium for a roadway UAV. Background Technology

[0002] Currently, multi-rotor drones are widely used in military, civilian enterprises, and daily life due to their flexibility. However, their flight environment and inherent characteristics generally involve a large number of disturbances and uncertainties. Among these, external wind has a particularly significant impact on drones. In related technologies, the main means of anti-interference control for drones under the influence of external wind include robust control methods such as H-infinity, sliding mode, active disturbance rejection, proportional-integration-differential (PID) controllers, observer-controller integrated control methods, and adaptive control methods. However, the above methods cannot estimate the random characteristics and wind interference assessment of turbulent wind fields with random characteristics, nor can they guarantee the safety of drones in turbulent wind fields. Therefore, a more reliable wind-resistant control method for drones in tunnels is urgently needed. Summary of the Invention

[0003] The first aspect of this application proposes a wind-resistant control method for a roadway unmanned aerial vehicle (UAV). The method includes: constructing a dynamic model of the UAV running in a roadway; acquiring the operating parameters generated by the UAV running in the roadway and the basic parameters of the roadway, to determine the impact pressure of the UAV at the roadway entrance based on the operating parameters and the basic parameters; determining the desired trajectory of the UAV running in the roadway according to the impact pressure and the dynamic model, wherein the desired trajectory includes a desired position and a desired yaw signal corresponding to the desired position; acquiring the current position and current navigation signal of the UAV in the roadway, and generating a yaw command corresponding to adjusting the current navigation signal into the desired yaw signal based on the position error between the desired position and the current position; and adjusting the operating attitude of the UAV according to the yaw command.

[0004] In one embodiment of this application, the step of obtaining the operating parameters generated by the UAV during its operation in the tunnel and the basic parameters of the tunnel, in order to determine the impact pressure of the UAV at the tunnel entrance based on the operating parameters and the basic parameters, includes: obtaining the operating parameters generated by the UAV during its operation in the tunnel and the basic parameters of the tunnel, wherein the operating parameters include the air pressure difference between the UAV inside and outside the tunnel and the wind speed generated by the UAV at its current flight speed, and the basic parameters include the cross-sectional area of ​​the tunnel entrance; and determining the impact pressure of the UAV at the tunnel entrance based on the air pressure difference between the UAV inside and outside the tunnel, the wind speed generated by the UAV at its current flight speed, and the cross-sectional area of ​​the tunnel entrance.

[0005] In one embodiment of this application, determining the impact pressure of the drone at the entrance of the alley based on the pressure difference between the drone and the outside of the alley, the wind speed generated by the drone at its current flight speed, and the cross-sectional area of ​​the alley entrance includes: determining the forward flight force of the drone and the wind resistance of the alley based on the pressure difference between the drone and the outside of the alley, the wind speed generated by the drone at its current flight speed, and the cross-sectional area of ​​the alley entrance; and using the sum of the pressure difference between the drone and the outside of the alley, the forward flight force of the drone, and the wind resistance of the alley as the impact pressure of the drone at the entrance of the alley.

[0006] In one embodiment of this application, the step of adjusting the operating attitude of the UAV according to the yaw command includes: obtaining the UAV pitch angle, UAV roll angle and UAV yaw angle corresponding to the current position of the UAV in the alley; and adjusting the operating attitude of the UAV according to the error between the UAV pitch angle, UAV roll angle and UAV yaw angle and the yaw command.

[0007] This application proposes a wind-resistant control method for unmanned aerial vehicles (UAVs) operating in a tunnel. A dynamic model of the UAV's operation in the tunnel is constructed. Based on the operating parameters generated by the UAV and the basic parameters of the tunnel, the impact pressure at the tunnel entrance is determined. According to the impact pressure and the dynamic model, the desired trajectory of the UAV is determined, including the desired position and the desired yaw signal. The current position and current navigation signal of the UAV in the tunnel are obtained. Based on the position error between the desired position and the current position, a yaw command corresponding to adjusting the current navigation signal to the desired yaw signal is generated. Based on the yaw command, the UAV's operating attitude is adjusted. Thus, based on the impact pressure at the tunnel entrance, the desired trajectory of the UAV operating in the tunnel is determined, and yaw commands are generated to adjust the UAV's yaw, achieving wind-resistant control of the UAV's operating attitude and ensuring the safety of the UAV when exiting the tunnel.

