Water-air dual-purpose electric unmanned aerial vehicle autonomous take-off and landing control system

Abstract

The invention provides an autonomous takeoff and landing control system for a water-air dual-purpose electric unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle takeoff and landing control, the cooperative contact attribute of a medium contact area during autonomous takeoff and landing of the unmanned aerial vehicle is determined through dynamic pressure distribution data, and a power compensation label of the unmanned aerial vehicle during vertical takeoff and landing on the medium contact area is determined; determining a transition confidence decision corresponding to the transition tilting state of the undercarriage when the unmanned aerial vehicle takes off and lands autonomously; and determining a disturbance suppression index of the unmanned aerial vehicle during vertical take-off and landing in the medium contact area according to the power compensation label and the attitude maintenance boundary after the position check, and performing tolerance adaptation control on the attitude of the unmanned aerial vehicle during take-off and landing in the water surface environment and the land environment by the disturbance suppression index. The dynamic contact state of the unmanned aerial vehicle in the medium contact area can be subjected to differential regulation and control under the condition of complex takeoff and landing environment change, so that the environmental adaptability of attitude regulation and control in the autonomous vertical takeoff and landing process is improved.

Description

Technical Field

[0001] This application relates to the technical field of unmanned aerial vehicle (UAV) takeoff and landing control. More specifically, this application relates to an autonomous takeoff and landing control system for a water-air dual-use electric UAV. Background Art

[0002] UAV takeoff and landing control refers to the skill of coordinating and adjusting the attitude, speed, thrust, and landing gear structure of a UAV through a flight control system during the takeoff and landing processes to achieve safe, stable, and precise takeoff and landing operations. For a water-air dual-use electric UAV, takeoff and landing control is particularly complex, as it not only needs to adapt to the high reaction force characteristics of a hard contact surface on land but also needs to cope with the non-linear changes caused by buoyancy, fluctuations, and reflection disturbances in a water environment. In an autonomous flight scenario, the takeoff and landing control system needs to combine sensor feedback information, dynamically identify the environmental state, and execute a joint control strategy based on mechanisms such as pose regulation, thrust vector adjustment, and center-of-gravity self-balancing.

[0003] However, the existing autonomous takeoff and landing control systems for water-air dual-use electric UAVs generally lack the ability to model the dynamic response characteristics during the medium contact process. As a result, it is difficult for the system to achieve real-time and precise control when dealing with the contact force changes and attitude disturbances under different media (such as water and land), leading to unstable disturbance suppression effects during the landing gear attitude adjustment process, thereby causing instability in the takeoff and landing attitudes of the landing gear structure. Therefore, how to differentially control the dynamic contact state of a UAV in the medium contact area under complex landing environment changes to improve the environmental adaptability of attitude control during autonomous vertical takeoff and landing is a difficult problem faced by the industry. Summary of the Invention

[0004] This application provides an autonomous takeoff and landing control system for a water-air dual-use electric UAV, which can differentially control the dynamic contact state of the UAV in the medium contact area under complex landing environment changes to improve the environmental adaptability of attitude control during autonomous vertical takeoff and landing.

[0005] In a first aspect, this application provides an autonomous takeoff and landing control system for a water-air dual-use electric UAV, and the takeoff and landing control system includes:

[0006] A data acquisition module, configured to acquire dynamic pressure distribution data of the medium contact area during the autonomous takeoff and landing of the UAV;

[0007] A differential compensation module, configured to determine the collaborative contact attributes of the medium contact area during the autonomous takeoff and landing of the UAV through the dynamic pressure distribution data, perform differential compensation on the collaborative contact attributes, and obtain a dynamic compensation label for the UAV during vertical takeoff and landing in the medium contact area;

[0008] The attitude verification module is used to determine the trajectory fitting deviation of the landing gear attitude adjustment during the takeoff and landing of the UAV in the water environment and the land environment, fuse and correct the trajectory fitting deviation, obtain the transition confidence decision corresponding to the transition tilting state of the landing gear during the autonomous takeoff and landing of the UAV, and then perform attitude verification on the attitude maintenance boundary of the UAV during the autonomous vertical takeoff, landing and cruising by the transition confidence decision;

[0009] The attitude adaptation module is used to determine the disturbance suppression index of the UAV during the vertical takeoff and landing in the medium contact area according to the power compensation label and the attitude maintenance boundary after attitude verification, and then perform tolerance adaptation control on the attitude of the UAV during the takeoff and landing in the water environment and the land environment by the disturbance suppression index.

[0010] In this embodiment, the medium contact area refers to the spatial area where the landing gear structure directly makes physical contact with the water surface and the land during the takeoff and landing of the UAV.

[0011] In this embodiment, determining the collaborative contact attribute of the medium contact area during the autonomous takeoff and landing of the UAV through the dynamic pressure distribution data specifically includes:

[0012] Determine the pressure center offset of the medium contact surface according to the dynamic pressure distribution data;

[0013] Determine the steady-state contact gradient of the medium contact area during the autonomous takeoff and landing of the UAV through the pressure center offset;

[0014] Determine the collaborative contact attribute of the medium contact area during the autonomous takeoff and landing of the UAV according to the steady-state contact gradient.

[0015] In this embodiment, the collaborative contact attribute refers to the collaborative characteristics of the landing gear actions at each contact point inside the medium contact area during the autonomous takeoff and landing of the UAV.

[0016] In this embodiment, determining the trajectory fitting deviation of the landing gear attitude adjustment during the takeoff and landing of the UAV in the water environment and the land environment specifically includes:

[0017] Collect the trajectory convergence index of the landing gear attitude adjustment during the autonomous takeoff and landing of the UAV in the water environment;

[0018] Collect the trajectory adaptation characteristics of the landing gear attitude adjustment during the autonomous takeoff and landing of the UAV in the land environment;

[0019] Determine the trajectory fitting deviation of the landing gear attitude adjustment during the autonomous takeoff and landing of the UAV according to the trajectory convergence index and the trajectory adaptation characteristics.

