An autonomous take-off and landing control system for a dual-purpose electric drone in water and air

Abstract

The present application provides an autonomous take-off and landing control system for a dual-purpose electric drone for water and air, which relates to the technical field of drone take-off and landing control. The system determines the coordinated contact properties of the medium contact area during autonomous take-off and landing of the drone through dynamic pressure distribution data, and determines the power compensation label of the drone during vertical take-off and landing on the medium contact area; then determines the transition confidence decision corresponding to the transition tilt state of the landing gear during autonomous take-off and landing of the drone; determines the disturbance suppression index of the drone during vertical take-off and landing in the medium contact area based on the power compensation label and the attitude maintenance boundary after position verification, and uses the disturbance suppression index to perform tolerance adaptive control on the attitude of the drone during take-off and landing in water and land environments. The present application can differentially control the dynamic contact state of the drone 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.

Description

Technical Field

[0001] The present application relates to the technical field of drone take-off and landing control, and more specifically, to an autonomous take-off and landing control system for a dual-purpose electric drone for water and air. Background Art

[0002] Drone takeoff and landing control refers to the skill of coordinating and adjusting the attitude, speed, thrust, and landing structure of a drone through the flight control system during takeoff and landing to achieve safe, smooth, and precise takeoff and landing operations. For dual-use electric drones, takeoff and landing control is particularly complex. Not only must they adapt to the high reaction force characteristics of hard contact surfaces on land, but they must also cope with nonlinear changes in the water environment caused by buoyancy, fluctuations, and reflected disturbances. In autonomous flight scenarios, the takeoff and landing control system needs to combine sensor feedback information, dynamically identify environmental conditions, and implement a joint control strategy based on mechanisms such as posture control, thrust vector adjustment, and center of gravity self-balancing.

[0003] However, existing autonomous takeoff and landing control systems for dual-purpose electric water and air drones generally lack the ability to model the dynamic response characteristics of the medium contact process. This makes it difficult for the system to achieve real-time and precise control when responding to changes in contact force and attitude disturbances in different media (such as water and land). This leads to unstable disturbance suppression during landing gear attitude adjustment, which in turn causes takeoff and landing attitude instability of the landing structure. Therefore, how to differentially control the dynamic contact state of the drone in the medium contact area under complex takeoff and landing environmental conditions 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] The present application provides an autonomous take-off and landing control system for a dual-purpose electric water and air UAV, which 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.

[0005] In a first aspect, the present application provides an autonomous take-off and landing control system for a dual-purpose electric drone, the take-off and landing control system comprising:

[0006] The data acquisition module is used to obtain dynamic pressure distribution data of the medium contact area during autonomous takeoff and landing of the UAV;

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

[0008] A position verification module is used to determine the trajectory fitting deviation of the landing gear attitude adjustment when the UAV takes off and lands in water and land environments, fuse and correct the trajectory fitting deviation, and obtain the transition confidence decision corresponding to the transition tilt state of the landing gear during autonomous takeoff and landing of the UAV. The transition confidence decision is then used to perform position verification on the attitude maintenance boundary of the UAV during autonomous vertical takeoff and landing cruise;

[0009] The attitude adaptation module is used to determine the disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area based on the power compensation tag 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.

[0010] In this embodiment, the medium contact area refers to the spatial area where the landing gear structure is in direct physical contact with the water surface and the land during the take-off and landing process of the UAV.

[0011] In this embodiment, determining the cooperative contact properties of the medium contact area during autonomous takeoff and landing of the drone using the dynamic pressure distribution data specifically includes:

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

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

[0014] The coordinated contact properties of the medium contact area during autonomous takeoff and landing of the UAV are determined according to the steady-state contact gradient.

[0015] In this embodiment, the cooperative contact attribute refers to the cooperative characteristics of the landing gear movements at each contact point within the medium contact area during the autonomous take-off and landing process of the UAV.

[0016] In this embodiment, determining 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 specifically includes:

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

[0018] Collect trajectory adaptation features of the landing gear attitude adjustment when the UAV takes off and lands autonomously in a terrestrial environment;

[0019] The trajectory fitting deviation of the landing gear attitude adjustment during autonomous take-off and landing of the UAV is determined according to the trajectory convergence index and the trajectory adaptation feature.

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

[0021] In this embodiment, the landing gear transition tilt state refers to the dynamic tilt state of the UAV landing gear when it changes from an initial posture to a stable posture during the posture adjustment process.

