JP7322237B1 - Temporary housing complex design system - Google Patents

Abstract

A temporary housing complex design system capable of shortening the time required to design a temporary housing complex is provided. A temporary housing complex design system 1 for designing a temporary housing complex, which acquires point cloud data of the site of the temporary housing complex and its surroundings (step S1 in FIG. 3) A point cloud data acquisition unit ( The communication unit 11, the calculation unit 13), the acquired point cloud data is separated into at least a point cloud inside the premises and a point group outside the premises, and the point clouds inside the premises are grouped into a plurality of clusters, A point cloud data separation unit (computing unit 13) that separates the point cloud in the site into at least the point cloud of the site surface and the point cloud other than the site surface based on the cluster (step S2 in FIG. 3); It comprises a modeling unit (computing unit 13) that creates a virtual model of the site surface using the point group of the surface (step S3 in FIG. 3). [Selection drawing] Fig. 3

Description

Application of Article 30, Paragraph 2 of the Patent Act 2021 Annual Meeting (Tokai) Summaries of technical papers of academic lectures and summaries of technical papers of architectural design presentations DVD version and booklet Architectural Institute of Japan (Publications, etc.) https://www. aij. or. jp/tokai2021dvd. html (Publications, etc.) 2021 Annual Meeting of Architectural Institute of Japan (Tokai) Academic Lecture/Architectural Design Presentation (Online)

The present invention relates to a technology of a temporary housing complex design system for designing a temporary housing complex.

Japan is known as a country with so many natural disasters that it is called a “disaster country”. Among them, there are many cases in which damage is caused over a wide area, such as earthquakes and typhoons. In the event of a large-scale disaster, provision of emergency temporary housing as described in Patent Document 1 is required for those whose residences have been completely or partially destroyed.

In the planning of temporary housing complexes including emergency temporary housing after a disaster, prompt provision of temporary housing is required in line with the process of site survey, layout planning, housing unit design, material procurement, and on-site construction. be done. Among these processes, an automatic placement program using a modeling tool such as BIM may be used to shorten the placement planning period.

However, in the conventional automatic layout program, the designer had to manually create a virtual model of the site of the temporary housing, which took a long time to design the temporary housing complex.

Utility Model Registration No. 3177005

The present invention has been made in view of the above circumstances, and the problem to be solved is to provide a temporary housing complex design system capable of shortening the time required to design a temporary housing complex. be.

The problems to be solved by the present invention are as described above, and the means for solving these problems will now be described.

That is, in claim 1, a temporary housing complex design system for designing a temporary housing complex, comprising: a point cloud data acquisition unit for acquiring point cloud data of the site of the temporary housing complex and its surroundings; Separating the point cloud data into at least a point cloud inside the premises and a point cloud outside the premises, grouping the point clouds inside the premises into a plurality of clusters, and dividing at least the point clouds inside the premises based on the clusters It comprises a point cloud data separation unit that separates the point cloud of the site surface and point groups other than the site surface, and a modeling unit that creates a virtual model of the site surface using the point cloud of the site surface. .

In claim 2, the point cloud data separation unit divides the acquired point cloud within the site into a plurality of cells in plan view, and each of the plurality of cells is included in the cell in plan view Points derived from a point cloud are specified as cell points, and when the gradient of a straight line connecting the cell points of the adjacent cells is less than or equal to a predetermined value, the point clouds in the adjacent cells are grouped into the same cluster. If the gradient of the straight line connecting the cell points of the adjacent cells is not equal to or less than a predetermined value, the point clouds in the adjacent cells are grouped into separate clusters.

In claim 3, the point cloud data separation unit has the same height as the highest point of the point cloud included in the cell in plan view and is set at the center of the cell in plan view, It is specified to the cell point.

In claim 4, the point cloud data separation unit sets the cell to a square of 500 mm×500 mm or less.

In claim 5, the point cloud data separation unit separates the acquired point cloud data into a point group within the site, a point group within the road surrounding the site, and a point group other than within the site and the road. Then, the point clouds within the site and the point clouds within the road are each grouped into a plurality of clusters, and based on the clusters, the point groups within the site and the point groups within the road are grouped together with the point groups of the site surface. The point group of the road surface and the point groups other than the site surface and the road surface are separated, and the modeling unit creates a virtual model of the site surface and the road surface using the point group of the site surface and the point group of the road surface. It is to create.

In claim 6, the point cloud data separation unit separates the point cloud within the site, the point cloud within the road, and the point cloud outside the site and the road based on the site boundary line and the road boundary line. separation.