[0020] In this embodiment, the trajectory fitting deviation refers to the error measure formed by the dynamic comparison result of the actual adjustment trajectory and the expected trajectory of the UAV landing gear attitude under different takeoff and landing media.

[0021] In this embodiment, the transitional tilting state of the landing gear refers to the dynamic tilting state of the UAV landing gear during the attitude adjustment process when it changes from the initial attitude to the stable attitude.

[0022] In this embodiment, the position and state verification of the attitude maintenance boundary of the UAV during autonomous vertical takeoff, landing and cruising by the transitional confidence decision specifically includes:

[0023] Generating a tolerance anchor position and state for the UAV attitude maintenance based on the transitional confidence decision;

[0024] Determining the motion correction rule of the UAV during autonomous vertical takeoff, landing and cruising;

[0025] Performing position and state verification on the tolerance anchor position and state according to the motion correction rule, and outputting the attitude maintenance boundary after position and state verification.

[0026] In this embodiment, the autonomous vertical takeoff, landing and cruising refers to a flight mode in which the UAV completes the whole process of vertical takeoff, vertical landing and stable cruising without manual intervention.

[0027] In this embodiment, determining the disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area according to the power compensation label and the attitude maintenance boundary after position and state verification specifically includes:

[0028] Determining the balance adjustment feedback amount of the UAV during vertical takeoff and landing in the medium contact area according to the power compensation label;

[0029] Determining the interaction guidance attribute of the UAV during vertical takeoff and landing in the medium contact area according to the attitude maintenance boundary after position and state verification;

[0030] Determining the disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area through the balance adjustment feedback amount and the interaction guidance attribute.

[0031] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects:

[0032] Acquire dynamic pressure distribution data of the medium contact area during autonomous takeoff and landing of the UAV; determine the collaborative contact properties of the medium contact area during autonomous takeoff and landing of the UAV through the dynamic pressure distribution data, perform differential compensation on the collaborative contact properties, and obtain a power compensation label for the UAV during vertical takeoff and landing on the medium contact area; determine the trajectory fitting deviation of the landing gear attitude adjustment when the UAV takes off and lands in water surface environment and land environment, perform fusion correction on the trajectory fitting deviation, and obtain a transition confidence decision corresponding to the transition tilt state of the landing gear during autonomous takeoff and landing of the UAV, and then use the transition confidence decision to perform position verification on the attitude maintenance boundary of the UAV during autonomous vertical takeoff and landing cruise; determine the disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area based on the power compensation label and the attitude maintenance boundary after position verification, and then use the disturbance suppression index to perform tolerance adaptive control on the attitude of the UAV during takeoff and landing in water surface environment and land environment.

[0033] It can be seen that in this application, the dynamic contact state of the UAV in the medium contact area can be adjusted in a coordinated manner under complex take-off and landing environment conditions. Specifically, by obtaining dynamic pressure distribution data in the medium contact area during the autonomous take-off and landing of the UAV, the force characteristics and load response changes of the contact medium can be identified with high precision and low latency, realizing real-time perception and contact behavior modeling of the UAV's take-off and landing attitude state. By analyzing the center offset of the pressure distribution, extracting the steady-state contact gradient and generating cooperative contact properties, it is possible to effectively characterize the landing force coordination under different take-off and landing environments, thereby forming a power control label with directional compensation capability, making attitude adjustment more stable and controllable. By fusing and correcting the trajectory fitting deviation, it is possible to generate confidence decisions corresponding to the landing gear transition tilt state under complex disturbance conditions, effectively realizing the time series prediction and coordinated judgment of the attitude adjustment process, thereby ensuring the continuity and stability of the attitude switching process. By fusing the power compensation label and the position verification results, an environment-adaptive disturbance suppression index is generated, which can dynamically adjust the attitude tolerance boundary and correction strategy in water and land environments, significantly enhancing the stable flight and attitude maintenance capabilities of the UAV take-off and landing control system in various medium contact scenarios.

[0034] In summary, the technical solution adopted in this application can differentially control the dynamic contact state of the UAV in the medium contact area under complex take-off and landing environment changes, so as to improve the environmental adaptability of attitude control during autonomous vertical take-off and landing. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0036] Figure 1 is a module structure diagram of an amphibious electric UAV autonomous takeoff and landing control system provided by the present application;

[0037] Figure 2 is a schematic flow chart of determining the power compensation label provided by the present application;

[0038] Figure 3 is a schematic flow chart of determining the transition confidence decision provided by the present application. Specific embodiments

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0040] The embodiments of the present application provide an amphibious electric UAV autonomous takeoff and landing control system. Its core is to obtain the dynamic pressure distribution data of the medium contact area during the autonomous takeoff and landing of the UAV; determine the collaborative contact attributes of the medium contact area during the autonomous takeoff and landing of the UAV through the dynamic pressure distribution data, perform differential compensation on the collaborative contact attributes to obtain the power compensation label when the UAV vertically takes off and lands on the medium contact area; determine the trajectory fitting deviation of the landing gear attitude adjustment during the takeoff and landing of the UAV in the water environment and the land environment, perform fusion correction on the trajectory fitting deviation to obtain the transition confidence decision corresponding to the transition tilting state of the landing gear during the autonomous takeoff and landing of the UAV, and then perform attitude verification on the attitude maintenance boundary during the autonomous vertical takeoff and landing cruise of the UAV by the transition confidence decision; determine the disturbance suppression index when the UAV vertically takes off and lands in the medium contact area according to the power compensation label and the attitude maintenance boundary after attitude verification, and then perform tolerance adaptation control on the attitude of the UAV during the takeoff and landing in the water environment and the land environment by the disturbance suppression index. By adopting the above solution, the dynamic contact state of the UAV in the medium contact area can be differentially regulated under the conditions of complex takeoff and landing environment changes, so as to improve the environmental adaptability of attitude regulation during the autonomous vertical takeoff and landing process.

