CN113808145A - Patrol road network obtaining method of patrol mobile device and patrol mobile device - Google Patents
Patrol road network obtaining method of patrol mobile device and patrol mobile device Download PDFInfo
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Abstract
The embodiment of the application provides a patrol and examine road network acquisition method and a patrol and examine mobile device of a patrol and examine mobile device, wherein the method includes: acquiring point cloud data generated by moving the inspection mobile device according to a preset advancing sequence; determining a patrol operation area according to the point cloud data, and dividing the patrol operation area according to a preset division grid to obtain an initial grid map; determining path grids occupied by path points in the initial grid map according to the point cloud data, and identifying the path grids of the initial grid map to obtain a path grid map; determining branch nodes from the point cloud data according to the path grid graph; and determining a routing inspection road network according to the point cloud data and the branch nodes. Therefore, the point cloud data which are actually moved are obtained through the field inspection operation of the inspection mobile device, the path section can be divided based on the more accurate and real moving point cloud data, an accurate inspection road network is obtained, and the accuracy and the practicability of the inspection road network are improved.
Description
Technical Field
The invention relates to the technical field of mobile device inspection, in particular to a method and a device for acquiring an inspection road network of a mobile device and computer equipment.
Background
In the prior art, a point-hitting operation is performed in an established map by manually using a mouse, so that an inspection road network is formed. In the dotting operation process, better dotting precision is required, the precision of a map is required to be higher, and only specific dotting connecting line data can be generated by using mouse dotting. The obtained track may not meet the requirements of the mobile inspection device on kinematics or dynamics, and the path formed by dotting on the map sometimes is difficult to consider the special situation of the actual obstacle, so that the road network data actually formed is unavailable, and the problem that the practicability of the existing road network data is poor is caused.
Disclosure of Invention
In order to solve the above technical problem, embodiments of the present invention provide a network delay processing method and apparatus, and a mobile terminal.
In a first aspect, an embodiment of the present invention provides an inspection road network obtaining method for an inspection mobile device, including:
acquiring point cloud data generated by moving the inspection mobile device according to a preset advancing sequence;
determining an inspection operation area according to the point cloud data, and dividing the inspection operation area according to a preset division grid to obtain an initial grid map;
determining path grids occupied by path points in the initial grid map according to the point cloud data, and identifying the path grids of the initial grid map to obtain a path grid map;
determining branch nodes from the point cloud data according to the path grid graph;
and determining a routing inspection road network according to the point cloud data and the branch nodes.
Optionally, the determining branch nodes from the point cloud data according to the path grid graph includes:
traversing the path grid graph by adopting a preset grid array, and taking a central grid of the current grid array as a branch grid when the number of the road section grids in the traversed current grid array is greater than the number of the preset grids;
determining the position information of each branch grid according to the number of rows and columns of each branch grid in the path grid graph and the size information of the preset segmentation grid;
and taking the path point in the preset range of the position information of each branch grid as the branch node.
Optionally, the preset range includes a circular area with the circle center of each branch position information and the radius of the preset length, and the taking the path point in the preset range of each branch grid position information as the branch node includes:
and taking a path point which is closest to the branch position information in the circular area corresponding to the branch grid position information as the branch node.
Optionally, the determining a routing inspection road network according to the point cloud data and the branch nodes includes:
dividing the point cloud data according to the branch nodes to obtain a plurality of sections of sub paths;
and determining the routing inspection road network according to the plurality of sections of sub-paths.
Optionally, obtaining the routing inspection road network according to the multiple sections of sub-paths includes:
determining repeated sub-paths in the multiple sub-paths according to the starting point and the end point of each sub-path;
determining a path grid to which each path point in the repeated sub-paths belongs according to the size information of the preset segmentation grids and each path point in the repeated sub-paths;
fusing path points belonging to the same path grid to obtain fused path points, and determining a fused sub-path according to the fused path points;
and obtaining the routing inspection road network according to the fusion sub-path and the rest sub-paths except the repeated sub-paths in the multi-section sub-paths.
Optionally, the merging the path points belonging to the same path mesh to obtain a merged path point includes:
and determining the mean value of the position information of the path points belonging to the same path grid, and taking the mean value of the position information as the position information of the fusion path point.
