Unmanned aerial vehicle landing method and device and unmanned aerial vehicle

Abstract

The invention provides an unmanned aerial vehicle landing method and device and an unmanned aerial vehicle, and the method comprises the steps: obtaining base station positioning information and visual positioning information, the base station positioning information being positioning information measured by a fixed base station on a mobile platform, and the visual positioning information being obtained by photographing a landing reference identifier on the mobile platform by the unmanned aerial vehicle; and performing autonomous landing according to the base station positioning information and the visual positioning information. In the implementation process of the scheme, the base station positioning information measured by the fixed base station on the mobile platform and the relative position information of the real-time environment change in the visual positioning information are combined, so that the base station positioning information and the relative position information complement each other, errors caused by a single information source are reduced, and the positioning accuracy is improved. Therefore, the unmanned aerial vehicle can realize the optimal landing trajectory according to the base station positioning information and the visual positioning information, and the landing precision of the unmanned aerial vehicle is improved.

Description

Technical Field

[0001] The present application relates to the technical field of aircraft control and unmanned aerial vehicle control, and in particular, to a method and device for landing an unmanned aerial vehicle and an unmanned aerial vehicle. Background Art

[0002] At present, most drones rely on the location information provided by the remote control or ground control station as the return point. However, this method is difficult to land accurately on the platform provided by a moving vehicle or ship under certain conditions. For example: suppose a drone is used for river mapping. The drone takes off from a moving ship and needs to return and land on the same ship after completing the mission. When the drone takes off, the position of the remote control (or ground control station) is recorded as the return point. However, during the drone's mission, the ship may have sailed a distance, and even if it has not sailed, it may move to a different location due to factors such as water flow and wind. Due to the movement of the ship, the original recorded return point is no longer accurate, resulting in the drone being unable to accurately return to the ship. Summary of the invention

[0003] The purpose of the embodiments of the present application is to provide a drone landing method, device and drone, which are used to improve the problem that drones are difficult to land accurately.

[0004] The embodiment of the present application provides a method for landing a drone, including: obtaining base station positioning information and visual positioning information, the base station positioning information is the positioning information measured by a fixed base station on a mobile platform, and the visual positioning information is obtained by the drone photographing a landing reference mark on the mobile platform; and autonomous landing is performed according to the base station positioning information and the visual positioning information. In the implementation process of the above scheme, by combining the base station positioning information measured by a fixed base station on a mobile platform and the relative position information of real-time environmental changes in the visual positioning information, the two complement each other, reducing the error caused by a single information source, so that the drone can achieve the most optimized landing trajectory according to the base station positioning information and the visual positioning information, thereby improving the accuracy of the drone landing.

[0005] Optionally, in an embodiment of the present application, the base station positioning information includes: the real-time absolute position of the mobile platform; before obtaining the base station positioning information, it also includes: if the signal quality of the fixed base station is detected to be lower than a preset quality threshold, or the distance between the real-time absolute position of the drone and the mobile platform is less than a preset distance threshold, a frequency increase instruction is sent to the fixed base station so that the fixed base station increases the sending frequency of the base station positioning information. In the implementation process of the above scheme, by introducing a fixed base station signal quality detection mechanism and a dynamic adjustment of the sending frequency mechanism, the drone can obtain more frequent and accurate positioning information, which helps to reduce positioning errors, thereby improving the positioning accuracy and reliability of the drone. Further, by dynamically adjusting the sending frequency of the fixed base station, the system can provide more timely positioning information at the critical moment of landing, enhancing the real-time response capability of the system, which is particularly important for autonomous landing tasks that require rapid adjustment of attitude and speed, because a higher sending frequency means a shorter data update cycle, reducing the control lag caused by data delay, thereby improving the response speed and control accuracy of the entire system.

[0006] Optionally, in an embodiment of the present application, obtaining base station positioning information includes: receiving the real-time absolute position of the mobile platform, the real-time absolute position is sent by the remote control of the drone after being obtained from the fixed base station. In the implementation process of the above scheme, through the remote control as an intermediary, the system can more flexibly adapt to different communication environments and network topologies. Since many existing drone systems are already equipped with remote controls, this design can make full use of existing hardware without adding additional complexity or cost, simplifying the integration and deployment of the system, thereby enhancing the flexibility and scalability of the system.

[0007] Optionally, in an embodiment of the present application, the base station positioning information also includes: the real-time absolute speed of the mobile platform; autonomous landing according to the base station positioning information and the visual positioning information, including: controlling the current speed of the drone according to the real-time absolute speed of the mobile platform so that the drone and the landing reference mark are relatively stationary; after the drone and the landing reference mark are relatively stationary, autonomous landing is performed according to the visual positioning information. In the implementation process of the above scheme, by obtaining the absolute speed of the mobile platform in real time and adjusting the speed of the drone accordingly, the drone can remain relatively stationary with the mobile platform, which is crucial for precise landing, especially when landing on a mobile platform (such as a ship or vehicle), which can significantly improve the safety and accuracy of the landing. Furthermore, after the drone and the landing reference mark are relatively stationary, the visual positioning information is further used for autonomous landing, ensuring the high accuracy of the final landing. The visual positioning information provides high-frequency and relative positioning information, which makes up for the deficiency of low-frequency updates of the RTK base station and improves the robustness of the overall positioning.

[0008] Optionally, in an embodiment of the present application, the visual positioning information includes: the relative position and relative speed between the drone and the landing reference mark; autonomous landing is performed according to the visual positioning information, including: inputting the relative position and relative speed into the proportional-integral-differential PID controller of the drone respectively, so that the PID controller uses the relative position as the outer loop parameter and the relative speed as the inner loop parameter to control the drone to land on the mobile platform. In the implementation process of the above scheme, a dual closed-loop control system is formed by using the relative position as the outer loop parameter and the relative speed as the inner loop parameter. The outer loop ensures that the drone gradually approaches the target position, while the inner loop quickly adjusts the speed to maintain stability and avoid oscillation or overshoot, so that the PID controller can dynamically adjust the attitude and speed of the drone according to the real-time relative position and relative speed errors to ensure that it accurately tracks the position changes of the landing reference mark, thereby improving the landing accuracy and stability of the drone.

[0009] Optionally, in an embodiment of the present application, autonomous landing is performed based on base station positioning information and visual positioning information, including: determining the return point based on the real-time absolute position of the mobile platform; after the drone reaches the return point, autonomous landing is performed based on the visual positioning information. In the implementation of the above scheme, by dividing the landing process into two stages, first using the high-precision absolute position information provided by the base station to ensure that the drone can accurately reach the return point, and then performing precise landing based on the local detail information provided by the visual positioning information, this dual positioning method significantly improves the accuracy and reliability of landing.