[0022] In this embodiment, the transition confidence decision is used to perform position verification on the attitude maintenance boundary of the UAV during autonomous vertical take-off and landing cruise, specifically including:

[0023] Generating a tolerance anchor state for maintaining the attitude of the UAV based on the transition confidence decision;

[0024] Determine the motion correction rules for the UAV during autonomous vertical take-off and landing cruise;

[0025] The tolerance anchor position is checked according to the motion correction rule, and the posture maintenance boundary after the position check is output.

[0026] In this embodiment, the autonomous vertical take-off and landing cruise refers to a flight mode in which the UAV completes the entire process of vertical take-off, vertical landing and stable cruising without human intervention.

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

[0028] determining a balance adjustment feedback amount when the UAV takes off and lands vertically in a medium contact area according to the power compensation tag;

[0029] The interactive guidance properties of the UAV during vertical takeoff and landing in the medium contact area are determined based on the attitude maintenance boundary after position verification;

[0030] The disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area is determined by the balance adjustment feedback amount and the interactive guidance attribute.

[0031] The technical solutions provided by the embodiments disclosed in this 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] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0036] Figure 1 This is a module structure diagram of an autonomous take-off and landing control system for a dual-purpose electric drone for water and air provided in this application;

[0037] Figure 2 This is a schematic diagram of the process of determining the power compensation tag provided by this application;

[0038] Figure 3 It is a flowchart of determining transition confidence decision provided by this application. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0040] The present invention provides an autonomous take-off and landing control system for a dual-purpose electric water-air drone. The core of the control system is to obtain dynamic pressure distribution data of the medium contact area during autonomous take-off and landing of the drone; determine the cooperative contact properties of the medium contact area during autonomous take-off and landing based on the dynamic pressure distribution data; perform differential compensation on the cooperative contact properties to obtain a dynamic compensation label for the drone during vertical take-off and landing on the medium contact area; determine the trajectory fitting deviation of the drone's landing gear attitude adjustment during take-off and landing in water and land environments; perform fusion correction on the trajectory fitting deviation to obtain a transition confidence decision corresponding to the landing gear transition tilt state during autonomous take-off and landing; and then use the transition confidence decision to perform position verification on the attitude maintenance boundary of the drone during autonomous vertical take-off and landing cruise; determine the disturbance suppression index of the drone during vertical take-off and landing in the medium contact area based on the dynamic compensation label and the attitude maintenance boundary after position verification; and then use the disturbance suppression index to perform tolerance adaptive control on the drone's attitude during take-off and landing in water and land environments. The above scheme can differentially control the dynamic contact state of the drone in the medium contact area under complex take-off and landing environment conditions, thereby improving the environmental adaptability of attitude control during autonomous vertical take-off and landing.

[0041] In order to better understand the above technical solution, the following will be described in detail with reference to the accompanying drawings and specific implementation methods. Figure 1 As shown in the figure, this figure is a module structure diagram of an autonomous take-off and landing control system for a water-air dual-purpose electric UAV according to this embodiment of the present application. The take-off and landing control system includes: a data acquisition module 100, a differential compensation module 200, a position verification module 300 and an attitude adaptation module 400, which are described as follows:

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

[0043] In a specific implementation, obtaining dynamic pressure distribution data in the media contact area during autonomous takeoff and landing of a drone can be accomplished by embedding a highly sensitive, two-dimensional, flexible pressure sensor array in the bottom structure of the drone's landing gear. This pressure sensor array, constructed from piezoresistive or capacitive materials, is capable of achieving millimeter-level spatial resolution and millisecond-level temporal response. During takeoff and landing, the pressure sensor array senses pressure changes at each contact point in real time and converts the analog pressure signal into a digital signal via an analog-to-digital conversion module. This digital signal is preprocessed by the flight control system's built-in edge computing unit, including time alignment, anomaly filtering, and spatial interpolation, ultimately outputting a complete time-space two-dimensional pressure distribution map. All processed results are stored in a local data cache in a time series format. Dynamic pressure distribution data in the media contact area during autonomous takeoff and landing is obtained by reading from the local data cache. In other embodiments, other methods can also be used to obtain dynamic pressure distribution data in the media contact area during autonomous takeoff and landing, which are 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 is in direct physical contact with the water surface and the land during the take-off and landing of the UAV; the dynamic pressure distribution data refers to the collection of pressure intensity information generated by each position point in the medium contact area as it changes with time during the take-off and landing of the UAV.