Optionally, the method further includes:
acquiring a path deviation distance corresponding to the repeated path execution of the mobile inspection terminal device;
and determining the size information of the preset segmentation grids according to the path deviation distance.
Optionally, determining the inspection work area according to the point cloud data includes:
respectively determining a first boundary line and a second boundary line in the first direction, and a third boundary line and a fourth boundary line in the second direction according to the point cloud data;
and determining the inspection operation area according to the first boundary line, the second boundary line, the third boundary line and the fourth boundary line.
In a second aspect, an embodiment of the present invention provides an inspection mobile device, including:
the acquisition module is used for acquiring point cloud data generated by the patrol mobile device moving according to a preset advancing sequence;
the division module is used for determining an inspection operation area according to the point cloud data and dividing the inspection operation area according to a preset division grid to obtain an initial grid map;
the identification module is used for determining the path grids occupied by the path points in the initial grid map according to the point cloud data, and identifying the path grids of the initial grid map to obtain a path grid map;
the first determining module is used for determining branch nodes from the point cloud data according to the path grid graph;
and the second determining module is used for determining the routing inspection road network according to the point cloud data and the branch nodes.
Optionally, the first determining module is further configured to traverse the path grid map by using a preset grid array, and when the number of road section grids in the traversed current grid array is greater than the preset grid number, use a center grid of the current grid array as a branch grid;
determining the position information of each branch grid according to the number of rows and columns of each branch grid in the path grid graph and the size information of the preset segmentation grid;
and taking the path point in the preset range of the position information of each branch grid as the branch node.
Optionally, the first determining module is further configured to use a path point closest to the branch position information in the circular area corresponding to the branch grid position information as the branch node.
Optionally, the second determining module is further configured to segment the point cloud data according to the branch node to obtain multiple segments of sub-paths;
and determining the routing inspection road network according to the plurality of sections of sub-paths.
Optionally, the second determining module is further configured to determine a repeated sub-path in the multiple segments of sub-paths according to a start point and an end point of each sub-path;
determining a path grid to which each path point in the repeated sub-paths belongs according to the size information of the preset segmentation grids and each path point in the repeated sub-paths;
fusing path points belonging to the same path grid to obtain fused path points, and determining a fused sub-path according to the fused path points;
and obtaining the routing inspection road network according to the fusion sub-path and the rest sub-paths except the repeated sub-paths in the multi-section sub-paths.
Optionally, the second determining module is further configured to determine a mean value of the position information of the path points belonging to the same path grid, and use the mean value of the position information as the position information of the fused path point.
Optionally, the mobile device of patrolling and examining still includes:
the acquisition module is used for acquiring a path deviation distance corresponding to the repeated path execution of the mobile inspection terminal device;
and determining the size information of the preset segmentation grids according to the path deviation distance.
Optionally, the dividing module is further configured to determine a first boundary line and a second boundary line in the first direction, and a third boundary line and a fourth boundary line in the second direction, respectively, according to the point cloud data;
and determining the inspection operation area according to the first boundary line, the second boundary line, the third boundary line and the fourth boundary line.
In a third aspect, an embodiment of the present invention provides an inspection mobile device, including a memory and a processor, where the memory is used to store a computer program, and the computer program executes the inspection road network obtaining method of the mobile device provided in the first aspect when the processor runs.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program, and when the computer program runs on a processor, the method for obtaining an inspection road network of a mobile device according to the first aspect is executed.
The inspection road network obtaining method, the inspection mobile device and the computer readable storage medium of the inspection mobile device provided by the application obtain point cloud data generated by the inspection mobile device moving according to a preset advancing sequence; determining an inspection operation area according to the point cloud data, and dividing the inspection operation area according to a preset division grid to obtain an initial grid map; determining path grids occupied by path points in the initial grid map according to the point cloud data, and identifying the path grids of the initial grid map to obtain a path grid map; determining branch nodes from the point cloud data according to the path grid graph; and determining a routing inspection road network according to the point cloud data and the branch nodes. Therefore, the point cloud data which are actually moved are obtained through the field inspection operation of the inspection mobile device, the path section can be divided based on the more accurate and real moving point cloud data, an accurate inspection road network is obtained, and the accuracy and the practicability of the inspection road network are improved.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings required to be used in the embodiments will be briefly described below, and it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope of the present invention. Like components are numbered similarly in the various figures.
