A general highway slope inspection route rapid determination method and device

Abstract

This invention belongs to the field of geotechnical engineering technology and provides a general method and device for rapidly determining the inspection route of highway slopes. The method includes determining the set of base points and the set of feature points for UAV inspection; determining the shortest inspection route based on the spatial distribution of the base point set and the feature point set; and finally determining the route direction by vectorizing the shortest inspection route. This invention effectively improves the efficiency and accuracy of highway slope inspections through systematic inspection point selection and scientific route planning.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering technology, specifically to a general method and device for rapidly determining the route of highway slope inspection. Background Technology

[0002] The current selection of inspection points in the drone inspection routes for highway slopes lacks a systematic approach, leading to problems such as incomplete inspection coverage, duplicate inspections, and wasted resources. The planning of inspection routes mostly relies on human experience and lacks scientific algorithm support, making it difficult to achieve the optimal path, resulting in longer inspection ranges, increased energy consumption, and higher inspection costs. The existing inspection route planning does not adequately consider the importance of key components such as drainage works, slope protection, and reinforcement projects, while the different states of these key components have a significant impact on slope stability and traffic safety.

[0003] To address the aforementioned issues, a general method for rapidly determining highway slope inspection routes is proposed. By clearly classifying basic and feature points and establishing unified selection criteria, the consistency and accuracy of inspections are improved. A shortest path algorithm automatically determines all basic and feature points, the shortest path connection method, and the optimal route direction, thereby significantly reducing travel distance and energy consumption while ensuring inspection effectiveness, achieving scientific route planning and improved inspection efficiency. Through systematic inspection point selection and scientific route planning, the efficiency and accuracy of inspections are effectively improved. This method is also versatile and applicable to various slope types, including rock, soil, and mixed rock-soil slopes, making it highly valuable for application and promotion. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a general method and apparatus for rapidly determining highway slope inspection routes, which effectively improves the efficiency and accuracy of inspections through systematic selection of inspection points and scientific route planning.

[0005] A general method for rapidly determining the inspection route for highway slopes includes:

[0006] Determine the set of base points and the set of feature points for drone inspection;

[0007] The shortest inspection route is determined based on the spatial distribution of the base point set and the feature point set.

[0008] By vectorizing the shortest inspection route, the direction of the shortest inspection route is determined.

[0009] Furthermore, the set of basic points for drone inspections includes:

[0010] Determine the equation of the slope profile curve;

[0011] By combining the contour curve equation, the target constraint function for the initial base points is constructed;

[0012] Determine the initial set of base points based on the initial base point objective constraint function;

[0013] Based on the initial set of base points, the set of base points is determined by filtering.

[0014] Furthermore, based on the initial base point objective constraint function, the initial base point set is determined, including:

[0015] The initial set of base points is determined using the method shown in the following formula, based on the initial base point objective constraint function:

[0016]

[0017] in, Let C represent the initial set of base points, C represent the shortest distance from each point on the slope profile to the initial base points, and λ represent the weighting coefficient. This represents the coordinates of the i1th initial base point. This represents the coordinates of j1 initial base points. and The coordinates of adjacent initial base points, d represents the average position of the initial base point. min and d max x represents the minimum and maximum distances between adjacent initial base point coordinates. amin and x amax The minimum and maximum values ​​of y represent the horizontal range of the slope profile. amin and y amax These represent the minimum and maximum values ​​of the vertical range of the slope profile. and Represents the x and y coordinates of the i1th initial base point. δ is the convergence threshold.

[0018] Furthermore, the set of feature points for drone inspection includes:

[0019] Determine the surface continuity function of the slope;

[0020] Calculate the surface curvature and gradient of the slope based on the surface continuity function of the slope.

[0021] The initial set of feature points is determined based on the surface curvature and gradient of the slope.

[0022] Based on the initial set of feature points, the set of feature points is determined by filtering.

[0023] Furthermore, the slope surface curvature and slope surface gradient are calculated based on the slope surface continuity function, including:

[0024] The surface curvature of the slope is calculated using the following formula:

[0025]

[0026] Where K is the surface curvature of the slope; f to x b y b First-order partial derivative, x b Represents the x-coordinate, y b Represents the ordinate; These are the second-order partial derivatives, and f is the slope continuity function;

[0027] The slope surface gradient is calculated using the following formula:

[0028]

[0029] in, Indicates the slope surface gradient; The continuous function f of the slope with respect to x b y b The partial derivatives of .