[0045] The differential compensation module 200 is used to determine the cooperative contact properties 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 cooperative contact properties, and obtain a power compensation label when the UAV takes off and lands vertically on the medium contact area.

[0046] In this embodiment, the collaborative contact properties of the medium contact area during autonomous takeoff and landing of the UAV can be determined by using the dynamic pressure distribution data in the following manner:

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

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

[0049] The coordinated contact properties of the medium contact area during autonomous takeoff and landing of the UAV are determined according to the steady-state contact gradient.

[0050] In a specific implementation, the dynamic pressure distribution data collected by the two-dimensional flexible pressure sensor array deployed at the bottom of the landing gear can first be input into the edge computing module. This edge computing module performs mass moment inference on the two-dimensional pressure matrix within each time slice. The spatially weighted average method is used to calculate the pressure center coordinates of the current pressure center of gravity. The difference between the pressure center coordinates and the geometric center coordinates of the contact area is calculated, and the difference result is used as the pressure center offset of the medium contact surface at that moment. Then, a sliding time window method is used to perform local fitting and trend analysis on the pressure center offset. Specifically, a fixed window length is set (e.g., 0.5 seconds), and the first-order derivative of the pressure center offset change rate within this fixed window length is calculated to analyze whether the pressure center offset change converges or approaches zero. A local linear regression method is then used to fit the pressure center offset curve of the pressure center offset, and the mean change slope and fluctuation standard deviation of the pressure center offset are extracted. If the fluctuation standard deviation is below a preset threshold and the change slope approaches zero, the contact process is determined to have entered the steady-state segment, and the contact gradient value within that segment is output. The smaller the contact gradient value, the better the pressure balance. The ratio of the mean change slope of the pressure center offset to the standard deviation of the fluctuation is used as the steady-state contact gradient of the medium contact area during autonomous takeoff and landing of the UAV. Finally, the steady-state contact gradient is used as an input parameter and integrated with the spatial coordination index of the pressure distribution area for judgment. Specifically, the steady-state gradient difference of each quadrant of the contact surface in the medium contact area is calculated. If the steady-state gradient difference between the quadrants is less than the set threshold (such as 5%), it means that the overall contact tends to be balanced. The temporal consistency of the force curves of different contact points is analyzed again. The cross-correlation function can be used to analyze the degree of synchronization between the pressure time series to obtain the contact consistency score. The gradient difference and consistency score are used to construct a collaborative contact evaluation function. The quantitative results output by the collaborative contact evaluation function are used as the collaborative contact attributes. High collaborative contact attributes indicate that the take-off and landing structures are well coordinated, the contact environment is controllable, and it is suitable for entering the attitude stabilization adjustment stage.

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

[0052] Preferably, in this embodiment, the cooperative contact properties are differentially compensated to obtain a dynamic compensation label when the UAV takes off and lands vertically on the medium contact area, referring to Figure 2 As shown in FIG, this figure is a schematic diagram of the process of determining the power compensation tag in some embodiments of the present application. In this embodiment, determining the power compensation tag can be achieved by using the following steps:

[0053] In step S21, the pressure imbalance of the medium contact surface is analyzed by using the cooperative contact properties;

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

[0055] In step S23, differential adaptation is performed on the take-off and landing posture of the UAV according to the pressure imbalance and the anti-interference matching information to obtain a tolerance adaptation property when the UAV takes off and lands vertically on the medium contact area;

[0056] In step S24, a power compensation tag of the UAV when vertically taking off and landing on the medium contact area is determined according to the tolerance adaptation attribute.