[0010] Optionally, in an embodiment of the present application, autonomous landing is performed according to the base station positioning information and the visual positioning information, including: if the base station positioning information and the visual positioning information cannot be obtained, the drone is controlled to fly to the alternate return point after hovering for a preset period of time, and the alternate return point is used to make the drone try to land again. In the implementation process of the above scheme, when key positioning information such as the base station positioning information and the visual positioning information are missing, the system will not blindly continue to try to land, but will adopt a safe hover and fly to the alternate return point, which significantly reduces the risk of collision or crash. The existence of the alternate return point provides additional safety protection, ensuring that even in extreme cases, the drone has a safe landing option, enhancing the safety and reliability of the system.

[0011] Optionally, in an embodiment of the present application, autonomous landing is performed according to the base station positioning information and the visual positioning information, including: determining the state vector of the UAV at the current moment according to the base station positioning information and the visual positioning information; obtaining the state vector at the previous moment, and establishing a state transfer equation according to the state vector at the previous moment and the state vector at the current moment; determining the covariance matrix of the estimated error at the current moment and the covariance matrix of the process noise according to the state vector at the previous moment and the state transfer equation; calculating the Kalman filter gain according to the total observation matrix constructed according to the base station positioning information and the visual positioning information, the covariance matrix of the estimated error at the current moment, and the covariance matrix of the process noise; fusing the base station positioning information and the visual positioning information according to the Kalman filter gain to obtain fused positioning information; and forwarding the fused positioning information to the flight control system of the UAV, so that the flight control system controls the UAV to land on the mobile platform.

[0012] In the implementation of the above scheme, the base station positioning information (high precision but low frequency) and the visual positioning information (high frequency but relative) are weightedly fused through the Kalman filter gain, which fully utilizes the advantages of the two sensors and significantly improves the positioning accuracy and robustness. In addition, the Kalman filter gain dynamically adjusts the weights according to the prediction error covariance matrix and the observation noise covariance matrix to ensure that the system can provide the best estimate under different conditions, thereby enhancing adaptability and flexibility.

[0013] An embodiment of the present application also provides a UAV landing device, which is applied to a UAV, including: an information acquisition module, used to obtain base station positioning information and visual positioning information, the base station positioning information is the positioning information measured by a fixed base station on the mobile platform, and the visual positioning information is obtained by the UAV photographing the landing reference mark on the mobile platform; an autonomous landing module, used to perform autonomous landing according to the base station positioning information and the visual positioning information.

[0014] Optionally, in an embodiment of the present application, the base station positioning information includes: the real-time absolute position of the mobile platform; the UAV landing device also includes: an instruction sending module, which is used to send a frequency increase instruction to the fixed base station if it is detected that the signal quality of the fixed base station is lower than a preset quality threshold, or the distance between the real-time absolute position of the UAV and the mobile platform is less than a preset distance threshold, so that the fixed base station increases the sending frequency of the base station positioning information.

[0015] Optionally, in an embodiment of the present application, the information acquisition module includes: an absolute position receiving submodule, which is used to receive the real-time absolute position of the mobile platform, and the real-time absolute position is sent after being acquired by the remote control of the drone from the fixed base station.

[0016] Optionally, in an embodiment of the present application, the base station positioning information also includes: the real-time absolute speed of the mobile platform; an autonomous landing module, including: a speed control submodule, used to control the current speed of the UAV according to the real-time absolute speed of the mobile platform so that the UAV and the landing reference mark are relatively stationary; an autonomous landing submodule, used to perform autonomous landing according to the visual positioning information after the UAV and the landing reference mark are relatively stationary.

[0017] Optionally, in an embodiment of the present application, the visual positioning information includes: the relative position and relative speed between the UAV and the landing reference mark; the autonomous landing submodule includes: a PID controlled landing unit, used to input the relative position and relative speed into the proportional-integral-differential PID controller of the UAV respectively, so that the PID controller uses the relative position as the outer loop parameter and the relative speed as the inner loop parameter to control the UAV to land on the mobile platform.

[0018] Optionally, in an embodiment of the present application, the autonomous landing module includes: a return point determination submodule, which determines the return point according to the real-time absolute position of the mobile platform; and an autonomous landing submodule, which is also used to perform autonomous landing according to visual positioning information after the drone reaches the return point.

[0019] Optionally, in an embodiment of the present application, the autonomous landing module includes: an alternate landing control submodule, which is used to control the drone to fly to an alternate landing return point after the drone has hovered for a preset period of time if neither the base station positioning information nor the visual positioning information can be obtained. The alternate landing return point is used to make the drone attempt to land again.

[0020] Optionally, in an embodiment of the present application, the autonomous landing module includes: a state vector determination submodule, which is used to determine the state vector of the drone at the current moment based on the base station positioning information and the visual positioning information; a transfer equation establishment submodule, which is used to obtain the state vector at the previous moment, and establish a state transfer equation based on the state vector at the previous moment and the state vector at the current moment; a variance matrix acquisition submodule, which is used to determine the covariance matrix of the estimated error at the current moment and the covariance matrix of the process noise based on the state vector at the previous moment and the state transfer equation; a Kalman filter gain calculation submodule, which is used to calculate the Kalman filter gain based on the total observation matrix constructed by the base station positioning information and the visual positioning information, the covariance matrix of the estimated error at the current moment, and the covariance matrix of the process noise; a positioning information fusion submodule, which is used to fuse the base station positioning information and the visual positioning information according to the Kalman filter gain to obtain fused positioning information; a positioning information forwarding submodule, which is used to forward the fused positioning information to the flight control system of the drone, so that the flight control system controls the drone to land on the mobile platform.

[0021] An embodiment of the present application also provides a drone, including: a processor and a memory, the memory storing machine-readable instructions executable by the processor, and the machine-readable instructions executing the method described above when executed by the processor.

[0022] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described above is executed.

[0023] The embodiment of the present application also provides a computer program product, including: a computer program or a computer instruction, and the computer program or the computer instruction executes the method described above when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 A schematic diagram of a drone landing system provided by an embodiment of the present application is shown;

[0026] Figure 2 A schematic diagram of a process flow of a drone landing method provided by an embodiment of the present application is shown;

[0027] Figure 3 A schematic diagram of the structure of a UAV landing device provided in an embodiment of the present application is shown;

[0028] Figure 4 A schematic diagram of the structure of a drone provided in an embodiment of the present application is shown.

