Methods, apparatus, electronic devices and storage media for constructing topology relation tables

Abstract

This invention discloses a method, apparatus, electronic device, and storage medium for constructing a topology relation table. The method includes obtaining a target grid from a preset grid spatial data table; identifying the nearest neighbor grids of the target grid in each direction according to preset constraints; calculating the three-dimensional distance between the target grid and each of the nearest neighbor grids to obtain cost information; and constructing a topology relation table based on the target grid, the nearest neighbor grids, and the cost information. This invention can improve the generation efficiency of BeiDou grid topology relation tables and meet real-time requirements.

Description

Technical Field

[0001] This invention relates to the field of BeiDou grid technology, and in particular to a method, apparatus, electronic device and storage medium for constructing a topology table. Background Technology

[0002] BeiDou grid codes are used to provide a unified encoding and partial framework for 3D geospatial entities. With the development of technologies such as drones and autonomous driving, refined spatial management and path planning based on BeiDou grids have become particularly important. The execution efficiency of path planning algorithms, in particular, highly depends on a pre-constructed topological graph that accurately describes the connectivity between grid cells.

[0003] Traditional methods for constructing topology graphs typically involve traversing all grids for each grid to search for the nearest neighbor that meets the criteria. However, when the number of grids is enormous, the time required for a global search increases exponentially, making the construction of the topology graph extremely time-consuming and unable to meet the real-time requirements of large-scale, high-precision scenarios. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, and storage medium for constructing a topology relation table, aiming to solve the problem of the long construction time of current topology relation graphs.

[0005] In a first aspect, embodiments of the present invention provide a method for constructing a topological relation table, the method comprising:

[0006] Obtain the target grid from the preset grid space data table;

[0007] The nearest neighbor meshes of the target mesh in each direction are determined according to preset constraints;

[0008] Calculate the three-dimensional distance between the target mesh and each of the nearest neighbor meshes to obtain cost information;

[0009] A topology table is constructed based on the target grid, the nearest neighbor grid, and the cost information.

[0010] Secondly, embodiments of the present invention also provide an apparatus for constructing a topological relation table, the apparatus comprising:

[0011] The first acquisition unit is used to acquire the target grid from a preset grid space data table;

[0012] The first confirmation unit is used to confirm the nearest neighbor grids of the target grid in each direction according to preset constraints.

[0013] The first computing unit is used to calculate the three-dimensional distance between the target grid and each of the nearest neighbor grids to obtain cost information;

[0014] The first construction unit is used to construct a topology table based on the target grid, the nearest neighbor grid, and the cost information.

[0015] Thirdly, embodiments of the present invention also provide an electronic device, which includes a memory and a processor connected to the memory, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0016] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the above-described method.

[0017] This invention provides a method, apparatus, electronic device, and storage medium for constructing a topology table. The method includes: obtaining a target mesh from a preset mesh space data table; identifying the nearest neighbor meshes of the target mesh in each direction according to preset constraints; calculating the three-dimensional distance between the target mesh and each nearest neighbor mesh to obtain cost information; and constructing a topology table based on the target mesh, the nearest neighbor meshes, and the cost information. This invention allows for rapid identification of nearest neighbor meshes in each direction based on preset constraints, shortening construction time. Furthermore, calculating the three-dimensional distance between each target mesh and its corresponding nearest neighbor mesh to obtain cost information reduces computational complexity. The construction of the topology table based on the cost information, the target mesh, and the nearest neighbor meshes enables rapid construction of the topology table, meeting the real-time requirements of large-scale, high-precision scenarios. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the method for constructing a topology table provided in an embodiment of the present invention;

[0020] Figure 2 This is a schematic diagram of the preset grid space data table of the method for constructing the topology relationship table provided in the embodiments of the present invention;

[0021] Figure 3 This is a schematic diagram of the first sub-process of the method for constructing a topology relationship table provided in an embodiment of the present invention;

[0022] Figure 4 This is a schematic diagram of the second sub-process of the method for constructing a topology table provided in an embodiment of the present invention;

[0023] Figure 5 This is a schematic diagram of the third sub-process of the method for constructing a topology relationship table provided in an embodiment of the present invention;

[0024] Figure 6 This is a schematic diagram of the fourth sub-process of the method for constructing a topology table provided in an embodiment of the present invention;

[0025] Figure 7 This is a schematic diagram of the fifth sub-process of the method for constructing a topology table provided in an embodiment of the present invention;

[0026] Figure 8 This is a schematic diagram of the sixth sub-process of the method for constructing a topology table provided in an embodiment of the present invention;

[0027] Figure 9 This is a schematic block diagram of a topology table construction apparatus provided in an embodiment of the present invention;

[0028] Figure 10 This is a schematic block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] It should be understood that, when used in this specification and the appended claims, the terms “comprising” and “including” indicate the presence of the described features, integrals, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, operations, elements, components and / or collections thereof.

