Landing trajectory planning method and system based on terrain obstacle convex hull error model
Through the landing trajectory planning method based on the terrain obstacle convex hull error model, the problem of safety zone judgment error caused by terrain detection data error is solved, and a high-safe deep space exploration landing is realized, which improves the success rate and environmental perception ability of the detector .
Patent Information
- Application Number
- CN202411021888.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-29
- Publication Date
- 2024-12-20
AI Technical Summary
In deep space exploration, errors in terrain detection data lead to errors in judgment of safety areas, affecting the safety and success rate of landers. Especially in areas with high scientific value but complex terrain, it is difficult for the existing technology to effectively avoid obstacles.
The landing trajectory planning method based on the convex hull error model of terrain obstacles is used to construct a convex hull model of obstacles through three-dimensional laser data, and the error matrix is calculated based on the Jacques matrix and propagation error law to generate the error range of obstacles, and the artificial potential field method is used. Implement the maximum collision probability model and carry out landing obstacle avoidance trajectory planning.
The safety and success rate of the lander are improved, and by accurately capturing the morphological characteristics and error descriptions of terrain obstacles, the probability of collision of terrain obstacles is minimized and the reliability and autonomy of the landing process is enhanced.
Smart Images
Figure CN119165854A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of deep space celestial body landing technology, and in particular to a landing trajectory planning method and system based on a terrain obstacle convex hull error model. Background Art
[0002] A safe and soft landing is the key prerequisite for the success or failure of deep space exploration missions. In order to improve the landing success rate, deep space exploration missions successfully implemented by countries around the world generally allow the lander to select a relatively flat and safe area for landing based on indicators such as roughness and slope. However, future exploration missions will be aimed at areas with high scientific value but complex terrain, which puts higher requirements on the reliability of landing safety. Landing trajectory planning needs to have stronger autonomous environmental perception and obstacle avoidance capabilities. At the same time, there are errors in the estimation of the lander position during landing, and due to the disturbance of the measuring instruments and processes, there are errors in the terrain data obtained by detection, which poses a hidden danger to the safety of the landing mission. It is necessary to consider the impact of the lander position and terrain data errors in landing trajectory planning.
[0003] In view of the high reliability requirements for landing in complex terrain areas of deep space exploration, a terrain data error modeling method and a landing trajectory planning method that takes into account the lander position and terrain data errors are provided. A three-dimensional convex hull modeling method for terrain obstacles and errors is proposed, and a terrain obstacle position error model is established to accurately represent the geometric characteristics and error distribution range of terrain obstacles of different forms. In the case where there are errors in both the lander position and terrain obstacles, a collision probability model is established, and a maximum collision probability artificial potential field landing obstacle avoidance trajectory planning method that takes into account terrain errors is proposed, achieving high-safety trajectory planning. Summary of the invention
[0004] In view of the above problems existing in the prior art, the present invention is proposed.
[0005] Therefore, the technical problem solved by the present invention is: to address the problem of misjudgment of the safety zone caused by errors in terrain detection data, a landing trajectory planning method based on a terrain obstacle convex hull error model is proposed based on three-dimensional laser data.
[0006] To solve the above technical problems, the present invention provides the following technical solutions: a landing trajectory planning method based on a terrain obstacle convex hull error model, comprising: using the three-dimensional point cloud data of the obstacle and adopting a random incremental algorithm to construct a three-dimensional convex hull model of the terrain obstacle; calculating the error matrix of the measured three-dimensional point cloud data using the Jacobian matrix and the propagation error law; translating the vertices of each triangular face on the obstacle convex hull along the direction of their respective plane normal vectors to generate uncertain boundary points of the obstacle, and reusing the three-dimensional convex hull generation algorithm based on the uncertain boundary points to generate the error range of the obstacle, and establishing an obstacle error model.
[0007] As a preferred solution of the landing trajectory planning method based on the terrain obstacle convex hull error model of the present invention, the three-dimensional point cloud data includes the original measurement values obtained by laser sensor measurement, namely the distance l and the angles α and β in the laser measurement coordinate system, and the coordinates of the measurement points in the reference coordinate system are expressed as follows:
[0008]
[0009] As a preferred solution of the landing trajectory planning method based on the terrain obstacle convex hull error model of the present invention, the error propagation law includes obtaining the error matrix of the point (X, Y, Z) as:
[0010]
[0011] Among them, K is the Jacobian matrix, D is the covariance matrix of the original measurement value (l, α, β), is the variance in the X direction, is the variance in the Y direction, is the variance in the Z direction, σX,Y is the covariance between the X and Y directions, σ X，Z is the covariance between the X and Z directions, σ Y，Z is the covariance between the Y direction and the Z direction; the uncertain boundary points are generated by translating along the directions of the respective plane normal vectors; the obstacle error model is established by reusing the 3D convex hull model generation algorithm and the obstacle error range according to the generated points.
