Skeleton path generation method and system based on triangulation network bidirectional search

Abstract

The invention provides a skeleton path generation method and system based on triangulation network bidirectional search, and relates to the technical field of additive manufacturing, and the method comprises the steps: carrying out the grouping and pairing of a plurality of inner contours and outer contours obtained through the slicing of a three-dimensional model; constructing a constraint Delaunay triangulation network for each group of contours, dividing a connected domain into a plurality of grid triangles, and defining a brother relationship between midpoints of two internal edges in a triangle at least comprising two internal edges; in each constructed triangulation network, any pair of points with a brother relationship is taken as a search starting point, and a skeleton path is adaptively generated according to contour characteristics by adopting a path point bidirectional search algorithm. According to the method, skeleton path generation is carried out on each connected domain through the path point bidirectional search algorithm based on the Delaunay triangulation network, the problems that in the prior art, skeleton extraction efficiency is low, and use conditions are limited are solved, and the additive manufacturability of complex and long and narrow features and thin-wall features is improved through the generated single skeleton path.

Description

Technical Field

[0001] The present disclosure relates to the field of additive manufacturing technology, and in particular to a skeleton path generation method and system based on triangulated network bidirectional search. Background Art

[0002] Additive manufacturing technology, also known as 3D printing technology, is a layered manufacturing technology that forms actual objects by stacking materials layer by layer. The printing path is the key to the additive manufacturing process. For the same model, printing with different paths may produce completely different printing accuracy and efficiency. Whether the path is selected appropriately has a profound impact on the printing efficiency, forming effect, and even the manufacturability of certain features of the parts. At present, the most commonly used paths in the field of additive manufacturing are Z-shaped paths and contour offset paths.

[0003] Narrow or thin-walled features are common structural features of components. At present, additive manufacturing of such features, such as using a Z-shaped path, will produce a large number of short paths and frequent turning points, which is time-consuming and of poor quality; if a contour offset path is used, since the contour offset path is obtained by offsetting inward along the contour of the narrow and long feature, the path fits the shape and direction of the feature contour, and a better forming quality can be obtained. However, the contour offset path also has its limitations, that is, its offset is based on a closed contour, so a closed path is inevitably obtained. This leads to: if the offset distance is given, then for particularly narrow and long features, the offset failure may occur due to the self-intersection of the closed path after the offset, and a reasonable offset path cannot be generated, and this part of the feature cannot be manufactured; if the offset distance is reduced to eliminate the self-intersection and generate a path, since the path needs to "go a circle" along the contour, material accumulation may occur in this area, and the dimensional accuracy of the narrow and long feature cannot be guaranteed. Therefore, the planning method of a single-channel skeleton path for additive manufacturing of narrow or thin-walled features is the key to solving the problem.

[0004] The skeleton is a simplified expression of the topological information of polygonal shapes. Common polygon skeleton extraction methods include the Voronoi diagram method, the angle bisector method and the Delaunay triangulation method. Among them, the Delaunay triangulation method constructs a constrained Delaunay triangulation for polygons. The main skeleton is directly obtained by connecting the midpoints of the mesh edges (or the centroid, incenter, etc. of the triangle). There is no need for tedious pruning operations. You only need to focus on the parallelism of the contours. The more parallel the contours are, the better the skeleton extraction effect will be. Narrow features and thin-walled features generally have good contour parallelism. Therefore, for such features, the skeleton extraction effects of the above three methods are not much different. However, compared with the cumbersome Voronoi diagram method and the angle bisector method, the Delaunay triangulation method has the advantages of simple implementation and efficient execution, so it has been favored by technical personnel.

[0005] The method of extracting skeleton based on Delaunay triangulation mostly uses a binary tree structure to search and store skeleton points. The shortcomings of this type of method are as follows: ① Before searching, it is necessary to specify the endpoints of the skeleton line as the search starting point. Compared with other non-endpoint skeleton points, the number of endpoints is relatively small, and the search requires extra time; ② The search is carried out in a single direction, and the search efficiency is low; ② For narrow and thin-walled structural features, such as rings, closed thin surfaces, etc., their skeletons are theoretically closed and there are no endpoints, so it is difficult to specify the skeleton endpoints. Therefore, the ability to generate closed skeleton paths is poor, and it cannot be used for additive manufacturing of closed narrow and thin-walled structures.

