Aerocar vertical take-off and landing method, system and device based on attitude compensation and medium

Abstract

The invention discloses a flying car vertical take-off and landing method, system and device based on attitude compensation and a medium, and the method comprises the steps: obtaining three-dimensional point cloud data and binocular parallax data of a take-off and landing region, and determining the terrain gradient information of the take-off and landing region according to the three-dimensional point cloud data and the binocular parallax data; vehicle body posture information of the hovercar is obtained, vehicle body posture changes in the future time period are predicted according to the vehicle body posture information and the terrain gradient information, and a first target thrust vector is determined according to the vehicle body posture changes; and performing multi-rotor power distribution on the first target thrust vector to obtain a first optimal thrust matrix, and performing attitude compensation on the hovercar according to the first optimal thrust matrix. The safety and reliability of vertical take-off and landing of the hovercar are enhanced, the dependence on ground conditions and the construction and maintenance cost of a take-off and landing area are reduced, the flexibility and adaptability of deployment of vertical take-off and landing in various environments are improved, and the method can be widely applied to the technical field of hovercars.

Description

Technical Field

[0001] The present invention relates to the technical field of flying cars, and in particular to a vertical takeoff and landing method, system, device and medium of a flying car based on attitude compensation. Background Art

[0002] Currently, flying cars mainly adopt the vertical takeoff and landing (VTOL) method, that is, multiple sets of rotors / propellers rotate downward at high speed to generate vertical lift to counteract gravity. The slope of the takeoff and landing area usually needs to be ≤ 1% to avoid power imbalance caused by the tilt of the fuselage. Therefore, the following problems exist:

[0003] 1) High construction and maintenance costs: The strict requirements for ground flatness in vertical takeoff and landing lead to a significant increase in construction costs. High-strength composite materials or asphalt concrete need to be used, and multiple calibrations are required during construction.

[0004] 2) Safety risks and reliability challenges: Even if the standards are met, extreme environments may still cause problems. For example, gusts or ground effect turbulence may amplify the impact of minor unevenness in the takeoff and landing area, resulting in thrust imbalance of multiple rotors.

[0005] 3) Limited deployment flexibility: The strict flatness requirements limit the application of vertical takeoff and landing in unstructured environments. Summary of the Invention

[0006] An object of the present invention is to solve at least to some extent one of the technical problems existing in the prior art.

[0007] To this end, an object of an embodiment of the present invention is to provide a vertical takeoff and landing method of a flying car based on attitude compensation, which enhances the safety and reliability of the vertical takeoff and landing of the flying car, reduces the dependence on ground conditions and the construction and maintenance costs of the takeoff and landing area, and improves the flexibility and adaptability of deploying vertical takeoff and landing in various environments.

[0008] Another object of an embodiment of the present invention is to provide a vertical takeoff and landing system of a flying car based on attitude compensation.

[0009] To achieve the above technical object, the technical solutions adopted in the embodiments of the present invention include:

[0010] In a first aspect, an embodiment of the present invention provides a vertical takeoff and landing method of a flying car based on attitude compensation, including the following steps:

[0011] Obtain the three-dimensional point cloud data and binocular disparity data of the takeoff and landing area, and determine the terrain slope information of the takeoff and landing area according to the three-dimensional point cloud data and the binocular disparity data;

[0012] Obtain the body attitude information of the flying car, predict the body attitude change in the future period according to the body attitude information and the terrain slope information, and determine the first target thrust vector according to the body attitude change;

[0013] Perform multi-rotor power distribution on the first target thrust vector to obtain the first optimal thrust matrix, and perform attitude compensation on the flying car according to the first optimal thrust matrix.

[0014] Further, in an embodiment of the present invention, the obtaining of the three-dimensional point cloud data and binocular disparity data of the take-off and landing area, and determining the terrain slope information of the take-off and landing area according to the three-dimensional point cloud data and the binocular disparity data specifically includes:

[0015] Perform high-frequency scanning on the take-off and landing area through a lidar to obtain the three-dimensional point cloud data;

[0016] Synchronously capture the left and right perspective images of the take-off and landing area through a binocular vision camera, and generate the binocular disparity data through a stereo matching algorithm;

[0017] Generate a digital elevation model according to the three-dimensional point cloud data, identify slope texture features according to the binocular disparity data, and then perform local detail optimization on the digital elevation model according to the slope texture features to obtain a terrain slope model;

[0018] Calculate the slope of each pixel according to the terrain slope model to obtain the terrain slope information.

[0019] Further, in an embodiment of the present invention, the obtaining of the body attitude information of the flying car, predicting the body attitude change in the future period according to the body attitude information and the terrain slope information, and determining the first target thrust vector specifically includes:

[0020] Obtain the body angular velocity, body acceleration and body attitude angle of the flying car through a six-axis attitude sensor to obtain the body attitude information;

[0021] Establish an aerodynamic model of the take-off and landing area according to the terrain slope information, and construct a state space equation of the flying car according to the aerodynamic model;

[0022] Obtain the current thrust vector of the flying car, and predict the body attitude change in the future period according to the body attitude information, the current thrust vector and the state space equation;

[0023] Determine the target compensation torque according to the body attitude change, and determine the first target thrust vector according to the target compensation torque and the current thrust vector.