In claim 7, the point cloud data separation unit acquires at least one of the site boundary line and the road boundary line by superimposing a map on the acquired point cloud data.

In claim 8, in the point group of the site surface and the point group of the road surface, the point group of the site surface and the point group of the road surface are divided so that the intervals between the points in a plan view are constant. It is provided with an arrangement section for arrangement.

In claim 9, if there is a missing point in the point group of the site surface and the point group of the road surface after being organized by the organizing unit, the modeling unit supplements the missing point with the point This is to create a virtual model of the site surface.

As effects of the present invention, the following effects are obtained.

In claim 1, it is possible to shorten the time required for designing a temporary housing complex.

In claim 2, it is possible to improve the accuracy of the virtual model of the site surface.

In claim 3, it is possible to improve the accuracy of point group separation.

In claim 4, it is possible to improve the accuracy of point group separation.

In claim 5, it is possible to further shorten the time required for designing the temporary housing complex.

In claim 6, it is possible to improve the accuracy of separating the point group.

In claim 7, it is possible to improve the accuracy of separating the point group.

In claim 8, it is possible to improve the accuracy of the virtual model of the site surface and the road surface.

In claim 9, it is possible to improve the accuracy of the virtual model of the site surface and the road surface.

1 is a block diagram showing the configuration of a temporary housing complex design system according to an embodiment of the present invention; FIG. 3 is a block diagram showing the configuration of a user terminal; FIG. 4 is a flow chart showing a procedure for modeling a site surface and a road surface; 4 is a flowchart showing a process of separating point cloud data; 4 is a flowchart showing point group separation processing. FIG. 4 is a plan view for explaining a method of acquiring cell points; FIG. 4 is a schematic side view for explaining the gradient of a straight line connecting cell points; FIG. 4 is a side view for explaining a clustering method; (a) A plan view showing an example of display of the point cloud within the site and the point cloud within the road. (b) A plan view showing a state in which the point group of the site surface and the point group of the road surface are specified. 4 is a flow chart showing processing for modeling a site surface and a road surface; (a) A schematic plan view showing a state in which the point cloud of the site surface after arrangement is missing within the site boundary line. (b) A schematic plan view showing a state in which a bounding box is created. (a) A schematic plan view showing a state in which points are added. (b) A schematic plan view showing a state in which the virtual model of the site surface is cut along the site boundary line. (a) The figure which showed the road boundary line. (b) The figure which showed the state which created the parting line in the road boundary line. (a) The figure which showed the state which created the square centering on the dividing line. (b) A diagram for showing a calculation method of point cloud height.

A temporary housing complex design system 1 according to an embodiment of the present invention will be described below with reference to FIG.

The temporary housing complex design system 1 is for designing a temporary housing complex including temporary housing. In this embodiment, the temporary housing complex design system 1 creates a virtual model using a BIM tool in designing a temporary housing complex. Point cloud data of the site of the temporary housing complex and its surroundings are used to create the virtual model. Point cloud data can be obtained by various methods, for example, from aerial photographs taken by drones.

More specifically, the temporary housing complex design system 1, based on the point cloud data of the site of the temporary housing complex and its surroundings, the surface that constitutes the site (hereinafter referred to as "site surface") and the roads around the site Create a virtual model (model point cloud data) of the surface (hereinafter referred to as "road surface") that constitutes the On the other hand, since trees and structures other than the site surface and the road surface have complicated shapes and are difficult to model, the temporary housing complex design system 1 uses the BIM tool to convert trees and structures into point clouds. displayed as is. Hereinafter, the site surface and the road surface may be collectively referred to as "ground".

The temporary housing complex design system 1 mainly comprises a user terminal 10 and a shared server 20 .

The user terminal 10 is a terminal used when a user (designer) designs a layout plan for temporary housing. A personal computer or the like can be used as the user terminal 10 . The user terminal 10 can model the point cloud data. Also, the user terminal 10 can design a temporary housing complex using point cloud data and a BIM model. A plurality of user terminals 10 are provided. In FIG. 1, three user terminals 10 are shown. Details of the user terminal 10 will be described later.

The shared server 20 is connected to each user terminal 10 via the network N. FIG. The network N includes a public network such as the Internet, a wireless network such as a mobile phone network, a LAN (Local Area Network), and the like. The shared server 20 stores the BIM model and various information.

Access authority is required to access the shared server 20, only the user terminal 10 to which the access authority is granted can access the shared server 20, and various data stored in the shared server 20 can be shared. For example, at each design stage, a BIM model is stored in the shared server 20, and the user terminal 10 to which the access authority is granted accesses the shared server 20 and downloads the BIM model stored in the shared server 20 to its own terminal. It is possible to import a BIM model into the user terminal 10 or upload a BIM model created by one's own user terminal 10 to the shared server 20 .