[0041] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments. Refer to Figure 1 As shown, this figure is a module structure diagram of an autonomous takeoff and landing control system for a water-air dual-use electric unmanned aerial vehicle according to this embodiment of the present application. The takeoff and landing control system includes: a data acquisition module 100, a differential compensation module 200, a position and state verification module 300, and an attitude adaptation module 400, which are described as follows:

[0042] The data acquisition module 100 is used to acquire the dynamic pressure distribution data of the medium contact area when the unmanned aerial vehicle takes off and lands autonomously.

[0043] Specifically, when implementing, acquiring the dynamic pressure distribution data of the medium contact area when the unmanned aerial vehicle takes off and lands autonomously can be achieved by the following method, that is: embed a highly sensitive two-dimensional flexible pressure sensor array in the bottom structure of the landing gear of the unmanned aerial vehicle. The pressure sensor array is composed of piezoresistive or capacitive materials and can achieve millimeter-level spatial resolution and millisecond-level time response. During the takeoff and landing process, the pressure sensor array senses the pressure changes at each contact point in real time, and converts the analog pressure signal into a digital signal through an analog-to-digital conversion module. The digital signal is preprocessed by an edge computing unit built into the flight control system, including time sequence alignment, anomaly filtering, and spatial interpolation, and finally outputs a complete time-space two-dimensional pressure distribution map. All processing results are stored in the local data buffer according to the time sequence, and the dynamic pressure distribution data of the medium contact area when the unmanned aerial vehicle takes off and lands autonomously is obtained by reading the local data buffer. In other embodiments, other methods can also be used to acquire the dynamic pressure distribution data of the medium contact area when the unmanned aerial vehicle takes off and lands autonomously, which is not limited here.

[0044] It should be noted that in this application, the medium contact area refers to the spatial area where the landing gear structure directly physically contacts the water surface and the land during the takeoff and landing process of the unmanned aerial vehicle; the dynamic pressure distribution data refers to the set of pressure intensity information generated by each position point in the medium contact area changing with time during the takeoff and landing of the unmanned aerial vehicle.

[0045] The differential compensation module 200 is used to determine the cooperative contact attribute of the medium contact area when the unmanned aerial vehicle takes off and lands autonomously through the dynamic pressure distribution data, and perform differential compensation on the cooperative contact attribute to obtain the power compensation label when the unmanned aerial vehicle vertically takes off and lands on the medium contact area.

[0046] In this embodiment, specifically, the following method can be used to determine the cooperative contact attribute of the medium contact area when the unmanned aerial vehicle takes off and lands autonomously through the dynamic pressure distribution data, that is:

[0047] Determine the pressure center offset of the medium contact surface according to the dynamic pressure distribution data;

[0048] Determine the steady-state contact gradient of the medium contact area during the autonomous takeoff and landing of the UAV based on the pressure center offset;

[0049] Determine the collaborative contact attribute of the medium contact area during the autonomous takeoff and landing of the UAV according to the steady-state contact gradient.

[0050] When specifically implemented, first, the dynamic pressure distribution data collected by the two-dimensional flexible pressure sensing array arranged at the bottom of the landing gear can be input into the edge computing module. The edge computing module performs mass moment calculation on the two-dimensional pressure matrix within each time slice. The spatial weighted average method can be used in the mass moment calculation to calculate the pressure center coordinates of the current pressure center of gravity; calculate the difference between the pressure center coordinates and the geometric center coordinates of the contact area, and use the difference calculation result as the pressure center offset of the medium contact surface at this moment. Then, a sliding time window method is used to perform local fitting and trend analysis on the pressure center offset. The specific approach is as follows: Set a fixed window length (such as 0.5 seconds), calculate the first derivative of the change rate of the pressure center offset within this fixed window length, analyze whether the change of the pressure center offset converges or approaches zero, and then introduce the local linear regression method to fit the pressure center offset curve of the pressure center offset, and extract the mean change slope and fluctuation standard deviation of the pressure center offset. If the fluctuation standard deviation is lower than the preset threshold and the change slope approaches zero, it is determined that the contact process has entered the steady-state section, and the contact gradient value within this section is output. The smaller the contact gradient value, the better the pressure balance; and use the ratio of the mean change slope and the fluctuation standard deviation of the pressure center offset as the steady-state contact gradient of the medium contact area during the autonomous takeoff and landing of the UAV. Finally, use the steady-state contact gradient as an input parameter to perform a fusion judgment with the spatial collaboration index of the pressure distribution area. Specifically: Calculate the steady-state gradient difference of each quadrant of the contact surface in the medium contact area. If the steady-state gradient difference between each quadrant is less than the set threshold (such as 5%), it indicates that the overall contact tends to be balanced; analyze the temporal consistency of the force curves at different contact points again. The cross-correlation function can be used to analyze the synchronization degree between the pressure time series to obtain the contact consistency score, and a collaborative contact evaluation function is constructed through the gradient difference and the consistency score. Use the quantization result output by the collaborative contact evaluation function as the collaborative contact attribute. A high collaborative contact attribute indicates that the landing gear structure is well coordinated, the contact environment is controllable, and it is suitable to enter the attitude stability adjustment link.

[0051] It should be noted that in this application, the pressure center offset refers to the spatial offset degree of the pressure distribution center of gravity relative to the geometric center in the medium contact area; the steady-state contact gradient refers to the change trend of the pressure center in the medium contact area within a certain time window during the takeoff and landing of the UAV; the collaborative contact attribute refers to the collaborative characteristics of the landing gear actions at each contact point within the medium contact area during the autonomous takeoff and landing of the UAV.