[0024] Further, in an embodiment of the present invention, obtaining the first optimal thrust matrix by performing multi-rotor power distribution on the first target thrust vector specifically includes:

[0025] Construct a rotor attitude matrix, and map the rotor attitude matrix to the Lie algebra space to obtain the Lie algebra parameters of each rotor of the flying vehicle;

[0026] Determine the Lie algebra parameters and thrust scalars of each rotor as optimization variables, construct an error function regarding the optimization variables, and determine the total thrust constraint according to the rotor attitude matrix, the thrust scalar, and the first target thrust vector;

[0027] Apply a small perturbation to the Lie algebra parameters, update the rotor attitude using Lie group multiplication, calculate the Jacobian matrix of the error function, and perform iterative optimization on the optimization variables by non-linear least squares method;

[0028] Stop iteration when the residual change or gradient norm is lower than a preset threshold to obtain the optimized Lie algebra parameters and the thrust scalar;

[0029] Convert the optimized Lie algebra parameters to the optimal rotor attitude matrix through exponential mapping, and determine the optimal thrust vector of each rotor according to the optimal rotor attitude matrix and the optimized thrust scalar to generate the first optimal thrust matrix.

[0030] Further, in an embodiment of the present invention, performing attitude compensation on the flying vehicle according to the first optimal thrust matrix specifically includes:

[0031] Determine the target rotational speeds of the rotors of the flying vehicle according to the first optimal thrust matrix;

[0032] Perform rotational control on each rotor according to the target rotational speeds so that the flying vehicle maintains lift balance.

[0033] Further, in an embodiment of the present invention, when the flying vehicle lands on the takeoff and landing area, the vertical takeoff and landing method of the flying vehicle further includes the following steps:

[0034] Obtain the landing gear contact pressure information of the flying vehicle, and judge whether the force on the landing gear of the flying vehicle exceeds the limit according to the landing gear contact pressure information;

[0035] When the force on the landing gear of the flying vehicle exceeds the limit, control the flying vehicle to hover above the takeoff and landing area;

[0036] When the force on the landing gear of the flying car does not exceed the limit, determine whether the force on the landing gear of the flying car is balanced;

[0037] When the force on the landing gear of the flying car is unbalanced, update the terrain slope information according to the contact point pressure information of the landing gear, and adjust the attitude of the flying car according to the updated terrain slope information.

[0038] Further, in an embodiment of the present invention, the updating the terrain slope information according to the contact point pressure information of the landing gear and adjusting the attitude of the flying car according to the updated terrain slope information specifically includes:

[0039] Determine the ground inclination angle of each landing gear contact point according to the contact point pressure information of the landing gear and the real-time body attitude of the flying car;

[0040] Update the terrain slope information according to the positions of the landing gear contact points and the ground inclination angle;

[0041] Determine the target body attitude for the landing gear of the flying car to be balanced according to the terrain slope information, and determine the target attitude change according to the real-time body attitude and the target body attitude;

[0042] Determine the second target thrust vector according to the target attitude change, perform multi-rotor power distribution on the second target thrust vector to obtain the second optimal thrust matrix, and adjust the attitude of the flying car according to the second optimal thrust matrix.

[0043] In a second aspect, an embodiment of the present invention provides a vertical take-off and landing system for a flying car based on attitude compensation, including:

[0044] A terrain slope determination module, configured to obtain three-dimensional point cloud data and binocular parallax data of a take-off and landing area, and determine the terrain slope information of the take-off and landing area according to the three-dimensional point cloud data and the binocular parallax data;

[0045] A thrust vector determination module, configured to obtain the body attitude information of the flying car, predict the body attitude change in a future period according to the body attitude information and the terrain slope information, and determine the first target thrust vector according to the body attitude change;

[0046] A power distribution and attitude compensation module, configured to perform multi-rotor power distribution on the first target thrust vector to obtain the first optimal thrust matrix, and perform attitude compensation on the flying car according to the first optimal thrust matrix.

[0047] In a third aspect, an embodiment of the present invention provides a vertical take-off and landing device for a flying car based on attitude compensation, including:

[0048] At least one processor;

[0049] At least one memory for storing at least one program;

[0050] When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned vertical takeoff and landing method of a flying car based on attitude compensation.

[0051] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, in which a program executable by a processor is stored, and the program executable by the processor is used to execute the above-mentioned vertical takeoff and landing method of a flying car based on attitude compensation when executed by the processor.

[0052] The advantages and beneficial effects of the present invention will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present invention:

[0053] The embodiment of the present invention acquires three-dimensional point cloud data and binocular disparity data of a takeoff and landing area, determines the terrain slope information of the takeoff and landing area according to the three-dimensional point cloud data and the binocular disparity data, acquires the body attitude information of the flying car, predicts the body attitude change in a future period according to the body attitude information and the terrain slope information, determines a first target thrust vector according to the body attitude change, performs multi-rotor power distribution on the first target thrust vector to obtain a first optimal thrust matrix, and performs attitude compensation on the flying car according to the first optimal thrust matrix. The embodiment of the present invention determines the terrain slope information based on the three-dimensional point cloud data and the binocular disparity data of the takeoff and landing area, and can determine the aerodynamic model of the takeoff and landing area according to the terrain slope information, so as to predict the body attitude change of the flying car in combination with the aerodynamic model, and then adjust the power distribution of each rotor of the flying car to achieve attitude compensation of the flying car, enhancing the safety and reliability of the vertical takeoff and landing of the flying car, reducing the dependence on ground conditions and the construction and maintenance costs of the takeoff and landing area, and improving the flexibility and adaptability of vertical takeoff and landing deployment in various environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following introduces the drawings required to be used in the embodiments of the present invention. It should be understood that the drawings introduced below only conveniently and clearly represent some embodiments of the technical solutions in the present invention, and those skilled in the art can also obtain other drawings based on these drawings without creative efforts.