[0008] A second aspect of this application provides a wind-resistant control device for a roadway unmanned aerial vehicle (UAV). The device includes: a construction module for establishing a dynamic model of the UAV running in the roadway; a first determination module for acquiring operating parameters generated by the UAV running in the roadway and basic parameters of the roadway, to determine the impact pressure of the UAV at the roadway entrance based on the operating parameters and basic parameters; a second determination module for determining the desired trajectory of the UAV running in the roadway according to the impact pressure and the dynamic model, wherein the desired trajectory includes a desired position and a desired yaw signal corresponding to the desired position; a generation module for acquiring the current position and current navigation signal of the UAV in the roadway, and generating a yaw command corresponding to adjusting the current navigation signal into the desired yaw signal based on the position error between the desired position and the current position; and a control module for controlling the operating attitude of the UAV according to the yaw command.

[0009] In one embodiment of this application, the first determining module includes: an acquisition unit, configured to acquire operating parameters generated by the UAV while it is running in the tunnel and basic parameters of the tunnel, wherein the operating parameters include the air pressure difference between the UAV inside and outside the tunnel and the wind speed generated by the UAV at its current flight speed, and the basic parameters include the cross-sectional area of ​​the tunnel entrance; and a determining unit, configured to determine the impact pressure of the UAV at the tunnel entrance based on the air pressure difference between the UAV inside and outside the tunnel, the wind speed generated by the UAV at its current flight speed, and the cross-sectional area of ​​the tunnel entrance.

[0010] In one embodiment of this application, the determining unit is specifically used to: determine the forward flight force of the drone and the wind resistance of the tunnel based on the air pressure difference between the drone and the inside and outside of the tunnel, the wind speed generated by the drone at its current flight speed, and the cross-sectional area of ​​the tunnel entrance; and use the sum of the air pressure difference between the drone and the inside and outside of the tunnel, the forward flight force of the drone, and the wind resistance of the tunnel as the impact pressure of the drone at the tunnel entrance.

[0011] In one embodiment of this application, the control unit is specifically used to: obtain the drone's pitch angle, roll angle, and yaw angle corresponding to the drone's current position in the alley; and adjust the drone's operating attitude based on the error between the drone's pitch angle, roll angle, and yaw angle and the yaw command.

[0012] This application proposes a wind-resistant control device for a drone operating in a tunnel. It constructs a dynamic model of the drone's operation in the tunnel, determines the impact pressure at the tunnel entrance based on the drone's operating parameters and the tunnel's basic parameters, and determines the drone's desired trajectory based on the impact pressure and the dynamic model. The desired trajectory includes the desired position and desired yaw signal. It acquires the drone's current position and current navigation signal in the tunnel, and generates a yaw command corresponding to adjusting the current navigation signal to the desired yaw signal based on the position error between the desired position and the current position. Based on the yaw command, it adjusts the drone's operating attitude. Thus, based on the impact pressure at the tunnel entrance, the desired trajectory of the drone operating in the tunnel is determined, generating yaw commands to control the drone, achieving wind-resistant control of the drone's operating attitude, and ensuring the drone's safety when exiting the tunnel.

[0013] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the wind-resistant control method for a roadway drone according to the embodiments of this application.

[0014] The fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, provides a wind-resistant control method for a roadway drone according to the embodiments of this application.

[0015] Other effects of the above-mentioned alternative methods will be described below in conjunction with specific embodiments. Attached Figure Description

[0016] Figure 1 This is a schematic flowchart of a wind-resistant control method for a roadway drone provided in an embodiment of this application;

[0017] Figure 2 This is a schematic flowchart of another wind-resistant control method for a roadway drone provided in an embodiment of this application;

[0018] Figure 3 This is an example diagram of a drone flying in a tunnel, provided in an embodiment of this application.