[0006] In summary, the existing Delaunay triangulation skeleton extraction method has low extraction efficiency and limited usage conditions, which affects the additive manufacturability of complex narrow features and thin-walled features. Summary of the invention

[0007] In order to solve the above problems, the present disclosure proposes a skeleton path generation method and system based on triangulated network bidirectional search. Through a bidirectional search algorithm of path points based on Delaunay triangulated network, skeleton paths are generated for each connected domain respectively, so as to solve the problems of low skeleton extraction efficiency and limited usage conditions in the prior art, and the generated single skeleton path is used to improve the additive manufacturability of complex narrow and long features and thin-walled features.

[0008] According to some embodiments, the present disclosure adopts the following technical solutions:

[0009] A skeleton path generation method based on triangulated network bidirectional search, comprising:

[0010] Slice the 3D model to be printed to obtain multiple inner and outer contours, and group and pair the inner and outer contours;

[0011] Construct a constrained Delaunay triangulation for each group of contours, divide the connected domain formed by each group of contours into multiple mesh triangles, classify the triangles according to the number of internal edges, and define the midpoints of the two internal edges of a triangle containing at least two internal edges as siblings.

[0012] In each constrained Delaunay triangulation constructed, a pair of points with a sibling relationship is randomly selected as the search starting point, and a bidirectional search algorithm for path points is used to adaptively generate a skeleton path according to the contour characteristics;

[0013] All skeleton paths generated by constrained Delaunay triangulations are merged and output as the final additive manufacturing printing path.

[0014] According to some embodiments, the present disclosure adopts the following technical solutions:

[0015] A skeleton path generation system based on triangulated network bidirectional search, comprising:

[0016] The contour grouping module is configured to: slice the three-dimensional model to be printed to obtain multiple inner contours and outer contours, and group and pair the inner and outer contours;

[0017] The triangulation module is configured to: construct a constrained Delaunay triangulation for each group of contours, divide the connected domain formed by each group of contours into multiple mesh triangles, classify the triangles according to the number of internal edges, and define the midpoints of two internal edges of a triangle containing at least two internal edges as siblings;

[0018] The bidirectional search module is configured as follows: in each constrained Delaunay triangulation constructed, a pair of points with a sibling relationship is randomly selected as the search starting point, and a path point bidirectional search algorithm is used to adaptively generate a skeleton path according to the contour characteristics;

[0019] The path output module is configured to merge and output all skeleton paths generated by constrained Delaunay triangulations as the final additive manufacturing printing path.

[0020] According to some embodiments, the present disclosure adopts the following technical solutions:

[0021] A computer program product comprises a computer program, wherein when the computer program is executed by a processor, the method for generating a skeleton path based on bidirectional search of a triangulated network is implemented.

[0022] According to some embodiments, the present disclosure adopts the following technical solutions:

[0023] A non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, a skeleton path generation method based on bidirectional search of a triangulated network is implemented.

[0024] According to some embodiments, the present disclosure adopts the following technical solutions:

[0025] An electronic device comprises: a processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory so that the electronic device executes the skeleton path generation method based on triangulated network bidirectional search.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1) The present invention groups and pairs multiple inner and outer contours obtained by slicing, constructs a network and generates a path for each connected domain respectively, and the skeleton search process of each connected domain does not interfere with each other, thereby improving the search efficiency of path points.

[0028] 2) The present invention improves the traditional skeleton line extraction algorithm based on Delaunay triangulation, so that before extracting the skeleton, it is no longer necessary to find and specify the endpoints of the skeleton line. Instead, a pair of points with a sibling relationship is randomly selected as the search starting point, reducing the limitations of the algorithm.

[0029] 3) The present invention proposes a bidirectional search algorithm for path points, which is more efficient than the traditional one-way skeleton line extraction algorithm based on a binary tree structure that requires specifying endpoints. At the same time, it can adaptively generate closed or non-closed skeleton paths according to contour characteristics and has good adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings constituting a part of the present disclosure are used to provide a further understanding of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure.

[0031] Figure 1 This is an overall flow chart of the skeleton path generation method of Example 1.

[0032] Figure 2 It is a comparison diagram of the unrefined and refined Delaunay triangulations of Example 1.

[0033] Figure 3 Schematic diagram of the internal edges of the triangular mesh of Example 1.

[0034] Figure 4 Schematic diagram of the bidirectional search algorithm of Example 1.