[0057] In the specific implementation, first, the steady-state pressure value of each pressure node is extracted from the collaborative contact properties, and a two-dimensional pressure distribution map of the contact area is constructed. The two-dimensional pressure distribution map is then divided into multiple sub-areas, where the areas can be divided into quadrants or annuli, and the average pressure value of each sub-area is calculated; then, the maximum pressure difference and standard deviation between all sub-areas are calculated, and the maximum pressure difference and standard deviation between all sub-areas are used as the pressure imbalance measure of the medium contact surface. Next, the current meteorological parameters (such as wind speed and direction) are collected through the environmental perception module integrated into the flight control system, and a micro anemometer or air pressure sensor is used to provide wind disturbance information. At the same time, the dynamic response of the attitude change during landing is measured in combination with the onboard accelerometer and gyroscope, and the rigidity feedback index of the ground support surface is derived. In addition, the instantaneous impact response curve of the landing gear contact can be used to fit the contact response time through the first-order system model to judge the ground material characteristics (such as soft soil, hard ground, water surface) and its response speed to disturbances. All rigidity feedback indices and response speeds to disturbances are then normalized and input into the anti-disturbance feature matching model, from which the anti-disturbance matching information is output. Then, using the pressure imbalance and disturbance rejection matching information as input, a multi-parameter differential control model is used to establish an attitude tolerance function. This attitude tolerance function evaluates the minimum correction angle required for the current attitude adjustment and the desired attitude boundary extension value. Based on the extended state observer mechanism, the differential control model makes adaptive adjustments based on historical control performance. If the pressure imbalance is large and the disturbance rejection capability is weak, it will tolerate larger pitch and roll angle deviations and reduce the attitude recovery rate to avoid oscillation. Conversely, the tolerance range is tightened. The tolerance adaptation attributes are output in the form of attitude angle threshold, reaction delay allowance, and adjustment rate, which are used to load the tolerance control strategy within the flight control system. Finally, the attitude deviation tolerance range, target attitude threshold, and execution hysteresis parameter in the tolerance adaptation attributes are input into the power control mapping model. Combined with the current output power state of the flight control system and the rotor response capability, a compensation force vector library is established. In this compensation force vector library, the main execution methods are motor thrust difference adjustment, servo arm response adjustment and propulsion vector offset. The required power adjustment instructions are calculated in real time according to the current attitude change trend and pressure distribution. The power adjustment instructions are used as the power compensation label when the UAV takes off and lands vertically on the medium contact area. Among them, the power compensation label includes indicators such as thrust increase and decrease ratio, left and right wing compensation level, and longitudinal attitude improvement rate.

[0058] It should be noted that in this application, the pressure imbalance refers to the degree of force inconsistency between different contact points in the medium contact area; the anti-interference matching information refers to the perception and response characteristics of the UAV to the disturbance in the current take-off and landing environment; the tolerance adaptation attribute refers to the attitude deviation range required to achieve stable take-off and landing under the influence of current pressure unevenness and environmental disturbances; the power compensation label refers to the power adjustment instructions required to ensure attitude stability, contact balance and anti-interference action during the vertical take-off and landing of the UAV.

[0059] The position verification module 300 is used 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, and obtain the transition confidence decision corresponding to the transition tilt state of the landing gear during the autonomous take-off and landing of the UAV. The transition confidence decision is then used to perform position verification on the attitude maintenance boundary of the UAV during autonomous vertical take-off and landing cruise.

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

[0061] Collect trajectory convergence indicators for the attitude adjustment of the landing gear of the UAV during autonomous takeoff and landing in a water environment;

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

[0063] The trajectory fitting deviation of the landing gear attitude adjustment during autonomous take-off and landing of the UAV is determined according to the trajectory convergence index and the trajectory adaptation feature.

[0064] In the specific implementation, first, a high-definition stereo vision system and an inertial measurement unit are deployed in a surface take-off and landing experimental environment to collect the spatial position and attitude angle data of the landing gear end in real time. The desired attitude trajectory is pre-defined by the flight control system as a time series function, including the target pitch angle, roll angle and altitude curve; in the actual adjustment process, the actual trajectory data is smoothed using the least squares fitting method, and then aligned point-to-point with the desired trajectory. The error distance and error direction change rate at each time point are calculated, and the descent rate of the sum of squared errors over time, the mean error value in the steady-state interval, and the maximum residual ratio are obtained. The descent rate, the mean error value in the steady-state interval, and the maximum residual ratio are used as trajectory convergence indicators. Then, during land takeoff and landing, the same visual and inertial measurement systems used in the surface experiments were used to collect complete trajectory data for landing gear adjustment movements. Feature points were extracted from the attitude curve, including the trajectory starting point, maximum excursion point, final stable point, and their corresponding time nodes. The response time (the time from control command issuance to stable attitude establishment), trajectory smoothness (the rate of change of the second-order derivative of curve continuity), and the maximum deviation angle and fitting residual between the target and actual trajectories were calculated. These response time, trajectory smoothness, maximum deviation angle, and fitting residual were used as trajectory adaptation features. Finally, the trajectory convergence index and the fitting error in the trajectory adaptation features were normalized to construct a unified multidimensional error space, which includes sub-indicators such as maximum excursion error, response delay, and trajectory volatility. Principal component analysis was then used to reduce the dimensionality of the multidimensional features and extract the main factors of the comprehensive trajectory performance. Support vector regression was used to fit the overall fitting curve between the actual and expected trajectories, calculate the average fitting error, and output a unified trajectory fitting deviation, which quantitatively represents the difference in consistency between the control model and structural execution under the two takeoff and landing environments. If the trajectory fitting deviation is greater than the preset threshold, it indicates that there is a mismatch between control and execution in the water or land take-off and landing scenarios, and model reconstruction or parameter adjustment is required.