[0019] Figure 4 This is an example diagram illustrating the calculation of impact pressure on a drone provided in an embodiment of this application;

[0020] Figure 5 This is a diagram of a wind-resistant control device for a roadway drone provided in an embodiment of this application;

[0021] Figure 6 This is a schematic diagram of the structure of a wind-resistant control device for a roadway drone provided in an embodiment of this application;

[0022] Figure 7 This is a block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0023] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0024] The wind-resistant control method, apparatus, electronic device, and storage medium for a roadway drone according to embodiments of this application are described below with reference to the accompanying drawings.

[0025] Figure 1 This is a flowchart illustrating a wind-resistant control method for a roadway drone provided in this embodiment. It should be noted that the executing entity of the wind-resistant control method for the roadway drone provided in this embodiment is the wind-resistant control device of the roadway drone. This wind-resistant control device can be implemented by software and / or hardware. In this embodiment, the wind-resistant control device can be configured in an electronic device, which may include a server. This embodiment does not specifically limit the type of electronic device.

[0026] Figure 1 This is a schematic flowchart of a wind-resistant control method for a roadway drone provided in an embodiment of this application.

[0027] like Figure 1 As shown, the wind resistance control method for this tunnel UAV may include:

[0028] Step 101: Construct a dynamic model of the drone operating in the alleyway.

[0029] Optionally, the drone may be a multi-rotor drone, but is not limited thereto, and this embodiment does not specifically limit it.

[0030] In some embodiments, one way to construct a dynamic model of a drone operating in a tunnel is to establish a rigid body kinematics and dynamics model of the multi-rotor drone, taking into account the wind field influence of the multi-rotor drone, as a dynamic model of the drone operating in the tunnel.

[0031] Step 102: Obtain the operating parameters and basic parameters of the tunnel generated by the UAV while it is running in the tunnel, so as to determine the impact pressure of the UAV at the tunnel entrance based on the operating parameters and basic parameters.

[0032] Optionally, the operating parameters generated by the drone while it is running in the tunnel may include, but are not limited to, the air pressure difference between the drone and the inside and outside of the tunnel and the wind speed generated by the drone at its current flight speed. This embodiment does not specifically limit these parameters.

[0033] Optionally, the basic parameters of the tunnel may include, but are not limited to, the cross-sectional area of ​​the tunnel entrance; this embodiment does not specifically limit this.

[0034] In some embodiments, to ensure the reliability of the impact pressure of the drone at the entrance of the alley, multiple sets of operating parameters and basic parameters can be set for testing to improve the accuracy of the impact pressure.

[0035] Step 103: Based on the impact pressure and dynamic model, determine the expected trajectory of the UAV running in the alleyway, wherein the expected trajectory includes the expected position and the expected yaw signal corresponding to the expected position.

[0036] In some embodiments, the position, velocity, Euler angles of the UAV in the inertial coordinate system and the angular velocity, torque, moment of inertia, gyroscopic torque generated by the rotation of the UAV rotor, and wind disturbance can be determined based on the impact pressure and dynamic model, thereby determining the desired position and desired yaw signal of the UAV when it is running in the tunnel, but not limited to these.

[0037] Step 104: Obtain the current position and current navigation signal of the UAV in the alleyway, and generate the yaw command corresponding to the adjustment of the current navigation signal into the desired yaw signal based on the position error between the desired position and the current position.

[0038] Optionally, a position tracker can be installed on the drone to enable real-time tracking of the drone's current position and current navigation signals in the alleyway, but this is not the only option.

[0039] In some embodiments, to ensure the reliability of yaw commands, the yaw command can be generated by tracking the wind speed of the UAV in the tunnel, combining the flight speed and the position error between the desired position and the current position, so as to improve the accuracy of the yaw command and ensure the safety of the UAV.

[0040] Step 105: Adjust the drone's operating attitude according to the yaw command.

[0041] In some embodiments, one way to control the operating attitude of a UAV according to a yaw command is to obtain the UAV pitch angle, UAV roll angle, and UAV yaw angle corresponding to the current position of the UAV in the alley, and to control the operating attitude of the UAV based on the error between the UAV pitch angle, UAV roll angle, UAV yaw angle and the yaw command.