[0035] Figure 5 and Figure 6 This is an example diagram of the generation effect of the skeleton path of Example 1. DETAILED DESCRIPTION

[0036] The present disclosure is further described below in conjunction with the accompanying drawings and embodiments.

[0037] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present disclosure belongs.

[0038] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0039] Example 1

[0040] In one embodiment of the present disclosure, a skeleton path generation method based on triangulated network bidirectional search is provided, comprising:

[0041] Step 1: Slice the 3D model to be printed to obtain multiple inner and outer contours, and group and pair the inner and outer contours;

[0042] Step 2: Construct a constrained Delaunay triangulation for each group of contours, divide the connected domain formed by each group of contours into multiple mesh triangles, classify the triangles according to the number of internal edges, and define the midpoints of the two internal edges of a triangle containing at least two internal edges as siblings;

[0043] Step 3: In each constrained Delaunay triangulation constructed, a pair of points with a sibling relationship is randomly selected as the search starting point, and a path point bidirectional search algorithm is used to adaptively generate a skeleton path according to the contour characteristics;

[0044] Step 4: Merge and output all the skeleton paths generated by constrained Delaunay triangulations as the final additive manufacturing printing path.

[0045] As an embodiment, the present invention discloses a skeleton path generation method based on triangulated network bidirectional search, which generates skeleton paths for each connected domain respectively through a bidirectional search algorithm of path points based on Delaunay triangulated network, thereby solving the problems of low skeleton extraction efficiency and limited use conditions in the prior art, and using the generated single skeleton path to improve the additive manufacturability of complex narrow and long features and thin-walled features, such as Figure 1 The specific implementation process is as follows:

[0046] S1. Input slice outline:

[0047] The slice outline may be a single or multiple two-dimensional closed polygons, which are obtained by slicing the three-dimensional model to be printed.

[0048] S2. Simplify the slice outline:

[0049] Use polygon simplification algorithm to delete redundant collinear points. This step not only provides a basis for building a good triangulated network in the subsequent steps, but also improves the network construction speed by reducing the number of contour points.

[0050] S3. Pair the inner and outer contours and write a .poly file, specifically:

[0051] S31. Distinguish inner contours and outer contours, and perform grouping and pairing.

[0052] Each inner contour corresponds to a unique outer contour. Each outer contour may contain multiple inner contours. Each group of contours forms a connected domain. Each group of contours has only one outer contour, and the number of inner contours is greater than or equal to 0.

[0053] S32. Write each group of contours into a .poly file.

[0054] The content to be written includes: contour point information, contour edge information, and hole characterization information. The .poly file is a file format unique to the Triangle library for storing polygon data. The Triangle library is a geometry library dedicated to triangular mesh generation.

[0055] S4. Construct a refined constrained Delaunay triangulation:

[0056] For each .poly file written in S3, use the constraint meshing and refinement meshing instructions of the Triangle library to build a Delaunay triangulation.

[0057] The constrained meshing refers to giving certain boundary constraints so that the triangulated mesh is only generated within the boundary; the refined meshing refers to encrypting and subdividing the mesh to generate more mesh triangles.

[0058] Attached Figure 2 The unrefined constraint meshing and refined constraint meshing effects are shown. The inverted "T"-shaped contour is the specified boundary constraint. It can be seen from the figure that the unrefined constraint meshing will likely produce narrow triangles, making it impossible to accurately detect the direction of the nearest contour through the mesh, which will reduce the accuracy of the skeleton's representation of the contour shape. Therefore, it is necessary to use the refined meshing command to construct an encrypted mesh to provide support for more accurate skeleton extraction. It can be seen from the figure that the use of the refined meshing command has a good inhibitory effect on the appearance of narrow triangles.

[0059] S5. Extract the internal edges of the triangular mesh:

[0060] For the Delaunay triangulation constructed in S4, the mesh edges that are not on the contour are defined as the internal edges of the current connected domain, otherwise they are contour edges, and the internal edge information is stored.

[0061] Attach Figure 3 For example, the inner and outer contours in the figure constitute a connected domain in the shape of a rectangular frame. ABC and BDE are two triangles in the Delaunay triangulation. According to the above definition of internal edges, in these two triangles, the edges AB, AC, BD, and BE are the internal edges of the current connected domain.

[0062] S6. Construct the topological relationship of three types of triangles:

[0063] The triangles in the Delaunay triangulation are divided into three categories according to the number of internal edges. The characteristics of the path segments (i.e., internal path segments) contained in each type of triangle are specified, and the topological relationships of each type of triangle are constructed respectively, including:

[0064] a) The first type (edge ​​triangle): contains one internal edge and two contour edges.