[0029] Icons: 100-UAV landing system; 110-UAV; 120-landing reference mark; 130-fixed base station; 140-remote controller. DETAILED DESCRIPTION

[0030] To make the purpose, technical scheme and advantages of the embodiment of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present application. It should be understood that the drawings in the embodiment of the present application only serve the purpose of explanation and description, and are not used to limit the protection scope of the embodiment of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in the embodiment of the present application shows the operation implemented according to some embodiments of the embodiment of the present application. It should be understood that the operation of the flowchart can be implemented out of order, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the embodiment of the present application, or remove one or more operations from the flowchart.

[0031] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all embodiments. The components of the embodiments of the present application described and shown in the drawings generally here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the embodiments of the present application claimed, but merely represents the selected embodiments of the embodiments of the present application.

[0032] It is understandable that the "first" and "second" in the embodiments of the present application are used to distinguish similar objects. Those skilled in the art will understand that the words "first" and "second" do not limit the quantity and execution order, and the words "first" and "second" do not necessarily limit the difference. In the description of the embodiments of the present application, the term "and / or" is merely a description of the association relationship of associated objects, indicating that there may be three relationships, such as A and / or B, which can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the related objects before and after are in an "or" relationship. The term "multiple" refers to more than two (including two), and similarly, "multiple groups" refers to more than two groups (including two groups).

[0033] It should be noted that the drone landing method provided in the embodiment of the present application can be executed by a drone. The drone here refers to an aircraft with the function of executing computer programs. The aircraft here include: single-rotor drones, multi-rotor drones, hybrid-wing drones that use rotors for lifting and lowering, etc.

[0034] The following is an example of an application scenario in which the drone landing method is applicable. In some scenarios where the drone needs to land autonomously on a mobile platform, for example, drones in the river surveying industry are usually required to be able to land on a landing platform provided by a sailing ship. Usually, the drone records a preset position as the return point when it takes off. However, during the period when the drone performs flight-related tasks (such as surveying and shooting, etc.), the ship may have sailed a distance, and even if it is not sailing, it may move to different locations due to factors such as water flow and wind. Due to the movement of the ship, the original recorded return point is no longer accurate, resulting in the drone being unable to return to the ship accurately. Even if the ship is equipped with a global positioning system (GPS), the accuracy of an ordinary GPS system is usually only a few meters, which is large enough for a small drone to make it difficult for the drone to land accurately.

[0035] For the above questions, please see Figure 1 The schematic diagram of one of the drone landing systems provided by the embodiment of the present application is shown; the drone landing system 100 may include: a drone 110, a landing reference mark 120 and a fixed base station 130; wherein the drone 110 and the fixed base station 130 may communicate with each other, for example, the fixed base station 130 directly and unidirectionally sends base station positioning information to the drone 110. Optionally, the above-mentioned drone landing system 100 may also include a remote controller 140, and the drone 110 may communicate with the fixed base station 130 directly or communicate with the fixed base station 130 through the remote controller 140, for example: the fixed base station 130 sends the base station positioning information to the remote controller 140 through wireless fidelity (Wireless Fidelity, Wi-Fi), and then the remote controller 140 sends the base station positioning information to the drone through the data transmission system, so that the data transmission system of the remote controller can be directly reused, reducing the maintenance cost of the data transmission system and improving the adaptability of the drone landing scene.

[0036] The drone 110 may be a single-rotor drone, a multi-rotor drone, a hybrid-wing drone using rotors for lifting, etc. The drone 110 may obtain a visual image of the landing reference mark 120 through a camera disposed below, and then calculate the visual image to obtain visual positioning information.

[0037] The landing reference mark 120 may be a specific pattern or a specific mark, such as Figure 1 The image of the landing reference mark 120 is used by the drone to calculate and obtain visual positioning information, such as the relative position and relative speed between the drone and the landing reference mark.

[0038] The fixed base station 130 refers to a device or apparatus that is fixed on a mobile platform in some way and is used to determine the positioning information of the mobile platform, such as a real-time kinematic (RTK) base station, a global positioning system (GPS) base station, or a Beidou Navigation Satellite (BDS) base station.

[0039] It is understandable that the positioning information of the mobile platform received by the drone 110 may be the base station positioning information resent by the remote controller 140 through the data transmission system, and the positioning message received by the remote controller 140 may be sent by the fixed base station 130. Of course, in other embodiments, the positioning information of the mobile platform received by the drone 110 may be directly sent to the drone 110 by the fixed base station 130. In this case, a data transmission system may be added to the fixed base station so that the fixed base station can send the positioning information of the mobile platform to the drone 110 through the data transmission system. The above-mentioned landing reference mark 120 and the fixed base station 130 may be both set on a mobile platform. The mobile platform here refers to a platform that the drone wants to land and can move, such as a landing platform provided on a moving vehicle or a ship. In addition, the mobile platform may not be limited to the platform form, and may be other shapes and forms, such as an open box form on a vehicle or a deck provided on a ship.

[0040] See also Figure 2 The flowchart of the drone landing method provided by the embodiment of the present application is shown; the main idea of ​​the drone landing method is to combine the base station positioning information measured by the fixed base station on the mobile platform as the absolute positioning source, and the visual positioning information as the relative positioning source of the real-time environmental changes, so that the two complement each other and reduce the error caused by a single information source, thereby improving the accuracy of the drone landing. The implementation method of the above drone landing method may include:

[0041] Step S210: Acquire base station positioning information and visual positioning information. The base station positioning information is positioning information measured by a fixed base station on the mobile platform, and the visual positioning information is obtained by the drone photographing the landing reference mark on the mobile platform.

[0042] Base station positioning information refers to the positioning information measured by the fixed base station installed on the mobile platform, such as the real-time absolute position and real-time absolute speed obtained by high-precision measurement of the mobile platform. It is understandable that the above-mentioned fixed base station can be an RTK base station, a GPS base station or a BDS base station. If the fixed base station is an RTK base station, then the base station positioning information can include the real-time absolute position of the RTK base station with centimeter-level positioning accuracy obtained through the GNSS satellite signal, and transmit it to the drone in real time. The drone can be equipped with a RTK Global Navigation Satellite System (GNSS) receiver to ensure that the drone can always know the real-time absolute position and real-time absolute speed of the mobile platform measured by the fixed base station. In other words, the drone can use the latest real-time absolute position of the mobile platform as the new return point until the distance between the drone and the real-time absolute position of the mobile platform is less than the preset distance threshold, and then enter the following autonomous landing stage.

[0043] Visual positioning information refers to the positioning information obtained by calculating the image taken by the drone of a landing reference mark (such as a specific pattern or mark) on a mobile platform, such as the relative position and relative speed between the drone and the landing reference mark.

[0044] Step S220: Perform autonomous landing according to the base station positioning information and the visual positioning information.