[0042] Specifically, the desired pitch angle, desired roll angle, and desired yaw angle of the UAV can be determined based on the desired pitch and roll commands in the yaw command. Then, by combining the errors between the UAV's pitch angle, roll angle, and yaw angle and the desired pitch angle, roll angle, and yaw angle, the UAV's pitch angle can be adjusted to the desired pitch angle, the roll angle can be adjusted to the desired roll angle, and the yaw angle can be adjusted to the desired yaw angle, thereby completing the control of the UAV's operating attitude.

[0043] This application proposes a wind-resistant control method for unmanned aerial vehicles (UAVs) operating in a tunnel. A dynamic model of the UAV's operation in the tunnel is constructed. Based on the operating parameters generated by the UAV and the basic parameters of the tunnel, the impact pressure at the tunnel entrance is determined. According to the impact pressure and the dynamic model, the desired trajectory of the UAV is determined, including the desired position and the desired yaw signal. The current position and current navigation signal of the UAV in the tunnel are obtained. Based on the position error between the desired position and the current position, a yaw command corresponding to adjusting the current navigation signal to the desired yaw signal is generated. Based on the yaw command, the UAV's operating attitude is adjusted. Thus, based on the impact pressure at the tunnel entrance, the desired trajectory of the UAV operating in the tunnel is determined, and yaw commands are generated to adjust the UAV's yaw, achieving wind-resistant control of the UAV's operating attitude and ensuring the safety of the UAV when exiting the tunnel.

[0044] Figure 2 This is a flowchart illustrating another wind-resistant control method for a roadway drone provided in this application embodiment. The method may include:

[0045] Step 201: Construct a dynamic model of the drone operating in the alleyway.

[0046] It should be noted that the specific implementation of step 201 can be found in the relevant description in the above embodiments.

[0047] Step 202: Obtain the operating parameters and basic parameters of the tunnel generated by the UAV during its operation in the tunnel. The operating parameters include the air pressure difference between the UAV inside and outside the tunnel and the wind speed generated by the UAV at its current flight speed. The basic parameters include the cross-sectional area of ​​the tunnel entrance.

[0048] Alternatively, the pressure difference between the drone and the inside and outside of the tunnel can be addressed by installing barometers inside and outside the tunnel, such as... Figure 3 As shown, the pressure change inside and outside the tunnel when the drone enters can be calculated using a barometer as the pressure difference, but it is not limited to this.

[0049] Optionally, the wind speed generated by the drone at its current flight speed can be measured by an anemometer installed on the drone at different speeds during operation, but this is not the only option.

[0050] Optionally, the cross-sectional area at the tunnel entrance can be obtained by establishing a three-dimensional model of the tunnel using sensors, and the cross-sectional area of ​​the tunnel can be calculated using this three-dimensional model, but this is not the only option.

[0051] Step 203: Determine the impact pressure of the drone at the entrance of the alley based on the air pressure difference between the drone inside and outside the alley, the wind speed generated by the drone at its current flight speed, and the cross-sectional area of ​​the alley entrance.

[0052] In some embodiments, the air pressure difference between the inside and outside of the tunnel, the wind speed generated by the drone at its current flight speed, and the cross-sectional area at the tunnel entrance all have a certain impact on the impact pressure of the drone at the tunnel entrance, as shown in Table 1:

[0053] Table 1 Factors affecting impact pressure

[0054]

[0055] The wind speed generated by the drone at its current flight speed can include the wind speed generated by the drone's rotor when there is no wind. and wind speed in the alley

[0056] It is understandable that, to better determine the impact pressure of the drone at the tunnel entrance, a cuboid of the same volume as the drone could be used to represent it, such as... Figure 4 As shown, the forces acting on the surfaces of the cuboid during motion can be measured, or pressure gauges can be directly installed on the drone to measure the impact pressure when entering and exiting the tunnel, and impact pressure curves can be plotted for different flight speeds of the drone (the trends of each curve should be similar, but the range of pressure values ​​should differ). Figure 4 In this context, Δt represents the unit of time.