[0031] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0032] Please see Figure 1 , Figure 1 This is a flowchart illustrating the method for constructing a topology table according to an embodiment of the present invention. This method can be applied to electronic devices to quickly construct a topology table of the BeiDou grid space, meeting real-time requirements. Figure 1 As shown, the method includes steps S110 to S140.

[0033] S110, obtain the target grid from the preset grid space data table.

[0034] In this embodiment of the invention, the preset grid data table is a pre-preset data table that contains attribute information of BeiDou grid data. The attribute information includes, but is not limited to, grid ID, grid code, latitude and longitude, elevation, three-dimensional spatial points, and status information. The grid ID is a unique integer identifier for a BeiDou grid unit (e.g., id=1001), used for quick location and association of grids in the data table, serving as the primary key of the data table to ensure the uniqueness of each grid in the database. The grid code is a unique code based on the BeiDou grid division standard, in the form of 310104_10_0000000001, containing rows... Information such as administrative divisions, levels, and grid numbers; longitude (east / west) and latitude (north / south) are spherical coordinates of two-dimensional positions on the Earth's surface. Longitude is used to identify east-west positions, and latitude is used to identify north-south positions. Elevation is the distance from the grid center point along the vertical line to the mean sea level of the Yellow Sea. The three-dimensional spatial point is a combination of the longitude, latitude, and elevation of the grid center point, used to provide a spatial index to facilitate the calculation of spatial relationships between grids. Status information includes static and dynamic status. Static status includes passable and impassable, and dynamic status includes occupied and unoccupied. Status information is used for dynamic control of accessibility.

[0035] When retrieving a target grid from a preset grid space data table, it can be obtained from grids that meet preset requirements. For example, if the preset grid space data table includes multiple grids, and some grids are statically impassable, then those grids can be removed, and the target grid can be obtained from the remaining grids. It is understood that the number of target grids can be multiple, as long as they meet the preset requirements.

[0036] In some embodiments, such as in embodiments of the present invention, as Figure 3 As shown, step S110 includes steps S111-S113.

[0037] S111, the preset grid space data table is filtered according to the target level to obtain the first candidate target grid;

[0038] S112, the grid in the first candidate target grid that is passable in static state and empty in dynamic state is taken as the second candidate target grid;

[0039] S113, sequentially select the grids in the second candidate target grid as the target grids.

[0040] In this embodiment of the invention, the preset requirements may include hierarchical requirements and static state requirements. The BeiDou grid divides the Earth from the surface to an altitude of 60,000 kilometers into 32 nested grids. The side length of each grid decreases in power of 2, forming a pyramid structure where the higher the level, the smaller the grid and the higher the accuracy. The required accuracy varies for different scenarios. For example, level 1 is usually used for large-scale area division, level 5 is usually used for urban macro planning, level 9 is usually used for fine obstacle avoidance of UAVs, and level 10 is usually used for centimeter-level path planning.

[0041] For example, if the layer requirement is layer 10, then the grid with layer information of layer 10 can be used as the first candidate target grid. The static state requirement is usually accessibility, meaning the grid needs to be accessible and not obstructed by buildings or other obstacles. Grids with an accessible static state from the first candidate target grid are used as second candidate grids, and then one grid from the second candidate grid is selected as the target grid. When selecting the target grid, specific requirements can be considered, such as using a particular grid as the starting grid for path planning, or using all grids from the second candidate grid as target grids, and constructing a topology table for each target grid in sequence.

[0042] S120, the nearest neighbor meshes of the target mesh in each direction are determined according to the preset constraints.

[0043] In this embodiment of the invention, preset constraints are used to filter meshes to reduce required complexity and improve construction efficiency. Preset constraints may include state constraints, hierarchical constraints, spatial constraints, directional constraints, and nearest neighbor constraints. State constraints constrain the state information of the mesh; hierarchical constraints constrain the hierarchical information of the mesh; spatial constraints constrain the longitude, latitude, and elevation information of the mesh; directional constraints constrain the relative positional relationship between the mesh and the target mesh; and nearest neighbor constraints constrain the distance between the mesh and the target mesh.