[0065] The characteristics of its path segment are as follows: the path segment will be connected to the contour edge by the midpoint of the internal edge, and the connection point is one of the two contour edge midpoints and the internal edge's opposite vertices. The specific selection method is: compare the angles between these three connection directions and the direction finally pointed to by the current path (i.e., the current path in the search process of step S7), and take the point corresponding to the direction with the smallest angle as the final connection point.

[0066] The topological relationship is: the midpoint of the only internal edge is defined as an isolated point, and the midpoints of the other two sides of the same triangle cannot be queried from the isolated point.

[0067] b) The second type (pathway triangle): contains two internal edges and one contour edge.

[0068] The characteristics of its path segment are: the line connecting the midpoints of the two internal edges (median line) is taken as the path segment.

[0069] Its topological relationship is: the midpoints of two internal edges are defined as siblings, and any point can be queried to the other point;

[0070] c) The third type (branching triangle): contains three internal edges.

[0071] The characteristics of its path segment are: it contains two path segments belonging to different paths, takes two internal edges, connects the midpoint of one of the internal edges, the centroid of the triangle, and the midpoint of the other internal edge in sequence as one path, and connects the remaining internal edge midpoint to the centroid of the triangle as another path.

[0072] The topological relationship is as follows: the midpoints of two internal edges are defined as brothers, and the midpoint of the remaining internal edge is defined as an isolated point.

[0073] The triangle topological relationship also includes: regardless of the triangle type, each internal edge actually belongs to two adjacent triangles, and a pair of midpoints of two triangles on their shared edges are defined as an adjacency relationship, and any point can be queried to the other point.

[0074] S7, bidirectionally searching for path points to generate a skeleton path, including the following steps:

[0075] For all connected domains after meshing (i.e., the constrained Delaunay triangulation formed by each group of contours), the path generation is carried out according to the following steps:

[0076] S71. Determine whether the Delaunay triangulation of the current connected domain contains only one triangle. If so, do not consider generating a skeleton path for it and jump to step S74; otherwise, proceed to the next step.

[0077] S72. Determine whether the Delaunay triangulation of the current connected domain contains only two triangles. If so, compare the lengths of the two medians passing through the midpoints of the common edges of the two triangles, select the two longer medians to form a skeleton path, and jump to step S74; otherwise, proceed to the next step.

[0078] S73. If the Delaunay triangulation of the current connected domain contains more than two triangles, a bidirectional search algorithm for path points is used, such as Figure 4 As shown in the figure (the triangle types are marked in the figure), specifically including:

[0079] S731. When there is an "unused midpoint", a new empty path is created, and an unused midpoint and its sibling points are selected to join the empty path as the starting point and end point of the current path respectively, and the point and its sibling points are marked as used, and then jump to S732 to continue searching the current path.

[0080] When there is no "unused midpoint", it means that the Delaunay triangulation search of the current connected domain is completed, and the process jumps to S74 to output the skeleton path of the current connected domain.

[0081] S732. Starting from the starting point and the end point of the current path, search on both sides of the path respectively, and continuously update the current starting point and the end point of the path: find the adjacent point of the current point through the adjacency relationship, and then query the brother point of the adjacent point, and add the internal path segment of the triangle constructed according to the classification to the current path until the search end condition is met.

[0082] The internal path segment of the triangle here is constructed by each triangle path segment method in S6. Adding the path segment to the current path means adding the points queried in the two search directions to the beginning and end of the path, updating the start and end points of the path, and marking the two points as used; if the triangle type to which the queried point belongs is the third type (branch triangle), then add the triangle centroid first, and then add the point. If no point can be queried in a certain direction, no operation is performed in that direction.

[0083] The search end conditions include three types of search end conditions. As long as any one of them is met, the search ends and the process jumps to S733 to finish the work. Otherwise, S732 is iterated.

[0084] S733, three types of search end conditions and finishing work, specifically:

[0085] a) If the points found in the two search directions are adjacent, the coordinates of the two points coincide and the current path will be closed. At this time, add the found points to the beginning and end of the path respectively, and mark the two points as used. If the triangle type of one of the points is three (three internal edges), add the centroid of the triangle first, then add the point, and finally generate a closed path.

