Fixed-point landing control method, system, medium and electronic equipment for tethered drone

Abstract

A method, system, medium and electronic device for controlling the fixed-point landing of a tethered drone, relating to the technical field of drone landing control. The method comprises: when a landing request of a drone is received, obtaining the current relative position and relative speed of the drone relative to the landing vehicle, and the landing mark of the landing vehicle; determining the target flight parameters of the drone based on the relative position and the relative speed; determining the target landing area based on the landing mark; obtaining the wind field parameters of the current environment of the drone, and generating the landing flight trajectory of the drone based on the wind field parameters, the target flight parameters and the target landing area; and controlling the drone to land in the target landing area according to the landing flight trajectory. The implementation of the technical solution provided in the present application improves the landing accuracy of the tethered drone.

Description

Technical Field

[0001] The present application relates to the technical field of drone landing control, and in particular to a method, system, medium and electronic equipment for controlling the fixed-point landing of a tethered drone. Background Art

[0002] With the development of drone technology, tethered drones have been widely used in vehicle-mounted mobile communications, emergency communications, etc. due to their advantages of continuous power supply and stable communication. In practical applications, tethered drones usually need to follow the vehicle for mobile operations and maintain connection with the vehicle-mounted power supply system through a tether rope, so as to achieve long-term uninterrupted operation.

[0003] In the actual application of tethered drones, the landing phase is one of the most critical links in the entire flight process. At present, in order to ensure landing accuracy and safety, the common landing method of tethered drones is to use a preset fixed landing trajectory for landing. However, in actual situations, due to the existence of the tether rope and especially in complex environments, it is difficult to accurately obtain the position of the drone relative to the vehicle-mounted landing platform, resulting in an inability to land accurately. Summary of the invention

[0004] The present application provides a fixed-point landing control method, system, medium and electronic equipment for a tethered drone, which improves the landing accuracy of the tethered drone.

[0005] In a first aspect, the present application provides a method for controlling a tethered drone to land at a fixed point, the method comprising:

[0006] When receiving a landing request from a drone, obtaining the current relative position and relative speed of the drone relative to the landing vehicle, and the landing identifier of the landing vehicle;

[0007] determining a target flight parameter of the drone based on the relative position and the relative speed;

[0008] Determine a target landing area based on the landing mark;

[0009] Acquire wind field parameters of the current environment of the UAV, and generate a landing flight trajectory of the UAV based on the wind field parameters, the target flight parameters, and the target landing area;

[0010] The UAV is controlled to land in the target landing area according to the landing flight trajectory.

[0011] By adopting the above technical solution, by acquiring the relative position and relative speed of the UAV relative to the landing vehicle, as well as the landing mark of the landing vehicle, the spatial relationship between the UAV and the landing platform can be grasped in real time; further, the target flight parameters of the UAV are determined based on the acquired relative position and relative speed, and the target landing area is determined based on the landing mark, thereby establishing the motion constraints and target position of the UAV during the landing process; then, by acquiring the wind field parameters of the current environment in which the UAV is located, and combining them with the target flight parameters and the target landing area, a landing flight trajectory that takes environmental influences into account is generated, and finally the UAV is controlled to land in the target landing area according to the trajectory, so that the tethered UAV can accurately complete the landing process in a complex environment, thereby improving the accuracy and reliability of the tethered UAV landing.

[0012] In a second aspect of the present application, a fixed-point landing control system for a tethered drone is provided, the system comprising:

[0013] A state parameter acquisition module, used for acquiring the current relative position and relative speed of the drone relative to the landing vehicle, and the landing identifier of the landing vehicle when receiving a landing request of the drone;

[0014] A flight parameter determination module, configured to determine a target flight parameter of the UAV based on the relative position and the relative speed;

[0015] A landing area determination module, used to determine a target landing area based on the landing mark;

[0016] A landing trajectory generation module, used to obtain the wind field parameters of the current environment of the UAV, and generate the landing flight trajectory of the UAV based on the wind field parameters, the target flight parameters and the target landing area;

[0017] The landing control module is used to control the UAV to land in the target landing area according to the landing flight trajectory.

[0018] In a third aspect of the present application, a computer storage medium is provided, wherein the computer storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the above method steps.

[0019] In a fourth aspect of the present application, an electronic device is provided, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the above-mentioned method steps.

[0020] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0021] The present application can grasp the spatial relationship between the UAV and the landing platform in real time by acquiring the relative position and relative speed of the UAV with respect to the landing vehicle, as well as the landing mark of the landing vehicle; further determine the target flight parameters of the UAV based on the acquired relative position and relative speed, and determine the target landing area based on the landing mark, thereby establishing the motion constraints and target position of the UAV during the landing process; then obtain the wind field parameters of the current environment of the UAV, and combine them with the target flight parameters and the target landing area to generate a landing flight trajectory that takes environmental influences into account, and finally control the UAV to land in the target landing area according to the trajectory, so that the tethered UAV can accurately complete the landing process in complex environments, thereby improving the accuracy and reliability of the tethered UAV landing. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of a method for controlling the fixed-point landing of a tethered UAV provided in an embodiment of the present application;

[0023] Figure 2 It is a module schematic diagram of a fixed-point landing control system for a tethered drone provided in an embodiment of the present application;

[0024] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0025] Description of reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0026] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0028] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0029] The following will provide a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0030] Please refer to Figure 1 , a flowchart of a fixed-point landing control method for a tethered UAV is proposed. The method can be implemented by a computer program, can be implemented by a single-chip microcomputer, and can also be run on a fixed-point landing control system for a tethered UAV. The computer program can be integrated in a computer device or run as an independent tool application. Specifically, the method includes steps 10 to 50, and the above steps are as follows:

[0031] Step 10: When receiving the landing request of the UAV, obtain the current relative position and relative speed of the UAV relative to the landing vehicle, as well as the landing mark of the landing vehicle.

