CN113808145B - Inspection road network acquisition method of inspection mobile device and inspection mobile device - Google Patents
Inspection road network acquisition method of inspection mobile device and inspection mobile device Download PDFInfo
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Abstract
The embodiment of the application provides a patrol road network acquisition method of a patrol mobile device and the patrol mobile device, wherein the method comprises the following steps: 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 a path grid occupied by the path points in the initial grid graph according to the point cloud data, and identifying the path grid of the initial grid graph to obtain a path grid graph; determining branch nodes from the point cloud data according to the path grid diagram; and determining the routing inspection road network according to the point cloud data and the branch nodes. Therefore, the actually-moved point cloud data is acquired through the on-site inspection operation of the inspection mobile device, the path segment can be segmented 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 present application relates to the field of mobile device inspection technologies, and in particular, to a method and an apparatus for acquiring an inspection road network of a mobile device, and a computer device.
Background
In the prior art, a pointing operation is performed in an established map by using a mouse manually, so that a patrol road network is formed. In such a dotting operation, a relatively good dotting accuracy is required, the accuracy of the map is required to be relatively high, and only specific dotting link data can be generated using a mouse for dotting. The obtained track may not meet the kinematic or dynamic requirements of the inspection mobile device, and the special situation that the obstacle exists in the actual situation is difficult to consider in some cases in the path formed by dotting in the map, so that the road network data formed in actual situation is unavailable, and the problem that the existing road network data is poor in practicability is caused.
Disclosure of Invention
In order to solve the technical problems, the embodiment of the application provides a patrol road network acquisition method of a patrol mobile device and the patrol mobile device.
In a first aspect, an embodiment of the present application provides a method for acquiring a routing inspection road network of a routing inspection mobile device, including:
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 diagram;
determining a path grid occupied by path points in the initial grid graph according to the point cloud data, and identifying the path grid of the initial grid graph to obtain a path grid graph;
determining branch nodes from the point cloud data according to the path grid diagram;
and determining a routing inspection road network according to the point cloud data and the branch nodes.
Optionally, the determining a branch node from the point cloud data according to the path mesh map includes:
traversing the path grid diagram by adopting a preset grid array, and taking the central grid of the current grid array as a branch grid when the number of road section grids in the traversed current grid array is larger than the number of the preset grids;
determining the position information of each branch grid according to the row number and the column number of each branch grid in the path grid diagram and the size information of the preset division grid;
and taking the path points in the preset range of the position information of each branch grid as the branch nodes.
Optionally, the preset range includes a circular area with each piece of branch position information as a center and a preset length as a radius, and the taking a path point in the preset range of each piece of branch grid position information as the branch node includes:
and taking a path point closest to the branch position information in a circular area corresponding to the branch grid position information as the branch node.
Optionally, the determining the routing network according to the point cloud data and the branch node 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 multi-section sub-paths.
Optionally, the obtaining the routing inspection road network according to the multi-segment sub-path includes:
determining repeated sub-paths in the multi-section 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-path belongs according to the size information of the preset division grid and each path point in the repeated sub-path;
fusing the path points belonging to the same path grid to obtain fused path points, and determining fused sub-paths 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 fusing the path points belonging to the same path grid to obtain a fused path point includes:
and determining the position information mean value of the path points belonging to the same path grid, and taking the position information mean value as the position information of the fusion path points.
Optionally, the method further comprises:
obtaining a corresponding path deviation distance when the patrol mobile terminal device executes a repeated path;
and determining the size information of the preset division lattice according to the path deviation distance.
Optionally, the determining the patrol operation area according to the point cloud data includes:
determining a first boundary line and a second boundary line in a first direction and a third boundary line and a fourth boundary line in a 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 application provides a patrol mobile device, including:
the acquisition module is used for acquiring the point cloud data generated by the movement of the inspection mobile device according to the preset advancing sequence;
the dividing module is used for 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 diagram;
the identification module is used for determining a path grid occupied by the path points in the initial grid graph according to the point cloud data, and identifying the path grid of the initial grid graph to obtain a path grid graph;
the first determining module is used for determining branch nodes from the point cloud data according to the path grid diagram;
and the second determining module is used for determining a 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 graph by using a preset grid array, and when the number of road section grids in the traversed current grid array is greater than the number of preset grids, take a central grid of the current grid array as a branch grid;
determining the position information of each branch grid according to the row number and the column number of each branch grid in the path grid diagram and the size information of the preset division grid;
and taking the path points in the preset range of the position information of each branch grid as the branch nodes.