[0045] It is understandable that when the drone reaches the return point, the return point here can be understood as the position coordinate point where the distance between the real-time absolute position of the drone and the mobile platform is less than the preset distance threshold (such as 5 meters), the drone can be guided to land autonomously based on the base station positioning information and visual positioning information, so that the drone lands at the landing reference mark (such as the marker plate) on the mobile platform. For example, a circle with the real-time absolute position of the mobile platform as the center and the preset distance threshold (such as 5 meters) as the radius, when the drone is in the circle for a preset period of time (such as 1 second), the drone can be guided to the autonomous landing stage based on the base station positioning information and visual positioning information.

[0046] In the process of implementing the above scheme, by combining the base station positioning information measured by the fixed base station on the mobile platform and the relative position information of the real-time environmental changes in the visual positioning information, the combination of the two is to combine the absolute positioning information from the base station with the relative positioning information of the visual system, so that the two complement each other, reducing the error caused by a single information source, so that the UAV can achieve the most optimized landing trajectory according to the base station positioning information and the visual positioning information, thereby improving the landing accuracy of the UAV.

[0047] As an optional implementation of the above-mentioned UAV landing method, the above-mentioned fixed base station can be used to locate the real-time absolute position of the mobile platform. Specifically, the above-mentioned fixed base station can include an RTK base station, a GPS base station or a BDS base station, and the above-mentioned base station positioning information may include: the real-time absolute position obtained by the fixed base station positioning the mobile platform. Assuming that the fixed base station is an RTK base station, the RTK base station uses the RTK technology of carrier phase differential measurement to provide centimeter-level high-precision positioning information. In the implementation process of the above-mentioned scheme, the real-time absolute position of the mobile platform is located by a fixed base station, and this information is sent to the UAV as base station positioning information, so that the UAV can maintain stable high-precision positioning throughout the landing process, reducing the landing deviation caused by positioning errors and improving the accuracy of the UAV landing.

[0048] As an optional implementation of the above-mentioned drone landing method, the above-mentioned base station positioning information may include: the real-time absolute position of the mobile platform; before obtaining the base station positioning information, a mechanism of signal quality detection and dynamic adjustment of the transmission frequency may be introduced to increase the transmission frequency of the base station positioning information. The implementation may include:

[0049] Step S201: If it is detected that the signal quality of the fixed base station is lower than the preset quality threshold, or the distance between the real-time absolute position of the UAV and the mobile platform is less than the preset distance threshold, a frequency increase instruction is sent to the fixed base station to enable the fixed base station to increase the sending frequency of the base station positioning information.

[0050] The implementation method of the above step S201 is, for example: before the drone enters autonomous landing, the communication frequency between the fixed base station and the drone can be increased first, and when the drone detects that the signal quality of the fixed base station is lower than the preset quality threshold, a frequency increase instruction can be sent to the fixed base station, so that the fixed base station increases the sending frequency of the base station positioning information until the highest sending frequency of the fixed base station is reached, so as to prepare for the drone to enter the autonomous landing stage. Alternatively, when the drone enters autonomous landing, that is, when the drone detects that the distance between the real-time absolute position of the drone and the mobile platform is less than the preset distance threshold (such as 5 meters), a frequency increase instruction is sent to the fixed base station, so that the fixed base station increases the sending frequency of the base station positioning information. The above preset distance threshold can be set according to the model of different drones and the visual range of the camera. The larger the model characterization fuselage and the larger the visual range, the preset distance threshold can be set larger, so that the drone can more easily identify the landing reference mark (such as the Marker version). By introducing the fixed base station signal quality detection mechanism and the dynamic adjustment of the sending frequency mechanism, the system can better adapt to various complex operating environments, such as different terrains, weather conditions and electromagnetic interference conditions, ensuring the stability and reliability of the system.

[0051] It is understandable that through intelligent detection and adjustment, the system can automatically optimize resource allocation according to actual needs and improve overall efficiency. For example, the transmission frequency is increased only when necessary (such as poor signal quality or close distance), avoiding unnecessary high-frequency communications, saving bandwidth and energy, and not only extending the flight time of fixed base stations and drones, but also reducing the burden on communication links.

[0052] In the implementation process of the above scheme, by detecting the signal quality of the fixed base station and taking measures when the signal quality is lower than the preset threshold, it is ensured that high-precision absolute positioning can be maintained even in complex environments (such as urban canyons or areas with tall buildings). When the distance between the UAV and the mobile platform is close to the preset threshold, the transmission frequency of the fixed base station is increased, so that the UAV can obtain more frequent and accurate positioning information, which helps to reduce positioning errors, especially in the approaching landing phase, which is crucial for safe and accurate landing. Further, by dynamically adjusting the transmission frequency of the fixed base station, the system can provide more timely positioning information at the critical moment of approaching landing, enhancing the real-time response capability of the system, which is particularly important for autonomous landing tasks that require rapid adjustment of attitude and speed, because a higher transmission frequency means a shorter data update cycle, reducing the control lag caused by data delay, thereby improving the response speed and control accuracy of the entire system.

[0053] As an optional implementation of the above step S210, the above implementation of obtaining the base station location information may include:

[0054] Step S211: The drone receives the real-time absolute position of the mobile platform, which is sent by the drone's remote controller after being acquired from the fixed base station.

[0055] It is understandable that the remote control of the drone can act as an efficient intermediate node to ensure that the base station positioning information is transmitted to the drone in a timely and accurate manner, especially in application scenarios that require high precision and low latency (such as autonomous landing). This approach can provide more reliable real-time data support, and the remote control can better coordinate the time synchronization between different devices, ensuring that all sensors and controllers work on the same time base, thereby improving the accuracy of the overall system.

[0056] For example, the implementation method of the above step S211 is as follows: Assuming that the fixed base station is an RTK base station set on a mobile platform, since the RTK base station is closely integrated with the mobile platform (for example, the RTK base station is fixedly installed on the mobile platform), the position of the RTK base station changes with the position of the mobile platform, so the RTK base station can measure the real-time absolute position of the mobile platform. Then, the real-time absolute position of the mobile platform is sent to the remote control of the drone via Wi-Fi. The remote control can receive the real-time absolute position sent by the RTK base station via Wi-Fi, and then send the real-time absolute position of the mobile platform to the drone through the data transmission system of the remote control. Finally, the drone receives the real-time absolute position sent by the remote control through the data transmission system. This approach can directly reuse the data transmission system between the drone and the remote control. Compared with installing an additional data transmission system on the RTK base station, this solution can effectively reduce costs and improve the adaptability of the drone landing scene.