[0032] In the embodiment of the present application, the drone refers to a multi-rotor aircraft connected to a ground landing vehicle via a tethered rope. The drone obtains continuous power supply through the tethered rope and maintains a data communication connection with the ground equipment.

[0033] In the embodiment of the present application, the landing vehicle refers to a mobile vehicle equipped with a tethered rope retracting device, a power supply system and a landing platform. The vehicle can perform mobile operations in a field environment and provide power supply and landing support for the tethered drone.

[0034] In the embodiment of the present application, the relative position refers to the three-dimensional spatial position vector of the drone relative to the landing platform of the landing vehicle, including the relative distance on the horizontal plane and the relative distance in the height direction. This position information is used to determine the spatial relationship between the drone and the landing target point.

[0035] In the embodiment of the present application, the relative speed refers to the motion speed vector of the UAV relative to the landing vehicle, including the speed components in the horizontal and vertical directions. The speed information reflects the relative motion state between the UAV and the landing vehicle.

[0036] In the embodiment of the present application, the landing mark refers to a visual feature mark set on the landing platform of the landing vehicle, including a specific geometric shape, color or pattern combination, which is used by the drone vision system to identify the landing target position and determine the spatial posture of the landing platform.

[0037] Specifically, when the tethered drone needs to land, it will first send a landing request signal to the control system. After receiving the landing request, the control system needs to obtain the basic information required for landing to ensure the accuracy of the landing. First, the current position information of the drone is obtained through the GPS module carried by the drone, and the real-time position information of the landing vehicle is obtained through the GPS module on the landing vehicle. By comparing the two sets of GPS position information, the initial relative position between the drone and the landing vehicle can be preliminarily determined. However, since there is a certain error in the GPS signal and the presence of the tether rope will affect the actual position of the drone, the control system also needs to obtain the spatial shape data of the tether rope through multiple spatial position sensors set on the tether rope. These sensors are evenly distributed along the length direction of the tether rope and can collect the three-dimensional coordinate information of their location in real time. The control system establishes a spatial deformation model of the tether rope based on the data of these spatial position sensors, which can reflect the actual shape of the tether rope in the current state. Based on the spatial deformation model, the control system corrects the initial relative position previously obtained by GPS to obtain a more accurate corrected relative position. Then, the control system performs a time differential operation on the relative position to calculate the relative speed of the drone relative to the landing vehicle. At the same time, the control system collects the landing mark image on the landing vehicle through the visual system on the drone. The landing mark contains the position and attitude information of the landing platform. In this way, the control system obtains all the basic information required for the landing process, laying the foundation for subsequent landing control. This step overcomes the limitations of a single information source by fusing multi-source information, improves the accuracy of position and speed information, and creates conditions for achieving precise landing.

[0038] Based on the above embodiment, as an optional embodiment, the step of obtaining the current relative position and relative speed of the drone relative to the landing vehicle may further include the following steps:

[0039] Step 101: Based on the GPS position information of the drone and the GPS position information of the landing vehicle, determine the initial relative position of the drone and the landing vehicle.

[0040] Specifically, before controlling the landing of the drone, it is necessary to first accurately obtain the relative position relationship between the drone and the landing vehicle. The GPS receiving module on the drone can receive GPS satellite signals in real time and calculate the current latitude and longitude coordinates and altitude of the drone. At the same time, the GPS receiving module on the landing vehicle can also obtain the real-time position information of the vehicle. The control system converts the two sets of GPS data to the same coordinate system and obtains the initial relative position vector of the drone relative to the landing vehicle through vector subtraction.

[0041] Step 102: Acquire position data of a plurality of spatial position sensors disposed on the tether of the drone.

[0042] Specifically, since GPS signals are affected by factors such as multipath effects and ionospheric delay in actual environments, it is difficult to meet the requirements of precise landing by relying solely on GPS positioning. Therefore, multiple spatial position sensors are evenly arranged along the length of the tether. These sensors use inertial measurement units (IMUs) and can measure the acceleration and angular velocity information of their locations. By integrating these sensor data, the three-dimensional position coordinates of each sensor relative to the fixed end of the tether can be obtained. The spacing of these spatial position sensors is determined according to the total length of the tether, usually at intervals of 0.5 meters to 2 meters, so as to ensure measurement accuracy while avoiding the system complexity caused by too many sensors. The sampling frequency of each sensor is set to above 50Hz to ensure that the dynamic changes of the tether can be captured in time.

[0043] Step 103: Establish a spatial deformation model of the mooring rope according to the position data of the spatial position sensor.

[0044] Specifically, after obtaining the position data of multiple spatial position sensors on the tether, it is necessary to establish an accurate spatial deformation model of the tether to correct the relative position of the drone. The tether is simplified into a flexible body composed of multiple micro-element segments, and the endpoints of each micro-element segment are the installation positions of the spatial position sensors. The control system uses a cubic spline interpolation algorithm and takes the position coordinates of adjacent sensors as control points to construct the spatial curve equation of the tether. The curve equation must not only pass through all sensor position points, but also ensure that the first-order derivative and second-order derivative of the curve at these position points are continuous to ensure that the model can truly reflect the bending state of the tether. After establishing the basic curve equation, the physical properties of the tether are further considered, including parameters such as the linear density, elastic modulus and initial tension of the rope. These parameters are substituted into the catenary equation to obtain the correction coefficient considering the effects of gravity and tension. By combining the basic curve equation with the correction coefficient, a spatial deformation model that can accurately describe the actual spatial form of the tether is finally obtained.

[0045] Step 104: Correct the initial relative position based on the spatial deformation model to obtain a corrected relative position.