Fig. 1 is a schematic flow chart illustrating an inspection road network obtaining method of an inspection mobile device according to an embodiment of the present disclosure;
fig. 2A is a schematic diagram illustrating a moving direction of the inspection mobile device according to the embodiment of the application;
fig. 2B shows a schematic diagram of path point cloud data of the mobile inspection device according to the embodiment of the present application;
FIG. 3 is a schematic diagram illustrating an inspection operation area according to an embodiment of the present disclosure;
FIG. 4A is a schematic diagram of an initial grid map provided by embodiments of the present application;
FIG. 4B is a schematic diagram of a path grid diagram provided by an embodiment of the present application;
FIG. 5A is a schematic diagram illustrating a grid array traversal scenario provided by embodiments of the present application;
FIG. 5B is a schematic diagram illustrating another trellis array traversal scenario provided by an embodiment of the present application;
FIG. 5C is a schematic diagram illustrating another trellis array traversal scenario provided by an embodiment of the present application;
FIG. 6 is a schematic diagram illustrating a branch point marking provided by an embodiment of the present application;
fig. 7 is a schematic diagram illustrating an inspection road network according to an embodiment of the present disclosure;
fig. 8 is a schematic flow chart illustrating a step S104 of the inspection road network obtaining method of the inspection mobile device according to the embodiment of the present application;
fig. 9 shows a distribution diagram of branch nodes provided by an embodiment of the present application;
fig. 10 is a schematic flow chart illustrating a step S105 of the inspection road network obtaining method of the inspection mobile device according to the embodiment of the present application;
fig. 11 shows a schematic structural diagram of an inspection mobile device according to an embodiment of the application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments.
The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
Hereinafter, the terms "including", "having", and their derivatives, which may be used in various embodiments of the present application, are intended to indicate only specific features, numbers, steps, operations, elements, components, or combinations of the foregoing, and should not be construed as first excluding the existence of, or adding to, one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
Furthermore, the terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of the present application belong. The terms (such as those defined in commonly used dictionaries) should be interpreted as having a meaning that is consistent with their contextual meaning in the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in various embodiments.
Example 1
The embodiment of the disclosure provides a patrol road network obtaining method of a patrol mobile device.
Specifically, referring to fig. 1, the method for acquiring an inspection road network of an inspection mobile device includes:
and S101, acquiring point cloud data generated by the inspection mobile device moving according to a preset advancing sequence.
In this embodiment, the inspection mobile device is a mobile device capable of performing a specific inspection task, for example, the inspection mobile device can inspect the mobile device for road surface conditions, which is not limited herein. Through patrolling and examining mobile device teaching and patrolling and examining once, the point cloud data of record can obtain to patrol and examine the mobile device and remove the point cloud data of actually producing at the road surface according to predetermineeing the order of marcing, this kind of mode of this embodiment and the manual work is got the operation and is formed the path point and compare in the map, can acquire the actual point cloud data of patrolling and examining the mobile device and marcing on the road surface, and the authenticity is higher.
The following describes the distance of the inspection scene of the inspection mobile device with reference to fig. 2A. Referring to fig. 2A, arrows in fig. 2A indicate the traveling directions of corresponding path segments, the numbers of the arrows indicate the sequence of the corresponding path segments, and in fig. 2A, the endpoints L1, L2, L3 and L4 of each path in the moving process of the inspection mobile device move according to the sequential traveling sequence of (1) L2 → (2) L2L3 → (3) L3L4 → (4) L4L1 → (5) L1L3 → (6) L3L2 → (7) L2L 4. Acquiring point cloud data, such as a plurality of point cloud data P marked by L1L2, during the moving process of the mobile inspection device, in this embodiment, the point cloud data P is linear point cloud data, and storing the linear point cloud data, where the stored point cloud may be set as { P |i＝(xi，yi)，i＝0，1，2，...}。
Referring to fig. 2B, the movement is performed according to the sequential progression order of (1) L1L2 → (2) L2L3 → (3) L3L4 → (4) L4L1 → (5) L1L3 → (6) L3L2 → (7) L2L4, and a plurality of point cloud data P are collected on each path segment of L1L2 → (2) L2L3 → (3) L3L4 → (4) L4L1 → (5) L1L3 → (6) L3L2 → (7) L2L4, so that the actually collected point cloud data more conforms to the movement reality of the inspection device.