The configuration of the user terminal 10 will be described below with reference to FIG. The user terminal 10 includes a communication section 11 , an operation input section 12 , a calculation section 13 and a display section 14 .

The communication unit 11 is a part that communicates with the shared server 20 . The communication unit 11 can transmit a BIM model created by the user terminal 10 to the shared server 20 and receive a BIM model stored in the shared server 20 .

The operation input unit 12 is a part for inputting various kinds of information by user's operation. A keyboard, a mouse, or the like is used as the operation input unit 12 . A user can design a temporary housing complex using a BIM model through the operation input unit 12 . Specifically, the user can model point cloud data, input data, and the like via the operation input unit 12 .

The calculation unit 13 is a part that performs various calculations. The calculation unit 13 can process point cloud data. Further, the calculation unit 13 can bring the user terminal 10 into a state in which a BIM model can be created by activating application software for BIM model design.

The calculation unit 13 has a storage unit that stores various data. The storage unit stores the BIM model and various information read from the shared server 20 via the communication unit 11 . A BIM model created by the user terminal 10 is stored in the storage unit. The storage unit stores programs for processing point cloud data and modeling the point cloud data. The calculation unit 13 reads each program and executes various processes described later.

The display unit 14 displays images. The display unit 14 can display point cloud data, BIM models, and the like. A display device such as a liquid crystal display is used as the display unit 14 .

The procedure for creating (modeling) a virtual model of the site surface and the road surface will be described below with reference to FIGS. 3 to 14 .

As shown in FIG. 3, first, point cloud data of the site of the temporary housing complex and its surroundings are acquired (step S1). Specifically, a drone is flown over the site to take aerial photographs of the site. Then, point cloud data of the site and its surroundings (hereinafter referred to as "whole area point cloud") is created from the image data of the aerial photograph taken by an appropriate method. The calculation unit 13 acquires the full-range point cloud via the communication unit 11 .

Next, the point cloud data is separated (step S2 shown in FIG. 3). A specific process of separating the point cloud data (step S2) will be described below with reference to FIG.

First, in step S21, the calculation unit 13 edits and converts the point cloud data (whole range point cloud) acquired in step S1. Specifically, the calculation unit 13 edits and converts the full-range point cloud into a format that can be processed in steps described later. After performing the process of step S21, the calculation unit 13 proceeds to step S22.

Next, in step S22, the calculation unit 13 acquires map information. Specifically, the calculation unit 13 acquires map information including at least one of the site and roads around the site from the outside. In this embodiment, the calculation unit 13 acquires road map information. After performing the process of step S22, the calculation unit 13 proceeds to step S23.

Next, in step S23, the calculation unit 13 creates a site boundary line and a road boundary line.
Here, the "site boundary line" refers to a line representing the boundary (outline) of the site, and the "road boundary line" refers to a line representing the boundary (outline) of the road. The calculation unit 13 causes the display unit 14 to display the full-range point cloud edited and converted in step S21. Then, the calculation unit 13 superimposes the map acquired in step S22 on the entire range point group on the display unit 14 . Then, the calculation unit 13 acquires site boundaries and/or road boundaries in the entire range point cloud based on the outline of the lot and/or the outline of the road on the map. In this embodiment, the calculation unit 13 acquires the road boundary line based on the outline of the road on the map, and the site boundary line is drawn by the user. After performing the process of step S23, the calculation unit 13 proceeds to step S24.

Next, in step S24, the calculation unit 13 separates the point group. Specifically, the calculation unit 13 divides the entire range point cloud into three types of point clouds: “point cloud on site surface”, “point cloud on road surface”, and “point cloud on other than site surface and road surface”. To separate. A specific process of separating the point group (step S24) will be described below with reference to FIG.

First, in step S241, the calculation unit 13 reads the data of the entire range point cloud edited and converted in step S21 and the site boundary line and road boundary line data created in step S23. The data includes vertex coordinates of site boundaries and road boundaries. After performing the process of step S241, the calculation unit 13 proceeds to step S242.

In step S242, the calculation unit 13 separates the entire range point cloud into three types of point clouds: "point cloud within site", "point cloud within road", and "point cloud outside site and road". do. The method will be specifically described below.