[0052] Preferably, in this embodiment, differential compensation is performed on the collaborative contact attribute to obtain a power compensation label for the vertical takeoff and landing of the drone in the medium contact area. Refer to Figure 2 As shown, this figure is a schematic flowchart of determining the power compensation label in some embodiments of the present application. The determination of the power compensation label in this embodiment can be implemented by the following steps:

[0053] In step S21, the pressure loss measurement of the medium contact surface is analyzed through the collaborative contact attribute;

[0054] In step S22, the anti-interference matching information in the current autonomous takeoff and landing environment is collected;

[0055] In step S23, differential adaptation is performed on the takeoff and landing attitude of the drone according to the pressure loss measurement and the anti-interference matching information to obtain a tolerance adaptation attribute for the vertical takeoff and landing of the drone in the medium contact area;

[0056] In step S24, the power compensation label for the vertical takeoff and landing of the drone in the medium contact area is determined from the tolerance adaptation attribute.

[0057] In specific implementation, first, extract the steady-state pressure value of each pressure node from the collaborative contact attributes, construct a two-dimensional pressure distribution map of the contact area, and divide the two-dimensional pressure distribution map into multiple sub-regions. When dividing the regions, it can be divided by quadrants or annuli, and calculate the average pressure value of each sub-region. Subsequently, calculate the maximum pressure difference and standard deviation between all sub-regions, and use the maximum pressure difference and standard deviation between all sub-regions as the pressure loss measure of the medium contact surface. Then, collect the current meteorological parameters (such as wind speed and wind direction) through the environmental perception module integrated in the flight control system, and use a micro anemometer or barometric sensor to provide wind disturbance information. At the same time, combine the airborne accelerometer and gyroscope to measure the dynamic response of the attitude change during the landing process, and deduce the rigid feedback index of the ground support surface. In addition, the instantaneous impact response curve of the landing gear contact point can be used to fit the contact response time through a first-order system model to judge the ground material characteristics (such as soft soil, hard ground, water surface) and its response speed to disturbances. Then, after unifying and normalizing all the rigid feedback indices and the response speed to disturbances, input them into the anti-disturbance feature matching model, and output anti-disturbance matching information from the anti-disturbance feature matching model. Then, use the pressure loss measure and anti-disturbance matching information as inputs, and establish an attitude tolerance function using a multi-parameter differential control model. The attitude tolerance function evaluates the minimum correction angle and the expected attitude boundary expansion value required for the current attitude adjustment. The differential control model is based on the extended state observer mechanism and makes adaptive adjustments in combination with historical control effects. If the pressure loss measure is large and the anti-disturbance ability is weak, a larger pitch angle and roll angle offset will be tolerated, and the attitude recovery rate will be reduced to avoid oscillation. Otherwise, the tolerance range will be tightened, and the tolerance adaptation attributes will be output in the form of attitude angle thresholds, reaction delay allowable values, and adjustment rates for loading the tolerance control strategy inside the flight control system. Finally, input information such as the attitude deviation tolerance range, target attitude threshold, and execution lag parameter in the tolerance adaptation attributes into the dynamic control mapping model, and establish a compensation force vector library in combination with the current output power state of the flight control system and the rotor response ability. In this compensation force vector library, the main execution methods are motor thrust difference adjustment, servo arm response adjustment, and propulsion vector offset. According to the current attitude change trend and pressure distribution, calculate the required dynamic adjustment command in real time, and use this dynamic adjustment command as the dynamic compensation label for the vertical takeoff and landing of the drone in the medium contact area. Among them, the dynamic compensation label includes indicators such as the thrust increase and decrease ratio, the left and right wing compensation levels, and the longitudinal attitude elevation rate.

[0058] It should be noted that in this application, the pressure loss measurement refers to the degree of inconsistent force between different contact points within the medium contact area; the anti-interference matching information refers to the perception and response characteristics of the UAV to the disturbance effect in the current takeoff and landing environment; the tolerance adaptation attribute refers to the range of attitude deviation that can be tolerated to achieve stable takeoff and landing under the influence of current pressure unevenness and environmental disturbance; the power compensation label refers to the power adjustment instruction required to ensure attitude stability, contact balance, and anti-interference actions during the vertical takeoff and landing process of the UAV.

[0059] The attitude calibration module 300 is configured to determine the trajectory fitting deviation of the landing gear attitude adjustment when the UAV takes off and lands in the water environment and the land environment, fuse and correct the trajectory fitting deviation to obtain a transition confidence decision corresponding to the transition tilting state of the landing gear during the UAV's autonomous takeoff and landing, and then perform attitude calibration on the attitude maintenance boundary of the UAV during autonomous vertical takeoff, landing, and cruising based on the transition confidence decision.

[0060] In this embodiment, the trajectory fitting deviation of the landing gear attitude adjustment when the UAV takes off and lands in the water environment and the land environment can be specifically implemented by the following steps, that is:

[0061] Collect the trajectory convergence index of the landing gear attitude adjustment when the UAV takes off and lands autonomously in the water environment;

[0062] Collect the trajectory adaptation characteristics of the landing gear attitude adjustment when the UAV takes off and lands autonomously in the land environment;

[0063] Determine the trajectory fitting deviation of the landing gear attitude adjustment when the UAV takes off and lands autonomously according to the trajectory convergence index and the trajectory adaptation characteristics.