[0012] As a preferred solution of the landing trajectory planning method based on the terrain obstacle convex hull error model of the present invention, the obstacle error model includes a triangle point set (P1, P2, P3), and the point position error of the triangle vertex P1 in the normal vector direction of the plane is expressed as:
[0013]
[0014] in, is the normal vector of the triangle, The error matrix representing point P1 is combined with the collision probability model to implement the landing trajectory planning method.
[0015] As a preferred solution of the landing trajectory planning method based on the terrain obstacle convex hull error model of the present invention, the collision probability model includes using the probability density value of the point closest to the lander in the obstacle error range as the probability density value of each point in the obstacle area to establish a maximum collision probability model, and the calculation formula is expressed as follows:
[0016]
[0017] Where V represents the obstacle error range volume, r is the position of the lander, It represents the point closest to the lander within the error range of the obstacle, and C is the error matrix of the lander position. When there are multiple obstacles, the maximum collision probability of the lander is the sum of the maximum collision probabilities of the lander and all terrain obstacles. Based on the artificial potential field method, the landing obstacle avoidance trajectory planning is realized.
[0018] As a preferred solution of the landing trajectory planning method based on the terrain obstacle convex hull error model of the present invention, the artificial potential field method includes establishing a dynamic model to determine that the motion equation of the lander in the fixed coordinate system ∑l of the landing point is expressed as:
[0019]
[0020] Among them, r l and v l The lander is l The position and velocity in represents the derivative of position with respect to time, represents the derivative of velocity with respect to time, r a is the coordinate system of the lander in the celestial body ∑ a The position in From ∑ l to∑ a The coordinate transformation matrix, l is from ∑ a From the origin to ∑ l The vector of the origin, ω = [0, 0, ω] T is the rotational angular velocity vector of the small celestial body, g a =[g x , g y , g z ] T Yes a The gravitational acceleration of the lower lander, a cl Yes l The control acceleration applied to the lander.
[0021] As a preferred solution of the landing trajectory planning method based on the terrain obstacle convex hull error model of the present invention, the landing obstacle avoidance trajectory planning includes combining the maximum collision probability as the repulsive potential based on the artificial potential field method, and the gravitational potential function is expressed as a quadratic function containing the current and target states:
[0022] φ p (x)=(xx t ) T p(xx t )
[0023] Where x = [x, y, z, v x , v y , v z ] represents the position and velocity variables of the lander at any time, x t is the target state, P = diag(P1, P2, P3, P4, P5, P6) is a positive definite matrix;
[0024] The maximum collision probability between the lander and the obstacle is expressed as a repulsive potential function:
[0025]
[0026] Among them, k i is the weight coefficient of the ith obstacle, and the overall potential function φ(x) is defined as:
[0027] φ(x)=φ p (x)+φ h (x)
[0028] According to Lyapunov's stability law, the derivative of φ(x) with respect to time is set to It is expressed as:
[0029]
[0030] get:
[0031]
[0032] Where v is the velocity of the lander, M = diag (m1, m2, m3) is a positive definite matrix, and a is the final control acceleration, which is divided into gravitational acceleration a p and repulsive acceleration a q Two parts, expressed as:
[0033]
[0034]
[0035] a=a p +a q
[0036] Where i = 1, ..., n, P r =diag(P1, P2, P3) is the first three items in P related to position, P v =diag(P4, P5, P6) is the last three items in P related to speed, g l =∑ l The gravitational acceleration on the lower lander.
[0037] Another object of the present invention is to provide a terrain data error modeling system to accurately represent the geometric characteristics and error distribution range of terrain obstacles of different forms, and a landing trajectory planning method that takes into account the lander position and terrain data errors. This method aims to enhance the autonomy and accuracy of landing trajectory planning by establishing a three-dimensional convex hull model of terrain obstacles and errors and improving the ability to understand the environment. These technical means jointly improve the reliability and success rate of the deep space probe landing process, and provide important technical support for future deep space exploration missions.
[0038] In order to solve the above technical problems, the present invention provides the following technical solutions: a landing trajectory planning system based on a terrain obstacle convex hull error model, comprising: a convex hull construction module, an error calculation module and an error range module;
[0039] The convex hull construction module generates a convex hull model based on the three-dimensional point cloud data of the obstacle using a random incremental algorithm. The convex hull model can effectively describe the overall shape of the obstacle.