[0030] Furthermore, based on the slope surface curvature and slope surface gradient, an initial set of feature points is determined, including:

[0031] Based on the surface curvature and gradient of the slope, determine the minimum point of the surface curvature modulus and the maximum point of the surface gradient modulus.

[0032] The following formula is used to determine the minimum point of the slope surface curvature modulus and the maximum point of the slope surface gradient modulus based on the slope surface curvature and slope surface gradient:

[0033]

[0034] in, This represents the point where the curvature modulus of the slope surface reaches its minimum. This represents the point where the gradient modulus on the slope surface reaches its maximum value. Denotes the Laplace operator, (x b ,y b () represents the coordinates of the initial feature point;

[0035] The initial set of feature points is determined based on the minimum point of the curvature modulus and the maximum point of the gradient modulus of the slope surface.

[0036] Furthermore, the shortest inspection route is determined based on the spatial distribution of the base point set and the feature point set, including:

[0037] Construct a weighted graph model based on the set of base points and the set of feature points;

[0038] Construct a mathematical model of the traveling salesman based on the weighted graph model;

[0039] Based on the traveling salesman mathematical model, output the shortest inspection route.

[0040] Furthermore, a mathematical model of the traveling salesman is constructed based on the weighted graphical model, including:

[0041] Constructing a mathematical model for the traveling salesman:

[0042]

[0043] Where n represents the total number of vertices in the weighted graph model, w ij x represents the weight of the edge connecting vertices i and j. ij Let x be the decision variable, representing whether vertex i to vertex j is on the path; V represents the vertex set in the weighted graph model, and S represents a proper subset of vertex set V, containing at least two vertices; x 1n =1, meaning starting from vertex v1 and returning to v1.

[0044] Furthermore, by vectorizing the shortest inspection route, the route direction is determined, including:

[0045] Vectorize the shortest inspection route and determine the angle between adjacent vectors;

[0046] The constraints on the flight path direction are determined based on the angle between adjacent vectors.

[0047] Based on the constraints of the route direction, determine the route direction of the shortest inspection route.

[0048] A general-purpose device for rapidly determining highway slope inspection routes includes a first determining unit, a second determining unit, and a third determining unit, wherein:

[0049] The first determining unit is used to determine the set of base points and the set of feature points for UAV inspection;

[0050] The second determining unit is used to determine the shortest inspection route based on the spatial distribution of the base point set and the feature point set.

[0051] The third determining unit is used to determine the route direction of the shortest inspection route by vectorizing the shortest inspection route.

[0052] The beneficial effects of this invention are:

[0053] (1) By clearly defining the basic points and feature points and formulating a unified selection standard, this invention can improve the consistency and accuracy of inspections; and this invention uses the shortest path algorithm to automatically determine all basic points and feature points, the shortest inspection route and the optimal route direction, thereby significantly reducing the flight distance and energy consumption while ensuring the inspection effect, and realizing the scientific planning of inspection routes and the improvement of inspection efficiency.

[0054] (2) This invention effectively improves the efficiency and accuracy of inspections through systematic selection of inspection points and scientific route planning. This invention is also versatile and can be applied to various types of slopes such as rock, soil and rock-soil mixture, and has great application and promotion value. Attached Figure Description

[0055] To more clearly illustrate the specific embodiments of the present invention, the accompanying drawings used in the description of the specific embodiments or prior art will be briefly introduced below. In all the drawings, the elements or parts are not necessarily drawn to scale.

[0056] Figure 1 A flowchart illustrating a general method for rapidly determining highway slope inspection routes, provided in an embodiment of the present invention;

[0057] Figure 2 This is a schematic diagram of the basic skeleton structure of an inspection route network provided in an embodiment of the present invention. Detailed Implementation

[0058] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0059] It should be noted that, unless otherwise stated, the technical or scientific terms used in this application should have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0060] In one embodiment, a general method for rapidly determining highway slope inspection routes is provided, including:

[0061] 1. Determine the set of basic points and the set of feature points for drone inspection;

[0062] like Figure 2 As shown, the inspection points in the drone inspection route for highway slopes are divided into basic points and feature points. The basic points form the basic framework of the inspection route network, ensuring that the drone can inspect and cover all corners of the slope. Basic points are usually located at key locations on the slope, such as the top, bottom, and turning points, to form a comprehensive inspection network for the slope.

[0063] Feature points are set for specific structures or affected areas on a slope, such as drainage ditches, retaining walls, cracks, and landslides. The purpose of setting feature points is to identify and assess potential risks to the slope in a timely manner through detailed observation of key areas.