[0065] It should be noted that, in this application, the trajectory convergence index refers to the degree of dynamic convergence of the actual action trajectory to the expected trajectory during the landing gear attitude adjustment process when the UAV takes off or lands in a 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 UAV's take-off and landing on land; the trajectory fitting deviation refers to the error measure formed by the dynamic comparison results of the actual adjustment trajectory of the UAV landing gear attitude and the expected trajectory under different take-off and landing media.

[0066] Preferably, in this embodiment, the trajectory fitting deviation is fused and corrected to obtain the transition confidence decision corresponding to the transition tilt state of the landing gear during autonomous take-off and landing of the UAV, with reference to Figure 3As shown in FIG, this figure is a schematic diagram of a process for determining a transition confidence decision in some embodiments of the present application. In this embodiment, determining a transition confidence decision can be implemented using the following steps:

[0067] In step S31, the position oscillation characteristics of the landing gear are extracted from the transition tilt state of the landing gear during autonomous take-off and landing of the UAV;

[0068] In step S32, the linkage confidence value of the landing gear transition tilt during autonomous takeoff and landing of the UAV is determined according to the position oscillation characteristics;

[0069] In step S33, the dynamic tilt index of the landing gear during transition tilting during autonomous takeoff and landing of the UAV is determined;

[0070] In step S34, the dynamic tilt index is mapped to the linkage confidence value of the transition tilt state of the landing gear during autonomous take-off and landing of the UAV, and a transition confidence decision corresponding to the transition tilt state of the landing gear during autonomous take-off and landing of the UAV is obtained.

[0071] In the specific implementation, first, high-frequency sampling of inertial measurement unit data, including linear acceleration, angular velocity, and angular acceleration, is used to record the three-axis time series of the landing gear's motion during the transition phase. The collected data is decomposed by wavelet transform to extract the main oscillation frequency components and identify the high-frequency disturbance segments. The mean square error, maximum amplitude difference, and main oscillation period of the attitude change in each time period are calculated. The mean square error, maximum amplitude difference, and main oscillation period of the attitude change in each time period are used as the position oscillation characteristics of the landing gear during the event segment. Next, a multi-point correlation analysis is performed on the position oscillation characteristics. The Pearson correlation coefficient method is used to calculate the degree of synchronization of the attitude changes between the landing gear support points during the oscillation process. Then, principal component analysis is used to identify the main oscillation direction and calculate the response delay and phase offset of the overall structure in this main direction. A confidence evaluation function is then constructed based on the three indicators of oscillation amplitude, frequency, and coordination. The response delay and phase offset in the main direction are input into the confidence evaluation function, and the output result is used as the linkage confidence value of the landing gear transition tilt during the autonomous takeoff and landing of the UAV. Then, the outputs of the inertial measurement unit and the center of gravity positioning module are called in the flight control system to obtain the angular velocity, angular acceleration of the pitch angle and roll angle, as well as the instantaneous offset of the center of gravity of the UAV relative to the contact surface in real time. The angular velocity, angular acceleration of the pitch angle and roll angle, as well as the instantaneous offset of the center of gravity of the UAV relative to the contact surface are then input into the state observation model to construct a three-dimensional index vector with the angular velocity change amplitude, center of gravity offset speed and attitude feedback lag as variables. The three-dimensional index vector is used as the dynamic tilt index during the transition tilt of the landing gear of the UAV during autonomous take-off and landing. Finally, a fusion mapping model is established, and the dynamic tilt index is input into a multi-layer perception neural network or fuzzy control rule system. At the same time, the linkage confidence is used as a mapping weight parameter. The mapping model outputs a confidence score, which usually ranges from 0 to 1. The confidence score represents the control credibility of the current tilt state. If the confidence score is higher than 0.7, it is considered a "controllable transition state" and attitude adjustment continues; if it is lower than 0.4, deceleration braking is triggered or adjustment is terminated to enter protection mode. The confidence score is used as the transition confidence decision corresponding to the transition tilt state of the landing gear during autonomous takeoff and landing of the UAV. The transition confidence decision will be refreshed in real time in the flight control main control system and used to dynamically switch attitude control strategies and control parameter templates to ensure that the UAV enters a safe and stable takeoff and landing state range.