And S102, determining an inspection operation area according to the point cloud data, and dividing the inspection operation area according to a preset division grid to obtain an initial grid map.
Optionally, the determining the inspection work area according to the point cloud data in step S102 includes:
respectively determining a first boundary line and a second boundary line in the first direction, and a third boundary line and a fourth boundary line in the second direction according to the point cloud data;
and determining the inspection operation area according to the first boundary line, the second boundary line, the third boundary line and the fourth boundary line.
Referring to fig. 3, all the point cloud data in fig. 3 are distributed in the corresponding inspection operation area, according to the position information of the cloud data of each point, an easst path point, a westest path point, a soutest path point and a northest path point can be determined, a straight line is made through the northest path point along the east-west direction to obtain a first boundary line W1, a straight line is made through the soutest path point along the east-west direction to obtain a second boundary line W2, a straight line is made through the easst path point along the north-south direction to obtain a third boundary line W3, a straight line is made through the westest path point along the north-south direction to obtain a fourth boundary line W4, and the inspection operation area S is obtained from the first boundary line W1, the second boundary line W2, the third boundary line W3 and the fourth boundary line W4.
In this embodiment, the preset division grid is used for dividing the inspection work area to obtain an initial grid map. Referring to fig. 4A, the inspection work area S is divided into an initial grid map according to a preset division grid, the initial grid map includes a plurality of initial grids 401, and the size of each initial grid is the same as the size of the preset division grid.
Optionally, the method for obtaining an inspection road network of the inspection mobile device further includes:
acquiring a path deviation distance corresponding to the repeated path execution of the mobile inspection terminal device;
and determining the size information of the preset segmentation grids according to the path deviation distance.
Referring to fig. 2B again, the end points of the path L2L3 and the path L3L2 are the same and are repeated paths, the path deviation distance d between the routing inspection mobile terminal device execution path L2L3 and the path L3L2 is determined, and the size of the preset partition is determined to be 2d, so that the preset partition is a rectangular grid with the side length of 2d, and when the preset partition is used for partitioning the inspection work area, it is ensured that the similar points in the repeated paths can be correspondingly partitioned into the same rectangular grid.
Step S103, determining path grids occupied by path points in the initial grid map according to the point cloud data, and identifying the path grids of the initial grid map to obtain a path grid map.
In this embodiment, the number of rows where the path mesh occupied by the path point is located is calculated by formula 1, where formula 1:
the number of columns in which the path grid occupied by the path points is located is calculated using equation 2,
wherein row represents the number of lines of the path grid occupied by the path point, col represents the number of lines of the path grid occupied by the path point, x represents the first direction position data of the path point cloud, y represents the second direction position data, d represents the side length of the preset segmentation lattice,
an integer representing a quotient by which x is divided down,
an integer representing the quotient by which y is divided down.
In this embodiment, the path mesh of the initial mesh map may be identified by color filling, or the path mesh of the initial mesh map may be identified by number marking. Referring to fig. 4B, the path mesh of the initial mesh map is identified by using a color filling method, so as to obtain a path mesh map 40. There are multiple path grids filled with colors in path grid map 40, and each path grid corresponds to at least 1 path point.
And step S104, determining branch nodes from the point cloud data according to the path grid graph.
In this embodiment, according to the actual situation of movement, the path grid map in fig. 4B is sequentially traversed from left to right and from top to bottom by using a preset grid array, and when the number of road segment grids in the traversed current grid array is greater than the preset grid number, it is described that a branch point exists here, the central grid of the current grid array is taken as a branch grid, and a path point is determined from the path points in the branch grid as a branch node.