[0064] This invention mainly uses the shortest path to connect all base points and feature points without repetition to form the shortest inspection route, and finally determines the route direction by vectorizing the shortest inspection route.

[0065] (1) Preferably, the set of basic points for UAV inspection is determined, including:

[0066] 1) Determine the equation of the slope profile curve:

[0067] Optionally, let the equation of the slope profile curve be y. a =f a (x a ), where x a y is the horizontal distance a This represents the vertical height. This curve equation is used to quantify the slope outline and the coordinates of the foundation points; that is, given the x-coordinate of the foundation point, the y-coordinate can be determined using the curve equation.

[0068] The purpose of setting the curve equation is to quantify the slope outline, making it easier to determine the coordinates of any point on the slope outline;

[0069] Specifically, establish a coordinate system parallel to the slope surface. This coordinate system takes the location of the left toe of the slope outline as the origin. The horizontal distance and vertical height of each base point can be obtained through the height and width of the slope (that is, the coordinates of each base point are obtained, where the horizontal distance refers to the x-coordinate of the base point and the vertical height refers to the y-coordinate of the base point).

[0070] 2) Based on the contour curve equation, construct the initial base point target constraint function, including:

[0071] ① Construct initial base point constraints by combining the contour curve equation;

[0072] Optionally, the initial base point constraints include the distance constraints between adjacent base points, the slope outline constraints, the horizontal distance constraints, and the vertical height constraints.

[0073] Specifically, the horizontal distance constraint is represented by the following formula:

[0074]

[0075] x amin and x amax These represent the minimum and maximum values ​​of the horizontal range of the slope profile. This represents the x-coordinate of the i1th initial base point.

[0076] The vertical height constraint is characterized by the following formula:

[0077]

[0078] y amin and y amax These represent the minimum and maximum values ​​of the vertical range of the slope profile. This represents the ordinate of the i1th initial base point.

[0079] The distance constraint between adjacent base points is represented by the following formula:

[0080]

[0081] in, and For adjacent initial base points, d min and d max This represents the minimum and maximum distances between adjacent initial base point coordinates.

[0082] The slope outline constraint is represented by the following formula:

[0083]

[0084] Where C is a function that constrains the selected initial base points to the slope outline, and x a f(x) represents the horizontal position of the initial foundation point on the slope profile. a () indicates that the initial foundation point is located horizontally at position x on the slope profile. a Vertical height at x amax and x amin These represent the maximum and minimum values ​​that the initial base point can take within the horizontal range of the slope profile, respectively. This means taking the point closest to the slope outline as the initial base point i1. The initial base point is closest to the slope outline only when it is located on the slope outline line, that is, the initial base point and the slope outline line coincide. This represents the horizontal distance integral over the base point i1.

[0085] ② Construct the objective function for the basic points based on the initial constraints;

[0086] Preferably, the objective function for the basic points is represented by the following formula:

[0087]

[0088] in, Let C represent the initial set of base points, C represent the shortest distance from each point on the slope profile to the initial base points, and λ represent the weighting coefficient. Represents the coordinates of any initial base point i1. This represents the average position of the initial base point.

[0089] ③ Combine the initial basic point constraints and the basic point objective function to construct the initial basic point objective constraint function.

[0090] 3) Determine the initial set of base points based on the initial base point objective constraint function;

[0091] Optionally, the initial set of base points is determined based on the following initial base point objective constraint function:

[0092]

[0093] in, Let C represent the initial set of base points, C represent the shortest distance from each point on the slope profile to the initial base points, and λ represent the weighting coefficient. This represents the coordinates of the i1th initial base point. This represents the coordinates of j1 initial base points. and For adjacent initial base points, d represents the average position of the initial base point. min and d max x represents the minimum and maximum distances between adjacent initial base point coordinates. amin and x amax The minimum and maximum values ​​of y represent the horizontal range of the slope profile. amin and y amax These represent the minimum and maximum values ​​of the vertical range of the slope profile. and Represents the x and y coordinates of the i1th initial base point. δ is the convergence threshold.

[0094] 4) Based on the initial set of base points, filter and determine the set of base points.

[0095] Preferably, based on the initial set of base points, the set of base points is selected and determined, including:

[0096] ① Determine the number of foundation points based on the length of the slope outline and the average spacing of the preset foundation points;

[0097] Preferably, the number of foundation points is determined using the method shown in the following formula, based on the length of the slope outline and the average spacing between preset foundation points:

[0098]

[0099] Where n is the number of base points, L is the length of the slope outline, and d avg The average spacing between preset base points.