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 a multi-segment sub-path;
and determining the routing inspection road network according to the multi-section sub-paths.
Optionally, the second determining module is further configured to determine a repeated sub-path in the multiple sections 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-path belongs according to the size information of the preset division grid and each path point in the repeated sub-path;
fusing the path points belonging to the same path grid to obtain fused path points, and determining fused sub-paths 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 position information average value of the path points belonging to the same path grid, and use the position information average value as the position information of the fused path points.
Optionally, the inspection mobile device further includes:
the acquisition module is used for acquiring the corresponding path deviation distance when the patrol mobile terminal device executes the repeated path;
and determining the size information of the preset division lattice 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 according to the point cloud data, respectively;
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 application provides a patrol mobile device, including a memory and a processor, where the memory is configured to store a computer program, and the computer program executes, when the processor runs, a patrol road-network acquiring method of the mobile device provided in the first aspect.
In a fourth aspect, an embodiment of the present application provides a computer readable storage medium storing a computer program, where the computer program when run on a processor performs the inspection road network acquiring method of the mobile device provided in the first aspect.
The inspection road network acquisition method of the inspection mobile device, the inspection mobile device and the computer readable storage medium provided by the application acquire point cloud data generated by the movement of 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 diagram; determining a path grid occupied by path points in the initial grid graph according to the point cloud data, and identifying the path grid of the initial grid graph to obtain a path grid graph; determining branch nodes from the point cloud data according to the path grid diagram; and determining a routing inspection road network according to the point cloud data and the branch nodes. Therefore, the actually-moved point cloud data is acquired through the on-site inspection operation of the inspection mobile device, the path segment can be segmented 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 solutions of the present application, the drawings that are required for the embodiments will be briefly described, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope of the present application. Like elements are numbered alike in the various figures.
Fig. 1 is a flow diagram of an inspection road network acquiring method of an inspection mobile device according to an embodiment of the present application;
fig. 2A is a schematic diagram illustrating a moving direction of the inspection mobile device according to an embodiment of the present application;
fig. 2B illustrates a path point cloud data schematic diagram of the inspection mobile device according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an inspection operation area according to an embodiment of the present application;
FIG. 4A is a schematic diagram of an initial grid pattern provided by an embodiment of the present application;
FIG. 4B is a schematic diagram of a path trellis diagram provided by an embodiment of the present application;
FIG. 5A is a diagram illustrating a grid array traversal of an embodiment of the application;
FIG. 5B is a schematic diagram illustrating another grid array traversal scenario provided by an embodiment of the application;
FIG. 5C is a diagram illustrating another grid array traversal provided by an embodiment of the application;
FIG. 6 is a schematic diagram of a branch point marker according to an embodiment of the present application;
fig. 7 is a schematic diagram of an inspection road network according to an embodiment of the present application;
fig. 8 is a schematic flow chart of step S104 of the inspection road network acquiring method of the inspection mobile device according to the embodiment of the present application;
fig. 9 shows a schematic distribution diagram of a branching node according to an embodiment of the present application;
fig. 10 is a schematic flow diagram of step S105 of a method for acquiring a patrol road network of a patrol mobile device according to an embodiment of the present application;
fig. 11 is a schematic structural diagram of a patrol mobile device according to an embodiment of the application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments.
The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
The terms "comprises," "comprising," "including," or any other variation thereof, are intended to cover a specific feature, number, step, operation, element, component, or combination of the foregoing, which may be used in various embodiments of the present application, and are not intended to first exclude the presence of or increase the likelihood of 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 merely to distinguish between descriptions and should not 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 various embodiments of the application belong. The terms (such as those defined in commonly used dictionaries) will be interpreted as having a meaning that is the same as the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in connection with the various embodiments of the application.
Example 1
The embodiment of the disclosure provides a patrol road network acquisition method of a patrol mobile device.