[0057] In the implementation process of the above scheme, the system can more flexibly adapt to different communication environments and network topologies by using the remote control as an intermediary. Since many existing drone systems are already equipped with remote controls, this design can make full use of existing hardware without adding additional complexity or cost, simplifying the integration and deployment of the system, thereby enhancing the flexibility and scalability of the system. Furthermore, by forwarding the base station positioning information through the remote control, an additional communication path is provided. In other words, even if the direct communication between the fixed base station and the drone is interrupted, as long as the remote control can maintain communication with the fixed base station and the drone, the system can still work normally, reducing the risk of single point failure. This method enhances the redundancy of the system. If there is a problem with the communication link directly from the fixed base station to the drone, the remote control forwarding method can be used as a backup method to ensure the continuity and reliability of the positioning information.

[0058] As an optional implementation of the above step S220, the above base station positioning information also includes: the real-time absolute speed of the mobile platform; the above implementation of autonomous landing based on the base station positioning information and the visual positioning information may include:

[0059] Step S221: Control the current speed of the UAV according to the real-time absolute speed of the mobile platform so that the UAV and the landing reference mark are relatively stationary.

[0060] It can be understood that by controlling the current speed of the UAV according to the real-time absolute speed of the mobile platform, the system is able to make necessary adjustments in a short time to ensure that the speed of the UAV is synchronized with the mobile platform, which is particularly important for precise control in dynamic environments, because higher transmission frequencies and shorter data update cycles reduce control lags caused by data delays and improve the response speed and control accuracy of the entire system.

[0061] The implementation method of the above step S221 is, for example: after the drone receives the real-time absolute speed of the mobile platform from the RTK base station, the flight control system can calculate the speed difference between the current speed detected by the drone's own sensor and the real-time absolute speed of the mobile platform, and adjust the current speed of the drone according to the calculated speed difference, so that the current speed of the drone and the real-time absolute speed of the mobile platform gradually become consistent in direction and the speed value gradually becomes consistent. Finally, the flight control system can make the relative speed between the drone and the mobile platform 0, that is, let the flight control system confirm that the drone has reached a relatively static state between the landing reference mark. In the implementation process of the above scheme, by obtaining the absolute speed of the mobile platform in real time and adjusting the speed of the drone accordingly, the drone can remain relatively static with the mobile platform, which is very important for accurate landing, especially when landing on a mobile platform (such as a ship or a vehicle), which can significantly improve the safety and accuracy of landing. Further, after the drone is relatively static with the landing reference mark, the visual positioning information is further used for autonomous landing, ensuring the high precision of the final landing. The visual positioning information provides high-frequency and relative positioning information, which makes up for the deficiency of low-frequency update of the RTK base station and improves the robustness of the overall positioning.

[0062] Step S222: After the UAV is relatively stationary with the landing reference mark, autonomous landing is performed according to the visual positioning information.

[0063] It can be understood that the above-mentioned visual positioning information may include: the relative position and relative speed between the drone and the landing reference mark, and this relative position and relative speed can be calculated by the drone through the image obtained by shooting the landing reference mark on the mobile platform.

[0064] An optional implementation of the above step S222 is, for example: after the flight control system of the drone confirms that it is relatively stationary with the landing reference mark, the flight control system enables the visual positioning system for precise landing guidance, that is, autonomous landing is performed according to the visual positioning information. Specifically, the relative position and relative speed can be respectively input into the proportional-integral-derivative (PID) controller of the drone, so that the PID controller uses the relative position as the outer loop parameter and the relative speed as the inner loop parameter, so that the PID controller can control the drone to land at the landing reference mark on the mobile platform through the PID control algorithm. It can be understood that the inner loop control (based on the relative speed) can quickly respond to the speed deviation, so that the drone can make necessary adjustments in a short time, reduce the control lag caused by the delay, and improve the response speed of the system. This dual closed-loop structure enhances the robustness of the system, and even under external interference (such as wind, electromagnetic interference, etc.), it can quickly adjust through the inner loop to maintain stable flight and ensure safe landing.

[0065] Optionally, the PID controller can automatically adjust the proportional, integral and differential coefficients according to real-time data to adapt to different environmental conditions and mission requirements, thereby improving the system's adaptability and intelligence. It can also continuously optimize the PID parameters by recording and analyzing the data of each landing, further improving the control performance and forming a self-improving closed-loop system, thereby improving the adaptability and intelligence of the flight control system.

[0066] In the implementation process of the above scheme, a dual closed-loop control system is formed by taking the relative position as the outer loop parameter and the relative speed as the inner loop parameter. The outer loop ensures that the UAV gradually approaches the target position, while the inner loop quickly adjusts the speed to maintain stability and avoid oscillation or overshoot. This enables the PID controller to dynamically adjust the attitude and speed of the UAV according to the real-time relative position and relative speed errors, ensuring that it accurately tracks the position changes of the landing reference mark, thereby improving the landing accuracy and stability of the UAV.

[0067] As an optional implementation of the above step S220, the above implementation of autonomous landing based on base station positioning information and visual positioning information may include:

[0068] Step S223: Determine the return point according to the real-time absolute position of the mobile platform.

[0069] It is understandable that the return point determined in step S223 can be executed by a drone, that is, the drone calculates the return point based on the real-time absolute position of the mobile platform. Of course, in some embodiments, the step of calculating the return point can also be performed by a fixed base station. For ease of understanding and explanation, the following example is used to illustrate the calculation of the return point by a drone based on the real-time absolute position of the mobile platform.

[0070] The implementation of the above step S223 may include: after the drone obtains the real-time absolute position of the mobile platform from the RTK base station through a remote control or a direct communication link, the drone can calculate the position of the return point based on the real-time absolute position of the mobile platform and a preset landing strategy. For example, if the mobile platform is a ship docked at sea, the return point can be a fixed landing area on the stern deck (for example, the return point is directly above the center point of the stern deck), and the flight control system of the drone can calculate the specific coordinates of the return point based on the current position and attitude of the ship. It can be understood that the position of the return point here is determined according to the preset landing strategy of the drone, and the return point determined by different landing strategies is also different. The return point can be determined from a selected position within a preset circle range. The preset circle can be a circle with the real-time absolute position of the mobile platform as the center and a preset distance threshold (such as 5 meters) as the radius.

[0071] Step S224: After the drone reaches the return point, it performs autonomous landing based on the visual positioning information.

[0072] The implementation method of the above step S224 includes: when the drone approaches the return point, start the downward camera or other visual sensor, start shooting the landing reference mark (such as a QR code, a specific pattern, etc.), and the image to be processed, and calculate the image to be processed by the image processing algorithm to obtain the relative position and relative speed between the drone and the landing reference mark. Then, the drone can forward the information such as the relative position and relative speed to the flight control system, so that the flight control system controls and adjusts the height, pitch angle and roll angle of the drone according to the information such as the relative position and relative speed, and finally docks at the position of the landing reference mark. During the entire landing process, the drone can continuously monitor the visual positioning information, adjust the landing parameters in real time, and ensure the stability and accuracy of the landing process.