[0064] In specific implementation, first, in the water takeoff and landing experimental environment, a high-definition stereo vision system and an inertial measurement unit are deployed to collect the spatial position and attitude angle data of the end of the landing gear in real time. The expected attitude trajectory is predefined by the flight control system as a time series function, including the target pitch angle, roll angle, and altitude curve. During the actual adjustment process, after smoothing the actual trajectory data using the least squares fitting method, it is aligned point by point with the expected trajectory, and the error distance and the rate of change of the error direction at each time point are calculated. By obtaining the rate of decrease of the sum of squared errors over time, the mean error within the steady state interval, and the maximum residual ratio, the rate of decrease, the mean error within the steady state interval, and the maximum residual ratio are used as trajectory convergence indicators. Then, during the land takeoff and landing process, the complete trajectory data of the landing gear adjustment action is collected using the same vision and inertial measurement system as in the water experiment, and feature points are extracted from the attitude curve, including the starting point of the trajectory, the maximum offset point, the final stable point, and their corresponding time nodes. Then, the response time of the trajectory curve (the time from the issuance of the control command to the establishment of the stable attitude), the trajectory smoothness (the rate of change of the second derivative of the curve continuity), and the maximum deviation angle and fitting residual between the target trajectory and the actual trajectory are calculated. The response time, the trajectory smoothness, the maximum deviation angle, and the fitting residual are used as trajectory adaptation features. Finally, the trajectory convergence indicators and the fitting error amount in the trajectory adaptation features are normalized to construct a unified multi-dimensional error space, which includes sub-indicators such as the maximum offset error, response delay, and trajectory volatility. Then, the principal component analysis method is used to reduce the dimension of the multi-dimensional features and extract the main factor of the comprehensive trajectory performance. The support vector regression method is used to fit the overall fitting curve between the actual trajectory and the expected trajectory, calculate its average fitting error, and output a unified trajectory fitting deviation. This trajectory fitting deviation quantitatively represents the consistency difference between the control model and the structure execution in the two takeoff and landing environments. If this trajectory fitting deviation is greater than the preset threshold, it indicates that there is a problem of mismatch between control and execution in the water or land takeoff and landing scenarios, and model reconstruction or parameter adjustment is required.

[0065] It should be noted that in this application, the trajectory convergence indicator refers to the degree of dynamic convergence of the actual action trajectory to the expected trajectory during the attitude adjustment of the landing gear when the UAV takes off or lands in the water environment; the trajectory adaptation feature refers to the degree of fit between the actual adjustment trajectory of the landing gear and the setting of the flight control system during the land takeoff and landing of the UAV; the trajectory fitting deviation refers to the error measure formed by the dynamic comparison results of the actual adjustment trajectory and the expected trajectory of the UAV landing gear attitude under different takeoff and landing media.

[0066] Preferably, in this embodiment, the trajectory fitting deviation is fused and corrected to obtain a transition confidence decision corresponding to the transition tilting state of the landing gear during the autonomous takeoff and landing of the UAV, referring to Figure 3As shown, the figure is a schematic flowchart of determining the transition confidence decision in some embodiments of the present application. In this embodiment, the determination of the transition confidence decision can be implemented by the following steps:

[0067] In step S31, extract the attitude oscillation characteristics of the landing gear from the transition tilting state of the landing gear during the autonomous takeoff and landing of the unmanned aerial vehicle (UAV).

[0068] In step S32, determine the linkage confidence quantity during the transition tilting of the landing gear during the autonomous takeoff and landing of the UAV according to the attitude oscillation characteristics.

[0069] In step S33, determine the dynamic tilting index during the transition tilting of the landing gear during the autonomous takeoff and landing of the UAV.

[0070] In step S34, map the dynamic tilting index into the linkage confidence quantity during the transition tilting of the landing gear during the autonomous takeoff and landing of the UAV to obtain the transition confidence decision corresponding to the transition tilting state of the landing gear during the autonomous takeoff and landing of the UAV.

[0071] In specific implementation, first, using the data of the inertial measurement unit with high-frequency sampling, including linear acceleration, angular velocity, and angular acceleration, record the three-axis time series of the movement of the landing gear during the transition phase. Decompose the collected data through wavelet transform, extract the main oscillation frequency components, identify the high-frequency disturbance sections therein, calculate the mean square deviation of attitude change, the maximum amplitude difference, and the main oscillation period within each time period, and use the mean square deviation of attitude change, the maximum amplitude difference, and the main oscillation period within each time period as the attitude oscillation characteristics of the landing gear within this event segment. Next, conduct multi-point correlation analysis on the attitude oscillation characteristics, use the Pearson correlation coefficient method to calculate the synchronization degree of attitude changes among the support points of the landing gear during the oscillation process. Subsequently, use the principal component analysis technique to identify the main oscillation direction, calculate the response delay and phase shift of the overall structure in this main direction, and then construct a confidence evaluation function based on the three indicators of oscillation amplitude, frequency, and synergy. Input the response delay and phase shift in the main direction into the confidence evaluation function, and use the output result as the linkage confidence quantity during the transition tilt of the landing gear during the autonomous takeoff and landing of the UAV. Then, in the flight control system, call the output of the inertial measurement unit and the center of gravity positioning module to obtain the angular velocity, angular acceleration of the pitch angle and roll angle in real time, as well as the instantaneous offset of the UAV's center of gravity relative to the contact surface. Then input the angular velocity, angular acceleration of the pitch angle and roll angle, and the instantaneous offset of the UAV's center of gravity relative to the contact surface into the state observation model, construct a three-dimensional index vector with the change amplitude of angular velocity, the center of gravity offset speed, and the attitude feedback lag amount as variables, and use this three-dimensional index vector as the dynamic tilt index during the transition tilt of the landing gear during the autonomous takeoff and landing of the UAV. Finally, establish a fusion mapping model, input the dynamic tilt index into a multi-layer perceptron neural network or a fuzzy control rule system, and at the same time use the linkage confidence quantity as the mapping weight parameter. The mapping model outputs a confidence score, and the numerical range is usually between 0 and 1. This confidence score represents the control credibility of the current tilt state. If the confidence score is higher than 0.7, it is regarded as a "controllable transition state", and the attitude adjustment continues; if it is lower than 0.4, trigger deceleration braking or terminate the adjustment and enter the protection mode. Use this confidence score as the transition confidence decision corresponding to the transition tilt state of the landing gear during the autonomous takeoff and landing of the UAV, and the transition confidence decision will be refreshed in real time in the flight control main system, which is used to dynamically switch the attitude control strategy and the control parameter template to ensure that the UAV enters a safe and stable landing state interval.