[0072] It should be noted that, in the present application, the landing gear transition tilt state refers to the dynamic tilt state of the UAV landing gear when it changes from the initial attitude to the stable attitude during the attitude adjustment process; the position oscillation feature refers to the periodic jitter behavior of the landing gear in spatial displacement and attitude angle during the period when the UAV enters the landing gear attitude transition adjustment state; the linkage confidence refers to an indicator of the degree of coordination of the overall landing structure of the UAV in the current attitude adjustment during take-off and landing; the dynamic tilt index refers to the set of characteristic values ​​of the UAV in the attitude angle change rate, center of gravity displacement and attitude control input response relative to the contact surface during the attitude transition adjustment process of the landing gear; the transition confidence decision refers to the standard for judging whether the current landing gear attitude is in a controllable transition state of the take-off and landing attitude.

[0073] In this embodiment, the transition confidence decision is used to perform position verification on the attitude maintenance boundary of the UAV during autonomous vertical take-off and landing cruise, which can be specifically implemented in the following manner, namely:

[0074] Generating a tolerance anchor state for maintaining the attitude of the UAV based on the transition confidence decision;

[0075] Determine the motion correction rules for the UAV during autonomous vertical take-off and landing cruise;

[0076] The tolerance anchor position is checked according to the motion correction rule, and the posture maintenance boundary after the position check is output.

[0077] In specific implementation, the transition confidence decision value is first input into the attitude assessment module, which is implemented by the fault-tolerant attitude calculation unit embedded in the flight control system. Based on the combination of the transition confidence decision value and the transition tilt indicator, three parameters are dynamically set in the three-axis flight attitude coordinate system: the maximum allowable pitch angle variation 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 state with small attitude stability deviation. When the transition confidence decision value decreases, the system expands the boundaries of the set parameters, tolerating more attitude oscillation without triggering adjustment behavior, and the tolerance anchor state is stored in the flight control attitude control cache as a data structure. Then, based on the drone's model parameters, flight load status, and current environmental disturbance parameters (such as wind speed and air pressure changes), the motion correction parameter template stored in the flight control system is dynamically called. The flight data feedback system then uses real-time readings of the three-axis angular velocity and angular acceleration values ​​output by the gyroscope. Combined with historical attitude repair efficiency, the system quickly predicts the current offset direction. Based on the offset direction and magnitude, a lookup table matching or fuzzy control rule is used to determine which correction path to use. For example, whether to adjust the roll angle by deflecting the left and right rotor thrust difference or to correct for fore-aft attitude deviation using the pitch motor is used. The used correction path is then 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 initiation threshold, a maximum allowable adjustment rate, and a correction priority, which guide the system to prioritize corrections in the direction most impacting flight stability when multiple deviations coexist. Finally, the three-axis angles of the current flight attitude and their changing trends are compared dimension by dimension with the tolerance anchor state, the deviation amplitude and speed are calculated, and it is determined whether they exceed the set threshold. If a certain attitude dimension is close to the tolerance boundary, the correction scheme in the aforementioned motion correction rule is called to predict the corrected attitude change trend and adjust the boundary width of the original tolerance anchor state accordingly. For example, the pitch angle tolerance range is dynamically scaled from ±5 degrees to ±3 degrees, and finally the attitude maintenance boundary after position verification is generated. The attitude maintenance boundary defines the maximum allowable angle offset range of the three axes, the control response trigger condition and the attitude maintenance time limit in matrix form.

[0078] It should be noted that, in this application, autonomous vertical take-off and landing cruise refers to a flight mode in which a UAV completes the entire process of vertical take-off, vertical landing and stable cruising without human intervention; tolerance anchor position state refers to a set of dynamic reference attitude parameters in the attitude control process of the UAV; motion correction rule refers to a set of strategies used by the flight control system to identify and repair attitude deviations during the vertical take-off and landing cruise phase; attitude maintenance boundary refers to the acceptable range of attitude changes of the UAV during flight, which is used to ensure flight stability and control safety; position verification refers to comparing the current flight state with the tolerance anchor position state, and correcting its boundary judgment criteria according to the motion correction rule, so as to obtain the actual executable attitude maintenance control range, which is used to limit the attitude changes of the UAV in real time.