[0040] The error calculation module analyzes the measured point cloud data using the Jacobian matrix and the propagation error law to generate a matrix describing the measurement error. These tools help quantify the possible errors in the model and provide a way to propagate the errors.
[0041] The error range module translates the vertices of the convex hull model along the plane normal vector direction of each triangular face to generate uncertain boundary points of the obstacle, and uses these boundary points to regenerate the convex hull model, thereby establishing a model that describes the error range of the obstacle position.
[0042] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the landing trajectory planning method based on the terrain obstacle convex hull error model as described above when executing the computer program.
[0043] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the landing trajectory planning method based on the terrain obstacle convex hull error model as described above.
[0044] The beneficial effects of the present invention are as follows: through the convex hull model, the morphological characteristics of terrain obstacles can be accurately captured, and the errors of terrain data can be quantified, thereby providing an accurate terrain information basis for subsequent landing trajectory planning, and providing an error description of the position of terrain obstacles, so that the landing trajectory planning can consider the impact of terrain data errors on safe landing, further improving the landing safety and success rate of the lander, and effectively avoiding terrain obstacles through the artificial potential field method, minimizing the probability of collision between the lander and terrain obstacles, thereby ensuring the safety and success rate of the landing mission. BRIEF DESCRIPTION OF THE DRAWINGS
[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.
[0046] Figure 1 A vertex translation graph of a landing trajectory planning method based on a terrain obstacle convex hull error model provided by an embodiment of the present invention.
[0047] Figure 2 An obstacle error range diagram of a landing trajectory planning method based on a terrain obstacle convex hull error model provided by an embodiment of the present invention.
[0048] Figure 3 A Monte Carlo simulation trajectory diagram of a landing trajectory planning method based on a terrain obstacle convex hull error model provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0049] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.
[0050] Example 1, reference Figure 1-Figure 2 , which is the first embodiment of the present invention, provides a landing trajectory planning method based on a terrain obstacle convex hull error model, comprising:
[0051] S1: Using the 3D point cloud data of obstacles, a random incremental algorithm is used to construct a 3D convex hull model of terrain obstacles.
[0052] It should be noted that the 3D point cloud data includes the original measurement values obtained by the laser sensor, namely the distance l and the angles α and β in the laser measurement coordinate system. The coordinates of the measurement points in the reference coordinate system are expressed as:
[0053]
[0054] S2: For the measured 3D point cloud data, the error matrix is calculated using the Jacobian matrix and the propagation error law.
[0055] It should be noted that the error propagation law includes obtaining the error matrix of the point (X, Y, Z) as:
[0056]
[0057] Among them, K is the Jacobian matrix, D is the covariance matrix of the original measurement value (l, α, β), is the variance in the X direction, is the variance in the Y direction, is the variance in the Z direction, σ X，Y is the covariance between the X and Y directions, σ X，Z is the covariance between the X and Z directions, σ Y，Z is the covariance between the Y and Z directions.
[0058] S3: Translate the vertices of each triangular face on the obstacle convex hull along the direction of their respective plane normal vectors to generate uncertain boundary points of the obstacle. Based on the uncertain boundary points, reuse the three-dimensional convex hull generation algorithm to generate the error range of the obstacle and establish an obstacle error model.
[0059] It should be noted that the obstacle error model includes a triangle point set (P1, P2, P3), and the point position error of the triangle vertex P1 in the normal vector direction of the plane is expressed as:
[0060]
[0061] in, is the normal vector of the triangle, The error matrix of point P1 is represented, and a landing obstacle avoidance trajectory planning method is proposed by combining the obstacle error model and the collision probability model;
[0062] Furthermore, the collision probability model includes representing the position error of the lander with a Gaussian distribution with a mean of zero, modeling the error of each obstacle through the obstacle convex hull model, determining the lander error size and the obstacle error range, and calculating the collision probability between the lander and the obstacle according to the probability that the actual position of the lander is located within the obstacle error range. It is assumed that the probability density value of the lander position is equal inside the obstacle area. By using the probability density value of the point closest to the lander on the obstacle error range as the probability density value of each point in the obstacle area, a maximum collision probability model is established. The calculation formula is expressed as follows:
[0063]
[0064] Where V is the obstacle error range volume, r is the position of the lander, It represents the point closest to the lander within the error range of the obstacle, C is the error matrix of the lander position, and when there are multiple obstacles, the maximum collision probability of the lander is the sum of the maximum collision probabilities of the lander and all terrain obstacles.