[0044] Preset constraints typically consist of multiple conditions, which can be used to filter the mesh sequentially. After filtering by multiple constraints, a single, best-matching mesh can usually be selected as the nearest neighbor mesh in that direction. Generally, it is necessary to identify the nearest neighbor meshes in six directions: east, west, south, north, up, and down. After filtering by preset constraints, six nearest neighbor meshes can be obtained, one in each direction.

[0045] In some embodiments, such as in embodiments of the present invention, as Figure 4 As shown, the preset constraints include state constraints, hierarchical constraints, spatial constraints, directional constraints, and nearest neighbor constraints. Step S120 includes steps S121-S122.

[0046] S121, Select a direction from the optional directions of the target mesh that does not have the nearest neighbor mesh as the target direction, and confirm the spatial constraint, directional constraint and nearest neighbor constraint based on the target direction to obtain the first spatial constraint, the first directional constraint and the first nearest neighbor constraint.

[0047] S122, based on the state constraint, the hierarchical constraint, the first spatial constraint, the first directional constraint, and the first nearest neighbor constraint, the nearest neighbor grid in the target direction is determined.

[0048] In this embodiment of the invention, the selectable directions include six directions: east, west, south, north, up, and down. Any direction among these six that does not have a nearest neighbor grid can be used as the target direction, such as east. Then, the state constraints, hierarchical constraints, spatial constraints, directional constraints, and nearest neighbor constraints corresponding to the east direction are confirmed. It is understood that some constraints in different directions may differ to some extent. For example, spatial constraints, directional constraints, and nearest neighbor constraints: for the east direction, the first spatial constraint can be latitude and elevation; the first directional constraint can be located east of the target grid; and the first nearest neighbor constraint can be the minimum longitude from the target grid. For the south direction, the second spatial constraint can be longitude and elevation; the second directional constraint can be located south of the target grid; and the second nearest neighbor constraint can be the maximum latitude from the target grid. After confirming the constraints in the target direction, the nearest neighbor grid in that direction can be selected based on the confirmed constraints.

[0049] In some embodiments, such as in embodiments of the present invention, as Figure 5 As shown, step S122 includes steps S1221-S1225.

[0050] S1221, All candidate meshes are filtered according to the state constraint to obtain a first candidate mesh, wherein the state constraint is that the state information of the candidate mesh is passable;

[0051] S1222, the first candidate mesh is filtered according to the hierarchical constraint to obtain a second candidate mesh, wherein the hierarchical constraint is that the hierarchical information of the candidate mesh is the same as the hierarchical information of the target mesh;

[0052] S1223, the second candidate mesh is filtered according to the first spatial constraint to obtain a third candidate mesh, wherein the first spatial constraint is that the candidate mesh and the target mesh are spatially aligned in the non-directional dimension;

[0053] S1224, the third candidate mesh is filtered according to the first directional constraint to obtain a fourth candidate mesh, wherein the first directional constraint is that the candidate mesh is located in the target direction of the target mesh;

[0054] S1225, the fourth candidate grid is filtered according to the first nearest neighbor constraint to obtain the nearest neighbor grid, wherein the first nearest neighbor constraint is that the candidate grid is closest to the target grid.

[0055] In this embodiment of the invention, for the due east direction, the preset constraints are state constraints, hierarchical constraints, a first spatial constraint, a first directional constraint, and a first nearest neighbor constraint; for the due south direction, the preset constraints are state constraints, hierarchical constraints, a second spatial constraint, a second directional constraint, and a second nearest neighbor constraint; for the due west direction, the preset constraints are state constraints, hierarchical constraints, a third spatial constraint, a third directional constraint, and a third nearest neighbor constraint; for the due north direction, the preset constraints are state constraints, hierarchical constraints, a fourth spatial constraint, a fourth directional constraint, and a fourth nearest neighbor constraint; for the upward direction, the preset constraints are state constraints, hierarchical constraints, a fifth spatial constraint, a fifth directional constraint, and a fifth nearest neighbor constraint; and for the downward direction, the preset constraints are state constraints, hierarchical constraints, a sixth spatial constraint, a sixth directional constraint, and a sixth nearest neighbor constraint.