[0055] Figure 1 It is a flowchart of the steps of a vertical takeoff and landing method of a flying car based on attitude compensation provided by an embodiment of the present invention;

[0056] Figure 2 The structural block diagram of a vertical takeoff and landing system for a flying car based on attitude compensation provided by an embodiment of the present invention;

[0057] Figure 3 The structural block diagram of a vertical takeoff and landing device for a flying car based on attitude compensation provided by an embodiment of the present invention. Detailed implementation manners

[0058] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary only for explaining the present invention and should not be construed as limiting the present invention. For the step numbers in the following embodiments, they are only set for the convenience of elaboration and explanation, and no limitation is imposed on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0059] In the description of the present invention, the meaning of "a plurality of" is two or more. If the first and second are described, it is only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence of the indicated technical features. In addition, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field of the present invention.

[0060] Referring to Figure 1 , an embodiment of the present invention provides a vertical takeoff and landing method for a flying car based on attitude compensation, which specifically includes the following steps:

[0061] S101. Obtain the three-dimensional point cloud data and binocular disparity data of the takeoff and landing area, and determine the terrain slope information of the takeoff and landing area according to the three-dimensional point cloud data and binocular disparity data;

[0062] S102. Obtain the body attitude information of the flying car, predict the body attitude change in the future period according to the body attitude information and terrain slope information, and determine the first target thrust vector according to the body attitude change;

[0063] S103. Perform multi-rotor power distribution on the first target thrust vector to obtain the first optimal thrust matrix, and perform attitude compensation on the flying car according to the first optimal thrust matrix.

[0064] In the embodiment of the present invention, the terrain slope information is determined based on the three-dimensional point cloud data and binocular disparity data of the takeoff and landing area. According to the terrain slope information, the aerodynamic model of the takeoff and landing area can be determined, so as to predict the change of the body attitude of the flying car in combination with the aerodynamic model, and then adjust the power distribution of each rotor of the flying car to achieve attitude compensation for the flying car, enhancing the safety and reliability of the vertical takeoff and landing of the flying car, reducing the dependence on ground conditions and the construction and maintenance costs of the takeoff and landing area, and improving the flexibility and adaptability of deploying vertical takeoff and landing in various environments.

[0065] Further as an optional implementation manner, the three-dimensional point cloud data and binocular disparity data of the takeoff and landing area are obtained, and the terrain slope information of the takeoff and landing area is determined according to the three-dimensional point cloud data and binocular disparity data, which specifically includes:

[0066] S1011. Perform high-frequency scanning on the takeoff and landing area through a lidar to obtain three-dimensional point cloud data;

[0067] S1012. Synchronously capture the left and right view images of the takeoff and landing area through a binocular vision camera, and generate binocular disparity data through a stereo matching algorithm;

[0068] S1013. Generate a digital elevation model according to the three-dimensional point cloud data, identify the slope texture features according to the binocular disparity data, and then perform local detail optimization on the digital elevation model according to the slope texture features to obtain a terrain slope model;

[0069] S1014. Calculate the slope of each pixel according to the terrain slope model to obtain the terrain slope information.

[0070] Specifically, the three-dimensional point cloud data and binocular disparity data of the takeoff and landing area are obtained through a lidar and a binocular vision camera, and a terrain slope model of the takeoff and landing area is constructed based on the three-dimensional point cloud data and binocular disparity data, so as to obtain the terrain slope information of the takeoff and landing area. The specific process is as follows:

[0071] 1) The lidar performs high-frequency scanning to generate three-dimensional point cloud data

[0072] Scanning equipment and parameter settings: Use a high-frequency scanning lidar (such as the RayShen Intelligent 1550nm fiber hybrid solid-state radar), set the horizontal scanning angle ≥ 330°, the vertical scanning angle ≥ 30°, and the scanning frequency ≥ 10Hz to ensure real-time performance. Synchronously record the radar position and attitude through the GPS / IMU system to achieve centimeter-level positioning accuracy.

[0073] Point cloud data preprocessing: Denoise the original point cloud (remove the interference points of the aircraft or vegetation), register (spatiotemporally align multiple frames of point clouds), and perform coordinate transformation (map the laser coordinate system to the geographic coordinate system). For example, use the RANSAC algorithm to separate the ground and non-ground points.

[0074] 2) Binocular Vision Synchronous Acquisition and Disparity Calculation

[0075] Binocular Camera Calibration and Synchronization: Deploy high-resolution binocular cameras (such as global shutter cameras), and complete the internal parameter calibration (focal length, distortion parameters) and external parameter calibration (spatial alignment with lidar). Ensure the time synchronization of images and point clouds through hardware triggering.

[0076] Stereo Matching to Generate Disparity Map: Use SGBM (Semi-Global Matching) or deep learning models (such as PSMNet) to calculate the disparity between the left and right images and generate a disparity map. The key steps include: epipolar rectification to eliminate the vertical deviation of the image and simplify the matching search range; cost aggregation to calculate the pixel matching cost by combining Census transform or gray similarity; disparity optimization to remove false matches through left-right consistency check and smooth the disparity jump region.

[0077] 3) Digital Elevation Model (DEM) Generation and Local Optimization

[0078] (1) Conversion from Point Cloud to DEM: Construct an irregular triangular network (TIN) based on the ground point cloud, and then rasterize it into a DEM grid (resolution 0.1 - 1m). Use Kriging interpolation to fill in the missing areas and retain the terrain undulation details.

[0079] (2) Binocular Disparity-Assisted Texture Feature Extraction, Analyze the Disparity Map to Identify Slope Texture Features:

[0080] Edge Detection: Extract the disparity mutation boundary (corresponding to steep slopes or obstacles) through the Canny algorithm.

[0081] Texture Analysis: Use Local Binary Pattern (LBP) to quantify the surface roughness and correlate with slope changes.

[0082] (3) DEM Local Optimization Method, Fusing Point Cloud Elevation and Texture Features:

[0083] Weighted Fusion: In areas with complex textures (such as scree slopes), increase the weight of disparity data to correct the local slope of the DEM.