[0100] ② Determine the coordinates of the base points based on the number of base points and the initial set of base points;

[0101] Here, we need to select the coordinates of base points that meet the required number of base points from the initial set of base points. This can be done manually.

[0102] For example, suppose the initial set of foundation points includes 100 initial foundation points, but n is calculated to be 50 based on the slope outline length and the preset average spacing between foundation points. A manual screening method can be chosen to filter the 100 initial foundation points according to the target of 50 foundation points, thereby determining the coordinates of the 50 foundation points.

[0103] When some base points are invalid or their selection affects the flight path, the base points can be optimized.

[0104] Preferably, the following formula is used to optimize the base points:

[0105]

[0106] Where η is the learning rate and k is the number of iterations; and For the k-th iteration and the (k+1)-th iteration, respectively Point coordinates.

[0107] The set of all the selected base points is the base point set.

[0108] (2) Determine the set of feature points for UAV inspection, including:

[0109] 1) Determine the surface continuity function of the slope;

[0110] Here, a coordinate system perpendicular to the slope surface is established. Each point in this coordinate system corresponds to a slope height. Specifically, let z = f(x) b ,y b ), representing the slope surface height as a function of the plane coordinate (x, y). b ,y b f is a function that changes over time, where f is a continuous function of the slope.

[0111] 2) Calculate the surface curvature and gradient of the slope based on the surface continuity function of the slope; including:

[0112] ① Preferably, the surface curvature of the slope is calculated using the following formula:

[0113]

[0114] Where K is the surface curvature of the slope; f to x b y b The first-order partial derivative of , where x b y is the x-axis. b The vertical axis is used as the coordinate. These are the second-order partial derivatives, and f is the slope continuity function;

[0115] ② The slope surface gradient is calculated using the following formula:

[0116]

[0117] in, Indicates the slope surface gradient; The continuous function f of the slope with respect to x b y b The partial derivatives of .

[0118] 3) Determine the initial set of feature points based on the slope surface curvature and slope surface gradient; including:

[0119] ①Based on the surface curvature and gradient of the slope, determine the minimum point of the surface curvature modulus and the maximum point of the surface gradient modulus;

[0120] The minimum points of the curvature modulus and the maximum points of the gradient modulus of the slope surface are calculated using the following formulas:

[0121]

[0122] in, This represents the point where the curvature modulus of the slope surface reaches its minimum. This represents the point where the gradient modulus on the slope surface reaches its maximum value. Let f(x) represent the Laplace operator. b ,y b ) represents the surface continuity function of the slope, (x b ,y b () represents the initial feature point;

[0123] ② Determine the initial feature points based on the minimum point of the curvature modulus of the slope surface and the maximum point of the gradient modulus of the slope surface.

[0124] The set of all minimum points of the curvature modulus and maximum points of the gradient modulus of the slope surface constitutes the initial set of feature points.

[0125] 4) Based on the initial set of feature points, filter and determine the final set of feature points. This includes:

[0126] ① Calculate the distance between any two points in the initial set of feature points using the geometric distance formula;

[0127] Preferably, the geometric distance between any two initial feature points is calculated using the following formula:

[0128]

[0129] in, This represents the geometric distance between initial feature points. and Represents the x-coordinates of the i2th and j2th initial feature points. and Represents the ordinates of the i2th and j2th initial feature points.

[0130] ② Calculate the gradient similarity between any two points in the initial feature point set according to the gradient similarity formula;

[0131] Preferably, the gradient similarity between any two initial feature points is calculated using the following formula:

[0132]

[0133] in, and These represent the initial feature points. and The slope gradient vector at the location; express and The similarity between two slope gradients is between 0 and 1. When the gradient vectors of the two initial feature points are exactly the same, the similarity is 1; when the gradient vectors of the two initial feature points are perpendicular, the similarity is 0.

[0134] ③ Based on the distance between any two points in the initial feature point set and the gradient similarity between any two points in the initial feature point set, the feature point set is selected and determined.

[0135] All initial feature points in the initial feature point set are filtered. Specifically, if the gradient similarity between any two initial feature points is higher than a set similarity threshold S, then... t (Similarity threshold S) t (This is manually set), and the distance between any two initial feature points is less than the set distance threshold d. t (distance threshold d) t (It is artificially set) to indicate that the two feature points are actually different representations of the same physical feature (e.g., small displacements due to noise or calculation errors). Select one of the initial feature points as the feature point and delete the other, thereby completing the screening of all initial feature points and determining the feature point set.