[0056] The first and third spatial constraints can be that the latitude tolerance between the grid and the target grid is less than a preset latitude tolerance, and the elevation tolerance between the grid and the target grid is less than a preset elevation tolerance. The second and fourth spatial constraints can be that the longitude tolerance between the grid and the target grid is less than a preset longitude tolerance, and the elevation tolerance between the grid and the target grid is less than a preset elevation tolerance. The fifth and sixth spatial constraints can be that the longitude tolerance between the grid and the target grid is less than a preset longitude tolerance, and the latitude tolerance between the grid and the target grid is less than a preset latitude tolerance.

[0057] The first directional constraint is that the mesh is located to the east of the target mesh; the second directional constraint is that the mesh is located to the south of the target mesh; the third directional constraint is that the mesh is located to the west of the target mesh; the fourth directional constraint is that the mesh is located to the north of the target mesh; the fifth directional constraint is that the mesh is located above the target mesh; and the sixth directional constraint is that the mesh is located below the target mesh.

[0058] The first nearest neighbor constraint is the grid with the minimum longitude, the second nearest neighbor constraint is the grid with the maximum latitude, the third nearest neighbor constraint is the grid with the maximum longitude, the fourth nearest neighbor constraint is the grid with the minimum latitude, the fifth nearest neighbor constraint is the grid with the minimum elevation, and the sixth nearest neighbor constraint is the grid with the maximum elevation.

[0059] Taking the due east direction as an example, its state constraint condition can be that the static state is passable, its hierarchical constraint condition is level 10, its first spatial constraint condition is that the latitude tolerance between the grid and the target grid is less than the preset latitude tolerance (the preset latitude tolerance can be 0.00001°), and the elevation tolerance between the grid and the target grid is less than the preset elevation tolerance (the preset elevation tolerance can be 0.05 meters). Its first directional constraint condition is that the grid is located to the east of the target grid, and its first nearest neighbor constraint condition is that the grid has the smallest longitude. The grid that meets the above conditions is the nearest neighbor grid in the due east direction. The nearest neighbor grids in other directions can be referred to the due east direction, which will not be elaborated here.

[0060] Additionally, uniqueness constraints can be set to avoid duplicate confirmations when identifying nearest neighbor grids in six directions. For example, after confirming the six nearest neighbor grids of the target grid, the ID of the target grid can be associated with the grid IDs of the six nearest neighbor grids. When any one of the six nearest neighbor grids is set as the target grid, the confirmation of nearest neighbor grids in at least one direction can be reduced. For instance, if the target grid is g1, and its nearest neighbor grid in the east direction is g2, then the grid IDs of g1 and g2 are associated. Simultaneously, if the target grid is g2, and its nearest neighbor grid in the west direction is g1, the confirmation of the nearest neighbor grid in the west direction for g2 can be skipped, further improving construction efficiency and reducing data redundancy, avoiding duplicate data. Understandably, during the specific association, the grid ID of the target grid and the grid ID of the nearest neighbor grid can be combined into a combined field and stored in a table. When a new combined field is added, a duplicate check can be performed on the table. If the combined field does not exist, it can be stored in the table; if the combined field exists, the record is skipped.

[0061] S130, calculate the three-dimensional distance between the target mesh and each of the nearest neighbor meshes to obtain cost information.

[0062] In this embodiment of the invention, after identifying the nearest neighbor grid of the target grid, the three-dimensional distance between the target grid and its nearest neighbor grid can be calculated to obtain cost information. Each target grid may include six nearest neighbor grids, and the three-dimensional distances between the target grid and its six nearest neighbor grids can be calculated sequentially, such as calculating the three-dimensional distance between the center point of the target grid and the center point of the nearest neighbor grid, thereby obtaining cost information. Cost information is mainly used to provide a quantified basis for the travel cost for path planning algorithms. The core objective of path planning is to find the optimal path from the starting grid to the ending grid, and the optimal path is usually based on the minimum cost (such as the shortest distance, the lowest energy consumption, etc.). Cost information directly quantifies the travel length between two grids by calculating the three-dimensional straight-line distance between the center points of the target grid and the nearest neighbor grid, becoming the core weight for path planning algorithms to determine which path is better. For example, an algorithm may calculate the total cost based on the sum of various cost information and prioritize the path with the minimum total cost. In addition, cost information also indirectly reflects the travel difficulty between two grids. In scenarios such as drones and autonomous driving, the travel cost between grids that are closer is lower (easier to reach), while the cost between grids that are farther apart is higher (requiring more energy or time). By quantifying this difference using cost information, we can ensure that the path planning results conform to actual physical constraints (such as shortest path priority).

[0063] S140, construct a topology table based on the target grid, the nearest neighbor grid, and the cost information.