[0073] Optionally, during the autonomous landing stage of the UAV, if the UAV cannot obtain visual positioning information (for example, a camera failure or fog causes visual abnormalities), it can temporarily perform autonomous landing based on the base station positioning information. Once the UAV detects the visual positioning information (such as the camera returns to normal or the fog dissipates), it can switch to autonomous landing based on the base station positioning information and the visual positioning information.

[0074] As an optional implementation of the above step S220, the above implementation of autonomous landing based on base station positioning information and visual positioning information may include:

[0075] Step S225: If both the base station positioning information and the visual positioning information cannot be obtained, the drone is controlled to fly to the alternate landing return point after hovering for a preset time. The alternate landing return point is used to make the drone try to land again.

[0076] The implementation method of the above step S225 is, for example: during the autonomous landing stage of the drone, if neither the base station positioning information nor the visual positioning information can be obtained, the drone will immediately hover. If after hovering for a preset time (such as 5 seconds), it is still impossible to obtain any of the base station positioning information and the visual positioning information, the drone can be controlled to fly to the alternate landing return point, which is used to make the drone try to land again. By setting the preset hovering time, the system can evaluate whether it can re-acquire the positioning information in a short time, instead of immediately entering a high-energy flight mode. If it cannot be recovered, it will turn to the alternate landing return point, reasonably allocate energy use, and extend the battery life, thereby avoiding continuing to try to land in an invalid state, reducing unnecessary energy consumption and mechanical wear, and improving overall efficiency.

[0077] Optionally, if the base station positioning information can be obtained within the preset hovering time (such as 5 seconds), the autonomous landing is carried out according to the base station positioning information; if the visual positioning information can be obtained within the preset hovering time (such as 5 seconds), the landing is carried out according to the visual positioning information; if the base station positioning information and the visual positioning information can be obtained at the same time within the preset hovering time (such as 5 seconds), the autonomous landing is carried out according to the base station positioning information and the visual positioning information. The flight control system of the drone can automatically make the best decision (such as hovering, returning to the alternate landing return point) when it detects that the positioning information is lost, which reflects a high degree of intelligence and adaptability.

[0078] In the process of implementing the above solution, when key positioning information such as base station positioning information and visual positioning information are missing, the system will not blindly continue to attempt to land, but will safely hover and fly to the alternate landing return point, significantly reducing the risk of collision or crash. The existence of the alternate landing return point provides additional safety protection, ensuring that even in extreme situations, the drone has a safe landing option, enhancing the safety and reliability of the system.

[0079] As an optional implementation of the above step S220, the above implementation of autonomous landing based on base station positioning information and visual positioning information may include:

[0080] Step S226a: Determine the state vector of the UAV at the current moment based on the base station positioning information and the visual positioning information.

[0081] The implementation method of the above step S226a is, for example: when the base station positioning information and the visual positioning information can be obtained at the same time, the current position of the drone can be determined according to the real-time absolute position of the mobile platform in the base station positioning information and the relative position in the visual positioning information, and the current position speed of the drone can be determined according to the real-time absolute speed of the mobile platform in the base station positioning information and the relative speed in the visual positioning information. Then, the state vector of the drone at the current moment is constructed according to the current position and current position speed of the drone. For example, the above state vector is: Assume that the current position of the drone at the kth moment is represented by (x k ,y k ,z k ), and the current speed is represented by V k , then the state vector of the drone at the kth moment can be expressed as Among them, S k represents the state vector of the drone at the kth moment, x k ,y k ,z k They represent the three-dimensional coordinate values ​​of the current position of the drone at the kth moment, They represent the velocity components of the current velocity of the drone on the x, y, and z axes at the kth moment respectively.

[0082] Optionally, in some embodiments, the state vector of the above-mentioned drone at the current moment may also include drone attitude information, that is, the state vector of the drone at the current moment may be constructed based on the drone's attitude information, current position and current position speed.

[0083] Step S226b: Obtain the state vector at the previous moment, and establish a state transfer equation based on the state vector at the previous moment and the state vector at the current moment.

[0084] The implementation method of the above step S226b is, for example: obtaining the state vector at the previous moment, and establishing a state transfer equation based on the state vector at the previous moment and the state vector at the current moment. The state transfer equation here can be expressed as in, represents the state vector predicted by the drone at the kth moment, S k-1 represents the state vector of the drone at the k-1th moment (i.e., the state vector of the previous moment), A represents the initialized state transfer matrix, B represents the preset control input matrix, and u k Represents the control input matrix of the UAV at the kth moment (such as propulsion force or steering angle, etc.).

[0085] Step S226c: Determine the covariance matrix of the estimation error and the covariance matrix of the process noise at the current moment according to the state vector and the state transfer equation at the previous moment.

[0086] The implementation method of the above step S226c is, for example, to use the formula Calculate the state vector and state transfer equation at the previous moment to obtain the covariance matrix of the estimation error and the covariance matrix of the process noise at the current moment. Represents the covariance matrix of the estimated error at the current moment, P k-1 represents the state estimation error covariance matrix of the previous moment, A represents the initialized state transfer matrix, Q k The covariance matrix representing the process noise can usually be set to a reasonable value based on historical data or experimental results.

[0087] Step S226d: Calculate the Kalman filter gain based on the total observation matrix constructed based on the base station positioning information and the visual positioning information, the covariance matrix of the current estimation error, and the covariance matrix of the process noise.

[0088] The implementation method of the above step S226d is, for example: constructing a total observation matrix based on the base station positioning information and the visual positioning information. Assume that the total observation matrix here is represented by H k , which describes how to extract observations from the state vector. Specifically, for the observations of the RTK base station and the visual positioning system, the total observation matrix can be a selection matrix used to extract only the parts related to the observations. The covariance matrix R of the observation noise is set according to the numerical accuracy required by the base station positioning information and the visual positioning information. k , then, using the formula The total observation matrix constructed by the base station positioning information and the visual positioning information, the covariance matrix of the current estimation error and the covariance matrix of the process noise are calculated to obtain the Kalman filter gain. k represents the Kalman filter gain, represents the covariance matrix of the estimation error at the kth moment, H k represents the total observation matrix, R k represents the covariance matrix of the observation noise, Q k Represents the covariance matrix of the process noise.

[0089] It is understandable that the flight control system of the above-mentioned UAV can automatically adjust the Kalman gain according to real-time data, adapt to different environmental conditions and mission requirements, and improve the system's adaptability and intelligence. In addition, the flight control system of the above-mentioned UAV can also continuously optimize the parameter settings of the Kalman filter by recording and analyzing the data of each landing, further improve the control performance, and form a self-improving closed-loop system.