Specifically, referring to fig. 1, the method for acquiring the inspection road network of the inspection mobile device includes:
step S101, the generated point cloud data of the inspection mobile device moving according to a preset advancing sequence is obtained.
In this embodiment, the inspection mobile device is a mobile device capable of performing a specific inspection task, for example, the inspection mobile device may be a road surface condition inspection mobile device, which is not limited herein. By teaching the inspection mobile device for one time and recording the point cloud data, the point cloud data actually produced by the inspection mobile device moving on the road surface according to the preset advancing sequence can be obtained.
The following describes a distance between inspection scenes of the inspection mobile device with reference to fig. 2A. Referring to fig. 2A, the arrow in fig. 2A indicates the traveling direction of the corresponding path segment, the number of the arrow indicates the sequence of the corresponding path segment, and fig. 2A shows the end point L1 of each path during the movement of the inspection mobile device,
L2, L3 and L4 are defined as (1) L1L 2. Fwdarw.2L 2L 3. Fwdarw.3L 3L 4. Fwdarw.4L 4L 1. Fwdarw.5)
The sequence of L1L 3- & gt (6) L3L 2- & gt (7) L2L4 is moved. In the moving process of the inspection mobile device, point cloud data, such as a plurality of point cloud data P marked by L1L2, are obtained, in this embodiment, the point cloud data P is linear point cloud data, the linear point cloud data is stored, and the stored point cloud can use { p|p } i ＝(x i ，y i )，i＝0，1，2，...}。
Referring to fig. 2B, the moving sequence of (1) L1L2→ (2) L2L3→ (3) L3L4→ (4) L4L1→ (5) L1L3→ (6) L3L2→ (7) L2L4 is performed, 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 accords with the moving situation of the inspection device.
Step S102, 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 diagram.
Optionally, in step S102, determining the patrol operation area according to the point cloud data includes:
determining a first boundary line and a second boundary line in a first direction and a third boundary line and a fourth boundary line in a 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 point cloud data, the easiest path point, the westst path point, the southwest path point and the northst path point can be determined, the northst path point is crossed to make a straight line along the east-west direction to obtain a first boundary W1, the southwest path point is crossed to make a straight line along the east-west direction to obtain a third boundary W3, the easiest path point is crossed to make a straight line along the north-south direction to obtain a fourth boundary W4, and the inspection operation area S is obtained by the first boundary W1, the second boundary W2, the third boundary W3 and the fourth boundary W4.
In this embodiment, the preset dividing grid is used to divide the inspection operation area to obtain the initial grid map. Referring to fig. 4A, the inspection operation area S is divided into an initial grid diagram according to a preset division grid, where the initial grid diagram 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 acquiring the inspection road network of the inspection mobile device further comprises the following steps:
obtaining a corresponding path deviation distance when the patrol mobile terminal device executes a repeated path;
and determining the size information of the preset division lattice according to the path deviation distance.
Referring to fig. 2B again, the end points of the path L2L3 and the path L3L2 are identical, and are repeated paths, the path deviation distance d between the path L2L3 and the path L3L2 executed by the inspection mobile terminal device is determined, and the size of the preset division lattice is determined to be 2d, so that the preset division lattice is a rectangular lattice with a side length of 2d, and when the preset division lattice is used for dividing the inspection operation area, it is ensured that similar points in the repeated paths can be correspondingly divided into the same rectangular lattice.
Step S103, determining a path grid occupied by the path points in the initial grid graph according to the point cloud data, and identifying the path grid of the initial grid graph to obtain a path grid graph.
In this embodiment, the path grid occupied by the path pointsThe number of rows is calculated using equation 1, equation 1:the number of columns of the path grid occupied by the path points is calculated using equation 2, +.>Wherein row represents the number of rows of the path grid occupied by the path points, col represents the number of rows of the path grid occupied by the path points, 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 division grid>Integer representing the quotient value divided by x down,/i>An integer representing the quotient value divided by y down.
In this embodiment, the path grid of the initial grid chart may be identified by using a color filling manner, or may be identified by using a digital marking manner. Referring to fig. 4B, the path grid of the initial grid chart is identified by using a color filling method, so as to obtain a path grid chart 40. The path grid map 40 has a plurality of color-filled path grids, each path grid corresponding to at least 1 path point.