[0064] In this embodiment of the invention, a topology table can be generated based on the target grid's grid ID, the nearest neighbor grid's grid ID, and cost information. This topology table stores the adjacency relationships between grids and describes their connectivity. Each record in the topology table can be considered a topology edge, used to identify which two grids are adjacent. For example, the target grid in the topology table serves as the starting grid of the topology edge, and the nearest neighbor grid serves as the ending grid. The attribute information corresponding to the starting and ending grids of the topology edge can be queried through a preset grid space data table. Furthermore, changes in the data in the preset grid space data table will trigger an update to the topology table. For instance, when the state information of a grid changes from passable to impassable, all topology edges in the topology table with that grid as the target grid or nearest neighbor grid will be deleted, and local edges will be reconstructed based on the new state.

[0065] For example, such as Figure 2 As shown, Figure 2The left side shows the preset grid spatial data table, and the right side shows the topology table. If grids ID=1001 (accessible) and ID=1002 (accessible) exist in the preset grid spatial data table, and they are adjacent in the due east direction, a record will be generated in the topology table: Target grid ID=1001, nearest neighbor grid ID=1002, cost information = 3D distance between the center points of the two grids. This record is associated with the preset grid spatial data table through 1001 and 1002, clearly indicating that grids 1001 and 1002 are connected in the due east direction. If the status information of 1002 changes to inaccessible, the record will be deleted in the topology table, and the nearest neighbor grids of 1001 and 1002 in the due east direction will be regenerated.

[0066] In some embodiments, such as in embodiments of the present invention, as Figure 6 As shown, the method for constructing the topology table further includes steps S150-S151.

[0067] S150, Obtain the attribute information of each BeiDou grid cell, wherein the attribute information includes at least grid ID, grid code, latitude and longitude, elevation, three-dimensional spatial point and status information;

[0068] S151, Generate a grid space attribute table based on the attribute information, and create a spatial index and a regular index for the grid space attribute table to obtain the preset grid space data table.

[0069] In this embodiment of the invention, the attribute information includes at least grid ID, grid code, latitude and longitude, elevation, three-dimensional spatial points, status information, and hierarchy information. A grid spatial attribute table is then generated based on this information to store the grid's attribute information. After obtaining the grid spatial attribute table, spatial and regular indexes can be created to obtain a preset grid spatial data table. For example, a spatial index can be created to store the three-dimensional coordinates of the grid center point to accelerate spatial queries (such as adjacency determination and distance calculation), and query indexes can be added to the hierarchy and status information to facilitate optimized sorting and equality queries.

[0070] In some embodiments, such as in embodiments of the present invention, as Figure 7 As shown, the method for constructing the topology table further includes steps S160-S162.

[0071] S160, obtain the spatial range of the static obstacle and the spatial range of the preset grid spatial data table to obtain a first spatial range and a second spatial range;

[0072] S161, if the first spatial range intersects with the second spatial range, then obtain the intersection of the first spatial range and the second spatial range;

[0073] S162, configure the static state of the grids located in the intersection of the preset grid space data table as impassable.

[0074] In this embodiment of the invention, each grid has initial state information, such as whether it is passable or impassable. The state information of the grid can be updated based on the spatial extent of static obstacles. For example, a 3D model data table of a building (containing geometric information and recording the 3D spatial extent of the building) and a user-specified static obstacle area (such as a 3DBox geometry of a no-fly zone, including longitude, latitude, and elevation ranges) can be obtained. Then, a first spatial extent is generated based on the above information. Next, the center point coordinates of each grid are obtained, and a second spatial extent is generated based on the obtained center point coordinates. Then, it is determined whether the first and second spatial extents intersect. If there is no intersection, no state information needs to be updated; if there is an intersection, the state information of the grids located in the intersection is updated to impassable.

[0075] In some embodiments, such as in embodiments of the present invention, as Figure 8 As shown, the method for constructing the topology table further includes steps S170-S171.

[0076] S170, acquire preset dynamic obstacle information and real-time detection data;

[0077] S171, Configure the dynamic state of each grid in the preset grid space data table based on the preset dynamic obstacle information and the real-time detection data.