[0079] The attitude adaptation module 400 is used to determine the disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area based on the power compensation tag and the attitude maintenance boundary after position verification, and then use the disturbance suppression index to perform tolerance adaptation control on the attitude of the UAV during takeoff and landing in water surface environment and land environment.

[0080] In this embodiment, the disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area is determined based on the power compensation tag and the attitude maintenance boundary after position verification, which can be specifically determined in the following manner, namely:

[0081] determining a balance adjustment feedback amount when the UAV takes off and lands vertically in a medium contact area according to the power compensation tag;

[0082] The interactive guidance properties of the UAV during vertical takeoff and landing in the medium contact area are determined based on the attitude maintenance boundary after position verification;

[0083] The disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area is determined by the balance adjustment feedback amount and the interactive guidance attribute.

[0084] In specific implementations, the system first reads the parameters contained in the power compensation tag, which may include thrust increment commands, takeoff and landing pivot adjustment angles, and rotor asymmetric acceleration. Combined with real-time flight attitude data (including three-axis angles and angular velocities), the power compensation tag parameters are compared with the current flight control response. Through the error inversion mechanism in the flight attitude control module, the error between the desired compensation attitude and the current actual attitude is converted into angular acceleration fine-tuning commands and lift allocation factors. These angular acceleration fine-tuning commands and lift allocation factors are then used as feedback for balance adjustment during vertical takeoff and landing in the medium contact area. For example, if the power compensation tag indicates a 5% increase in left front thrust, but the actual attitude does not show a corresponding pitch response, the feedback will be recorded as "low thrust, hysteresis correction required" and output as a quantized value, such as "+0.15 pitch vector coefficient." Then, the three-axis attitude maintenance boundary output by the position verification is used as input, and combined with the current flight stage (approaching the contact area or the initial departure area), it is determined whether the current phase belongs to "descent phase control" or "take-off phase control", and the characteristic data of the current medium contact area are extracted, such as the stability of the support surface and the frequency of the water surface reaction force disturbance. According to the extracted external constraints, an interactive adjustment priority matrix is ​​constructed. The interactive adjustment priority matrix uses the direction of the minimum attitude boundary offset as the main adjustment axis, supplemented by the secondary adjustment axis for nonlinear guidance. For example, in a water surface environment, pitch correction is performed first to cope with buoyancy disturbances; in a hard ground environment, roll correction is performed first to avoid single-point force overturning. The interactive adjustment priority matrix can be used as the balance adjustment feedback amount for the UAV during vertical takeoff and landing in the medium contact area. Finally, the balance adjustment feedback amount and the interactive guidance attribute matrix are fused and calculated. The fusion calculation uses a fuzzy logic mapping system or rule inference engine to multiply the feedback correction amplitude on different attitude axes by the control priority to form a disturbance response intensity vector. The disturbance response intensity vector is then subjected to a time sliding window analysis to extract indicators such as system response time, maximum correction amplitude, and energy utilization efficiency. Finally, the system response time, maximum correction amplitude, and energy utilization efficiency are weighted and fused to generate a disturbance suppression score value. The disturbance suppression score value is used as the disturbance suppression index for the UAV during vertical takeoff and landing in the medium contact area. For example, within a certain window period, the system's response delay to roll disturbance is 0.12 seconds, the maximum attitude correction amplitude is 3.6 degrees, and the energy efficiency is 92%. 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 the set of feedback parameters that dynamically maintain the posture balance of the UAV during vertical take-off and landing; the interactive guidance attribute refers to the set of control strategy features used to guide the flight control system to select a reasonable correction path; the disturbance suppression index refers to the parameter that measures the flight control system's ability to actively suppress random disturbance factors during vertical take-off and landing in the medium contact area.

[0086] In addition, in a specific implementation, the tolerance adaptive 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: 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 couples the disturbance suppression index with the current attitude offset data for analysis to identify the current disturbance trend and response lag; in the water environment, the pitch direction tolerance is enhanced to adapt to the nonlinear reaction force changes caused by buoyancy disturbances; while in the land environment, the roll angle tolerance is compressed to improve the ground symmetrical force control accuracy. At the same time, during the tolerance adaptive control process, the correction threshold, correction rate upper limit and multi-axis control priority sequence are adjusted according to the value of the disturbance suppression index to ensure that the attitude adjustment is neither excessive nor unstable. In other embodiments, other methods can also be used for tolerance adaptive control, which is not limited here.