[0136] If some feature points fail or their selection affects the flight path, the feature points can be optimized.

[0137] Preferably, the feature points are optimized using the following formula:

[0138]

[0139] In the formula, η is the learning rate, k is the number of iterations, and L is the loss function. and For the k-th iteration and the (k+1)-th iteration, respectively Point coordinates.

[0140] The set of all selected feature points is called the feature point set.

[0141] 2. Determine the shortest inspection route based on the spatial distribution of the base point set and the feature point set;

[0142] Preferably, the shortest inspection route is determined based on the spatial distribution of the base point set and the feature point set, including:

[0143] (1) Construct a weighted graph model based on the set of base points and the set of feature points;

[0144] The base points and feature points are considered as vertices in a weighted graph, and the direct connection between two vertices is considered as an edge in the graph. The weight of the edge is defined as the vertex set V containing all the points that need to be connected.

[0145] Let the vertex set V = {v1, v2, ..., v} n}, where vi represents the i-th vertex (vertices include base points or feature points).

[0146] Edge set E = {(v i v j w ij )|v i v j ∈V, i≠j} is used to describe the connection relationship between points, where vi represents the i-th vertex in the weighted graph model, v j Let w represent the j-th vertex in the weighted graph model. ij The weight of the edge connecting vertices i and j is represented by the weight function w: E→R. + ,satisfy Used to describe the cost of a connection; adjacency matrix A = [a ij ], where a ij =w(v i v j ), (v i v j If i = j, a ∈ E, ij =0, otherwise a ij =∞; Degree matrix D = diag[d1, d2, ..., d... n ],in The degree matrix is ​​a diagonal matrix, and the elements on the diagonal correspond to the degree of each vertex in the weighted graph model (i.e., the number of edges that are directly connected to that vertex); the adjacency matrix A and the degree matrix D are important representations of the weighted graph model and are used for subsequent algorithm processing.

[0147] (2) Construct a mathematical model of the traveling salesman based on the weighted graph model;

[0148] Preferably, a mathematical model of the traveling salesman is constructed by combining a weighted graphical model:

[0149]

[0150] Where n represents the total number of vertices in the weighted graph model, w ij x represents the weight of the edge connecting vertices i and j. ij Let x be the decision variable, representing whether vertex i to vertex j is on the path; V represents the vertex set in the weighted graph model, and S represents a proper subset of vertex set V, containing at least two vertices; x 1n =1, meaning starting from vertex v1 and returning to v1.

[0151] Specifically, the objective function in the traveling salesman mathematical model is:

[0152]

[0153] x ij Let x be the decision variable, representing whether vertex i to vertex j is on the path, where x ij =1 indicates that on the path, x ij =0 indicates that it is not on the path.

[0154] The constraints are:

[0155] This means that each vertex is visited exactly once;

[0156] This means that each vertex leaves exactly once;

[0157] ∑ i∈S ∑ j∈S,j≠i x ij ≤|S-1, 2≤|S|≤n-1 indicates sub-cycle elimination, used to prevent the formation of sub-cycles, where S is a proper subset of the vertex set V and contains at least two vertices.

[0158] x 1n =1 indicates that the starting point is the same constraint, starting from vertex v1 and returning to v1.

[0159] (3) Determine the shortest inspection route based on the traveling salesman mathematical model.

[0160] Specifically, the traveling salesman mathematical model is solved by combining linear programming relaxation and integer programming. That is, the problem is first relaxed by linear programming to obtain fractional solutions, and then integer programming is used to transform it into integer solutions.

[0161] Relaxing the objective function in linear programming: Where c ij =w ij ;

[0162] The relaxed constraints are the same as those in the traveling salesman mathematical model.

[0163] The objective function and constraints of integer programming are the same as those of relaxed linear programming, but the decision variable x is different. ij It must be an integer (0 or 1).

[0164] Let the solution space of integer programming be X, the initial solution set be X0 = X, and the upper bound of the objective value be Z. u =+∞, lower bound Z l =-∞.

[0165] The branch and bound method is used to approximate the optimal solution by continuously narrowing the solution space. The process is as follows:

[0166] ① Select a fractional solution x* obtained from solving a linear programming problem, and calculate the target value Z* of the corresponding integer programming problem;

[0167] ②If Z*>Z l And Z* < Z u Then update Z l =Z*;

[0168] ③ Based on the fractional part of x*, choose a variable x. ij The problem branches out, generating two subproblems.