[0078] In this embodiment of the invention, in addition to static obstacle updates, dynamic obstacle updates can also be performed. Dynamic obstacles refer to temporarily existing or moving obstacles (such as drones, temporary control zones, construction areas, etc.). The purpose of marking them is to update the temporary occupancy status of the grid in real time, ensuring that the topology can dynamically respond to environmental changes. Preset dynamic obstacle information can be obtained based on the drone's preset flight path (represented by a grid ID sequence or geometric path), the time and spatial range of the temporary control zone (e.g., a certain area is closed to traffic from 10:00 to 12:00), and real-time detection information can be obtained based on the drone's real-time positioning information (latitude, longitude, and elevation, which can be converted into the corresponding BeiDou grid code) and the real-time trajectory of the moving obstacles (obtained through sensors or monitoring equipment).

[0079] For a pre-defined flight path of a drone, the dynamic state of all grids covered by the flight path is updated to a specific identifier (such as drone ID or mission ID), indicating that the grid is temporarily occupied during the flight path execution. Specifically, the geometric path of the pre-defined flight path can be converted into a corresponding grid ID sequence (using a grid code generation algorithm to match the covered grids based on the path coordinates). Then, for the grids in the sequence, their dynamic state is set to the drone ID and mission ID, indicating that the grid is temporarily occupied.

[0080] For moving obstacles (such as drones in flight or accident scenes), the dynamic status of the grid is dynamically updated based on real-time positioning data. For example, real-time positioning coordinates (latitude, longitude, and altitude) are converted into corresponding BeiDou grid codes to determine the currently occupied grid. The dynamic status of this grid is marked as an obstacle identifier and continuously refreshed according to the positioning frequency.

[0081] The method for constructing a BeiDou grid spatial topology table provided by this invention can determine the nearest neighbor grids of each target grid in each direction according to preset constraints, thereby quickly identifying the nearest neighbor grids, shortening the construction time, and calculating the three-dimensional distance between each target grid and its corresponding nearest neighbor grid to obtain cost information, reducing computational complexity. Then, based on the cost information, target grids and nearest neighbor grids, a topology table is constructed, thereby achieving rapid construction of the topology table, which can meet the real-time requirements of large-scale, high-precision scenarios.

[0082] Figure 9 This is a schematic block diagram of a topological relationship table construction apparatus 200 provided in an embodiment of the present invention. Figure 9 As shown, corresponding to the above method for constructing a topology table, the present invention also provides a topology table construction apparatus 200. This topology table construction apparatus 200 includes a unit for performing the above-described method for constructing a topology table. Specifically, please refer to... Figure 9 The topology table construction device 200 includes a first acquisition unit 201, a first confirmation unit 202, a first calculation unit 203, and a first construction unit 204.

[0083] The first acquisition unit 201 is used to acquire the target grid from a preset grid space data table;

[0084] The first confirmation unit 202 is used to confirm the nearest neighbor mesh of the target mesh in each direction according to preset constraint conditions;

[0085] The first calculation unit 203 is used to calculate the three-dimensional distance between the target grid and each of the nearest neighbor grids to obtain cost information;

[0086] The first construction unit 204 is used to construct a topology table based on the target grid, the nearest neighbor grid, and the cost information.

[0087] In some embodiments, such as this embodiment, the first acquisition unit 201 further includes a first filtering unit, a second filtering unit, and a second confirmation unit.

[0088] The first filtering unit is used to filter the preset grid space data table according to the target level to obtain a first candidate target grid.

[0089] The second filtering unit is used to select the grids in the first candidate target grids whose static state is passable and whose dynamic state is empty as the second candidate target grids.

[0090] The second confirmation unit is used to sequentially identify the grids in the second candidate target grids as the target grids.

[0091] In some embodiments, such as this one, the first confirmation unit 202 further includes a first selection unit and a third confirmation unit.

[0092] The first selection unit is used to select a direction from the optional directions of the target grid that does not have the nearest neighbor grid as the target direction, and to confirm the spatial constraint, directional constraint and nearest neighbor constraint based on the target direction to obtain the first spatial constraint, the first directional constraint and the first nearest neighbor constraint.

[0093] The third confirmation unit is used to confirm the nearest neighbor grid in the target direction based on the state constraint, the hierarchical constraint, the first spatial constraint, the first directional constraint, and the first nearest neighbor constraint.

[0094] In some embodiments, such as this embodiment, the third confirmation unit further includes a third screening unit, a fourth screening unit, a fifth screening unit, a sixth screening unit, and a seventh screening unit.