[0046] Specifically, based on the spatial deformation model, the precise path of the tether rope from the fixed end to the drone connection end can be calculated, and the positional relationship between the actual position of the drone and the end point of the tether rope can be obtained. The control system compares and fuses the positional relationship with the initial relative position previously obtained through GPS, and corrects the initial relative position using a weighted average method, where the weight of the position information obtained by the spatial deformation model is 0.7, and the weight of the GPS position information is 0.3, ultimately obtaining a more accurate corrected relative position. This position correction method based on multi-source information fusion effectively overcomes the error of relying solely on GPS positioning and provides a more reliable position reference.

[0047] Step 105: Perform time differentiation operation on the relative position to obtain the relative speed.

[0048] Specifically, the time differential operation is performed based on the corrected relative position, and the relative speed is calculated using the central difference method. The control system first sets a time window with a length of 20ms, and continuously collects 5 sets of corrected relative position data within the time window. For each sampling time t, the position data of the two moments before and after (t-Δt and t+Δt) are used to calculate the instantaneous speed at that moment through the formula v(t)=(x(t+Δt)-x(t-Δt)) / (2Δt), where x represents the position vector and Δt is the sampling time interval. In order to reduce the influence of noise in the calculation process, the control system applies the Kalman filtering algorithm to smooth the calculated speed data. In the Kalman filtering process, the state transfer matrix of the speed is set to the unit matrix, and the appropriate process noise covariance and measurement noise covariance are set according to the fluctuation of the actual measurement data. After filtering, smoother relative speed data is obtained, which can accurately reflect the movement trend of the UAV relative to the landing vehicle and provide important kinematic reference for subsequent landing trajectory planning.

[0049] Step 20: Determine the target flight parameters of the UAV based on the relative position and relative speed.

[0050] In the embodiment of the present application, the target flight parameters refer to a set of flight control indicators that the UAV needs to follow during the landing process, including but not limited to the target flight altitude, target horizontal position, target descent speed and target attitude angle, etc. These parameters are dynamically updated as the landing phase progresses and are used to guide the UAV to land safely along the expected trajectory.

[0051] Specifically, the relative position vector is projected onto the horizontal plane and the vertical plane respectively to obtain the horizontal relative position and the vertical relative position, and the relative velocity vector is decomposed into the horizontal relative velocity and the vertical relative velocity components. Based on the horizontal relative position and the horizontal relative velocity, the control system uses the uniform deceleration motion model to calculate the horizontal time margin. Assuming that the drone takes the current horizontal velocity as the initial velocity and moves at a deceleration of 0.5 m / s2, the time required to reach the target horizontal position is calculated. Similarly, according to the vertical relative position and the vertical relative velocity, the uniform acceleration model is used to calculate the vertical time margin, that is, the time required for the drone to descend to the target height at a uniform speed is calculated. The control system compares the horizontal time margin and the vertical time margin, selects the larger time margin as the reference time, and generates the target velocity vector accordingly. In the horizontal direction, the target velocity is the horizontal relative position divided by the reference time, and the direction points to the center of the target landing area; in the vertical direction, the target velocity is the vertical relative position divided by the reference time. At the same time, the target pitch angle and the target yaw angle are calculated according to the direction of the target velocity vector, and the target attitude angle is formed by combining the target roll angle. Finally, the control system combines the target velocity vector and the target attitude angle to form a complete set of target flight parameters. This parameter generation method based on time margin can ensure the time coordination of horizontal and vertical motion, avoid sudden changes in motion states during landing, and achieve smooth landing control of the UAV.

[0052] Based on the above embodiment, as an optional embodiment, the step of determining the target flight parameters of the UAV based on the relative position and relative speed may further include the following steps:

[0053] Step 201: Project the relative position onto the horizontal plane and the vertical plane to obtain the horizontal relative position and the vertical relative position, and decompose the relative velocity into the horizontal relative velocity and the vertical relative velocity.

[0054] Specifically, in order to achieve precise motion control of the UAV in three-dimensional space, the motion characteristics of the horizontal and vertical planes need to be considered separately. The control system first obtains the relative position vector (x, y, z) between the UAV and the landing vehicle, where the x and y components represent the position difference in the east and north directions, and the z component represents the height difference. Through the vector projection method, the relative position is projected onto the horizontal plane to obtain the horizontal relative position vector (x, y), and its size is calculated by the square and square root to obtain the horizontal relative distance; the z component is extracted separately as the vertical relative position. Similarly, for the relative velocity vector (v x ,v y ,v z ) is decomposed to obtain the horizontal relative velocity vector (v x ,v y ) and vertical relative velocity v z .

[0055] Step 202: Calculate the horizontal time margin according to the horizontal relative position and the horizontal relative speed.

[0056] Specifically, the kinematic equation is used to calculate the horizontal time margin, taking into account the current horizontal speed v of the drone. h (i.e. the modulus of the horizontal relative velocity) and the target horizontal deceleration a h (set to 0.5 m / s2), the horizontal time margin t is calculated using the uniformly decelerated linear motion formula h The specific calculation process is: first solve the quadratic equation a h ·t h ² / 2=s, where s is the horizontal relative distance, t h is the horizontal time margin to be determined; then combined with v h =a h ·t h The final horizontal time margin is obtained. This time margin calculation method based on the kinematic equation not only takes into account the current motion state, but also ensures the stability of the motion process, providing an important time constraint basis for subsequent trajectory planning.

[0057] Step 203: Calculate the vertical time margin according to the vertical relative position and the vertical relative speed.