[0169] ④ Repeat the above process until an integer solution is found or the stopping condition is met.

[0170] By using linear programming relaxation and integer programming, we can obtain the path with the minimum weight that passes through all inspected points (i.e., vertices) in the traveling salesman mathematical model, which corresponds to the objective function. This path is the one between two points x that are visited only once while satisfying all constraints. ij =1, and the w of the entire route ij Minimum.

[0171] The output shortest inspection route includes the order in which each point is passed and the corresponding weight of each edge.

[0172] 3. Determine the route direction based on the shortest inspection route. This includes:

[0173] (1) Vectorize the shortest inspection route and determine the angle between adjacent vectors;

[0174] use Let represent the vector between adjacent inspection points along the shortest inspection route determined above; then the angle between adjacent vectors along the route is .

[0175]

[0176] Where, θ k It is the angle between adjacent vectors in the flight path. This represents the vector between adjacent inspection points in the k-th group. This represents the vector between k-1 adjacent inspection points. denoted by , where arccos is the inverse cosine function.

[0177] (2) Determine the constraints on the route direction based on the angle between adjacent vectors;

[0178] Using the smoothing function θ s,k =Smooth(θ) k ) for the included angle θ k Smoothing is performed, θ s,k The angle after smooth adjustment;

[0179] According to θ g,k =argmin θ (θ-θ s,k ) 2 +γE(θ) is used for orientation optimization, where γ is a weighting coefficient, E(θ) is the energy consumption of the UAV at the orientation angle θ, and θ g,k The optimized included angle; argmin θ This means that the expression (θ-θ) s,k ) 2 The value of the variable when it reaches its minimum value.

[0180] according to Adjust the direction, among which The adjusted direction vector;

[0181] according to Update the set of route direction vectors, where P is the updated set of route direction vectors and N is the number of inspection points.

[0182] The determination of the flight path direction is subject to the following constraints:

[0183] Ensure the drone operates within the permitted flight speed range:

[0184] Ensure the drone is within the permissible flight angle range: θ min ≤θ g，k ≤θ max

[0185] Among them, v min and v max This indicates the maximum and minimum permitted flight speeds for the drone in the corresponding area; for some areas, this is determined according to regulations, and for others, it is determined based on the drone's performance. θ min and θ max This indicates the minimum and maximum turning angles that the drone can achieve while ensuring it flies along the designated route, obtained through flight testing.

[0186] (3) Determine the route direction of the shortest inspection route based on the constraints of the route direction.

[0187] Finally, the global optimal algorithm is used to solve for the globally optimal direction that satisfies the constraints, and the following results are obtained: This represents the final route direction determined after optimization, which is an inspection route containing N inspection points connected by N-1 connecting lines. Starting from the angle between the direction vectors of the initial connecting line and its adjacent subsequent connecting lines, it is ensured that the angle between all adjacent direction vectors and the vector between adjacent inspection points simultaneously satisfy "the UAV is within the allowable flight speed range and the UAV is within the allowable flight angle range". The corresponding direction is the route direction.

[0188] This invention proposes a universal method and device for rapidly determining inspection routes for highway slopes. By clearly defining basic points and feature points and establishing unified selection criteria, the consistency and accuracy of inspections can be improved. Furthermore, this invention utilizes a shortest path algorithm to automatically determine all basic points and feature points, the shortest inspection route, and the optimal route direction. This significantly reduces travel distance and energy consumption while ensuring inspection effectiveness, achieving scientific planning of inspection routes and improved inspection efficiency. In summary, this invention effectively improves the efficiency and accuracy of inspections through systematic inspection point selection and scientific route planning. The method and device are also versatile and applicable to various types of slopes, including rock, soil, and mixed rock-soil slopes, making them highly valuable for application and promotion.

[0189] In one embodiment, a general-purpose highway slope inspection route rapid determination device is also provided, including a first determination unit, a second determination unit, and a third determination unit, wherein:

[0190] The first determining unit is used to determine the set of base points and the set of feature points for UAV inspection;

[0191] The second determining unit is used to determine the shortest inspection route based on the spatial distribution of the base point set and the feature point set.

[0192] The third determining unit is used to determine the route direction of the shortest inspection route by vectorizing the shortest inspection route.