Referring to fig. 5A, 5B, and 5C, more than 4 meshes of the 8 meshes around the central mesh 501 of the current mesh array K1 in fig. 5A are path meshes, and the central mesh 501 is a branch mesh. More than 4 of the 8 meshes around the central mesh 502 of the current mesh array K2 in fig. 5B are path meshes, and the central mesh 502 is a branch mesh. More than 4 meshes out of 8 meshes around the central mesh 503 of the current mesh array K3 in fig. 5C are path meshes, and the central mesh 503 is a branch mesh. One path point is selected as a branch node from among the path points of the center mesh 501, the center mesh 502, and the center mesh 503.
And S105, determining a routing inspection road network according to the point cloud data and the branch nodes.
Referring to fig. 6 and 7, in fig. 6, branch nodes a, B, C, D, and E are marked in the point cloud data P, and corresponding routing inspection road networks are obtained according to the branch nodes a, B, C, D, and E.
Referring to fig. 7, the routing inspection road network includes a branch node a, a branch node B, a branch node C, a branch node D, a branch node E, and an edge connecting two branch nodes.
In this embodiment, after the routing inspection road network is obtained through calculation, the routing inspection road network can be used for multiple times in the subsequent process, the routing inspection road network is used for a path selection algorithm, the obtained segmented road network data can be well used in an a-star algorithm and a Dijkstra algorithm, the application range of the routing inspection road network is wide, and the actual application degree is improved.
Therefore, a mode of constructing a road network by manual dotting is avoided, the point cloud data which is actually moved is obtained through the field inspection operation of the inspection mobile device, and the path section is divided based on the real point cloud data, so that a real and accurate inspection road network can be obtained, and the practicability and accuracy of the inspection road network are improved.
Optionally, referring to fig. 8, step S104 includes:
and step S1041, traversing the path grid map by adopting a preset grid array, and taking the central grid of the current grid array as a branch grid when the number of the road section grids in the traversed current grid array is larger than the preset grid number.
Step S1042, determining position information of each branch grid according to the number of rows and columns of each branch grid in the path grid map and the size information of the preset division grid.
Step S1043, taking the path point in the preset range of the position information of each branch grid as the branch node.
In the present embodiment, the path points within the range of each branch mesh position information are taken as branch points. Therefore, the branch node can be accurately selected, so that the accurate routing inspection network can be obtained according to the branch node.
In step S1041, the preset grid array may be a 3 × 3 grid array, and the number of preset grids may be set to 4. Referring again to fig. 5B, in fig. 5B, the current grid array K2 includes 9 grids, more than 4 grids of 8 grids around the central grid 502 are path grids, and the central grid 502 is a branch grid. Similarly, the current grid array K3 in fig. 5C includes 9 grids, more than 4 grids out of 8 grids around the central grid 503 are path grids, and the central grid 503 is a branch grid.
In this embodiment, the step S1042 includes the following steps:
determining first direction position information of each branch grid according to a formula 3, and determining second direction position information of each branch grid according to a formula 4;
equation 3: x1 ═ rowAXd, where x1 denotes the first direction position data of the branch grid, rowAThe number of lines of the branch grid is shown, and d is the side length of the preset segmentation grid.
Equation 4: y1 ═ colAXd where y1 denotes second-direction position data of the branch grid, colAThe number of lines of the branch grid is shown, and d is the side length of the preset segmentation grid.
Optionally, step S1043 includes:
and taking a path point which is closest to the branch position information in the circular area corresponding to the branch grid position information as the branch node.
And calculating the path points in the stored path point cloud which meet the condition that the position information of each branch grid is taken as the center of a circle and the side length of the preset segmentation grid is taken as the radius, and if a plurality of continuous path points meet the condition, only one path point is selected. Because the circular area may include more than one point, and may be a plurality of points, only one point needs to be selected as a node, and the point closest to the center of the circle can be used as an actual branch node. Referring to fig. 9, regarding the branch mesh position information PA as the center of the circle, there are 3 path points P1, P2, and P3 in the circle with the side length d of the preset partition as the radius, and a path point P2 closest to the branch mesh position information PA is selected from the 3 path points P1, P2, and P3 as the branch point. Regarding the branch mesh position information PB as the center, there are 3 path points P4, P5, and P6 in a circle having a radius of the side length d of the preset segment, and a path point P4 closest to the branch mesh position information PB is selected as a branch point from the 3 path points P4, P5, and P6.