[0087] It should be noted that, in this application, tolerance adaptive 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 disturbance level.

[0088] 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.

[0089] 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.

[0090] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0091] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program. The program can be stored in a computer-readable storage medium, including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, magnetic disk storage, or magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0092] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

Claims

1. An autonomous take-off and landing control system for a dual-purpose electric drone for water and air, characterized in that: The take-off and landing control system includes: The data acquisition module is used to obtain dynamic pressure distribution data of the medium contact area during autonomous takeoff and landing of the UAV; a differential compensation module, configured to determine, using the dynamic pressure distribution data, a cooperative contact property of a medium contact area during autonomous takeoff and landing of the UAV, and to perform differential compensation on the cooperative contact property to obtain a dynamic compensation label for vertical takeoff and landing of the UAV on the medium contact area; A position verification module is used to determine the trajectory fitting deviation of the landing gear attitude adjustment when the UAV takes off and lands in water and land environments, fuse and correct the trajectory fitting deviation, and obtain the transition confidence decision corresponding to the transition tilt state of the landing gear during autonomous takeoff and landing of the UAV. The transition confidence decision is then used to perform position verification on the attitude maintenance boundary of the UAV during autonomous vertical takeoff and landing cruise; The attitude adaptation module is used to determine the disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area based on the power compensation tag 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.

2. The autonomous take-off and landing control system for an electric dual-purpose water-air UAV according to claim 1, characterized in that: The medium contact area refers to the spatial area where the landing gear structure is in direct physical contact with the water surface and the land during the take-off and landing of the UAV.

3. 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: Determining the cooperative contact properties of the medium contact area during autonomous takeoff and landing of the UAV using the dynamic pressure distribution data specifically includes: determining a pressure center offset of a medium contact surface according to the dynamic pressure distribution data; Determine the steady-state contact gradient of the medium contact area during autonomous takeoff and landing of the UAV by using the pressure center offset; The coordinated contact properties of the medium contact area during autonomous takeoff and landing of the UAV are determined 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 cooperative contact property refers to the cooperative characteristics of the landing gear movements at each contact point within the medium contact area during the autonomous take-off and landing process of the UAV.

5. 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: 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, specifically including: Collect trajectory convergence indicators for the attitude adjustment of the landing gear of the UAV during autonomous takeoff and landing in a water environment; Collect trajectory adaptation features of the landing gear attitude adjustment when the UAV takes off and lands autonomously in a terrestrial environment; The trajectory fitting deviation of the landing gear attitude adjustment during autonomous take-off and landing of the UAV is determined according to the trajectory convergence index and the trajectory adaptation feature.

6. 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 trajectory fitting deviation refers to the error measurement formed by the dynamic comparison results of the actual adjustment trajectory of the UAV landing gear attitude and the expected trajectory under different take-off and landing media.

7. 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 landing gear transition tilt state refers to the dynamic tilt state of the UAV landing gear when it changes from an initial attitude to a stable attitude during attitude adjustment.

8. 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 transition confidence decision is used to perform position verification on the attitude maintenance boundary of the UAV during autonomous vertical take-off and landing cruise, specifically including: Generating a tolerance anchor state for maintaining the attitude of the UAV based on the transition confidence decision; Determine the motion correction rules for the UAV during autonomous vertical take-off and landing cruise; The tolerance anchor position is checked according to the motion correction rule, and the posture maintenance boundary after the position check is output.

9. 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 autonomous vertical take-off and landing cruise refers to a flight mode in which the UAV completes the entire process of vertical take-off, vertical landing and stable cruising without human intervention.

10. 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 disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area is determined based on the power compensation tag and the attitude maintenance boundary after position verification, specifically including: determining a balance adjustment feedback amount when the UAV takes off and lands vertically in a medium contact area according to the power compensation tag; The interactive guidance properties of the UAV during vertical takeoff and landing in the medium contact area are determined based on the attitude maintenance boundary after position verification; The disturbance suppression index of the UAV during vertical takeoff and landing in the medium contact area is determined by the balance adjustment feedback amount and the interactive guidance attribute.

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