[0095] The third filtering unit is used to filter all candidate grids according to the state constraint to obtain a first candidate grid, wherein the state constraint is that the state information of the candidate grid is passable;

[0096] The fourth filtering unit is used to filter the first candidate mesh according to the hierarchical constraint to obtain a second candidate mesh, wherein the hierarchical constraint is that the hierarchical information of the candidate mesh is the same as the hierarchical information of the target mesh;

[0097] The fifth filtering unit is used to filter the second candidate mesh according to the first spatial constraint to obtain a third candidate mesh, wherein the first spatial constraint is that the candidate mesh and the target mesh are spatially aligned in the non-directional dimension;

[0098] The sixth filtering unit is used to filter the third candidate mesh according to the first directional constraint to obtain a fourth candidate mesh, wherein the first directional constraint is that the candidate mesh is located in the target direction of the target mesh;

[0099] The seventh filtering unit is used to filter the fourth candidate grid according to the first nearest neighbor constraint to obtain the nearest neighbor grid, wherein the first nearest neighbor constraint is that the candidate grid is closest to the target grid.

[0100] In some embodiments, such as this one, the topology table construction apparatus 200 further includes a second acquisition unit and a first generation unit.

[0101] The second acquisition unit is used to acquire the attribute information of each Beidou grid cell, wherein the attribute information includes at least grid ID, grid code, latitude and longitude, elevation, three-dimensional spatial points and status information;

[0102] The first generation unit is used to generate a grid space attribute table based on the attribute information, and to create a spatial index and a regular index for the grid space attribute table to obtain the preset grid space data table.

[0103] In some embodiments, such as this one, the topology table construction apparatus 200 further includes a third acquisition unit, a fourth acquisition unit, and a first configuration unit.

[0104] The third acquisition unit is used to acquire the spatial range of the static obstacle and the spatial range of the preset grid spatial data table to obtain the first spatial range and the second spatial range.

[0105] The fourth acquisition unit is used to acquire the intersection of the first spatial range and the second spatial range if the first spatial range intersects with the second spatial range;

[0106] The first configuration unit is used to configure the static state of the grids located in the intersection of the preset grid space data table as impassable.

[0107] In some embodiments, such as this one, the topology table construction apparatus 200 further includes a fifth acquisition unit and a second configuration unit.

[0108] The fifth acquisition unit is used to acquire preset dynamic obstacle information and real-time detection data.

[0109] The second configuration unit is used to configure the dynamic state of each grid in the preset grid space data table based on the preset dynamic obstacle information and the real-time detection data.

[0110] It should be noted that those skilled in the art can clearly understand that the construction device for the above-mentioned topology table and the specific implementation process of each unit can be referred to the corresponding description in the foregoing method embodiments. For the sake of convenience and brevity, they will not be repeated here.

[0111] The aforementioned apparatus for constructing the topological relation table can be implemented as a computer program, which can, for example... Figure 10 It runs on the electronic device shown.

[0112] Please see Figure 10 , Figure 10 This is a schematic block diagram of an electronic device provided in an embodiment of this application. It can be a terminal or a server. The terminal can be an electronic device with communication functions, such as a smartphone, tablet, laptop, desktop computer, personal digital assistant, or wearable device. The server can be a standalone server or a server cluster composed of multiple servers.

[0113] See Figure 10 The electronic device 300 includes a processor 302, a memory, and a network interface 305 connected via a system bus 301. The memory may include a non-volatile storage medium 303 and internal memory 304.

[0114] The non-volatile storage medium 303 can store an operating system 3031 and a computer program 3032. When the computer program 3032 is executed, it causes the processor 302 to execute a method for constructing a topology table.

[0115] The processor 302 provides computing and control capabilities to support the operation of the entire electronic device 300.

[0116] The internal memory 304 provides an environment for the execution of the computer program 3032 in the non-volatile storage medium 303. When the computer program 3032 is executed by the processor 302, the processor 302 can execute a method for constructing a topology table.

[0117] This network interface 305 is used for communication with other devices. Those skilled in the art will understand that... Figure 10The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device 300 to which the present application is applied. The specific electronic device 300 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0118] It should be understood that in the embodiments of this application, the processor 302 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (FSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0119] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0120] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program. When executed by a processor, the computer program implements any embodiment of the above-described method for constructing the topological relation table.