[0086] b) If the points found in the two search directions are sibling points, the two points belong to the same triangle and the current path will be closed. At this time, select any point and add it to the end of the path in the corresponding search direction, and mark the two points as used. If the selected point belongs to the triangle type three, add the triangle centroid first, then add the point, and finally generate a closed path.

[0087] c) If no point can be found in either search direction, for the starting point and end point of the current path: if the triangle type of its adjacent point is one, the path at the current point is extended according to the characteristics of the first type of triangle path segment, and the points on the contour edge are added after the current point; if the triangle type of its adjacent point is three, the path at the current point is extended according to the characteristics of the third type of triangle path segment, and the centroid of the triangle is added after the current point, and finally a non-closed path is generated.

[0088] After finishing the finishing work of the current path, jump to S731 to determine whether to create an empty path.

[0089] S74, output the skeleton path of the current connected domain,

[0090] The skeleton path may be a single / multiple closed paths, a single / multiple non-closed paths, or a closed / non-closed mixed path.

[0091] S8. Merge redundant paths:

[0092] Each path contained in the skeleton path is simplified. A path may be composed of multiple line segments. If there are multiple consecutive line segments on the same line, it is necessary to delete the redundant path points and merge the multiple line segments into one segment, thereby reducing the amount of code and storage size of the processing code generated from the path.

[0093] Specifically, multiple consecutive collinear line segments in a path will generate multiple "G1" machining instructions. After simplification, the multiple line segments are merged into one segment and can be represented by only one "G1" instruction.

[0094] Figure 5 to Figure 6 As an example of the generation effect of the skeleton path in this embodiment, in order to clearly show that the skeleton path of a complex contour is composed of multiple different paths, the path effect of not extending the path to the centroid of the third type of triangle is also provided in the dotted box.

[0095] Example 2

[0096] In one embodiment of the present disclosure, a skeleton path generation system based on triangulated network bidirectional search is provided, comprising:

[0097] The contour grouping module is configured to: slice the three-dimensional model to be printed to obtain multiple inner contours and outer contours, and group and pair the inner and outer contours;

[0098] The triangulation module is configured to: construct a constrained Delaunay triangulation for each group of contours, divide the connected domain formed by each group of contours into multiple mesh triangles, classify the triangles according to the number of internal edges, and define the midpoints of two internal edges of a triangle containing at least two internal edges as siblings;

[0099] The bidirectional search module is configured as follows: in each constrained Delaunay triangulation constructed, a pair of points with a sibling relationship is randomly selected as the search starting point, and a path point bidirectional search algorithm is used to adaptively generate a skeleton path according to the contour characteristics;

[0100] The path output module is configured to merge and output all skeleton paths generated by constrained Delaunay triangulations as the final additive manufacturing printing path.

[0101] Example 3

[0102] In one embodiment of the present disclosure, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the method for generating a skeleton path based on a triangulated network bidirectional search is implemented.

[0103] Example 4

[0104] In one embodiment of the present disclosure, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the skeleton path generation method based on triangulated network bidirectional search is implemented.

[0105] Example 5

[0106] In one embodiment of the present disclosure, an electronic device is provided, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, and the computer program is stored in the memory. When the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes the skeleton path generation method based on triangulated network bidirectional search.

[0107] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0108] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0109] Although the above describes the specific implementation methods of the present disclosure in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present disclosure. Technical personnel in the relevant field should understand that on the basis of the technical solution of the present disclosure, various modifications or variations that can be made by those skilled in the art without creative work are still within the scope of protection of the present disclosure.

Claims

1. A skeleton path generation method based on triangulated network bidirectional search, characterized in that: include: Slice the 3D model to be printed to obtain multiple inner and outer contours, and group and pair the inner and outer contours; Construct a constrained Delaunay triangulation for each group of contours, divide the connected domain formed by each group of contours into multiple mesh triangles, classify the triangles according to the number of internal edges, and define the midpoints of the two internal edges of a triangle containing at least two internal edges as siblings. In each constrained Delaunay triangulation constructed, a pair of points with a sibling relationship is randomly selected as the search starting point, and a bidirectional search algorithm for path points is used to adaptively generate a skeleton path according to the contour characteristics; All skeleton paths generated by constrained Delaunay triangulations are merged and output as the final additive manufacturing printing path.