[0057] Specifically, through multiple flight experiments, the following can be measured: ① the impact pressure generated by different UAV flight speeds under the same air pressure difference; ② the impact pressure under different air pressure differences at the same UAV flight speed; ③ the impact pressure of the UAV at different locations in the tunnel under the same air pressure difference and the same UAV speed; ④ the impact pressure under different wind speeds at the same air pressure difference, the same UAV speed, and the same tunnel location. The above experimental results can be listed in a table to provide interference when the UAV is entering or leaving the tunnel to resist wind.

[0058] In some embodiments, the impact pressure can be expressed as the sum of the air pressure difference between the UAV inside and outside the tunnel, the forward flight force of the UAV, and the wind resistance of the tunnel, or as the sum of a polynomial of the three. The impact pressure f can be calculated as follows:

[0059]

[0060] or

[0061] Where l0, m0, and n0 are powers, which are positive integers, and m1 is the mass of the UAV. S1 represents the acceleration generated by the drone's rotor, S1 represents the drone's frontal area, and k represents the acceleration generated by the rotor. p ,k1,k2,k3,k pl ,k 1m ,k 2n ,k 3n is a coefficient.

[0062] Among them, the wind force on an object = windward area * windward area coefficient * wind speed resistance, and wind speed resistance = coefficient K * wind speed, where K changes with wind speed and is called step change.

[0063] Step 204: Based on the impact pressure and dynamic model, determine the expected trajectory of the UAV running in the tunnel, wherein the expected trajectory includes the expected position and the expected yaw signal corresponding to the expected position.

[0064] Step 205: Obtain the current position and current navigation signal of the UAV in the alleyway, and generate the yaw command corresponding to the adjustment of the current navigation signal into the desired yaw signal based on the position error between the desired position and the current position.

[0065] Step 206: Adjust the drone's operating attitude according to the yaw command.

[0066] This application proposes a wind-resistant control method for unmanned aerial vehicles (UAVs) operating in a tunnel. It constructs a dynamic model of the UAV's operation in the tunnel, acquiring the operational parameters generated by the UAV and the basic parameters of the tunnel. The operational parameters include the air pressure difference between the UAV and the outside of the tunnel and the wind speed generated by the UAV at its current flight speed. The basic parameters include the cross-sectional area of ​​the tunnel entrance. Based on the air pressure difference between the UAV and the outside of the tunnel, the wind speed generated by the UAV at its current flight speed, and the cross-sectional area of ​​the tunnel entrance, the impact pressure at the tunnel entrance is determined. Based on the impact pressure and the dynamic model, the desired trajectory of the UAV is determined, including the desired position and the desired yaw signal. The current position and current navigation signal of the UAV in the tunnel are acquired. Based on the position error between the desired position and the current position, a yaw command corresponding to adjusting the current navigation signal to the desired yaw signal is generated. Based on the yaw command, the UAV's operating attitude is adjusted. Thus, based on the impact pressure at the tunnel entrance, the desired trajectory of the UAV operating in the tunnel is accurately determined, enabling the generation of yaw commands to adjust the UAV, achieving impact pressure interference assessment, and ensuring the safety of the UAV when exiting the tunnel.

[0067] In summary, to better understand the wind-resistant control method for roadway drones of this application, the wind-resistant control method for roadway drones can also be applied to a wind-resistant control device for roadway drones, as shown in the diagram. Figure 5 As shown, Figure 5 This diagram illustrates a wind-resistant control device for a roadway drone proposed in this application. Specifically, the device is applied in a turbulent wind field. The device may include a multi-rotor drone, a filter, an attitude controller, an inner-loop observer, a position controller, an outer-loop observer, and a command generation module. Specifically, when the multi-rotor drone operates in the turbulent wind field of a roadway, the filter precisely filters the impact pressure on the drone to determine the desired pose, which is then input to the outer-loop observer, the inner-loop controller, and the command generation module. The position controller determines the current position and then the position error between the current position and the desired position. Based on the position error, the command generation module generates a corresponding yaw command to adjust the pose. Based on this yaw command, the position controller adjusts the position, and the attitude controller adjusts the drone's pose, achieving precise control of the drone's pose.

[0068] Figure 6 This is a schematic diagram of the structure of a wind-resistant control device for a roadway drone provided in an embodiment of this application.