[0058] Specifically, based on the acquired vertical relative position z and vertical relative velocity v z , use the uniformly accelerated motion model to calculate the vertical time margin t v The calculation process takes into account the safe landing speed limit in the vertical direction (set to 0.3 m / s) and the maximum acceleration limit (set to 0.2 m / s2) by solving the equation of motion z=v z ·t v +0.5·a z ·t v ²Get the vertical time margin, where a z is the vertical acceleration. The control system calculates the horizontal time margin t h With vertical time margin t v After comparison, the larger value is selected as the base time margin t_base to ensure that the movements in the two directions can be completed synchronously.

[0059] Step 204: Generate a target velocity vector and a target attitude angle based on the horizontal time margin and the vertical time margin.

[0060] Specifically, based on the reference time margin, the control system generates a target velocity vector whose horizontal component v x _target and v y_target is equal to the x and y components of the horizontal relative position divided by the reference time margin, and the vertical component v z _target is equal to the vertical relative position divided by the reference time margin. At the same time, the target attitude angle is calculated according to the direction of the target velocity vector, where the target yaw angle ψ is calculated by the inverse tangent function ψ=arctan(v y _target / v x _target), the target pitch angle θ is calculated by projecting the target velocity vector on the vertical plane: θ=arctan(v z _target / sqrt(v x _target²+v y _target²)), the target roll angle φ is set to 0 to maintain flight stability. This parameter generation method based on time margin coordination can keep the drone in a stable motion state during the landing process, avoid drastic attitude changes caused by uncoordinated horizontal and vertical motion, and improve the safety and reliability of the landing process.

[0061] Step 205: Combine the target velocity vector and the target attitude angle to generate target flight parameters.

[0062] Specifically, the three components of the target velocity vector v x _target, v y _target and v z _target is uniformly converted to the body coordinate system to obtain the forward velocity, lateral velocity and vertical velocity. Then, the yaw angle ψ, pitch angle θ and roll angle φ in the target attitude angle are converted into quaternion representation, and the converted velocity components and attitude quaternions are packaged according to the preset format to construct a target flight parameter vector containing nine components, of which the first three components are velocity values, the middle four components are attitude quaternions, and the last two components are the desired position error convergence coefficients. This parameter combination method not only contains the complete information required for kinematics, but also provides a basis for feedback control through the position error convergence coefficient.

[0063] Step 30: Determine the target landing area based on the landing mark.

[0064] In the embodiment of the present application, the target landing area refers to a three-dimensional spatial range defined above the landing platform with the landing mark on the landing vehicle as the center. For example, the horizontal cross-section of the area is a square area with a side length of 2 meters, and the vertical height range is 0.5 meters to 5 meters above the landing platform, which is used to limit the effective activity space of the UAV during the landing process.

[0065] Specifically, the initial target landing area is determined by the GPS coordinate information of the landing vehicle sent by the ground station. In this stage, a cylindrical area is defined as the rough target landing area with the GPS position of the landing vehicle as the center. The bottom radius is set to 10 meters (considering the GPS positioning error), and the height range extends from the ground to the current flight altitude of the UAV. As the UAV gradually lowers its flight altitude (for example, to below 50 meters), when the onboard camera can capture and identify the ground landing mark, the control system will switch to the precise landing stage, obtain the precise position of the landing mark through image recognition technology, and accordingly reduce the target landing area to a cylindrical area with a radius of 1.5 meters centered on the landing mark. This staged area determination method not only ensures the reliability of the high-altitude segment, but also achieves the accuracy of the low-altitude segment, forming a complete landing area determination strategy. The control system ensures that the UAV can complete the entire landing process safely and smoothly by adjusting the parameters of the target landing area in real time.

[0066] Based on the above embodiment, as another optional embodiment, the step of determining the target landing area based on the landing mark may further include the following steps:

[0067] Step 301: Extract feature points and boundary information of the landing mark.

[0068] Specifically, in order to accurately obtain the spatial position and attitude information of the landing mark, the control system needs to process and analyze the acquired images. When the drone descends below the preset height, such as below 50 meters, and the onboard camera captures the landing mark image, the image is first preprocessed, including Gaussian filtering denoising and adaptive threshold classification, and then the contour detection algorithm is used to extract the boundary information of the landing mark. The boundary is polygonally approximated by the Douglas-Peucker algorithm to obtain key contour points. On this basis, the Harris corner detection algorithm is used to extract the feature points inside the landing mark, which usually include the corners and intersections of the mark pattern.

[0069] Step 302: Calculate the three-dimensional attitude angle of the landing mark based on the feature points.

[0070] Specifically, the extracted feature points are matched with the pre-stored standard landing mark template to establish the correspondence between the two-dimensional image plane and the three-dimensional space. Based on the known camera intrinsic parameter matrix and distortion coefficient, the PnP (Perspective-n-Point) algorithm is used to solve the spatial position equations of the feature points to obtain the rotation matrix R and translation vector t of the landing mark relative to the camera coordinate system. The rotation matrix is ​​decomposed into the Euler angle representation to obtain the yaw angle ψ_pad, pitch angle θ_pad and roll angle φ_pad of the landing mark in three-dimensional space. In order to improve the stability of attitude estimation, the RANSAC algorithm is used to eliminate outliers, and the extended Kalman filter is used to smooth the attitude estimation results between consecutive frames. This three-dimensional attitude calculation method based on feature points can not only accurately obtain the spatial orientation information of the landing mark, but also provide an important reference basis for subsequent precise landing, effectively improving the accuracy and reliability of the landing process.

[0071] Step 303: Construct a safety buffer zone around the landing mark according to the boundary information.

[0072] Specifically, based on the extracted landing mark boundary information, a morphological expansion algorithm is used to construct a safety buffer zone. For example, the boundary of the landing mark is expanded outward by 2 meters as the basic safety buffer zone. Considering the influence of wind force and obstacles, the basic safety buffer zone can also be adaptively adjusted according to the current wind speed and wind direction data, and the buffer distance on the windward side can be appropriately increased.