[0193] Numerous specific details are set forth in this specification. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0194] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0195] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A general method for rapidly determining the inspection route for highway slopes, characterized in that, include: Determine the set of base points and the set of feature points for drone inspection; The base points form the basic framework of the inspection route network, ensuring that the drone can inspect and cover all corners of the slope; the base points are located at key locations on the slope, including the top, bottom, and turning points. The feature points are set for specific structures or diseased areas on the slope, including drainage ditches, retaining walls, cracks, and landslides; The set of basic points for determining drone inspection includes: Determine the equation of the slope profile curve; The equation of the slope profile curve is determined using the following formula: y a =f a (x a ) Where, x a y is the horizontal distance a Vertical height; By combining the contour curve equation, the target constraint function for the initial base points is constructed; Determine the initial set of base points based on the initial base point objective constraint function; Based on the initial set of base points, the set of base points is determined by filtering. The set of feature points for determining drone inspection includes: Determine the surface continuity function of the slope; Calculate the surface curvature and gradient of the slope based on the surface continuity function of the slope. The initial set of feature points is determined based on the surface curvature and gradient of the slope. Based on the initial set of feature points, the set of feature points is then determined through filtering. The shortest inspection route is determined based on the spatial distribution of the set of base points and the set of feature points. By vectorizing the shortest inspection route, the direction of the shortest inspection route is determined.

2. The method for rapidly determining a general-purpose highway slope inspection route as described in claim 1, characterized in that, Based on the contour curve equation, the initial base point objective constraint function is constructed, including: By combining the contour curve equation, the initial basic point constraints are constructed; The initial base point constraints include adjacent base point distance constraints, slope outline constraints, horizontal distance constraints, and vertical height constraints. The horizontal distance constraint is characterized by the following formula: in, and These represent the minimum and maximum values ​​of the horizontal range of the slope profile. This represents the x-coordinate of the i1th initial base point; The vertical height constraint is characterized by the following formula: and These represent the minimum and maximum values ​​of the vertical range of the slope profile. This represents the ordinate of the i1th initial base point; The distance constraint between adjacent base points is represented by the following formula: in, and For adjacent initial base points, =( , ), =( , ), and This represents the minimum and maximum distances between adjacent initial base point coordinates; The slope outline constraint is characterized by the following formula: Where C is a function that constrains the selected initial base points to the slope outline. This indicates the horizontal position of the initial foundation point on the slope profile. This indicates that the initial foundation point is located horizontally on the slope profile. Vertical height at x amax and x amin These represent the maximum and minimum values ​​that the initial base point can take within the horizontal range of the slope profile, respectively. This means taking the point closest to the slope outline as the initial base point i1. The initial base point is closest to the slope outline only when it is located on the slope outline line, that is, the initial base point and the slope outline line coincide. This represents the horizontal distance integral over the base point i1; Based on the initial constraints of the foundation points, a foundation point objective function is constructed, which is characterized by the following formula: in, Let C represent the initial set of base points, and let C represent the shortest distance from each point on the slope profile to the initial base points. Indicates the weighting coefficient. Represents the coordinates of any initial base point i1. This represents the average position of the initial base point; By combining the initial basic point constraints and the basic point objective function, the initial basic point objective constraint function is constructed.

3. The method for rapidly determining a general-purpose highway slope inspection route as described in claim 1, characterized in that, The initial base point objective constraint function is expressed as follows: ， in, Let C represent the initial set of base points, and let C represent the shortest distance from each point on the slope profile to the initial base points. Indicates the weighting coefficient. This represents the coordinates of the i1th initial base point. This represents the coordinates of j1 initial base points. and The coordinates of adjacent initial base points, This represents the average position of the initial base point. and This represents the minimum and maximum distances between adjacent initial base point coordinates. and These represent the minimum and maximum values ​​of the horizontal range of the slope profile. and These represent the minimum and maximum values ​​of the vertical range of the slope profile. and Represents the x and y coordinates of the i1th initial base point. =( , ), where δ is the convergence threshold.

4. The method for rapidly determining a general-purpose highway slope inspection route as described in claim 1, characterized in that, Based on the initial set of feature points, a final set of feature points is determined, including: Calculate the distance between any two points in the initial set of feature points using the geometric distance formula: in, This represents the geometric distance between initial feature points. and Represents the x-coordinates of the i2th and j2th initial feature points. and Represents the ordinates of the i2th and j2th initial feature points; Calculate the gradient similarity between any two points in the initial feature point set using the gradient similarity formula: in, and These represent the initial feature points. and The slope gradient vector at the location; express and The similarity between two slope gradients is between 0 and 1. When the gradient vectors of the two initial feature points are exactly the same, the similarity is 1; when the gradient vectors of the two initial feature points are perpendicular, the similarity is 0. The feature point set is determined by filtering based on the distance between any two points in the initial feature point set and the gradient similarity between any two points in the initial feature point set.