[0072] It should be noted that in this application, the transition tilting state of the landing gear refers to the dynamic tilting state of the UAV landing gear during the attitude adjustment process when it changes from the initial attitude to the stable attitude; the attitude oscillation characteristic refers to the periodic jitter behavior of the landing gear in terms of spatial displacement and attitude angle during the UAV entering the landing gear attitude transition adjustment state; the linkage confidence level is an index indicating the coordination degree of the overall landing structure of the UAV during takeoff and landing in the current attitude adjustment; the dynamic tilting index refers to the set of characteristic values of the UAV relative to the contact surface in terms of the attitude angle change rate, center of gravity displacement, and attitude control input response during the attitude transition adjustment of the landing gear; the transition confidence decision is the criterion for judging whether the current landing gear attitude is in the controllable transition state of the takeoff and landing attitude.

[0073] In this embodiment, the attitude maintenance boundary of the UAV during autonomous vertical takeoff and landing cruise is checked for attitude by the transition confidence decision, which can be specifically implemented in the following manner, that is:

[0074] Generate a tolerance anchor attitude for the UAV attitude maintenance based on the transition confidence decision;

[0075] Determine the motion correction rule of the UAV during autonomous vertical takeoff and landing cruise;

[0076] Check the tolerance anchor attitude according to the motion correction rule and output the attitude maintenance boundary after attitude check.

[0077] In specific implementation, first, input the transition confidence decision value into the attitude evaluation module, which is implemented by the fault-tolerant attitude calculation unit embedded in the flight control system. According to the combined result of the transition confidence decision value and the index of the transition tilt, three parameters are dynamically set in the three-axis coordinate system of the flight attitude: the maximum allowable pitch angle change range, the maximum roll angle adjustment amount, and the upper limit of the allowable attitude oscillation frequency. For example, when the transition confidence decision value is high, the system can tighten the set parameters to form a tolerance anchor attitude with a small attitude stability deviation; when the transition confidence decision value decreases, the system expands the boundary of the set parameters, tolerates more attitude oscillations but does not trigger adjustment behavior, and the tolerance anchor attitude is stored in the flight control attitude control cache in the form of a data structure. Then, according to the aircraft model structure parameters, flight load status, and current environmental disturbance parameters (such as wind speed, air pressure change, etc.), dynamically call the motion correction parameter template stored in the flight control system, and then use the flight data feedback system to read the three-axis angular velocity and angular acceleration values output by the gyroscope in real time, and combine the historical attitude repair efficiency to quickly predict the current deviation direction. According to the deviation direction and amplitude, determine which correction path should be used by means of look-up table matching or fuzzy control rules. For example, whether to adjust the roll angle by deflecting the thrust difference between the left and right rotors, or to correct the front and rear attitude deviation by the pitch motor. The used correction path is used as the motion correction rule. In other embodiments, other methods can also be used to determine the motion correction rule, which is not limited here. The motion correction rule also includes a correction start threshold, a maximum allowable adjustment rate, and a correction priority, which are used to guide the system to preferentially correct the direction that most affects flight stability in the case of multiple deviations coexisting. Finally, compare the current three-axis angles of the flight attitude and their change trends with the tolerance anchor attitude dimension by dimension, calculate the deviation amplitude and speed, and determine whether it exceeds the set threshold. If a certain attitude dimension is close to the tolerance boundary, call the correction scheme in the aforementioned motion correction rule, predict the change trend of the attitude after correction, and adjust the boundary width of the original tolerance anchor attitude accordingly. For example, dynamically scale the pitch angle tolerance range from ±5 degrees to ±3 degrees, and finally generate an attitude maintenance boundary after position verification. The attitude maintenance boundary defines the maximum allowable angle offset range, control response trigger conditions, and attitude maintenance time limit of the three axes in the form of a matrix.

[0078] It should be noted that in this application, autonomous vertical takeoff, landing and cruise refers to a flight mode in which the drone completes the entire process of vertical takeoff, vertical landing and stable cruise without manual intervention; tolerance anchor position state refers to a set of dynamic reference attitude parameters during the attitude regulation process of the drone; motion correction rules refer to a set of strategies used by the flight control system to identify and correct attitude offsets during the vertical takeoff, landing and cruise phase; attitude maintenance boundary refers to the acceptable attitude change range of the drone during flight, which is used to ensure flight stability and control safety; position state verification refers to comparing the current flight state with the tolerance anchor position state and correcting its boundary determination criteria according to the motion correction rules, so as to obtain the actually executable attitude maintenance control range, which is used to limit the attitude change of the drone in real time.

[0079] The attitude adaptation module 400 is configured to determine the disturbance suppression index of the drone during vertical takeoff and landing in the medium contact area according to the power compensation label and the attitude maintenance boundary after position state verification, and then perform tolerance adaptation control on the attitude of the drone during takeoff and landing in the water environment and the land environment according to the disturbance suppression index.

[0080] In this embodiment, the method for determining the disturbance suppression index of the drone during vertical takeoff and landing in the medium contact area according to the power compensation label and the attitude maintenance boundary after position state verification may specifically adopt the following method, that is:

[0081] Determine the balance adjustment feedback amount of the drone during vertical takeoff and landing in the medium contact area according to the power compensation label;

[0082] Determine the interaction guidance attribute of the drone during vertical takeoff and landing in the medium contact area according to the attitude maintenance boundary after position state verification;

[0083] Determine the disturbance suppression index of the drone during vertical takeoff and landing in the medium contact area through the balance adjustment feedback amount and the interaction guidance attribute.