[0073] Step 304: Obtain the current deformation state of the tether rope of the UAV and calculate the predicted swing range of the tether rope during the landing process.

[0074] Specifically, the deformation data of the mooring rope, including tensile strain and torsional strain, are obtained in real time through the strain sensor installed on the mooring rope, and the dynamic model of the mooring rope is established in combination with the material properties of the mooring rope (such as elastic modulus and Poisson's ratio). Based on the model and the current environmental parameters (such as wind speed and air pressure), the control system uses the finite element method to calculate the possible swing trajectory of the mooring rope during the landing process, and obtains a cone-shaped predicted swing range with the current mooring point as the vertex. The half-vertex angle of this range is dynamically adjusted according to the length and tension of the mooring rope. The longer the mooring rope is or the smaller the tension is, the larger the half-vertex angle is.

[0075] Step 305: Determine the overlapping area between the safety buffer zone and the predicted swing range as the target landing area.

[0076] Specifically, a Boolean intersection operation is performed on the safety buffer and the predicted swing range to obtain the overlapping part of the two areas, and the overlapping area is determined as the final target landing area. This landing area determination method based on multiple constraints not only takes into account the safety spacing requirements of ground facilities, but also takes into account the dynamic characteristics of the tethered rope. It can effectively avoid the risks of collision and entanglement that may occur during the landing process, and significantly improves the safety and reliability of the tethered drone landing process.

[0077] Step 40: Obtain the wind field parameters of the current environment of the UAV, and generate the landing flight trajectory of the UAV based on the wind field parameters, target flight parameters, and target landing area.

[0078] Specifically, the displacement data of the mooring rope in three-dimensional space {(x1, y1, z1), (x2, y2, z2), ..., (xn, yn, zn)} are collected by setting fiber grating displacement sensors at different heights of the mooring rope. Based on these discrete displacement data points, the continuous spatial deformation curve S(h) of the mooring rope is fitted by the cubic spline interpolation method, where h is the height from the ground. In order to improve the calculation accuracy, the control system evenly divides the spatial deformation curve into m micro-element segments, and the length Δl of each micro-element segment is set to 0.5 meters. For the material properties of the mooring rope, a strain-stress relationship model is established based on the elastic modulus E, Poisson's ratio μ and diameter d of its carbon fiber composite material, which takes into account the linear elastic deformation characteristics of the material. For each micro-element segment, its deformation variable Δs is first calculated, that is, the difference between the shape of the micro-element segment under load and the shape under no load. Combining Hooke's law and the geometric parameters of the micro-element segment, the elastic stress σ of the micro-element segment is solved. Considering that the wind load on the mooring rope in the airflow mainly includes normal resistance Fn and tangential resistance Ft, by establishing the force balance equation group of the micro-element segment and substituting known quantities such as elastic stress, gravity and tension, the wind load acting on the micro-element segment can be solved. Finally, based on the square relationship between wind load and wind speed, combined with the drag coefficient Cd of the mooring rope, the wind speed and direction at the height are reversed. By performing similar calculations on all micro-element segments, the wind field distribution within the height range covered by the mooring rope is finally obtained.

[0079] Using the wind field data obtained above, combined with the target flight parameters of the drone and the target landing area, the initial trajectory is generated through the improved RRT* algorithm, the trajectory is smoothed using the Bezier curve, and converted into a specific waypoint sequence. In order to adapt to the changes in the wind field, a sliding time domain control strategy with a period of 0.5s is used to continuously optimize the landing trajectory. When the wind field changes significantly (such as wind speed changes exceeding 2m / s), the system will re-plan the trajectory of the remaining segments to ensure that the flight process continues to meet safety constraints.

[0080] Based on the above embodiment, as another optional embodiment, the step of generating the landing flight trajectory of the UAV based on the wind field parameters, the target flight parameters and the target landing area may further include the following steps:

[0081] Step 401: Calculate the estimated landing time of the UAV according to the target flight parameters.

[0082] Specifically, based on the target flight parameters of the UAV, including the maximum descent speed v d _max (set to 2m / s), maximum horizontal speed v h _max (set to 5m / s), current flight altitude h and target landing point position coordinates (x0, y0, z0), and calculate the estimated total landing time T through the kinematic equation. The calculation formula is T=h / v d _max, when the drone is at an altitude of 100 meters, the estimated landing time is about 50 seconds.

[0083] Step 402: Divide the estimated landing time into multiple time intervals, and determine the position offset under the action of wind force based on wind field parameters in each time interval.

[0084] Specifically, in order to improve the accuracy of trajectory prediction, the control system divides the landing time into n equal time intervals {Δt1, Δt2, ..., Δtn}, and the length of each time interval is set to 0.5 seconds, that is, the 50-second landing process is divided into 100 time segments. For each time interval Δti, first determine the height h of the drone at that moment i =hv d _max×(i-1)×Δt, and obtain the wind field parameter v corresponding to the altitude layer i Based on the aerodynamic characteristics of the drone, including its equivalent frontal area S, drag coefficient Cd, combined with wind speed and angle of attack, the drift speed v generated by the wind during this time interval is calculated. w _i. Specifically, the horizontal drift velocity v wh _i=k w ×v i ×cos(θi), vertical drift velocity v wv _i=k w ×v i ×sin(θ i ), where k w is the wind influence coefficient, θ i is the wind direction angle. Integrate the drift velocity in the time interval Δti to obtain the position offset Δpi=(Δxi,Δyi,Δzi) in this time period, where Δxi=v wh _i×cos(φ i)×Δt,Δyi=v wh _i×sin(φ i )×Δt,Δzi=v wv _i×Δt,φ i is the wind direction angle in the horizontal plane.