[0065] The above is a schematic scheme of the landing trajectory planning method based on the terrain obstacle convex hull error model of this embodiment. It should be noted that the technical scheme of the system of the landing trajectory planning method based on the terrain obstacle convex hull error model and the technical scheme of the landing trajectory planning method based on the terrain obstacle convex hull error model mentioned above belong to the same concept. The details of the technical scheme of the landing trajectory planning system based on the terrain obstacle convex hull error model in this embodiment that are not described in detail can all be referred to the description of the technical scheme of the landing trajectory planning method based on the terrain obstacle convex hull error model mentioned above.
[0066] The landing trajectory planning system based on the terrain obstacle convex hull error model in this example includes: a convex hull construction module, an error calculation module, and an error range module;
[0067] The convex hull construction module generates a convex hull model based on the three-dimensional point cloud data of the obstacle using a random incremental algorithm. The convex hull model can effectively describe the overall shape of the obstacle.
[0068] The error calculation module analyzes the measured point cloud data using the Jacobian matrix and the propagation error law to generate a matrix describing the measurement error. These tools help quantify the possible errors in the model and provide a way to propagate the errors.
[0069] The error range module translates the vertices of the convex hull model along the plane normal vector direction of each triangular face to generate uncertain boundary points of the obstacle, and uses these boundary points to regenerate the convex hull model, thereby establishing a model that describes the error range of the obstacle position.
[0070] This embodiment further provides a computing device, which is applicable to the case of a landing trajectory planning method based on a terrain obstacle convex hull error model, and includes:
[0071] A memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the landing trajectory planning method based on the terrain obstacle convex hull error model proposed in the above embodiment.
[0072] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the landing trajectory planning method based on the terrain obstacle convex hull error model proposed in the above embodiment is implemented.
[0073] The storage medium proposed in this embodiment and the landing trajectory planning method based on the terrain obstacle convex hull error model proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.
[0074] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.
[0075] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.
[0076] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of 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, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.
[0077] Example 2, reference Figure 3 Based on the previous embodiment, this embodiment provides a landing trajectory planning method and system based on a terrain obstacle convex hull error model. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.
[0078] In order to verify the feasibility and robustness of the obstacle error modeling method and landing obstacle avoidance trajectory planning method, 1000 sets of Monte Carlo experiments were carried out.
[0079] Taking the final landing stage in the complex terrain area on the moon as the background, the parameter settings in the fixed coordinate system of the landing point are shown in Table 1. Considering the limitation of the lander engine thrust, the maximum control acceleration of the three axes is set to a max =0.05m / s 2 , the frequency of the instruction is 1Hz.
[0080] Table 1 Boundary conditions and control parameter settings
[0081]
[0082] The sizes of different types of uncertainty are shown in Table 2, and the following are obtained: Figure 3 1000 trajectories shown.
[0083] Table 2 Uncertainty of each variable
[0084]
[0085] During the landing process, the overall obstacle avoidance success rate of the obstacle avoidance method based on maximum collision probability was 100%, indicating that this method has good robustness under the condition of uncertainty in the positions of the lander and obstacles.
[0086] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.
Claims
1. A landing trajectory planning method based on a terrain obstacle convex hull error model, characterized in that: include: Using the 3D point cloud data of obstacles, a random incremental algorithm is used to construct a 3D convex hull model of terrain obstacles; For the measured 3D point cloud data, the error matrix is calculated using the Jacobian matrix and propagation error law; The vertices of each triangular face on the obstacle convex hull are translated along the direction of their respective plane normal vectors to generate the uncertain boundary points of the obstacle. Based on the uncertain boundary points, the three-dimensional convex hull generation algorithm is reused to generate the error range of the obstacle and establish the obstacle error model.
2. The landing trajectory planning method based on the terrain obstacle convex hull error model according to claim 1, characterized in that: The three-dimensional point cloud data includes the original measurement values obtained by using the laser sensor, namely the distance l and the angles α and β in the laser measurement coordinate system, and the coordinates of the measurement points in the reference coordinate system are expressed as:
3. The landing trajectory planning method based on the terrain obstacle convex hull error model according to claim 2, characterized in that: The error propagation law includes obtaining the error matrix of the point (X, Y, Z) as: Among them, K is the Jacobian matrix, D is the covariance matrix of the original measurement value (l, α, β), is the variance in the X direction, is the variance in the Y direction, is the variance in the Z direction, σ X,Y is the covariance between the X and Y directions, σ X,Z is the covariance between the X and Z directions, σ Y,Z is the covariance between the Y direction and the Z direction; the uncertain boundary points are generated by translating along the directions of the respective plane normal vectors; the obstacle error model is established by reusing the 3D convex hull model generation algorithm and the obstacle error range according to the generated points.