And step S104, determining branch nodes from the point cloud data according to the path grid diagram.
In this embodiment, according to the actual situation of movement, the path grid diagram in fig. 4B is sequentially traversed from left to right and from top to bottom by using a preset grid array, when the number of road segment grids in the traversed current grid array is greater than the preset grid number, it is indicated that there are branch points, the central grid of the current grid array is used 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 out of 8 meshes around a center mesh 501 of the current mesh array K1 in fig. 5A are path meshes, and the center mesh 501 is a branch mesh. More than 4 of the 8 grids surrounding the center grid 502 of the current grid array K2 in fig. 5B are path grids, and the center grid 502 is a finger grid. More than 4 of 8 grids around the center grid 503 of the current grid array K3 in fig. 5C are path grids, and the center grid 503 is a branch grid. One path point is selected as a branching node from the path points of the center mesh 501, the center mesh 502, and the center mesh 503, respectively.
And step 105, 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 are marked in a plurality of point cloud data P, and a corresponding routing inspection road network is obtained according to the branch nodes a, B, C, D, and E.
Referring to fig. 7, the routing inspection network includes a branch node a, a branch node B, a branch node C, a branch node D, a branch node E, and edges connecting two branch nodes.
In this embodiment, after the routing inspection road network is obtained by calculation, the routing inspection road network can be used for multiple times in the following 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-algorithm and a Dijkstra algorithm, the application range of the routing inspection road network is wide, and the practical application degree is improved.
Therefore, the way of constructing the road network in a manual dotting way is avoided, the actually moving point cloud data is obtained through the field inspection operation of the inspection mobile device, the path segment is divided based on the real point cloud data, the 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:
step S1041, traversing the path grid graph by using a preset grid array, and taking the central grid of the current grid array as a branch grid when the number of road section grids in the traversed current grid array is greater than the preset grid number.
Step S1042, determining the position information of each branch grid according to the number of rows and columns of each branch grid in the path grid diagram and the size information of the preset division grid.
Step S1043, taking a path point within a preset range of the position information of each branch grid as the branch node.
In the present embodiment, a path point within the range of each branch grid position information is taken as a branch point. Thus, the branch node can be accurately selected, so that an accurate patrol network can be acquired according to the branch node.
In step S1041, the preset mesh array may be a 3×3 mesh array, and the preset mesh number 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 among 8 grids around the center grid 502 are path grids, and the center grid 502 is a finger grid. Similarly, the current grid array K3 in fig. 5C includes 9 grids, more than 4 grids among 8 grids around the center grid 503 are path grids, and the center grid 503 is a branch grid.
In the present embodiment, step S1042 includes the steps of:
determining first direction position information of each branch grid according to formula 3, and determining second direction position information of each branch grid according to formula 4;
equation 3: x1=row A X d, where x1 represents first direction position data of the branch grid, row A The number of rows where the branch grid is located is represented, and d represents the side length of the preset division grid.
Equation 4: y1=col A X d where y1 represents second direction position data of the branch grid, col A The number of rows where the branch grid is located is represented, and d represents the side length of the preset division grid.
Optionally, step S1043 includes:
and taking a path point closest to the branch position information in a circular area corresponding to the branch grid position information as the branch node.
And calculating the path points in the stored path point cloud, wherein the path points are satisfied in a circle taking the position information of each branch grid as the circle center and the side length of a preset division grid as the radius, and if a plurality of continuous path points satisfy the condition, only one of the path points is selected. Because the circular area may include more than one point, possibly multiple points, only one point needs to be selected as a node, and the closest point to the center of the circle can be used as an actual branch node. Referring to fig. 9, 3 path points P1, P2, P3 are located in a circle with the branch grid position information PA as a center and the side length d of the preset division grid as a radius, and a path point P2 closest to the branch grid position information PA is selected from the 3 path points P1, P2, P3 as a branching point. The 3 path points P4, P5, and P6 are located in a circle having the branch grid position information PB as the center and the side length d of the preset division grid as the radius, and the path point P4 closest to the branch grid position information PB is selected from the 3 path points P4, P5, and P6 as the branching point.
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 sub paths;
step S1052, determining the routing inspection road network according to the multi-segment sub-paths.