2. A skeleton path generation method based on triangulated network bidirectional search as claimed in claim 1, characterized in that: The group pairing is specifically: Each inner contour corresponds to a unique outer contour, each outer contour contains multiple inner contours, an outer contour and the inner contours it contains are considered as a group of contours, and each group of contours forms a connected domain.

3. A skeleton path generation method based on triangulated network bidirectional search as claimed in claim 1, characterized in that: The specific steps of constructing a constrained Delaunay triangulation are as follows: Write each set of contours into a .poly file; For the compiled .poly file, use the constraint meshing and refinement meshing commands of the Triangle library to construct a constrained Delaunay triangulation. The constrained meshing is to give certain boundary constraints so that the triangulated mesh is only generated within the boundary; the refined meshing is to encrypt and subdivide the mesh to generate more mesh triangles.

4. A skeleton path generation method based on triangulated network bidirectional search as claimed in claim 1, characterized in that: The classification includes three categories: An edge triangle containing one interior edge and two contour edges; A path triangle with two interior edges and one contour edge; A branching triangle with three internal edges; There are two kinds of relationships between centers that define internal edges: sibling relationships and adjacency relationships; The adjacency relationship is that a pair of midpoints on the common side of two adjacent triangles are in an adjacency relationship.

5. A skeleton path generation method based on triangulated network bidirectional search as claimed in claim 4, characterized in that: The path point bidirectional search algorithm is specifically: Create a new empty path, take a pair of points with a sibling relationship as the search starting point, add the found midpoint and its sibling point to the path, and mark the two points as the starting point and end point of the current path; Starting from the starting point and end point of the current path, search on both sides of the path respectively, and continuously update the current starting point and end point of the path: find the adjacent point of the current point through the adjacency relationship, and then query the sibling points of the adjacent point, and add the internal path segment of the triangle constructed according to the classification to the current path, until the search end condition is met; When the search end condition is met, the current path is finished to obtain the skeleton path of the current connected domain.

6. A skeleton path generation method based on triangulated network bidirectional search as claimed in claim 5, characterized in that: The triangle internal path segments constructed according to the classification are specifically: When the edge triangle is formed, a point is selected from the three points consisting of the midpoints of the two contour edges and the vertex opposite to the internal edge, and connected to the midpoint of the internal edge as the internal path segment; When traversing a triangle, take the line connecting the midpoints of the two internal edges as the internal path segment; When branching a triangle, take two internal edges, connect the midpoint of one of the internal edges, the centroid of the triangle, and the midpoint of the other internal edge in sequence as the first internal path segment, and connect the remaining internal edge midpoint to the centroid of the triangle as the second internal path segment; Among them, the inner path segment of the edge triangle and the second inner path segment of the branch triangle are only used for finishing work.

7. A skeleton path generation method based on triangulated network bidirectional search as claimed in claim 5, characterized in that: The search end conditions and finishing work include: If the points queried in the two search directions are adjacent to each other, corresponding internal path segments are added to the beginning and end of the path according to the triangle type to which the queried points belong, so as to generate a closed path.

8. The skeleton path generation method based on triangulated network bidirectional search according to claim 5, characterized in that: The search end conditions and finishing work also include: If the points found in the two search directions are sibling points, select any point and add the corresponding internal path segment to the end of the path in the search direction corresponding to the point according to the triangle type to which the point belongs, so as to generate a closed path.

9. The skeleton path generation method based on triangulated network bidirectional search according to claim 5, characterized in that: The search end conditions and finishing work also include: If no point can be found in either search direction, for the start and end points of the current path, corresponding internal path segments are added to the beginning and end of the path according to the triangle types of the adjacent points of the two points to generate a non-closed path.

10. A skeleton path generation system based on triangulated network bidirectional search, characterized in that: include: The contour grouping module is configured to: slice the three-dimensional model to be printed to obtain multiple inner contours and outer contours, and group and pair the inner and outer contours; The triangulation module is configured to: construct a constrained Delaunay triangulation for each group of contours, divide the connected domain formed by each group of contours into multiple mesh triangles, classify the triangles according to the number of internal edges, and define the midpoints of two internal edges of a triangle containing at least two internal edges as siblings; The bidirectional search module is configured as follows: in each constrained Delaunay triangulation constructed, a pair of points with a sibling relationship is randomly selected as the search starting point, and a path point bidirectional search algorithm is used to adaptively generate a skeleton path according to the contour characteristics; The path output module is configured to merge and output all skeleton paths generated by constrained Delaunay triangulations as the final additive manufacturing printing path.

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