Optionally, referring to fig. 10, step S104 includes:
step S1051, dividing the point cloud data according to the branch nodes to obtain a plurality of sections of sub paths;
step S1052, determining the routing inspection road network according to the plurality of sub paths.
Referring to fig. 6 again, the point cloud data P includes branch nodes marked, a branch node a, a branch node B, a branch node C, a branch node D, and a branch node E, where the branch node a and the branch node B form a sub-path AB, the branch node B and the branch node C form a sub-path BC, the branch node C and the branch node D form a sub-path CD, the branch node D and the branch node a form a sub-path DA, the branch node a and the branch node E form a sub-path AE, the branch node E and the branch node C form a sub-path EC, the branch node C and the branch node B form a sub-path CB, the branch node B and the branch node E form a sub-path BE, and the branch node E and the branch node D form a sub-path ED. When there is no duplicate path, the route inspection network can be directly configured from the sub-paths, and when there is a sub-path CB and a sub-path BC as shown in fig. 6, the duplicate sub-path CB and sub-path BC are merged to obtain the route inspection network as shown in fig. 7.
Optionally, step S1051 includes:
determining repeated sub-paths in the multiple sub-paths according to the starting point and the end point of each sub-path;
determining a path grid to which each path point in the repeated sub-paths belongs according to the size information of the preset segmentation grids and each path point in the repeated sub-paths;
fusing path points belonging to the same path grid to obtain fused path points, and determining a fused sub-path according to the fused path points;
and obtaining the routing inspection road network according to the fusion sub-path and the rest sub-paths except the repeated sub-paths in the multi-section sub-paths.
Referring to fig. 6 again, for sub-path CB and sub-path BC, since the end points are route point B and route point C, sub-path CB and sub-path BC form a repeated path. Referring to fig. 4A again, in the initial grid map, the length of each boundary line is obtained, the length of the first boundary line is located at the side length of the preset partition, the number of grid lines in the initial grid map can be obtained, the length of the third boundary line is divided by the side length of the preset partition, the number of grid lines in the initial grid map can be obtained, and the path grids to which the path points on the sub-path CB and the sub-path BC belong can be determined by combining the position information of the path points on the sub-path CB and the sub-path BC.
In this embodiment, the path points belonging to the same path grid may be averaged and fused, or the path points belonging to the same path grid may be averaged and fused, which is not limited herein.
In this way, the repeated sub-paths are fused, so that the connection relation between the sub-paths can be simplified, and further, the topological road network in the form of a graph structure can be obtained.
Optionally, the merging the path points belonging to the same path mesh to obtain a merged path point includes:
and determining the mean value of the position information of the path points belonging to the same path grid, and taking the mean value of the position information as the position information of the fusion path point.
For example, the path point p of the current sub-path BCi(xi,yi) And path point p of sub-path CBj(xj,yj) If the paths are located in the same path grid, the fused path points fused into the same path are recorded as
After the fusion, the routing inspection road network shown in fig. 7 can be obtained.
According to the inspection road network obtaining method of the inspection mobile device, point cloud data generated by the inspection mobile device moving according to a preset advancing sequence are obtained; determining an inspection operation area according to the point cloud data, and dividing the inspection operation area according to a preset division grid to obtain an initial grid map; determining path grids occupied by path points in the initial grid map according to the point cloud data, and identifying the path grids of the initial grid map to obtain a path grid map; determining branch nodes from the point cloud data according to the path grid graph; and determining a routing inspection road network according to the point cloud data and the branch nodes. Therefore, the point cloud data which are actually moved are obtained through the field inspection operation of the inspection mobile device, the path section can be divided based on the more accurate and real moving point cloud data, an accurate inspection road network is obtained, and the accuracy and the practicability of the inspection road network are improved.
Example 2
In addition, the embodiment of the disclosure provides a mobile device patrols and examines.
Specifically, as shown in fig. 11, the inspection mobile device 1100 includes:
an obtaining module 1101, configured to obtain point cloud data generated by moving the inspection mobile device according to a preset moving sequence;
the dividing module 1102 is configured to determine an inspection work area according to the point cloud data, and divide the inspection work area according to preset division grids to obtain an initial grid map;
an identification module 1103, configured to determine, according to the point cloud data, a path mesh occupied by path points in the initial mesh map, and identify the path mesh of the initial mesh map to obtain a path mesh map;
a first determining module 1104, configured to determine branch nodes from the point cloud data according to the path grid map;
a second determining module 1105, configured to determine a routing inspection road network according to the point cloud data and the branch nodes.