Referring to fig. 6 again, the plurality of point cloud data P marks branch nodes, including branch node a, branch node B, branch node C, branch node D, and branch node E, including branch node a and branch node B forming sub-path AB, including branch node B and branch node C forming sub-path BC, including branch node C and branch node D forming sub-path CD, including branch node D and branch node a forming sub-path DA, including branch node a and branch node E forming sub-path AE, including branch node E and branch node C forming sub-path EC, including branch node C and branch node B forming sub-path CB, including branch node B and branch node E forming sub-path BE, and including branch node E and branch node D forming sub-path ED. When there is no repeating path, the patrol road network can be directly formed according to each sub-path, and when there is a sub-path CB and a sub-path BC shown in FIG. 6, the repeated sub-paths CB and BC are fused to obtain the patrol road network shown in FIG. 7.
Optionally, step S1051 includes:
determining repeated sub-paths in the multi-section 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-path belongs according to the size information of the preset division grid and each path point in the repeated sub-path;
fusing the path points belonging to the same path grid to obtain fused path points, and determining fused sub-paths 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 the sub-paths CB and BC, since the end points are the path point B and the path point C, the sub-paths CB and BC form a duplicate path. Referring to fig. 4A again, in the initial grid diagram, the lengths of the boundary lines are obtained, the length of the first boundary line is located at the side length of the preset division grid, the grid line number in the initial grid diagram can be obtained, the length of the third boundary line is divided by the side length of the preset division grid, the grid line number in the initial grid diagram can be obtained, and the path grids of the path points on the sub-path CB and the sub-path BC 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 average values of the path points belonging to the same path grid may be fused, or the median values of the path points belonging to the same path grid may be 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 the topological road network in the form of a graph structure can be obtained.
Optionally, the fusing the path points belonging to the same path grid to obtain a fused path point includes:
and determining the position information mean value of the path points belonging to the same path grid, and taking the position information mean value as the position information of the fusion path points.
For example, when the path point p of the sub-path BC i (x i ,y i ) And path point p of sub-path CB j (x j ,y j ) Located on the same path grid, then the merged path points merged into the same path are marked asAfter fusion, the inspection road network shown in fig. 7 can be obtained.
According to the inspection road network acquisition method of the inspection mobile device, point cloud data generated by the movement of the inspection mobile device according to a preset advancing sequence are acquired; 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 diagram; determining a path grid occupied by path points in the initial grid graph according to the point cloud data, and identifying the path grid of the initial grid graph to obtain a path grid graph; determining branch nodes from the point cloud data according to the path grid diagram; and determining a routing inspection road network according to the point cloud data and the branch nodes. Therefore, the actually-moved point cloud data is acquired through the on-site inspection operation of the inspection mobile device, the path segment can be segmented 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 patrol mobile device.
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 advancing sequence;
the dividing module 1102 is configured to determine a routing inspection operation area according to the point cloud data, and divide the routing inspection operation area according to a preset division grid to obtain an initial grid map;
an identification module 1103, configured to determine a path grid occupied by a path point in the initial grid graph according to the point cloud data, and identify the path grid of the initial grid graph to obtain a path grid graph;
a first determining module 1104, configured to determine a branch node from the point cloud data according to the path mesh map;
a second determining module 1105 is configured to determine a routing network according to the point cloud data and the branch node.
Optionally, the first determining module 1104 is further configured to traverse the path grid graph by using a preset grid array, and when the number of road segments grids in the traversed current grid array is greater than the number of preset grids, take the central grid of the current grid array as a branch grid;
determining the position information of each branch grid according to the row number and the column number of each branch grid in the path grid diagram and the size information of the preset division grid;
and taking the path points in the preset range of the position information of each branch grid as the branch nodes.
Optionally, the first determining module 1104 is further configured to use a path point closest to the branch location information in the circular area corresponding to the branch grid location information as the branch node.
Optionally, the second determining module 1105 is further configured to segment the point cloud data according to the branch node to obtain a multi-segment sub-path;
and determining the routing inspection road network according to the multi-section sub-paths.
Optionally, the second determining module 1105 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-path belongs according to the size information of the preset division grid and each path point in the repeated sub-path;
fusing the path points belonging to the same path grid to obtain fused path points, and determining fused sub-paths 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 location information of the path points belonging to the same path grid, and use the mean value of the location information as the location information of the fused path points.