[0090] Step S226e: Fuse the base station positioning information and the visual positioning information according to the Kalman filter gain to obtain fused positioning information.

[0091] The implementation method of the above step S226e is, for example: using the Kalman filter gain to update the state estimation fusion of the base station positioning information and the visual positioning information to obtain the fused positioning information. The above formula for updating the state estimation can be expressed as Among them, S k It means that the UAV fuses the positioning information at the kth moment, represents the state vector predicted by the drone at the kth moment, K k represents the Kalman filter gain, z k represents the current observation value (e.g., the observed base station positioning information or visual positioning information, or one of the three cases of base station positioning information and visual positioning information), H k represents the total observation matrix.

[0092] It can be understood that the above fusion process occurs in the process of updating the state estimation fusion, that is, in the process of correcting the predicted state according to the observed value. The predicted value of the state vector of the drone at the kth moment is actually the predicted value of the state vector at the current moment predicted based on the state at the previous moment and the state transfer equation, while z k is the current observation value, including data from the RTK base station and the visual positioning system, and H k is the total observation matrix, which represents the mapping of the state vector to the observation space. Represents the observation residual, that is, the difference between the observed value and the predicted value. The Kalman filter gain is used to adjust the impact of this difference on the final state estimate. In other words, the Kalman filter gain K k The weights of observed and predicted values ​​are adjusted dynamically. When the observation noise is small and the prediction error is large, K k When the prediction error is small and the observation noise is large, K k Smaller and more dependent on predicted values.

[0093] Optionally, the Kalman filter gain can also be used to update the covariance matrix of the state estimation error, for example using the formula Update the covariance matrix of the state estimation error, where P k represents the covariance matrix of the estimated error at the kth moment after the update, I represents the identity matrix, K k represents the Kalman filter gain, H k represents the total observation matrix, Represents the covariance matrix of the estimated error at the kth moment before the update. Through frequent state updates and dynamic adjustment of the Kalman filter gain, the system can quickly respond to environmental changes, reduce control lags caused by data delays, and improve real-time performance. The above-mentioned Kalman filter effectively reduces error accumulation by continuously correcting state estimates, ensuring high accuracy and stability during long-term operation.

[0094] Step S226f: forward the fused positioning information to the flight control system of the UAV so that the flight control system controls the UAV to land on the mobile platform.

[0095] The implementation method of the above step S226f is, for example: the drone forwards the fused positioning information of the updated state estimation (and the covariance matrix) to the flight control system of the drone through the internal communication interface, and the flight control system adjusts the attitude (such as pitch angle, roll angle and yaw angle), speed and position of the drone according to the fused positioning information to ensure that it can land safely and smoothly on the landing reference mark of the mobile platform. Through the Kalman filter fusion processing, the dependence on a single sensor is reduced, the communication frequency and bandwidth requirements are reduced, thereby saving energy and communication resources, and the flight control system can perform more precise control based on the fused high-precision positioning information, reduce unnecessary adjustment actions, extend the flight time and reduce mechanical wear, thereby optimizing resource utilization and power consumption management.

[0096] In the implementation of the above scheme, the base station positioning information (high precision but low frequency) and the visual positioning information (high frequency but relative) are weightedly fused through the Kalman filter gain, which fully utilizes the advantages of the two sensors and significantly improves the positioning accuracy and robustness. In addition, the Kalman filter gain dynamically adjusts the weights according to the prediction error covariance matrix and the observation noise covariance matrix to ensure that the system can provide the best estimate under different conditions, thereby enhancing adaptability and flexibility.

[0097] See also Figure 3 The structural schematic diagram of the drone landing device provided in the embodiment of the present application is shown; the embodiment of the present application provides a drone landing device 300, including:

[0098] The information acquisition module 310 is used to obtain base station positioning information and visual positioning information. The base station positioning information is the positioning information measured by the fixed base station on the mobile platform, and the visual positioning information is obtained by the drone shooting the landing reference mark on the mobile platform.

[0099] The autonomous landing module 320 is used to perform autonomous landing according to the base station positioning information and the visual positioning information.

[0100] As an optional implementation of the above device, the fixed base station positioning information includes: the fixed base station measures the real-time absolute position of the mobile platform; the UAV landing device also includes:

[0101] The instruction sending module is used to send a frequency increase instruction to the fixed base station if it is detected that the signal quality of the fixed base station is lower than a preset quality threshold, or the distance between the real-time absolute positions of the UAV and the mobile platform is less than a preset distance threshold, so that the fixed base station increases the sending frequency of the base station positioning information.

[0102] As an optional implementation of the above device, the information acquisition module includes:

[0103] The absolute position receiving submodule is used to receive the real-time absolute position of the mobile platform. The real-time absolute position is sent by the remote controller of the drone after being obtained from the fixed base station.

[0104] As an optional implementation of the above device, the base station positioning information also includes: the real-time absolute speed of the mobile platform; the autonomous landing module includes:

[0105] The speed control submodule is used to control the current speed of the UAV according to the real-time absolute speed of the mobile platform so that the UAV and the landing reference mark are relatively stationary.

[0106] The autonomous landing submodule is used to perform autonomous landing based on visual positioning information after the UAV is relatively stationary with the landing reference mark.

[0107] As an optional implementation of the above device, the visual positioning information includes: the relative position and relative speed between the drone and the landing reference mark; the autonomous landing submodule includes:

[0108] The PID controlled landing unit is used to input the relative position and relative speed into the proportional-integral-differential PID controller of the UAV respectively, so that the PID controller uses the relative position as the outer loop parameter and the relative speed as the inner loop parameter to control the UAV to land on the mobile platform.

[0109] As an optional implementation of the above device, the autonomous landing module includes:

[0110] The return point determination submodule is used to determine the return point according to the real-time absolute position of the mobile platform;

[0111] The autonomous landing submodule is used to perform autonomous landing based on visual positioning information after the drone reaches the return point.

[0112] As an optional implementation of the above device, the autonomous landing module includes:

[0113] The alternate landing control submodule is used to control the drone to fly to the alternate landing return point after hovering for a preset time if both the base station positioning information and the visual positioning information cannot be obtained. The alternate landing return point is used to make the drone try to land again.

[0114] As an optional implementation of the above device, the autonomous landing module includes:

[0115] The state vector determination submodule is used to determine the state vector of the drone at the current moment based on the base station positioning information and the visual positioning information.

[0116] The transfer equation establishment submodule is used to obtain the state vector at the previous moment and establish the state transfer equation based on the state vector at the previous moment and the state vector at the current moment.