Optionally, the first determining module 1104 is further configured to traverse the path grid map by using a preset grid array, and when the number of road section grids in the traversed current grid array is greater than the preset grid number, use a center grid of the current grid array as a branch grid;
determining the position information of each branch grid according to the number of rows and columns of each branch grid in the path grid graph and the size information of the preset segmentation grid;
and taking the path point in the preset range of the position information of each branch grid as the branch node.
Optionally, the first determining module 1104 is further configured to use a path point closest to the branch position information in the circular area corresponding to the branch grid position information as the branch node.
Optionally, the second determining module 1105 is further configured to segment the point cloud data according to the branch nodes to obtain multiple segments of sub-paths;
and determining the routing inspection road network according to the plurality of sections of sub-paths.
Optionally, the second determining module 1105 is further configured to determine repeated sub-paths in the multiple sub-paths according to the starting point and the ending point of each sub-path;
determining a path grid to which each path point in the repeated sub-paths belongs according to the size information of the preset segmentation grids and each path point in the repeated sub-paths;
fusing path points belonging to the same path grid to obtain fused path points, and determining a fused sub-path according to the fused path points;
and obtaining the routing inspection road network according to the fusion sub-path and the rest sub-paths except the repeated sub-paths in the multi-section sub-paths.
Optionally, the second determining module 1105 is further configured to determine a mean value of the position information of the waypoints belonging to the same path grid, and use the mean value of the position information as the position information of the fused waypoint.
Optionally, the inspection mobile device 1100 further includes:
the acquisition module is used for acquiring a path deviation distance corresponding to the repeated path execution of the mobile inspection terminal device;
and determining the size information of the preset segmentation grids according to the path deviation distance.
Optionally, the dividing module 1102 is further configured to determine a first boundary line and a second boundary line in the first direction, and a third boundary line and a fourth boundary line in the second direction according to the point cloud data;
and determining the inspection operation area according to the first boundary line, the second boundary line, the third boundary line and the fourth boundary line.
The embodiment provides the method for acquiring the routing inspection road network of the routing inspection mobile device 1000 according to the routing inspection mobile device shown in the embodiment 1, and details are not repeated herein in order to avoid repetition.
The mobile inspection device provided by the embodiment obtains point cloud data generated by the mobile inspection device moving according to a preset advancing sequence; determining an inspection operation area according to the point cloud data, and dividing the inspection operation area according to a preset division grid to obtain an initial grid map; determining path grids occupied by path points in the initial grid map according to the point cloud data, and identifying the path grids of the initial grid map to obtain a path grid map; determining branch nodes from the point cloud data according to the path grid graph; and determining a routing inspection road network according to the point cloud data and the branch nodes. Therefore, the point cloud data which are actually moved are obtained through the field inspection operation of the inspection mobile device, the path section can be divided based on the more accurate and real moving point cloud data, an accurate inspection road network is obtained, and the accuracy and the practicability of the inspection road network are improved.
Example 3
Furthermore, an embodiment of the present disclosure provides an inspection mobile device, including a memory and a processor, where the memory stores a computer program, and the computer program, when running on the processor, executes the inspection road network obtaining method of the inspection mobile device provided in the above method embodiment 1.
The embodiment provides the method for acquiring the routing inspection road network of the routing inspection mobile device in embodiment 1, and is not repeated herein to avoid repetition.
Example 4
The present application further provides a computer-readable storage medium, where a computer program is stored, and when the computer program runs on the processor, the method for obtaining an inspection road network of an inspection mobile device according to embodiment 1 of the foregoing method is executed.
The computer-readable storage medium provided in this embodiment may be the method for obtaining an inspection road network of the inspection mobile device shown in embodiment 1, and is not described herein again to avoid repetition.
In this embodiment, the computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
In this embodiment, the computer-readable storage medium may be the method for obtaining the route network for routing inspection of the mobile device in embodiment 1, and is not described herein again to avoid repetition.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.