Optionally, the inspection mobile device 1100 further includes:
the acquisition module is used for acquiring the corresponding path deviation distance when the patrol mobile terminal device executes the repeated path;
and determining the size information of the preset division lattice 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, respectively;
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 present embodiment provides a method for acquiring a patrol road network of a patrol mobile device 1000, which can be the patrol mobile device shown in embodiment 1, and is not described herein again for avoiding repetition.
The inspection mobile device acquires point cloud data generated by the movement of 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 diagram; determining a path grid occupied by path points in the initial grid graph according to the point cloud data, and identifying the path grid of the initial grid graph to obtain a path grid graph; determining branch nodes from the point cloud data according to the path grid diagram; and determining a routing inspection road network according to the point cloud data and the branch nodes. Therefore, the actually-moved point cloud data is acquired through the on-site inspection operation of the inspection mobile device, the path segment can be segmented 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
In addition, an embodiment of the present disclosure provides a patrol mobile device, including a memory and a processor, where the memory stores a computer program, and the computer program executes the patrol road network acquisition method of the patrol mobile device provided in the foregoing method embodiment 1 when running on the processor.
The present embodiment provides a method for acquiring a patrol road network by using a patrol mobile device, which can be implemented by using a patrol mobile device as shown in embodiment 1, and in order to avoid repetition, a description thereof will be omitted.
Example 4
The application also provides a computer readable storage medium, on which a computer program is stored, which executes the inspection road network acquisition method of the inspection mobile device provided in the above method embodiment 1 when running on the processor.
The method for acquiring the patrol road network of the patrol mobile device according to embodiment 1 can be provided by the computer readable storage medium of this embodiment, and is not described herein again for avoiding repetition.
In the present embodiment, the computer readable storage medium may be a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, an optical disk, or the like.
The method for acquiring the patrol road network of the patrol mobile device according to embodiment 1 can be provided in the computer readable storage medium, and is not described herein again for avoiding 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 one … …" does not exclude the presence of other like elements in a process, method, article or terminal comprising the element.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are to be protected by the present application.
Claims (9)
1. The method for acquiring the patrol road network of the patrol 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 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 diagram;
determining a path grid occupied by path points in the initial grid graph according to the point cloud data, and identifying the path grid of the initial grid graph to obtain a path grid graph;
traversing the path grid diagram by adopting a preset grid array, and taking the central grid of the current grid array as a branch grid when the number of road section grids in the traversed current grid array is larger than the number of the preset grids;
determining the position information of each branch grid according to the row number and the column number of each branch grid in the path grid diagram and the size information of the preset division grid;
taking path points in a preset range of the position information of each branch grid as branch nodes;
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 multi-section sub-paths.
2. The method according to claim 1, wherein the preset range includes a circular area with each branch position information as a center and a preset length as a radius, and the taking a path point within the preset range of each branch grid position information as the branch node includes:
and taking a path point closest to the branch position information in a circular area corresponding to the branch grid position information as the branch node.
3. The method of claim 1, wherein said deriving the routing network from the multi-segment sub-path comprises:
determining repeated sub-paths in the multi-section 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-path belongs according to the size information of the preset division grid and each path point in the repeated sub-path;
fusing the path points belonging to the same path grid to obtain fused path points, and determining fused sub-paths 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.
4. A method according to claim 3, wherein the fusing the path points belonging to the same path grid to obtain the fused path points includes:
and determining the position information mean value of the path points belonging to the same path grid, and taking the position information mean value as the position information of the fusion path points.
5. The method according to claim 1, wherein the method further comprises:
obtaining a corresponding path deviation distance when the patrol mobile terminal device executes a repeated path;
and determining the size information of the preset division lattice according to the path deviation distance.
6. The method of claim 1, wherein the determining a patrol job area from the point cloud data comprises:
determining a first boundary line and a second boundary line in a first direction and a third boundary line and a fourth boundary line in a 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.