[0084] Edge Enhancement: Based on the disparity boundary, constrain the vertex distribution of the TIN to improve the model accuracy in steep slope areas.

[0085] 4) Terrain Slope Calculation and Output

[0086] (1) Slope Algorithm

[0087] Calculate the slope for each pixel of the optimized DEM, and the formula is:

[0088]

[0089] Among them, and calculate the neighborhood elevation gradient through the Sobel operator.

[0090] (2) Slope grading and visualization

[0091] Grade according to 0° to 5° (flat), 5° to 15° (gentle slope), 15° to 30° (moderate slope), >30° (steep slope), and output as a raster map or a contour overlay map.

[0092] Further as an optional implementation, obtain the body attitude information of the flying car, predict the change of the body attitude in the future period according to the body attitude information and the terrain slope information, and determine the first target thrust vector according to the change of the body attitude, which specifically includes:

[0093] S1021. Obtain the body angular velocity, body acceleration, and body attitude angle of the flying car through a six-axis attitude sensor to obtain the body attitude information;

[0094] S1022. Establish an aerodynamic model of the takeoff and landing area according to the terrain slope information, and construct the state space equation of the flying car according to the aerodynamic model;

[0095] S1023. Obtain the current thrust vector of the flying car, and predict the change of the body attitude in the future period according to the body attitude information, the current thrust vector, and the state space equation;

[0096] S1024. Determine the target compensation torque according to the change of the body attitude, and determine the first target thrust vector according to the target compensation torque and the current thrust vector.

[0097] Specifically, obtain the body attitude information of the flying car through a six-axis attitude sensor, perform aerodynamic modeling on the takeoff and landing area according to the terrain slope information, and construct the state space equation of the flying car. Predict the change of the body attitude of the flying car in the future period through model predictive control, so as to determine the target compensation torque, and then obtain the first target thrust vector. The specific process is as follows:

[0098] 1) Acquisition of body attitude information (six-axis sensor data fusion)

[0099] Sensor data acquisition:

[0100] Use a six-axis attitude sensor to measure the three-axis angular velocity (gyroscope) and three-axis acceleration (accelerometer) of the body in real time, and the original data is transmitted to the processor through the I 2 C / SPI interface.

[0101] Attitude solution and filtering:

[0102] The accelerometer and gyroscope data are fused using complementary filtering or Kalman filtering algorithms. The accelerometer corrects the long-term drift of the gyroscope, and the gyroscope compensates for the high-frequency noise of the accelerometer, outputting stable pitch, roll, and yaw angles.

[0103] The complementary filtering formula is as follows:

[0104] θ 融合 = α · (θ 陀螺仪 + ω · Δt) + (1 - α) · θ 加速度计

[0105] where α is the weight coefficient, ω is the angular velocity, and Δt is the sampling period.

[0106] 2) Aerodynamic modeling and state-space equation construction

[0107] Terrain slope modeling: Combining lidar or vision sensors to obtain terrain slope information (such as slope angle β), and converting the slope influence into correction terms of aerodynamic parameters (such as lift coefficient C L , drag coefficient C D ).

[0108] State-space equation establishment: Based on Newton-Euler equations, define state variables (attitude angle θ, angular velocity ω, position p, velocity v) and control inputs (thrust vector T, moment M), and construct a nonlinear dynamics model:

[0109]

[0110] where x = [θ, ω, p, v] T , u = [T x , T y , T z T . Simplify the model to a linear state-space form through linearization or system identification methods (such as the least squares method):

[0111]

[0112] where d(β) is the terrain disturbance term.

[0113] 3) Future attitude change prediction

[0114] Based on the current thrust vector T 当前 and the state-space equation, use model predictive control (MPC) or extended Kalman filter (EKF) to predict the attitude change in the future time period (such as t + Δt):

[0115] x 预测 = e AΔt x 当前 ​+∫0 Δt e A(Δt-τ) Bu(τ)dτ

[0116] Considering the influence of terrain disturbance d(β), calculate the attitude angle deviation Δθ = θ 预测 -θ 目标 .

[0117] 4) Target compensation torque calculation

[0118] Design the target compensation torque M according to the attitude deviation Δθ 目标 , usually using the PID control law:

[0119]

[0120] where K p , K i , K d are the controller gains.

[0121] According to the target compensation torque M 目标 and the current thrust vector T 当前 the first target thrust vector T 目标 can be calculated.

[0122] Furthermore, as an optional implementation, the first target thrust vector is subjected to multi-rotor power distribution to obtain the first optimal thrust matrix, which specifically includes:

[0123] S1031. Construct the rotor attitude matrix and map the rotor attitude matrix to the Lie algebra space to obtain the Lie algebra parameters of each rotor of the flying car;

[0124] S1032. Determine the Lie algebra parameters and thrust scalar of each rotor as optimization variables, construct an error function about the optimization variables, and determine the total thrust constraint according to the rotor attitude matrix, thrust scalar, and the first target thrust vector;

[0125] S1033. Apply a small perturbation to the Lie algebra parameters, update the rotor attitude using Lie group multiplication, calculate the Jacobian matrix of the error function, and iteratively optimize the optimization variables by the nonlinear least squares method;

[0126] S1034. Stop the iteration when the residual change or gradient norm is lower than the preset threshold to obtain the optimized Lie algebra parameters and thrust scalar;

[0127] S1035. Convert the optimized Lie algebra parameters to the optimal rotor attitude matrix through exponential mapping, and determine the optimal thrust vector of each rotor according to the optimal rotor attitude matrix and the optimized thrust scalar to generate the first optimal thrust matrix.