While the present embodiments have been described with reference to the accompanying drawings, it is to be understood that the invention is not limited to the precise embodiments described above, which are meant to be illustrative and not restrictive, and that various changes may be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (11)
1. An inspection road network obtaining method of an inspection mobile device is characterized by comprising the following steps:
acquiring point cloud data generated by moving the inspection mobile device according to a preset advancing sequence;
determining an inspection operation area according to the point cloud data, and dividing the inspection operation area according to a preset division grid to obtain an initial grid map;
determining path grids occupied by path points in the initial grid map according to the point cloud data, and identifying the path grids of the initial grid map to obtain a path grid map;
determining branch nodes from the point cloud data according to the path grid graph;
and determining a routing inspection road network according to the point cloud data and the branch nodes.
2. The method of claim 1, wherein determining branch nodes from the point cloud data according to the path grid graph comprises:
traversing the path grid graph by adopting a preset grid array, and taking a central grid of the current grid array as a branch grid when the number of the road section grids in the traversed current grid array is greater than the number of the preset grids;
determining the position information of each branch grid according to the number of rows and columns of each branch grid in the path grid graph and the size information of the preset segmentation grid;
and taking the path point in the preset range of the position information of each branch grid as the branch node.
3. The method according to claim 2, wherein the preset range includes a circular area with a circle center at each branch position information and a radius at a preset length, and the taking a path point in the preset range of each branch grid position information as the branch node includes:
and taking a path point which is closest to the branch position information in the circular area corresponding to the branch grid position information as the branch node.
4. The method of claim 1, wherein determining a routing inspection road network from the point cloud data and the branch nodes comprises:
dividing the point cloud data according to the branch nodes to obtain a plurality of sections of sub paths;
and determining the routing inspection road network according to the plurality of sections of sub-paths.
5. The method according to claim 4, wherein the obtaining the routing inspection road network according to the plurality of sections of sub-paths comprises:
determining repeated sub-paths in the multiple sub-paths according to the starting point and the end point of each sub-path;
determining a path grid to which each path point in the repeated sub-paths belongs according to the size information of the preset segmentation grids and each path point in the repeated sub-paths;
fusing path points belonging to the same path grid to obtain fused path points, and determining a fused sub-path according to the fused path points;
and obtaining the routing inspection road network according to the fusion sub-path and the rest sub-paths except the repeated sub-paths in the multi-section sub-paths.
6. The method according to claim 5, wherein said fusing path points belonging to the same path mesh to obtain fused path points comprises:
and determining the mean value of the position information of the path points belonging to the same path grid, and taking the mean value of the position information as the position information of the fusion path point.
7. The method of claim 1, further comprising:
acquiring a path deviation distance corresponding to the repeated path execution of the mobile inspection terminal device;
and determining the size information of the preset segmentation grids according to the path deviation distance.
8. The method of claim 1, wherein determining an inspection work area from the point cloud data comprises:
respectively determining a first boundary line and a second boundary line in the first direction, and a third boundary line and a fourth boundary line in the second direction according to the point cloud data;
and determining the inspection operation area according to the first boundary line, the second boundary line, the third boundary line and the fourth boundary line.
9. A mobile device patrols and examines, its characterized in that includes:
the acquisition module is used for acquiring point cloud data generated by the patrol mobile device moving according to a preset advancing sequence;
the division module is used for determining an inspection operation area according to the point cloud data and dividing the inspection operation area according to a preset division grid to obtain an initial grid map;
the identification module is used for determining the path grids occupied by the path points in the initial grid map according to the point cloud data, and identifying the path grids of the initial grid map to obtain a path grid map;
the first determining module is used for determining branch nodes from the point cloud data according to the path grid graph;
and the second determining module is used for determining the routing inspection road network according to the point cloud data and the branch nodes.
10. An inspection mobile device, comprising a memory for storing a computer program that executes the inspection road network acquisition method of the mobile device according to any one of claims 1 to 9 when the processor is operated, and a processor.
11. A computer-readable storage medium storing a computer program which, when executed on a processor, executes the patrol road network acquisition method for a mobile device according to any one of claims 1 to 9.
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