[0069] like Figure 6 As shown, the monitoring device 600 for this business data includes: a construction module 601, a first determination module 602, a second determination module 603, a generation module 604, and a control module 605, wherein:

[0070] Module 601 is used to build a dynamic model of the UAV running in the tunnel;

[0071] The first determining module 602 is used to acquire the operating parameters generated by the UAV when it runs in the tunnel and the basic parameters of the tunnel, so as to determine the impact pressure of the UAV at the tunnel entrance based on the operating parameters and the basic parameters.

[0072] The second determining module 603 is used to determine the expected trajectory of the UAV running in the alleyway based on the impact pressure and dynamic model, wherein the expected trajectory includes the expected position and the expected yaw signal corresponding to the expected position;

[0073] The generation module 604 is used to acquire the current position and current navigation signal of the UAV in the alley, and generate a yaw command corresponding to the adjustment of the current navigation signal into the desired yaw signal based on the position error between the desired position and the current position.

[0074] The control module 605 is used to control the operating attitude of the UAV according to the yaw command.

[0075] Furthermore, in one possible implementation of this application embodiment, the first determining module 602 includes:

[0076] The acquisition unit is used to acquire the operating parameters generated by the UAV when it runs in the tunnel and the basic parameters of the tunnel. The operating parameters include the air pressure difference between the UAV inside and outside the tunnel and the wind speed generated by the UAV at its current flight speed. The basic parameters include the cross-sectional area of ​​the tunnel entrance.

[0077] The determining unit is used to determine the impact pressure of the drone at the entrance of the alley based on the air pressure difference between the drone inside and outside the alley, the wind speed generated by the drone at its current flight speed, and the cross-sectional area of ​​the alley entrance.

[0078] Furthermore, in one possible implementation of this application embodiment, the determining unit is specifically used for:

[0079] Based on the air pressure difference between the UAV inside and outside the tunnel, the wind speed generated by the UAV at its current flight speed, and the cross-sectional area at the tunnel entrance, the forward flight force of the UAV and the wind resistance of the tunnel are determined.

[0080] The pressure difference between the drone inside and outside the tunnel, the forward flight force of the drone, and the wind resistance of the tunnel are taken as the impact pressure of the drone at the entrance of the tunnel.

[0081] Furthermore, in one possible implementation of this application embodiment, the control unit is specifically used for:

[0082] Obtain the drone's pitch angle, roll angle, and yaw angle corresponding to its current position in the alleyway;

[0083] The drone's operating attitude is adjusted based on the error between the drone's pitch angle, roll angle, yaw angle, and yaw command.

[0084] This application proposes a wind-resistant control device for a drone operating in a tunnel. It constructs a dynamic model of the drone's operation in the tunnel, determines the impact pressure at the tunnel entrance based on the drone's operating parameters and the tunnel's basic parameters, and determines the drone's desired trajectory based on the impact pressure and the dynamic model. The desired trajectory includes the desired position and desired yaw signal. It acquires the drone's current position and current navigation signal in the tunnel, and generates a yaw command corresponding to adjusting the current navigation signal to the desired yaw signal based on the position error between the desired position and the current position. Based on the yaw command, it adjusts the drone's operating attitude. Thus, based on the impact pressure at the tunnel entrance, the desired trajectory of the drone operating in the tunnel is determined, generating yaw commands to control the drone, achieving wind-resistant control of the drone's operating attitude, and ensuring the drone's safety when exiting the tunnel.

[0085] To implement the above embodiments, this application also proposes an electronic device, such as... Figure 7 The diagram shown is a block diagram of an electronic device according to an embodiment of this application.

[0086] like Figure 7 As shown, the electronic device includes:

[0087] The memory 701, the processor 702, and computer instructions stored in the memory 701 and executable on the processor 702.

[0088] When the processor 702 executes instructions, it implements the wind-resistant control method for the roadway UAV provided in the above embodiments.

[0089] Furthermore, electronic devices also include:

[0090] Communication interface 703 is used for communication between memory 701 and processor 702.

[0091] Memory 701 is used to store computer instructions that can be executed on processor 702.

[0092] The memory 701 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0093] The processor 702 is used to implement the wind-resistant control method for the roadway UAV in the above embodiment when executing the program.