[0117] The variance matrix acquisition submodule is used to determine the covariance matrix of the estimation error and the covariance matrix of the process noise at the current moment according to the state vector and the state transfer equation at the previous moment.

[0118] The Kalman filter gain calculation submodule is used to calculate the Kalman filter gain based on the total observation matrix constructed by the base station positioning information and the visual positioning information, the covariance matrix of the current estimation error, and the covariance matrix of the process noise.

[0119] The positioning information fusion submodule is used to fuse the base station positioning information and the visual positioning information according to the Kalman filter gain to obtain the fused positioning information;

[0120] The positioning information forwarding submodule is used to forward the fused positioning information to the flight control system of the UAV so that the flight control system can control the UAV to land on the mobile platform.

[0121] It should be understood that the device corresponds to the above-mentioned drone landing method embodiment and can perform the various steps involved in the above-mentioned method embodiment. The specific functions of the device can be found in the description above, and the detailed description is appropriately omitted here. The device includes at least one software function module that can be stored in a memory in the form of software or firmware or solidified in the operating system (OS) of the device.

[0122] See also Figure 4 The structural diagram of the drone provided by the embodiment of the present application is shown. A drone 400 provided by the embodiment of the present application includes: a processor 410 and a memory 420, the memory 420 stores machine-readable instructions executable by the processor 410, and the machine-readable instructions are executed by the processor 410 to perform the above method.

[0123] The embodiment of the present application also provides a computer-readable storage medium 430, on which a computer program is stored, and the computer program is executed by the processor 410 to execute the above method. The computer-readable storage medium 430 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk.

[0124] The embodiment of the present application also provides a computer program product, including: a computer program or a computer instruction, and the computer program or the computer instruction executes the method described above when executed by a processor.

[0125] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0126] In several embodiments provided by the embodiments of the present application, it should be understood that the disclosed device and method can also be implemented in other ways. The device embodiments described above are only schematic, for example, the flowcharts and block diagrams in the accompanying drawings show the possible implementation architecture, functions and operations of the devices, methods and computer program products according to the multiple embodiments of the embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a part of a module, a program segment or a code, and a part of a module, a program segment or a code includes one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also be different from the order of occurrence marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which is mainly determined by the functions involved.

[0127] In addition, each functional module of each embodiment in the embodiment of the present application can be integrated together to form an independent part, or each module can exist separately, or two or more modules can be integrated to form an independent part. In addition, in the description of this specification, the description of reference terms "one embodiment", "some embodiments", "example", "specific example", "some examples", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of the present application. In this specification, the schematic representation of the above terms does not necessarily target the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples without contradiction.

[0128] The above description is only an optional implementation manner of the embodiments of the present application, but the protection scope of the embodiments of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or replacements within the technical scope disclosed in the embodiments of the present application, which should be covered within the protection scope of the embodiments of the present application.

Claims

1. A method for landing a drone, characterized in that: include: Acquire base station positioning information and visual positioning information, wherein the base station positioning information is positioning information measured by a fixed base station on the mobile platform, and the visual positioning information is obtained by photographing a landing reference mark on the mobile platform by a drone; Autonomous landing is performed according to the base station positioning information and the visual positioning information.

2. The method according to claim 1, characterized in that The base station positioning information includes: the real-time absolute position of the mobile platform; before acquiring the base station positioning information, it also includes: If it is detected that the signal quality of the fixed base station is lower than a preset quality threshold, or the distance between the real-time absolute position of the UAV and the mobile platform is less than a preset distance threshold, a frequency increase instruction is sent to the fixed base station so that the fixed base station increases the sending frequency of the base station positioning information.

3. The method according to claim 2, characterized in that The obtaining of base station location information includes: The real-time absolute position of the mobile platform is received, where the real-time absolute position is sent after being acquired by the remote controller of the drone from the fixed base station.

4. The method according to claim 3, characterized in that The base station positioning information also includes: the real-time absolute speed of the mobile platform; the autonomous landing according to the base station positioning information and the visual positioning information includes: Controlling the current speed of the UAV according to the real-time absolute speed of the mobile platform so that the UAV and the landing reference mark are relatively stationary; After the UAV and the landing reference mark are relatively stationary, autonomous landing is performed according to the visual positioning information.

5. The method according to claim 4, characterized in that The visual positioning information includes: the relative position and relative speed between the UAV and the landing reference mark; and the autonomous landing according to the visual positioning information includes: The relative position and the relative speed are respectively input into the proportional-integral-differential PID controller of the UAV, so that the PID controller uses the relative position as an outer loop parameter and the relative speed as an inner loop parameter to control the UAV to land on the mobile platform.

6. The method according to claim 2, characterized in that The autonomous landing according to the base station positioning information and the visual positioning information includes: Determining a return point according to the real-time absolute position of the mobile platform; After the UAV reaches the home point, autonomous landing is performed according to the visual positioning information.

7. The method according to claim 1, characterized in that The autonomous landing according to the base station positioning information and the visual positioning information includes: If both the base station positioning information and the visual positioning information cannot be obtained, the drone is controlled to fly to the alternate landing return point after hovering for a preset time, and the alternate landing return point is used to make the drone try to land again.

8. The method according to claim 1, characterized in that The autonomous landing according to the base station positioning information and the visual positioning information includes: Determine the state vector of the UAV at the current moment according to the base station positioning information and the visual positioning information; Acquire the state vector at the previous moment, and establish a state transfer equation according to the state vector at the previous moment and the state vector at the current moment; Determine the covariance matrix of the estimation error and the covariance matrix of the process noise at the current moment according to the state vector at the previous moment and the state transfer equation; Calculate the Kalman filter gain according to the total observation matrix constructed by the base station positioning information and the visual positioning information, the covariance matrix of the estimation error at the current moment, and the covariance matrix of the process noise; fusing the base station positioning information and the visual positioning information according to the Kalman filter gain to obtain fused positioning information; The fused positioning information is forwarded to the flight control system of the UAV, so that the flight control system controls the UAV to land on the mobile platform.

9. A drone landing device, characterized in that: Applications in drones include: An information acquisition module, used to acquire base station positioning information and visual positioning information, wherein the base station positioning information is positioning information measured by a fixed base station on the mobile platform, and the visual positioning information is obtained by a drone photographing a landing reference mark on the mobile platform; An autonomous landing module is used to perform autonomous landing according to the base station positioning information and the visual positioning information.

10. A drone, characterized in that: include: A processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and the machine-readable instructions are executed by the processor to perform any method according to claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is executed.

12. A computer program product, characterized in that include: A computer program or a computer instruction, wherein when the computer program or the computer instruction is executed by a processor, the method according to any one of claims 1 to 8 is executed.

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