7. A patrol mobile device, comprising:
the acquisition module is used for acquiring the point cloud data generated by the movement of the inspection mobile device according to the preset advancing sequence;
the dividing module is used for 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 diagram;
the identification module is used for determining a path grid occupied by the path points in the initial grid graph according to the point cloud data, and identifying the path grid of the initial grid graph to obtain a path grid graph;
the first determining module is used for traversing the path grid graph by adopting a preset grid array, and taking the central grid of the current grid array as a branch grid when the number of road section grids in the traversed current grid array is larger than the preset grid number;
determining the position information of each branch grid according to the row number and the column number of each branch grid in the path grid diagram and the size information of the preset division grid;
taking path points in a preset range of the position information of each branch grid as branch nodes;
the second determining module is used for 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 multi-section sub-paths.
8. A patrol mobile device comprising a memory and a processor, the memory for storing a computer program which, when run by the processor, performs a patrol road-network acquisition method of a mobile device according to any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that it stores a computer program which, when run on a processor, performs the inspection road network acquisition method of a mobile device according to any one of claims 1 to 6.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101839701A (en) * | 2010-05-27 | 2010-09-22 | 中国科学院自动化研究所 | Method for automatically partitioning tree point cloud data |
| CN109118500A (en) * | 2018-07-16 | 2019-01-01 | 重庆大学产业技术研究院 | A kind of dividing method of the Point Cloud Data from Three Dimension Laser Scanning based on image |
| CN110780681A (en) * | 2019-11-26 | 2020-02-11 | 贵州电网有限责任公司 | Unmanned aerial vehicle autonomous inspection insulator path planning method based on laser point cloud |
| CN112014857A (en) * | 2020-08-31 | 2020-12-01 | 上海宇航系统工程研究所 | Three-dimensional laser radar positioning and navigation method for intelligent inspection and inspection robot |
| CN112033414A (en) * | 2020-09-11 | 2020-12-04 | 浙江华云清洁能源有限公司 | Unmanned aerial vehicle inspection route generation method, device, equipment and medium |
| CN112612273A (en) * | 2020-12-21 | 2021-04-06 | 南方电网电力科技股份有限公司 | Routing inspection robot obstacle avoidance path planning method, system, equipment and medium |
| KR20210063841A (en) * | 2019-11-25 | 2021-06-02 | 숭실대학교산학협력단 | Method of clustering 3d point cloud data and apparatuses operating the same |
| CN113238578A (en) * | 2021-05-11 | 2021-08-10 | 上海电力大学 | Routing planning method and system for power tower unmanned aerial vehicle inspection route |
-
2021
- 2021-09-30 CN CN202111161263.7A patent/CN113808145B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101839701A (en) * | 2010-05-27 | 2010-09-22 | 中国科学院自动化研究所 | Method for automatically partitioning tree point cloud data |
| CN109118500A (en) * | 2018-07-16 | 2019-01-01 | 重庆大学产业技术研究院 | A kind of dividing method of the Point Cloud Data from Three Dimension Laser Scanning based on image |
| KR20210063841A (en) * | 2019-11-25 | 2021-06-02 | 숭실대학교산학협력단 | Method of clustering 3d point cloud data and apparatuses operating the same |
| CN110780681A (en) * | 2019-11-26 | 2020-02-11 | 贵州电网有限责任公司 | Unmanned aerial vehicle autonomous inspection insulator path planning method based on laser point cloud |
| CN112014857A (en) * | 2020-08-31 | 2020-12-01 | 上海宇航系统工程研究所 | Three-dimensional laser radar positioning and navigation method for intelligent inspection and inspection robot |
| CN112033414A (en) * | 2020-09-11 | 2020-12-04 | 浙江华云清洁能源有限公司 | Unmanned aerial vehicle inspection route generation method, device, equipment and medium |
| CN112612273A (en) * | 2020-12-21 | 2021-04-06 | 南方电网电力科技股份有限公司 | Routing inspection robot obstacle avoidance path planning method, system, equipment and medium |
| CN113238578A (en) * | 2021-05-11 | 2021-08-10 | 上海电力大学 | Routing planning method and system for power tower unmanned aerial vehicle inspection route |
Non-Patent Citations (1)
| Title |
|---|
| 基于渐进三角网的线路巡检点云地面点快速提取方法;吴蔚 等;《南方能源建设》;第7卷(第1期);第53-58页 * |
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