[0094] If the memory 701, processor 702, and communication interface 703 are implemented independently, then the communication interface 703, memory 701, and processor 702 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 7 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0095] Optionally, in a specific implementation, if the memory 701, processor 702, and communication interface 703 are integrated on a single chip, then the memory 701, processor 702, and communication interface 703 can communicate with each other through an internal interface.

[0096] The processor 702 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0097] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0098] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0099] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A wind-resistant control method of a roadway drone, characterized by, The method includes: Construct a dynamic model of the drone operating in the alleyway; The system acquires the operating parameters generated by the drone while it is running in the tunnel and the basic parameters of the tunnel. The operating parameters include the air pressure difference between the drone and the inside and outside of the tunnel and the wind speed generated by the drone at its current flight speed. The basic parameters include the cross-sectional area of ​​the tunnel entrance. Based on the air pressure difference between the UAV inside and outside the tunnel, the wind speed generated by the UAV at its current flight speed, and the cross-sectional area at the tunnel entrance, the forward flight force of the UAV and the wind resistance of the tunnel are determined. The pressure difference between the drone inside and outside the tunnel, the forward flight force of the drone, and the wind resistance of the tunnel are taken as the impact pressure of the drone at the entrance of the tunnel. Based on the impact pressure and dynamic model, the expected trajectory of the UAV running in the tunnel is determined, wherein the expected trajectory includes the expected position and the expected yaw signal corresponding to the expected position; The current position and current navigation signal of the UAV in the alley are obtained, and based on the position error between the desired position and the current position, a yaw command is generated to adjust the current navigation signal into the desired yaw signal. The operating attitude of the UAV is adjusted according to the yaw command.

2. The method of claim 1, wherein, The step of adjusting the operating attitude of the UAV according to the yaw command includes: Obtain the drone's pitch angle, roll angle, and yaw angle corresponding to its current position in the alleyway; The drone's operating attitude is adjusted based on the error between the drone's pitch angle, roll angle, yaw angle, and yaw command.

3. A wind resistant control device for a roadway drone, characterized by, The device includes: Modules are used to build dynamic models of drones operating in tunnels; The first determining module is used to acquire the operating parameters generated by the UAV when it runs in the tunnel and the basic parameters of the tunnel, so as to determine the impact pressure of the UAV at the tunnel entrance based on the operating parameters and the basic parameters. The second determining module is used to determine the expected trajectory of the UAV running in the alleyway based on the impact pressure and dynamic model, wherein the expected trajectory includes the expected position and the expected yaw signal corresponding to the expected position; The generation module is used to acquire the current position and current navigation signal of the UAV in the alley, and generate a yaw command corresponding to the adjustment of the current navigation signal into the desired yaw signal based on the position error between the desired position and the current position. The control module is used to control the operating attitude of the UAV according to the yaw command; The first determining module includes: The acquisition unit is used to acquire the operating parameters generated by the UAV when it runs in the tunnel and the basic parameters of the tunnel. The operating parameters include the air pressure difference between the UAV inside and outside the tunnel and the wind speed generated by the UAV at its current flight speed. The basic parameters include the cross-sectional area of ​​the tunnel entrance. The determining unit is used to determine the forward flight force of the UAV and the wind resistance of the tunnel based on the air pressure difference between the UAV inside and outside the tunnel, the wind speed generated by the UAV at its current flight speed, and the cross-sectional area of ​​the tunnel entrance. The pressure difference between the drone inside and outside the tunnel, the forward flight force of the drone, and the wind resistance of the tunnel are taken as the impact pressure of the drone at the entrance of the tunnel.

4. The apparatus of claim 3, wherein, The control module is specifically used for: Obtain the drone's pitch angle, roll angle, and yaw angle corresponding to its current position in the alleyway; The drone's operating attitude is adjusted based on the error between the drone's pitch angle, roll angle, yaw angle, and yaw command.

5. An electronic device, comprising: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the program, it implements the wind-resistant control method for a roadway unmanned aerial vehicle as described in any one of claims 1-2.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the wind-resistant control method for a roadway drone as described in any of claims 1-2.

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