[0085] Step 403: Taking the center of the target landing area as the end point, a Bezier curve is used to generate a control point sequence of the initial landing trajectory.

[0086] Specifically, first determine the starting point of the trajectory as the current drone position coordinates (xs, ys, zs), and the end point as the center coordinates of the target landing area (x0, y0, z0). The control system uniformly selects n time points (n is set to 20) in the trajectory planning space, and generates a control point sequence {P1, P2, ..., Pn} according to the parametric equation of the Bezier curve. For each time point ti=i / n (i from 1 to n), the coordinates of the corresponding control point Pi are calculated by the following parametric equation: xi=xs+(x0-xs)×(1-t)³+3×x1×t×(1-t)²+3×x2×t²×(1-t)+x0×t³, yi and zi are calculated in a similar way to xi, where (x1, y1, z1) and (x2, y2, z2) are the two intermediate control points of the Bezier curve, and the initial positions are set at 1 / 3 and 2 / 3 between the starting point and the end point, respectively. The control point sequence generated in this way forms a smooth space curve, which not only meets the position constraints of the start and end points, but also has good continuity and controllability, providing a suitable initial solution for subsequent trajectory optimization. This initial trajectory generation method based on Bezier curves not only ensures the smoothness of the trajectory, but also reserves adjustment space for subsequent optimization considering wind field effects and mooring constraints.

[0087] Step 404: Perform position compensation on the control point sequence according to the position offset at each time interval to generate compensated control points.

[0088] Specifically, for each control point Pi=(xi,yi,zi) generated by the Bezier curve, the position offset ΔPi=(Δxi,Δyi,Δzi) of the drone under the action of wind in the time interval is estimated according to the wind field conditions at the time point ti. In order to effectively compensate for these position offsets, the control system introduces a compensation coefficient kc (set to 1.2) to adjust the position of the control point. The coordinates of the compensated control point Pi' are calculated as follows: xi'=xi+kc×Δxi, yi'=yi+kc×Δyi, zi'=zi+kc×Δzi. The compensation coefficient kc is greater than 1 in order to provide a certain amount of advance compensation to better offset the influence of wind. For the n initial control points, the above compensation calculations are performed respectively, and finally the compensated control point sequence {P1',P2',...,Pn'} is obtained. This position compensation method based on wind influence applies appropriate position corrections to each control point, so that the final generated flight trajectory can actively counteract wind disturbances, thereby improving the landing accuracy and control stability of the system under complex wind field conditions. At the same time, since the compensation amount is calculated based on the actual wind field parameters, this compensation method has strong adaptability and real-time performance, providing a good foundation for subsequent trajectory optimization.

[0089] Step 405: The trajectory is smoothed by combining the compensation control point and the maximum tension constraint of the tether of the UAV to obtain a landing flight trajectory.

[0090] Specifically, the maximum allowable tethering distance Rmax is calculated based on the maximum tension constraint Tmax of the tethering rope (set to 200N). For each compensation control point Pi'=(xi',yi',zi'), calculate its spatial distance di=[(xi'-xa)²+(yi'-ya)²+(zi'-za)²]^(1 / 2) to the tethering point A(xa,ya,za). Considering the mass m of the drone, the acceleration of gravity g, and the flight attitude angle θi, estimate the tethering rope tension Ti=m×g×cosθi×(di / hi) at this point, where hi is the height corresponding to the control point Pi'. When the calculated tension Ti exceeds the maximum tension Tmax, adjust the control point to the allowable range through iterative projection: first calculate the unit direction vector ui=(Pi'-A) / di, and then project the control point onto a sphere with a radius of Rmax centered at the tethering point to obtain the new control point position Pi''=A+Rmax×ui. After completing the constraint processing of all control points, the cubic spline interpolation method is used to smooth the corrected control point sequence. Natural boundary conditions are used during interpolation to ensure that the start and end points of the trajectory have zero curvature, thereby generating the final landing flight trajectory. The entire trajectory has a second-order continuous differentiable characteristic, which ensures smooth changes in velocity and acceleration. This trajectory smoothing method based on constraint optimization not only meets the tethered safety requirements, but also ensures the stability of the flight process, providing an ideal path reference for the precise landing control of tethered drones.

[0091] Step 50: Control the drone to land in the target landing area according to the landing flight trajectory.

[0092] Specifically, the planned landing flight trajectory is discretized into a series of expected position points Pd(t)=(xd(t), yd(t), zd(t)), and the expected speed vd(t) and expected acceleration ad(t) at each moment are calculated. In the actual control process, the current position of the drone P(t)=(x(t), y(t), z(t)) and the actual speed v(t) are obtained in real time, and the position tracking error ep(t)=Pd(t)-P(t) and the speed tracking error ev(t)=vd(t)-v(t) are calculated. Based on these error information, the control system uses a PID controller to generate the expected acceleration correction Δa(t): Δa(t)=kp×ep(t)+ki×∫ep(t)dt+kd×ev(t), where kp, ki and kd are proportional, integral and differential control parameters, respectively. The correction is superimposed on the expected acceleration ad(t) to obtain the actual control instruction ac(t)=ad(t)+Δa(t). The control system converts the acceleration command ac(t) into the attitude angle command θc(t) and thrust command Tc(t) of the drone, and accurately tracks the flight trajectory by adjusting the pitch angle, roll angle and throttle output of the drone. During the landing process, the control system continuously monitors the tether tension T(t) to ensure that it is always less than the maximum tension constraint Tmax. When it is detected that the tension is close to the constraint limit, the control system appropriately reduces the control gain to ensure that the system completes the trajectory tracking while ensuring safety.