[0128] Specifically, the embodiment of the present invention performs multi-rotor power distribution on the first target thrust vector based on Lie groups and Lie algebras. The specific process is as follows:

[0129] 1) Construct the rotor attitude matrix and map it to the Lie algebra space

[0130] Construct the rotor attitude matrix: The rotor attitude of the flying car can usually be represented by the rotation matrix R. The rotation matrix is a 3×3 orthogonal matrix that satisfies R T R = I and det(R) = 1. The rotation matrix can be constructed by means of Euler angles (such as pitch angle θ, roll angle φ, and yaw angle ψ) or quaternions. For example, the construction formula of the rotation matrix based on Z-Y-X Euler angles is: R = R z (ψ)R y (θ)R x (φ), where

[0131] Map to the Lie algebra space: The rotation matrix R belongs to the special orthogonal group SO(3), and its corresponding Lie algebra so(3) is a three-dimensional vector ω. The logarithmic mapping can be used to convert the rotation matrix R into Lie algebra parameters. For the rotation matrix R, its logarithmic mapping is ω = ln(R). In actual calculations, the inverse of the Rodriguez formula can be used to achieve this. Let R = I + sin(θ)[u] × +(1 - cos(θ))[u] × 2 , where θ is the rotation angle, u is the unit vector of the rotation axis, and [u] × is the skew-symmetric matrix of u, then ω = θu.

[0132] 2) Determine the optimization variables, construct the error function, and the total thrust constraint

[0133] Determine the optimization variables: The optimization variables include the Lie algebra parameters ω i (i = 1, 2,..., n, where n is the number of rotors) and the thrust scalar T i .

[0134] Construct the error function: The error function E is used to measure the difference between the current state and the desired state. It can be defined according to specific task requirements. For example, consider the attitude error and thrust error of each rotor. Let the desired attitude matrix be R d,i , and the desired thrust vector be F d,i , then the error function can be defined as:

[0135]

[0136] where e z,iis the axial unit vector of the i-th rotor, and α is the weight coefficient.

[0137] Determine the total thrust constraint: The total thrust constraint can be determined based on the dynamic requirements of the flying car. Let the first target thrust vector be F total,d , then the total thrust constraint is:

[0138] 3) Calculate the Jacobian matrix and perform iterative optimization

[0139] Apply a small perturbation and update the rotor attitude: i Apply a small perturbation δω i , use Lie group multiplication to update the rotor attitude. For the rotation matrix R i , the updated rotation matrix is:

[0140] R′ i =exp([δω i ] × )R i

[0141] where exp([δω i ] × ) is based on the Lie algebra δω i The exponential map of .

[0142] Calculate the Jacobian matrix: The Jacobian matrix J is used to describe the partial derivatives of the error function E with respect to the optimization variables. Let the optimization variable vector be Then the Jacobian matrix The Jacobian matrix can be calculated by numerical methods (such as the finite difference method) or analytical methods.

[0143] Nonlinear least squares iterative optimization: Use nonlinear least squares to iteratively optimize the optimization variables. The iterative formula is x k+1 =x k -λ(J T J) -1 J T r, where r is the error vector, λ is the step size factor, and k is the number of iterations.

[0144] 4) Stop iterating condition judgment

[0145] Set the preset thresholds ∈1 and ∈2 to judge the residual change and gradient norm respectively. After each iteration, calculate the residual change ΔE=E k -E k+1 and the gradient norm When ΔE<∈1 or When , stop the iteration and get the optimized Lie algebra parameters and thrust scalar

[0146] 5) Convert to the optimal rotor attitude matrix and generate the first optimal thrust matrix

[0147] Exponential mapping transformation: Transform the optimized Lie algebra parameters through exponential mapping into the optimal rotor attitude matrix That is

[0148] Determine the optimal thrust vector and generate the first optimal thrust matrix: According to the optimal rotor attitude matrix and the optimized thrust scalar determine the optimal thrust vector of each rotor Arrange the optimal thrust vectors of each rotor by column to obtain the first optimal thrust matrix

[0149] Further as an optional implementation manner, perform attitude compensation on the flying car according to the first optimal thrust matrix, which specifically includes:

[0150] S1036. Determine the target speed of each rotor of the flying car according to the first optimal thrust matrix;

[0151] S1037. Rotate each rotor according to the target speed to keep the flying car in lift balance.

[0152] Specifically, determine the thrust component of each rotor according to the first optimal thrust matrix, and use the propeller thrust model T i = C T ρN i 2 D p 4 to inversely deduce the target speed N i , where C T is the thrust coefficient, ρ is the air density, and D p is the blade diameter; according to the target speed, use the architecture of outer-loop attitude control + inner-loop speed control for cascade PID adjustment, so as to rotate each rotor and achieve the lift balance of the flying car.

[0153] Further as an optional implementation manner, when the flying car lands on the takeoff and landing area, the vertical takeoff and landing method of the flying car further includes the following steps:

[0154] S201. Obtain the landing gear contact pressure information of the flying car, and judge whether the force on the landing gear of the flying car exceeds the limit according to the landing gear contact pressure information;

[0155] S202. When the force on the landing gear of the flying car exceeds the limit, control the flying car to hover above the takeoff and landing area;

[0156] S203. When the force on the landing gear of the flying car does not exceed the limit, determine whether the force on the landing gear of the flying car is balanced;

[0157] S204. When the force on the landing gear of the flying car is unbalanced, update the terrain slope information according to the contact pressure information of the landing gear, and adjust the attitude of the flying car according to the updated terrain slope information.