5. The method for rapidly determining a general-purpose highway slope inspection route as described in claim 1, characterized in that, Calculate the surface curvature and gradient of a slope based on its surface continuity function, including: The surface curvature of the slope is calculated using the following formula: Where K is the surface curvature of the slope; f to x b y b First-order partial derivative, x b Represents the x-coordinate, y b Represents the ordinate; , , These are the second-order partial derivatives, and f is the slope continuity function; The slope surface gradient is calculated using the following formula: Where ∇f represents the slope surface gradient; The continuous function f of the slope with respect to x b y b The partial derivatives of .

6. The method for rapidly determining a general-purpose highway slope inspection route as described in claim 5, characterized in that, Initial feature points are determined based on the slope surface curvature and slope surface gradient, including: Based on the surface curvature and gradient of the slope, determine the minimum point of the surface curvature modulus and the maximum point of the surface gradient modulus. The following formula is used to determine the minimum point of the slope surface curvature modulus and the maximum point of the slope surface gradient modulus based on the slope surface curvature and slope surface gradient: in, This represents the point where the curvature modulus of the slope surface reaches its minimum. Represents the point where the gradient modulus of the slope surface reaches its maximum, ∇ 2 Represents the Laplace operator. Represents the coordinates of the initial feature points; Initial feature points are determined based on the minimum point of the curvature modulus and the maximum point of the gradient modulus of the slope surface.

7. The method for rapidly determining a general-purpose highway slope inspection route as described in claim 1, characterized in that, The shortest inspection route is determined based on the spatial distribution of the base point set and the feature point set, including: Construct a weighted graph model based on the set of base points and the set of feature points; Construct a mathematical model of the traveling salesman based on the weighted graph model; Based on the traveling salesman mathematical model, output the shortest inspection route.

8. The method for rapidly determining a general-purpose highway slope inspection route as described in claim 7, characterized in that, The construction of the traveling salesman mathematical model based on the weighted graph model includes: Constructing a mathematical model for the traveling salesman: Where n represents the total number of vertices in the weighted graph model, w ij x represents the weight of the edge connecting vertices i and j. ij Let x be the decision variable, representing whether vertex i to vertex j is on the path; V represents the vertex set in the weighted graph model, and S represents a proper subset of vertex set V, containing at least two vertices; x 1n =1, meaning starting from vertex v1 and returning to v1.

9. The method for rapidly determining a general-purpose highway slope inspection route as described in claim 1, characterized in that, By vectorizing the shortest inspection route, the route direction is determined, including: Vectorize the shortest inspection route and determine the angle between adjacent vectors; The constraints on the flight path direction are determined based on the angle between adjacent vectors. Based on the constraints of the route direction, determine the route direction of the shortest inspection route.

10. A general-purpose device for rapidly determining the route of highway slope inspection, characterized in that, It includes a first determining unit, a second determining unit, and a third determining unit, wherein: The first determining unit is used to determine the set of basic points and the set of feature points for UAV inspection; The base points form the basic framework of the inspection route network, ensuring that the drone can inspect and cover all corners of the slope; the base points are located at key locations on the slope, including the top, bottom, and turning points. The feature points are set for specific structures or diseased areas on the slope, including drainage ditches, retaining walls, cracks, and landslides; The set of basic points for determining drone inspection includes: Determine the equation of the slope profile curve; The equation of the slope profile curve is determined using the following formula: y a =f a (x a ) Where, x a y is the horizontal distance a Vertical height; By combining the contour curve equation, the target constraint function for the initial base points is constructed; Determine the initial set of base points based on the initial base point objective constraint function; Based on the initial set of base points, the set of base points is determined by filtering. The set of feature points for determining drone inspection includes: Determine the surface continuity function of the slope; Calculate the surface curvature and gradient of the slope based on the surface continuity function of the slope. The initial set of feature points is determined based on the surface curvature and gradient of the slope. Based on the initial set of feature points, the set of feature points is then determined through filtering. The second determining unit is used to determine the shortest inspection route based on the spatial distribution of the set of base points and the set of feature points; The third determining unit is used to determine the route direction of the shortest inspection route by vectorizing the shortest inspection route.

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