[0093] Based on the above embodiment, as another optional embodiment, the step of determining the target landing area based on the landing mark may further include the following steps:

[0094] Specifically, the control system collects the tension value T(t) of the tether rope in real time through the torque sensor installed at the connection between the tether rope and the drone, and measures the connection angle α(t) between the tether rope and the drone body through the attitude sensor. The control system compares the collected tension value T(t) with the preset tension threshold Tth (set to 180N), and determines whether the connection angle α(t) exceeds the preset safety angle range [αmin, αmax] (set to [-60°, 60°]). When it is detected that T(t)>Tth or α(t)∉[αmin, αmax], the control system immediately starts the emergency handling procedure. First, based on the current tension value T(t) and the connection angle α(t), the safety buffer distance ds is calculated: ds=k1×(T(t)-Tth) / Tth+k2×|α(t)-αmax| / αmax, where k1 and k2 are safety factors (set to 2 meters and 1.5 meters respectively). Then, based on the current position P(t)=(x(t), y(t), z(t)), the emergency hovering point Ph is calculated in the direction away from the tethering point A: Ph=P(t)+ds×(P(t)-A) / |P(t)-A|. The control system then switches to emergency mode and quickly adjusts the attitude and thrust of the drone through the PD controller to move it to the emergency hovering point Ph and maintain stable hovering. In the emergency hovering state, the system continuously monitors the tension value and connection angle. When these parameters return to a safe range and remain stable for a period of time (such as 5 seconds), the control system replans the landing trajectory and resumes normal landing control.

[0095] See also Figure 2 , is a module schematic diagram of a fixed-point landing control system for a tethered drone provided in an embodiment of the present application, wherein the system includes:

[0096] A state parameter acquisition module, used for acquiring the current relative position and relative speed of the drone relative to the landing vehicle, and the landing identifier of the landing vehicle when receiving a landing request of the drone;

[0097] A flight parameter determination module, configured to determine a target flight parameter of the UAV based on the relative position and the relative speed;

[0098] A landing area determination module, used to determine a target landing area based on the landing mark;

[0099] A landing trajectory generation module, used to obtain the wind field parameters of the current environment of the UAV, and generate the landing flight trajectory of the UAV based on the wind field parameters, the target flight parameters and the target landing area;

[0100] The landing control module is used to control the UAV to land in the target landing area according to the landing flight trajectory.

[0101] Optionally, the state parameter acquisition module is further used to determine the initial relative position of the drone and the landing vehicle based on the GPS position information of the drone and the GPS position information of the landing vehicle;

[0102] Acquiring position data of a plurality of spatial position sensors disposed on a tether of the drone;

[0103] Establishing a spatial deformation model of the mooring rope according to the position data of the spatial position sensor;

[0104] Correcting the initial relative position based on the spatial deformation model to obtain a corrected relative position;

[0105] The relative position is subjected to a time differentiation operation to obtain the relative speed.

[0106] Optionally, the flight parameter determination module is further used to project the relative position onto a horizontal plane and a vertical plane to obtain a horizontal relative position and a vertical relative position, and to decompose the relative speed into a horizontal relative speed and a vertical relative speed;

[0107] Calculating a horizontal time margin according to the horizontal relative position and the horizontal relative speed;

[0108] Calculating a vertical time margin according to the vertical relative position and the vertical relative speed;

[0109] Generate a target velocity vector and a target attitude angle based on the horizontal time margin and the vertical time margin;

[0110] The target flight parameters are generated by combining the target velocity vector and the target attitude angle.

[0111] Optionally, the landing area determination module is further used to extract feature points and boundary information of the landing mark;

[0112] Calculate the three-dimensional attitude angle of the landing mark based on the feature points;

[0113] Constructing a safety buffer zone around the landing mark according to the boundary information;

[0114] Acquiring a current deformation state of a tether rope of the UAV, and calculating a predicted swing range of the tether rope during landing;

[0115] An overlapping area between the safety buffer zone and the predicted swing range is determined as a target landing area.

[0116] Optionally, the landing trajectory generating module is further used to obtain displacement sensor data at different height positions on the tethering rope of the UAV, and establish a spatial deformation curve of the tethering rope based on the displacement sensor data;

[0117] Dividing the spatial deformation curve into a plurality of equally spaced micro-element segments;

[0118] Based on the material parameters and structural parameters of the mooring rope, a strain-stress relationship model of the mooring rope is established;

[0119] Based on the strain-stress relationship model, the wind load on each microelement segment is solved, and the wind field parameters at the corresponding height are calculated according to the wind load.

[0120] Optionally, the landing trajectory generating module is further used to calculate the estimated landing time of the UAV according to the target flight parameters;

[0121] Dividing the estimated landing time into a plurality of time intervals, and determining a position offset under the action of wind force based on the wind field parameters in each of the time intervals;

[0122] Taking the center of the target landing area as the end point, a control point sequence of an initial landing trajectory is generated using a Bezier curve;

[0123] Performing position compensation on the control point sequence according to the position offset of each time interval to generate a compensated control point;

[0124] The trajectory is smoothed by combining the compensation control point and the maximum tension constraint of the tether rope of the UAV to obtain a landing flight trajectory.

[0125] Optionally, the landing control module is further used to monitor in real time the tension value of the tether rope of the drone and the connection angle between the tether rope and the drone;

[0126] When the tension value exceeds a preset tension threshold or the connection angle exceeds a preset angle range, a safety buffer distance is calculated;

[0127] An emergency hovering point is determined based on the safety buffer distance, and the UAV is controlled to enter an emergency hovering state.

[0128] It should be noted that: when the system provided in the above embodiment realizes its functions, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0129] An embodiment of the present application also provides a computer storage medium, which can store multiple instructions. The instructions are suitable for being loaded by a processor and executing a fixed-point landing control method for a tethered drone in the above embodiment. The specific execution process can be found in the specific description of the above embodiment, which will not be repeated here.