[0158] Specifically, the embedded multi-dimensional force sensor networking technology is adopted. A strain pressure sensor array is deployed at each support point of the landing gear, and a distributed acquisition system is established through the CAN bus architecture. The sampling frequency needs to reach more than 200 Hz to capture the transient landing impact load. When the single-point pressure of the landing gear is greater than the preset threshold, the force on the landing gear exceeds the limit, and the vector propulsion system is activated to achieve hovering. When the force on the landing gear of the flying car does not exceed the limit, the least squares method is used to calculate the pressure distribution variance value, and whether the force on the landing gear is balanced is judged according to the pressure distribution variance value. When the force on the landing gear of the flying car is unbalanced, the slope angles of the contacts of each landing gear are inversed through the pressure difference, and the terrain slope information is updated in combination with the terrain slope model constructed in the previous steps. The attitude is adjusted adaptively according to the updated terrain slope information.

[0159] Further as an optional implementation manner, updating the terrain slope information according to the contact pressure information of the landing gear, and adjusting the attitude of the flying car according to the updated terrain slope information specifically includes:

[0160] S2041. Determine the ground tilt angles of the contacts of each landing gear according to the contact pressure information of the landing gear and the real-time body attitude of the flying car;

[0161] Specifically, the process of determining the ground tilt angles of the contacts of each landing gear is as follows:

[0162] Data acquisition: Use pressure sensors to collect the pressure information of the contacts of the landing gear. These sensors need to be installed at the contact positions of each landing gear to accurately obtain the pressure at each point. At the same time, devices such as an inertial measurement unit (IMU) and a global positioning system (GPS) are used to obtain the real-time body attitude data of the flying car, including pitch angle, roll angle, yaw angle, etc.

[0163] Calculate the tilt angle: Based on the collected pressure information of the contacts of the landing gear and the real-time body attitude, relevant mechanical models and geometric algorithms are used for calculation. For example, when the pressure of a certain landing gear contact is large, combined with the body attitude, it can be inferred that the ground at the position of this contact may be relatively low. Through the comprehensive analysis of the pressures of multiple landing gear contacts and the body attitude, the ground tilt angles of the contacts of each landing gear can be determined.

[0164] S2042. Update the terrain slope information according to the positions and ground tilt angles of the contacts of each landing gear;

[0165] Specifically, the process of updating the terrain slope information is as follows:

[0166] Determine the landing gear contact positions: Through the positioning system of the flying car and the internal coordinate system, accurately determine the positions of each landing gear contact in three-dimensional space. This position information can be represented by coordinates relative to the centroid of the flying car or a certain fixed reference point.

[0167] Update the terrain slope information: Based on the determined landing gear contact positions and the ground tilt angle, update the terrain slope information under the flying car. The terrain slope model constructed in the previous steps can be used to incorporate the new tilt angle and position information, thereby obtaining more accurate terrain slope information.

[0168] S2043. Determine the target body attitude that makes the landing gears of the flying car bear balanced forces according to the terrain slope information, and determine the target attitude change based on the real-time body attitude and the target body attitude;

[0169] Specifically, the process of determining the target attitude change is as follows:

[0170] Calculate the target body attitude: According to the updated terrain slope information, use an optimization algorithm to determine the target body attitude that makes the landing gears of the flying car bear balanced forces. This algorithm needs to consider factors such as the structural characteristics of the flying car, the center of gravity position, and the load-bearing capacity of each landing gear. For example, when the flying car is on an inclined ground, adjust the body attitude to make the pressures borne by each landing gear as equal as possible to ensure the stability and safety of the flying car.

[0171] Determine the target attitude change: Compare the real-time body attitude with the target body attitude and calculate the difference between the two, that is, the target attitude change. This change can be represented by the angle change amount, including the changes in pitch angle, roll angle, and yaw angle.

[0172] S2044. Determine the second target thrust vector according to the target attitude change, perform multi-rotor power distribution on the second target thrust vector to obtain the second optimal thrust matrix, and adjust the attitude of the flying car according to the second optimal thrust matrix.

[0173] Specifically, the process of attitude adjustment is as follows:

[0174] Determine the second target thrust vector: According to the calculated target attitude change and combined with the dynamic model of the flying car, determine the second target thrust vector required to achieve this attitude change. This thrust vector includes magnitude and direction, which determines the resultant force and the direction of the resultant force that each rotor of the flying car needs to provide.

[0175] Multi-rotor power distribution: Perform multi-rotor power distribution on the second target thrust vector, reasonably distribute the total thrust to each rotor, and obtain the second optimal thrust matrix. This requires considering factors such as the position, rotation direction, and maximum thrust of each rotor to ensure that each rotor can work together to achieve the attitude adjustment of the flying car.

[0176] Attitude adjustment: According to the second optimal thrust matrix, control each rotor of the flying car, adjust its rotation speed and thrust magnitude, so as to achieve the attitude adjustment of the flying car. During the adjustment process, it is necessary to monitor the attitude change of the flying car in real time and dynamically adjust the thrust matrix according to the feedback information to ensure the accuracy and stability of the attitude adjustment.

[0177] By repeatedly executing the above steps, the flying car can adjust its own attitude in real time according to terrain changes, ensure the balanced force on the landing gear, and improve the safety and stability of flight.

[0178] The above has described the method steps of the embodiments of the present invention. It can be understood that the embodiments of the present invention determine the terrain slope information based on the three-dimensional point cloud data and binocular disparity data of the takeoff and landing area, and can determine the aerodynamic model of the takeoff and landing area according to the terrain slope information. Thus, combined with the aerodynamic model, predict the body attitude change of the flying car, and then adjust the power distribution of each rotor of the flying car to achieve attitude compensation for the flying car, enhancing the safety and reliability of the vertical takeoff and landing of the flying car, reducing the dependence on ground conditions and the construction and maintenance costs of the takeoff and landing area, and improving the flexibility and adaptability of deploying vertical takeoff and landing in various environments.