[0121] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0122] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0123] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for constructing a topological relation table, characterized in that, The method includes: Obtain the attribute information of each BeiDou grid cell, wherein the attribute information includes at least grid ID, grid code, latitude and longitude, elevation, three-dimensional spatial points, and status information; A grid space attribute table is generated based on the attribute information, and a spatial index and a regular index are created for the grid space attribute table to obtain a preset grid space data table. Obtain the target grid from the preset grid space data table; The nearest neighbor meshes of the target mesh in each direction are determined according to preset constraints; Calculate the three-dimensional distance between the target mesh and each of the nearest neighbor meshes to obtain cost information; A topology table is constructed based on the target grid, the nearest neighbor grid, and the cost information; The step of obtaining the target grid from the preset grid space data table includes: The preset grid spatial data table is filtered according to the target level to obtain the first candidate target grid; The grids in the first candidate target grids that are statically passable and dynamically empty are selected as the second candidate target grids. The grids in the second candidate target grid are sequentially selected as the target grids.

2. The method as described in claim 1, characterized in that, The preset constraints include state constraints, hierarchical constraints, spatial constraints, directional constraints, and nearest neighbor constraints. The step of determining the nearest neighbor meshes of the target mesh in each direction according to the preset constraints includes: Select a direction from the optional directions of the target grid that does not have the nearest neighbor grid as the target direction, and confirm the spatial constraints, directional constraints and nearest neighbor constraints based on the target direction to obtain the first spatial constraints, the first directional constraints and the first nearest neighbor constraints. Based on the state constraints, the hierarchical constraints, the first spatial constraints, the first directional constraints, and the first nearest neighbor constraints, the nearest neighbor grid in the target direction is identified.

3. The method as described in claim 2, characterized in that, The step of determining the nearest neighbor grid in the target direction based on the state constraint, the hierarchical constraint, the first spatial constraint, the first directional constraint, and the first nearest neighbor constraint includes: All candidate grids are filtered according to the state constraint to obtain a first candidate grid, wherein the state constraint is that the state information of the candidate grid is passable; The first candidate mesh is filtered according to the hierarchical constraint to obtain the second candidate mesh, wherein the hierarchical constraint is that the hierarchical information of the candidate mesh is the same as the hierarchical information of the target mesh; The second candidate mesh is filtered according to the first spatial constraint to obtain a third candidate mesh, wherein the first spatial constraint is that the candidate mesh and the target mesh are spatially aligned in the non-directional dimension; The third candidate mesh is filtered according to the first directional constraint to obtain a fourth candidate mesh, wherein the first directional constraint is that the candidate mesh is located in the target direction of the target mesh; The fourth candidate grid is filtered according to the first nearest neighbor constraint to obtain the nearest neighbor grid, wherein the first nearest neighbor constraint is that the candidate grid is closest to the target grid.

4. The method as described in claim 1, characterized in that, The method further includes: The spatial range of static obstacles and the spatial range of the preset grid spatial data table are obtained to obtain a first spatial range and a second spatial range; If the first spatial range intersects with the second spatial range, then the intersection of the first spatial range and the second spatial range is obtained; Configure the static state of the grids located in the intersection of the preset grid space data table as impassable.

5. The method as described in claim 1, characterized in that, The method further includes: Acquire preset dynamic obstacle information and real-time detection data; The dynamic state of each grid in the preset grid space data table is configured based on the preset dynamic obstacle information and the real-time detection data.

6. A device for constructing a topological relation table, characterized in that, The device includes: The second acquisition unit is used to acquire the attribute information of each Beidou grid cell, wherein the attribute information includes at least grid ID, grid code, latitude and longitude, elevation, three-dimensional spatial points and status information; The first generation unit is used to generate a grid space attribute table based on the attribute information, and to create a spatial index and a regular index for the grid space attribute table to obtain a preset grid space data table. The first acquisition unit is used to acquire the target grid from the preset grid space data table; The first confirmation unit is used to confirm the nearest neighbor grids of the target grid in each direction according to preset constraints. The first computing unit is used to calculate the three-dimensional distance between the target grid and each of the nearest neighbor grids to obtain cost information; The first construction unit is used to construct a topology table based on the target grid, the nearest neighbor grid, and the cost information; The first acquisition unit includes: The first filtering unit is used to filter the preset grid spatial data table according to the target level to obtain the first candidate target grid; The second filtering unit is used to select the grids in the first candidate target grids whose static state is passable and whose dynamic state is empty as the second candidate target grids. The second confirmation unit is used to sequentially identify the grids in the second candidate target grids as the target grids.

7. An electronic device, characterized in that, The electronic device includes a memory and a processor connected to the memory; the memory is used to store a computer program; the processor is used to run the computer program stored in the memory to perform the steps of the method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, can implement the steps of the method as described in any one of claims 1-5.

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