[0084] In specific implementation, first, read the parameters included in the power compensation tag. The parameters can be thrust increment instructions, landing and takeoff fulcrum adjustment angles, rotor asymmetric acceleration amounts, etc. Combine the real-time flight attitude data (including three-axis angles and angular velocities), compare the parameters of the power compensation tag with the current flight control response, and through the error inversion mechanism in the flight attitude control module, convert the error between the expected compensation attitude and the current actual attitude into angular acceleration fine-tuning instructions and lift distribution factors, and use the angular acceleration fine-tuning instructions and lift distribution factors as the balance adjustment feedback amount when the UAV vertically takes off and lands in the medium contact area. For example, if the power compensation tag indicates that the left front thrust needs to be increased by 5%, but the actual attitude does not show the corresponding pitch response, the feedback amount will be recorded as "thrust is small, lag correction required", and output as a quantization value, such as "+0.15 pitch vector coefficient". Then, use the three-axis attitude maintenance boundary output by the attitude verification as the input, combine the current flight stage (close to the contact area or initial departure area) to determine whether it is in the "descent section control" or "takeoff section control" currently, and extract the characteristic data of the current medium contact area, such as the stability of the support surface, the disturbance frequency of the water surface reaction force. According to the extracted external constraint conditions, construct an interactive adjustment priority matrix. The interactive adjustment priority matrix uses the direction with the smallest attitude boundary offset as the main adjustment axis and is supplemented by secondary adjustment axes for non-linear guidance. For example, in a water surface environment, pitch correction is preferentially executed to cope with buoyancy disturbance; while in a hard ground environment, roll correction is preferentially corrected to avoid tipping due to single-point force. The interactive adjustment priority matrix can be used as the balance adjustment feedback amount when the UAV vertically takes off and lands in the medium contact area. Finally, fuse and calculate the balance adjustment feedback amount and the interactive guidance attribute matrix. Among them, the fusion calculation uses a fuzzy logic mapping system or a rule inference engine, multiplies the feedback correction amplitude and control priority on different attitude axes to form a disturbance response intensity vector, and then performs a time sliding window analysis on the disturbance response intensity vector to extract indicators such as system response time, maximum correction amplitude, and energy use efficiency. Finally, weight and fuse the indicators such as system response time, maximum correction amplitude, and energy use efficiency to generate a disturbance suppression score value, and use the disturbance suppression score value as the disturbance suppression index when the UAV vertically takes off and lands in the medium contact area. For example: within a certain time window, the system response delay to roll disturbance is 0.12 seconds, the maximum attitude correction amplitude is 3.6 degrees, and the energy consumption efficiency is 92%, then the disturbance suppression index for this period is a comprehensive score of 0.83.

[0085] It should be noted that in this application, the balance adjustment feedback amount refers to a set of feedback parameters for dynamically maintaining the attitude balance of the UAV during vertical takeoff and landing; the interactive guidance attribute refers to a set of control strategy characteristics for guiding the flight control system to select a reasonable correction path; the disturbance suppression index refers to a parameter for measuring the active suppression ability of the flight control system against random disturbance factors during the vertical takeoff and landing process in the medium contact area.

[0086] In addition, during specific implementation, the tolerance adaptation control of the attitude of the UAV during takeoff and landing in the water environment and the land environment by the disturbance suppression index can be specifically implemented in the following manner, that is: First, before entering the takeoff and landing mode, the current environment type is detected in real time, and the corresponding disturbance suppression index is called. Subsequently, the flight control system performs a coupling analysis on the disturbance suppression index and the current attitude offset data to identify the current disturbance trend and response lag situation; in the water environment, the tolerance in the pitch direction is enhanced to adapt to the non-linear reaction force change caused by buoyancy disturbance; while in the land environment, the roll angle tolerance is compressed to improve the ground symmetric force control accuracy. At the same time, during the tolerance adaptation control process, the correction threshold, the upper limit of the correction rate, and the multi-axis control priority sequence are adjusted according to the value of the disturbance suppression index to ensure that the attitude adjustment neither over-intervenes nor becomes unstable. In other embodiments, other methods can also be used for tolerance adaptation control, which is not limited here.

[0087] It should be noted that in this application, tolerance adaptation control refers to a method of dynamically adjusting the tolerance range and correction strategy of the UAV attitude control parameters according to the flight environment and the degree of disturbance.

[0088] Thus, it can be seen that in this application, the dynamic contact state of the UAV in the medium contact area can be linked and adjusted under the conditions of complex takeoff and landing environment changes; among them, by obtaining the dynamic pressure distribution data in the medium contact area during the autonomous takeoff and landing process of the UAV, the force characteristics and load response changes of the contact medium can be identified with high precision and low latency, realizing the real-time perception of the UAV takeoff and landing attitude state and the contact behavior modeling; by analyzing the center offset of the pressure distribution, extracting the steady-state contact gradient and generating the collaborative contact attribute, the landing force collaboration under different takeoff and landing environments can be effectively characterized, and then a dynamic control label with direction compensation ability can be formed, making the attitude adjustment smoother and more controllable; by fusing and correcting the trajectory fitting deviation, a confidence decision corresponding to the transition tilting state of the landing gear can be generated under complex disturbance conditions, effectively realizing the timing prediction and linkage determination of the attitude adjustment process, thereby ensuring the continuity and stability of the attitude switching process; by fusing the dynamic compensation label and the position and state verification result, a disturbance suppression index adaptable to the environment is generated, which can dynamically adjust the attitude tolerance boundary and correction strategy in the water and land environments, significantly enhancing the stable flight and attitude maintenance ability of the UAV takeoff and landing control system in various medium contact scenarios.