[0179] Compared with the prior art, the embodiments of the present invention also have the following advantages:

[0180] 1) Improve stability in complex environments

[0181] The attitude compensation algorithm significantly enhances the adaptability in unstructured environments by monitoring the aircraft attitude (such as tilt, roll, pitch) in real time and dynamically adjusting the thrust distribution.

[0182] 2) Reduce dependence on ground conditions

[0183] Reduce site construction costs: Reduce the need for a highly flat apron.

[0184] Adapt to soft terrain: On soft ground such as sand and wetlands, the system adjusts the support force of the landing gear and the attitude angle to avoid the risk of tipping caused by local settlement, expanding the deployment ability in remote areas.

[0185] 3) Improve safety and reliability

[0186] Dynamic fault tolerance: If a propulsion unit (such as a rotor or nozzle) fails, the attitude compensation system can reallocate thrust to ensure that the aircraft can still return safely.

[0187] Reduce mechanical stress: By actively canceling vibrations and shocks, extend the lifespan of the landing gear and power system.

[0188] Refer to Figure 2 , an embodiment of the present invention provides a vertical takeoff and landing system for a flying car based on attitude compensation, including:

[0189] A terrain slope determination module, configured to obtain three-dimensional point cloud data and binocular disparity data of the takeoff and landing area, and determine the terrain slope information of the takeoff and landing area according to the three-dimensional point cloud data and the binocular disparity data;

[0190] A thrust vector determination module, configured to obtain the body attitude information of the flying car, predict the body attitude change in the future period according to the body attitude information and the terrain slope information, and determine the first target thrust vector according to the body attitude change;

[0191] A power distribution and attitude compensation module, configured to perform multi-rotor power distribution on the first target thrust vector to obtain the first optimal thrust matrix, and perform attitude compensation on the flying car according to the first optimal thrust matrix.

[0192] The content in the above method embodiments is applicable to the system embodiments of the present invention. The functions specifically implemented by the system embodiments of the present invention are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0193] Refer to Figure 3 , an embodiment of the present invention provides a vertical takeoff and landing device for a flying car based on attitude compensation, including:

[0194] At least one processor;

[0195] At least one memory, configured to store at least one program;

[0196] When the above at least one program is executed by the above at least one processor, the above at least one processor implements the above vertical takeoff and landing method for a flying car based on attitude compensation.

[0197] The content in the above method embodiments is applicable to the device embodiments of the present invention. The functions specifically implemented by the device embodiments of the present invention are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0198] An embodiment of the present invention also provides a computer-readable storage medium, which stores a program executable by a processor. When the program executable by the processor is executed by the processor, it is used to execute the above-mentioned method for vertical takeoff and landing of a flying car based on attitude compensation.

[0199] A computer-readable storage medium according to an embodiment of the present invention can execute a method for vertical takeoff and landing of a flying car based on attitude compensation provided by an embodiment of the method of the present invention, can execute any combination of implementation steps of the method embodiment, and has the corresponding functions and beneficial effects of the method.

[0200] An embodiment of the present invention also discloses a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium, and when the processor executes the computer instructions, the computer device is caused to execute Figure 1 the method shown.

[0201] In some alternative embodiments, the functions / operations mentioned in the block diagram may not occur in the order mentioned in the operating diagram. For example, depending on the functions / operations involved, two consecutive blocks shown may actually be executed substantially simultaneously, or the above-mentioned blocks can sometimes be executed in the reverse order. In addition, the embodiments presented and described in the flowcharts of the present invention are provided by way of example for the purpose of providing a more comprehensive understanding of the technology. The disclosed method is not limited to the operations and logical flows presented herein. Alternative embodiments are foreseeable, in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0202] In addition, although the present invention has been described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the above functions and / or features may be integrated in a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It can also be understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present invention. More precisely, considering the attributes, functions, and internal relationships of various functional modules in the devices disclosed herein, the actual implementation of the modules will be understood within the ordinary skills of an engineer. Therefore, those skilled in the art can implement the present invention as set forth in the claims without undue experimentation. It can also be understood that the specific concepts disclosed are illustrative only and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0203] If the above functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs, etc., which can store program codes of various kinds.

[0204] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or in combination with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in combination with an instruction execution system, apparatus, or device.

[0205] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection part with one or more wirings (electronic device), a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the above program can be printed, because the above program can be obtained electronically, for example, by optically scanning the paper or other media, then editing, interpreting, or processing it in other suitable ways when necessary, and then storing it in a computer memory.

[0206] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following techniques known in the art or a combination thereof can be used: discrete logic circuits having logic gate circuits for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0207] In the above description of this specification, the descriptions referring to the terms "one embodiment / example", "another embodiment / example", or "certain embodiments / examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiments or examples are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0208] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and purposes of the present invention, and the scope of the present invention is defined by the claims and their equivalents.

[0209] The above has specifically described the preferred embodiments of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present invention, and these equivalent deformations or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A vertical takeoff and landing method for a flying car based on attitude compensation, characterized in that Including the following steps: Obtain the three-dimensional point cloud data and binocular disparity data of the takeoff and landing area, and determine the terrain slope information of the takeoff and landing area according to the three-dimensional point cloud data and the binocular disparity data; Obtain the body attitude information of the flying car, predict the body attitude change in the future period according to the body attitude information and the terrain slope information, and determine the first target thrust vector according to the body attitude change; Perform multi-rotor power distribution on the first target thrust vector to obtain the first optimal thrust matrix, and perform attitude compensation on the flying car according to the first optimal thrust matrix.