[0130] Please refer to Figure 3 The application also discloses an electronic device. Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0131] The communication bus 302 is used to realize the connection and communication between these components.

[0132] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0133] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0134] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0135] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 , the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of a fixed-point landing control method for a tethered drone.

[0136] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call the application program of a fixed-point landing control method of a tethered drone stored in the memory 305. When executed by one or more processors 301, the electronic device 300 executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0137] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0138] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0139] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0140] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0141] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0142] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0143] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for controlling the fixed-point landing of a tethered drone, characterized in that: The method comprises: When receiving a landing request from a drone, obtaining the current relative position and relative speed of the drone relative to the landing vehicle, and the landing identifier of the landing vehicle; Projecting the relative position onto a horizontal plane and a vertical plane to obtain a horizontal relative position and a vertical relative position, and decomposing the relative velocity into a horizontal relative velocity and a vertical relative velocity; Calculating a horizontal time margin according to the horizontal relative position and the horizontal relative speed; Calculating a vertical time margin according to the vertical relative position and the vertical relative speed; Generate a target velocity vector and a target attitude angle based on the horizontal time margin and the vertical time margin; Combining the target velocity vector and the target attitude angle to generate target flight parameters; Determine a target landing area based on the landing mark; Acquire wind field parameters of the current environment of the UAV, and generate a landing flight trajectory of the UAV based on the wind field parameters, the target flight parameters, and the target landing area; The UAV is controlled to land in the target landing area according to the landing flight trajectory.

2. The fixed-point landing control method of a tethered drone according to claim 1, characterized in that: The obtaining of the current relative position and relative speed of the UAV relative to the landing vehicle comprises: Determining the initial relative position of the drone and the landing vehicle based on the GPS position information of the drone and the GPS position information of the landing vehicle; Acquiring position data of a plurality of spatial position sensors disposed on a tether of the drone; Establishing a spatial deformation model of the mooring rope according to the position data of the spatial position sensor; Correcting the initial relative position based on the spatial deformation model to obtain a corrected relative position; The relative position is subjected to a time differentiation operation to obtain the relative speed.

3. The method for controlling the fixed-point landing of a tethered drone according to claim 1, characterized in that: The determining of the target landing area based on the landing mark includes: Extracting feature points and boundary information of the landing mark; Calculate the three-dimensional attitude angle of the landing mark based on the feature points; Constructing a safety buffer zone around the landing mark according to the boundary information; Acquiring a current deformation state of a tether rope of the UAV, and calculating a predicted swing range of the tether rope during landing; An overlapping area between the safety buffer zone and the predicted swing range is determined as a target landing area.

4. The method for controlling the fixed-point landing of a tethered drone according to claim 1, characterized in that: The obtaining of wind field parameters of the current environment of the UAV includes: Acquire displacement sensor data at different heights of the tether rope of the UAV, and establish a spatial deformation curve of the tether rope based on the displacement sensor data; Dividing the spatial deformation curve into a plurality of equally spaced micro-element segments; Based on the material parameters and structural parameters of the mooring rope, a strain-stress relationship model of the mooring rope is established; Based on the strain-stress relationship model, the wind load on each microelement segment is solved, and the wind field parameters at the corresponding height are calculated according to the wind load.

5. The method for controlling the fixed-point landing of a tethered drone according to claim 1, characterized in that: The step of generating a landing flight trajectory of the UAV based on the wind field parameters, the target flight parameters, and the target landing area includes: Calculating an estimated landing time of the UAV according to the target flight parameters; Dividing the estimated landing time into a plurality of time intervals, and determining a position offset under the action of wind force based on the wind field parameters in each of the time intervals; Taking the center of the target landing area as the end point, a control point sequence of an initial landing trajectory is generated using a Bezier curve; Performing position compensation on the control point sequence according to the position offset of each time interval to generate a compensated control point; The trajectory is smoothed by combining the compensation control point and the maximum tension constraint of the tether rope of the UAV to obtain a landing flight trajectory.

6. The method for controlling the fixed-point landing of a tethered drone according to claim 1, characterized in that: The method further comprises: Real-time monitoring of the tension value of the tether rope of the drone and the connection angle between the tether rope and the drone; When the tension value exceeds a preset tension threshold or the connection angle exceeds a preset angle range, a safety buffer distance is calculated; An emergency hovering point is determined based on the safety buffer distance, and the UAV is controlled to enter an emergency hovering state.

7. A fixed-point landing control system for a tethered drone, characterized in that: The system comprises: A state parameter acquisition module, used for acquiring the current relative position and relative speed of the drone relative to the landing vehicle, and the landing identifier of the landing vehicle when receiving a landing request of the drone; A flight parameter determination module is used to project the relative position onto a horizontal plane and a vertical plane to obtain a horizontal relative position and a vertical relative position, and to decompose the relative speed into a horizontal relative speed and a vertical relative speed; calculate a horizontal time margin according to the horizontal relative position and the horizontal relative speed; calculate a vertical time margin according to the vertical relative position and the vertical relative speed; generate a target velocity vector and a target attitude angle based on the horizontal time margin and the vertical time margin; and combine the target velocity vector and the target attitude angle to generate a target flight parameter; A landing area determination module, used to determine a target landing area based on the landing mark; A landing trajectory generation module, used to obtain the wind field parameters of the current environment of the UAV, and generate the landing flight trajectory of the UAV based on the wind field parameters, the target flight parameters and the target landing area; The landing control module is used to control the UAV to land in the target landing area according to the landing flight trajectory.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method according to any one of claims 1 to 6.

9. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-6.

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