[0089] In summary, the technical solution adopted in this application can perform differential regulation on the dynamic contact state of the UAV in the medium contact area under the conditions of complex takeoff and landing environment changes, so as to improve the environmental adaptability of the attitude regulation during the autonomous vertical takeoff and landing process.

[0090] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of flows and / or blocks in the flowchart and / or block diagram can also be implemented. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0091] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and this program can be stored in a computer-readable storage medium. The storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), or other optical disc memories, magnetic disk memories, tape memories, or any other medium that can be used to carry or store data and is computer-readable.

[0092] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitations, the element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, commodity or device including the element.

Claims

1. An autonomous takeoff and landing control system for an electric water-air dual-use unmanned aerial vehicle, characterized in that, The takeoff and landing control system includes: A data acquisition module for acquiring dynamic pressure distribution data of the medium contact area during the autonomous takeoff and landing of the UAV; A differential compensation module for determining the collaborative contact attribute of the medium contact area during the autonomous takeoff and landing of the UAV through the dynamic pressure distribution data, performing differential compensation on the collaborative contact attribute, and obtaining a power compensation label for the vertical takeoff and landing of the UAV in the medium contact area; A position and state verification module for determining the trajectory fitting deviation of the landing gear attitude adjustment during the takeoff and landing of the UAV in the water environment and the land environment, performing fusion correction on the trajectory fitting deviation, obtaining a transition confidence decision corresponding to the transition tilting state of the landing gear during the autonomous takeoff and landing of the UAV, and then performing position and state verification on the attitude maintenance boundary of the UAV during autonomous vertical takeoff and landing cruise by the transition confidence decision; An attitude adaptation module for determining the disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area according to the power compensation label and the attitude maintenance boundary after position and state verification, and then performing tolerance adaptation control on the attitude of the UAV during takeoff and landing in the water environment and the land environment by the disturbance suppression index.

2. The autonomous takeoff and landing control system of a water-air dual-purpose electric unmanned aerial vehicle according to claim 1, characterized in that, The medium contact area refers to the spatial area where the landing gear structure directly makes physical contact with the water surface and the land during the takeoff and landing process of the UAV.

3. The autonomous takeoff and landing control system of a water-air dual-purpose electric unmanned aerial vehicle according to claim 1, characterized in that, Determining the collaborative contact attribute of the medium contact area during the autonomous takeoff and landing of the UAV through the dynamic pressure distribution data specifically includes: Determining the pressure center offset of the medium contact surface according to the dynamic pressure distribution data; Determining the steady-state contact gradient of the medium contact area during the autonomous takeoff and landing of the UAV through the pressure center offset; Determining the collaborative contact attribute of the medium contact area during the autonomous takeoff and landing of the UAV according to the steady-state contact gradient.

4. The autonomous take-off and landing control system for a dual-purpose electric drone for water and air as claimed in claim 1, characterized in that: The collaborative contact attribute refers to the collaborative characteristics of the landing gear actions at each contact point inside the medium contact area during the autonomous takeoff and landing process of the UAV.

5. The autonomous takeoff and landing control system of a water-air dual-purpose electric unmanned aerial vehicle according to claim 1, wherein, Determining the trajectory fitting deviation of the landing gear attitude adjustment during the takeoff and landing of the UAV in the water environment and the land environment specifically includes: Collecting the trajectory convergence index of the landing gear attitude adjustment during the autonomous takeoff and landing of the UAV in the water environment; Collecting the trajectory adaptation characteristics of the landing gear attitude adjustment during the autonomous takeoff and landing of the UAV in the land environment; Determining the trajectory fitting deviation of the landing gear attitude adjustment during the autonomous takeoff and landing of the UAV according to the trajectory convergence index and the trajectory adaptation characteristics.

6. The autonomous takeoff and landing control system of a water-air dual-purpose electric unmanned aerial vehicle according to claim 1, characterized in that, The trajectory fitting deviation refers to the error measure formed by the dynamic comparison result of the actual adjustment trajectory and the expected trajectory of the UAV landing gear attitude under different takeoff and landing media.

7. The autonomous takeoff and landing control system of a water-air dual-use electric unmanned aerial vehicle according to claim 1, characterized in that, The transition tilting state of the landing gear refers to the dynamic tilting state of the UAV landing gear when it changes from the initial attitude to the stable attitude during the attitude adjustment process.

8. The autonomous takeoff and landing control system of a water-air dual-use electric unmanned aerial vehicle according to claim 1, characterized in that, Performing position and state verification on the attitude maintenance boundary of the UAV during autonomous vertical takeoff and landing cruise by the transition confidence decision specifically includes: Generating a tolerance anchor position and state for the UAV attitude maintenance based on the transition confidence decision; Determining the motion correction rule of the UAV during autonomous vertical takeoff and landing cruise; Performing position and state verification on the tolerance anchor position and state according to the motion correction rule, and outputting the attitude maintenance boundary after position and state verification.

9. The autonomous takeoff and landing control system of a water-air dual-use electric unmanned aerial vehicle according to claim 1, characterized in that The autonomous vertical takeoff, landing and cruise mentioned above refers to the flight mode in which the UAV completes the whole process of vertical takeoff, vertical landing and stable cruise without manual intervention.

10. The autonomous takeoff and landing control system of a water-air dual-use electric unmanned aerial vehicle according to claim 1, characterized in that, According to the power compensation label and the attitude maintenance boundary after position and attitude verification, the disturbance suppression indexes for the UAV during vertical takeoff and landing in the medium contact area are specifically as follows: Determine the balance adjustment feedback amount of the UAV during vertical takeoff and landing in the medium contact area according to the power compensation label; Determine the interactive guidance attribute of the UAV during vertical takeoff and landing in the medium contact area according to the attitude maintenance boundary after position and attitude verification; Determine the disturbance suppression indexes of the UAV during vertical takeoff and landing in the medium contact area through the balance adjustment feedback amount and the interactive guidance attribute.

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