2. A vertical takeoff and landing method for a flying car based on attitude compensation according to claim 1, characterized in that, The step of obtaining the three-dimensional point cloud data and binocular disparity data of the takeoff and landing area, and determining the terrain slope information of the takeoff and landing area according to the three-dimensional point cloud data and the binocular disparity data specifically includes: Perform high-frequency scanning on the takeoff and landing area through a lidar to obtain the three-dimensional point cloud data; Synchronously capture the left and right perspective images of the takeoff and landing area through a binocular vision camera, and generate the binocular disparity data through a stereo matching algorithm; Generate a digital elevation model according to the three-dimensional point cloud data, identify the slope texture features according to the binocular disparity data, and then perform local detail optimization on the digital elevation model according to the slope texture features to obtain a terrain slope model; Calculate the slope of each pixel according to the terrain slope model to obtain the terrain slope information.

3. A vertical takeoff and landing method for a flying car based on attitude compensation according to claim 1, characterized in that The step of obtaining the body attitude information of the flying car, predicting the body attitude change in the future period according to the body attitude information and the terrain slope information, and determining the first target thrust vector specifically includes: Obtain the body angular velocity, body acceleration, and body attitude angle of the flying car through a six-axis attitude sensor to obtain the body attitude information; Establish an aerodynamic model of the takeoff and landing area according to the terrain slope information, and construct a state space equation of the flying car according to the aerodynamic model; Obtain the current thrust vector of the flying car, and predict the body attitude change in the future period according to the body attitude information, the current thrust vector, and the state space equation; Determine the target compensation torque according to the body attitude change, and determine the first target thrust vector according to the target compensation torque and the current thrust vector.

4. A vertical takeoff and landing method for a flying car based on attitude compensation according to claim 1, characterized in that, The step of performing multi-rotor power distribution on the first target thrust vector to obtain the first optimal thrust matrix specifically includes: Construct a rotor attitude matrix, and map the rotor attitude matrix to the Lie algebra space to obtain the Lie algebra parameters of each rotor of the flying car; Determine the Lie algebra parameters and thrust scalars of each rotor as optimization variables, construct an error function about the optimization variables, and determine the total thrust constraint according to the rotor attitude matrix, the thrust scalar, and the first target thrust vector; Apply a small perturbation to the Lie algebra parameters, update the rotor attitude using Lie group multiplication, calculate the Jacobian matrix of the error function, and perform iterative optimization on the optimization variables through nonlinear least squares method. Stop the iteration when the residual change or the gradient norm is lower than the preset threshold, and obtain the optimized Lie algebra parameters and the thrust scalar; Convert the optimized Lie algebra parameters into the optimal rotor attitude matrix through exponential mapping, and determine the optimal thrust vector of each rotor according to the optimal rotor attitude matrix and the optimized thrust scalar, and generate the first optimal thrust matrix.

5. A vertical takeoff and landing method for a flying car based on attitude compensation according to claim 1, characterized in that, The attitude compensation of the flying car according to the first optimal thrust matrix specifically includes: Determine the target rotational speed of each rotor of the flying car according to the first optimal thrust matrix; Perform rotational control on each rotor according to the target rotational speed, so that the flying car maintains lift balance.

6. A vertical take-off and landing method for a flying car based on attitude compensation according to any one of claims 1 to 5, characterized in that, When the flying car lands on the takeoff and landing area, the vertical takeoff and landing method of the flying car further includes the following steps: Obtain the landing gear contact pressure information of the flying car, and judge whether the force on the landing gear of the flying car exceeds the limit according to the landing gear contact pressure information; When the force on the landing gear of the flying car exceeds the limit, control the flying car to hover above the takeoff and landing area; When the force on the landing gear of the flying car does not exceed the limit, judge whether the force on the landing gear of the flying car is balanced; When the force on the landing gear of the flying car is unbalanced, update the terrain slope information according to the landing gear contact pressure information, and perform attitude adjustment on the flying car according to the updated terrain slope information.

7. A vertical takeoff and landing method for a flying car based on attitude compensation according to claim 6, characterized in that, The updating the terrain slope information according to the landing gear contact pressure information and performing attitude adjustment on the flying car according to the updated terrain slope information specifically includes: Determine the ground tilt angle of each landing gear contact according to the landing gear contact pressure information and the real-time body attitude of the flying car; Update the terrain slope information according to the position of each landing gear contact and the ground tilt angle; Determine the target body attitude that makes the force on the landing gear of the flying car balanced according to the terrain slope information, and determine the target attitude change according to the real-time body attitude and the target body attitude; Determine the second target thrust vector according to the target attitude change, perform multi-rotor power distribution on the second target thrust vector to obtain the second optimal thrust matrix, and perform attitude adjustment on the flying car according to the second optimal thrust matrix.

8. A vertical takeoff and landing system for a flying car based on attitude compensation, characterized in that, Includes: A terrain slope determination module, configured to obtain three-dimensional point cloud data and binocular parallax data of the takeoff and landing area, and determine the terrain slope information of the takeoff and landing area according to the three-dimensional point cloud data and the binocular parallax data; A thrust vector determination module, configured to obtain the body attitude information of the flying car, predict the body attitude change in the future period according to the body attitude information and the terrain slope information, and determine the first target thrust vector according to the body attitude change; A power distribution and attitude compensation module, configured to perform multi-rotor power distribution on the first target thrust vector to obtain the first optimal thrust matrix, and perform attitude compensation on the flying car according to the first optimal thrust matrix.

9. A vertical takeoff and landing device for a flying car based on attitude compensation, characterized in that, Includes: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements a vertical takeoff and landing method for a flying car based on attitude compensation as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that, The program executable by the processor, when executed by the processor, is used to execute a vertical takeoff and landing method for a flying car based on attitude compensation as described in any one of claims 1 to 7.

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