4. The landing trajectory planning method based on the terrain obstacle convex hull error model as claimed in claim 3, characterized in that: The obstacle error model includes a triangular point set (P1, P2, P3), and the point position error of the triangle vertex P1 in the normal vector direction of the plane is expressed as: in, is the normal vector of the triangle, The error matrix representing point P1 is combined with the collision probability model to implement the landing trajectory planning method.
5. The landing trajectory planning method based on the terrain obstacle convex hull error model according to claim 4, characterized in that: The collision probability model includes using the probability density value of the point closest to the lander within the obstacle error range as the probability density value of each point in the obstacle area to establish a maximum collision probability model. The calculation formula is expressed as: Where V is the obstacle error range volume, r is the position of the lander, It represents the point closest to the lander within the error range of the obstacle, and C is the error matrix of the lander position. When there are multiple obstacles, the maximum collision probability of the lander is the sum of the maximum collision probabilities of the lander and all terrain obstacles. Based on the artificial potential field method, the landing obstacle avoidance trajectory planning is realized.
6. The landing trajectory planning method based on the terrain obstacle convex hull error model according to claim 5, characterized in that: The artificial potential field method includes establishing a dynamic model, determining the fixed coordinate system ∑ l The equation of motion in is expressed as: Among them, r l and v l The lander is l The position and velocity in represents the derivative of position with respect to time, represents the derivative of velocity with respect to time, r a is the coordinate system of the lander in the celestial body ∑ a The position in From ∑ l to∑ a The coordinate transformation matrix, l is from ∑ a From the origin to ∑ l The vector of the origin, ω=[0,0,ω] T is the rotational angular velocity vector of the small celestial body, g a =[g x ,g y ,g z ] T Yes a The gravitational acceleration of the lower lander, a cl Yes l The control acceleration applied to the lander.
7. The landing trajectory planning method based on the terrain obstacle convex hull error model according to claim 6, characterized in that: The landing obstacle avoidance trajectory planning includes an artificial potential field method, combining the maximum collision probability as the repulsive potential, and the gravitational potential function is expressed as a quadratic function including the current and target states: φ p (x)=(x-x t ) T p(x-x t ) Where x = [x, y, z, v x ,v y ,v z ] represents the position and velocity variables of the lander at any time, x t is the target state, P = diag(P1, P2, P3, P4, P5, P6) is a positive definite matrix; The maximum collision probability between the lander and the obstacle is expressed as a repulsive potential function: Among them, k i is the weight coefficient of the ith obstacle, and the overall potential function φ(x) is defined as: φ(x)=φ p (x)+φ h (x) According to Lyapunov's stability law, the derivative of φ(x) with respect to time is set to It is expressed as: get: Where v is the velocity of the lander, M = diag (m1, m2, m3) is a positive definite matrix, and a is the final control acceleration, which is divided into gravitational acceleration a p and repulsive acceleration a q Two parts, expressed as: a=a p +a q Where i = 1,…,n, P r =diag(P1,P2,P3) is the first three items in P related to position, P v =diag(P4,P5,P6) is the last three items in P related to speed, g l =∑ l The gravitational acceleration on the lower lander.
8. A system based on the landing trajectory planning method based on the terrain obstacle convex hull error model according to any one of claims 1 to 7, characterized in that: include: Convex hull construction module, error calculation module and error range module; The convex hull construction module generates a convex hull model based on the three-dimensional point cloud data of the obstacle using a random incremental algorithm. The convex hull model can effectively describe the overall shape of the obstacle. The error calculation module analyzes the measured point cloud data using the Jacobian matrix and the propagation error law to generate a matrix describing the measurement error. These tools help quantify the possible errors in the model and provide a way to propagate the errors. The error range module translates the vertices of the convex hull model along the plane normal vector direction of each triangular face to generate uncertain boundary points of the obstacle, and uses these boundary points to regenerate the convex hull model, thereby establishing a model that describes the error range of the obstacle position.
9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the landing trajectory planning method based on the terrain obstacle convex hull error model described in any one of claims 1 to 7 are implemented.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the landing trajectory planning method based on the terrain obstacle convex hull error model described in any one of claims 1 to 7 are implemented.