The calculation unit 13 determines whether or not each point of the entire range point group is included in the polygon of the site boundary line, and groups the points that are determined to be included in the "site point group". Next, the calculation unit 13 determines whether or not the points that are not included in the polygon of the site boundary line are included in the polygon of the road boundary line, and the points that are determined to be included are referred to as "inside the road". group into "point clouds". Finally, the computing unit 13 groups all the remaining points that are not included in the polygon of the site boundary line and the polygon of the road boundary line into the "point group other than the site and road". After performing the process of step S242, the calculation unit 13 proceeds to step S243.

In step S243, the calculation unit 13 divides the "point group within the site" and the "point group within the road" into cells, and obtains the center points thereof. The method will be specifically described below.

First, as shown in FIG. 6, the calculation unit 13 acquires bounding boxes for each of the "point group within the site" and the "point group within the road", and obtains the "point group within the site" and the "road point group" in a plan view. Each point cloud in is divided into multiple cells. The cell to be divided shall be a square of 500 mm x 500 mm or less. In this embodiment, the cell size is 250 mm×250 mm. The calculation unit 13 selects only cells that include a point group in plan view, and sets the center point of the selected cells (hereinafter referred to as "cell point p"). The height of each cell point p is the same height as the point having the highest height in the point group included in the cell in plan view. After performing the process of step S243, the calculation unit 13 proceeds to step S244.

In step S244, the calculation unit 13 clusters the cell-divided "point groups in the site" and "point groups in the road" and groups them into a plurality of clusters. The clustering method will be described below.

As shown in FIG. 7, the calculation unit 13 acquires the horizontal distance X between cell points p of adjacent cells and the height direction distance Y between cell points p of adjacent cells. In this embodiment, since the length of one side of the cell is 250 mm, the horizontal distance X between the cell points p is also 250 mm. Then, the calculation unit 13 calculates the ratio of the distance Y to the distance X ((Y/X)×100[%]), that is, the gradient of the straight line E connecting the cell points p.

When the gradient of the straight line E connecting the cell points p of adjacent cells is equal to or less than a predetermined threshold value, the computing unit 13 groups the point groups in the adjacent cells into the same cluster. On the other hand, if the gradient of the straight line E connecting the cell points p of adjacent cells is not equal to or less than a predetermined threshold value (exceeds a predetermined threshold value), the calculation unit 13 groups the point groups in the adjacent cells into separate clusters. Divide.

Here, the predetermined threshold value of the slope takes into consideration the general slope of the site surface and the road surface, and the height of other elements (for example, structures such as trees and benches) other than the site surface and the road surface. is preferably set. More specifically, the predetermined threshold value may be set to a value that is larger than the upper limit of the slope of the site surface and the road surface and smaller than the slope derived from the height of other elements such as benches. preferable. In this embodiment, the predetermined threshold for slope is set at 20%.

This groups point clouds in adjacent cells into separate clusters if the slope of line E is greater than 20% (i.e., the slope of line E is too steep to be considered on the ground). . Therefore, it is possible to easily separate the point group of the ground from the point group of other elements such as trees and structures. On the other hand, if the slope of the straight line E is less than 20% (ie, the slope of the straight line E is gentle), the point clouds in adjacent cells are grouped into the same cluster. For this reason, it is possible to suppress the point group of the ground from being separated as the point group of other elements, and in addition, in the later-described process (step S3 in FIG. 3), even though the ground is actually continuous, discontinuous modeling can be suppressed.

Here, as shown in FIG. 7, when the gradient of the straight line E is 20%, the distance Y in the height direction between the cell points p is 50 mm, and the length ε of the straight line E is approximately 255 mm. , length ε=255 mm). Therefore, in an actual system, the calculation unit 13 determines whether to group the point groups in adjacent cells into separate clusters or into the same cluster based on the length ε of the straight line E. It can be carried out. That is, when the length ε of the straight line E is 255 mm or less, the computing unit 13 groups the point groups in the adjacent cells into the same cluster. On the other hand, when the length ε of the straight line E is not less than 255 mm (exceeds 255 mm), the calculation unit 13 groups the point groups in the adjacent cells into separate clusters.

Density-based spatial clustering of applications with noise (DBSCAN) can be used as such a clustering algorithm. DBSCAN groups points within a distance of ε by specifying two parameters: ``permissible distance ε for forming the same cluster'' and ``minimum number of points n required to form a cluster''. The method.

Specifically, among the plurality of cell points p acquired in step S243, the calculation unit 13 calculates the total number of cell points, including other cell points and the self point within a distance (radius) ε, of n or more. Let p be defined as a "core point" and all other cell points p within a distance ε from this core point to be in the same cluster. Then, the calculation unit 13 defines another cell point p having a core point within the distance ε, although there are no n or more cell points p within the distance ε, as a “reachable point”. Then, the calculation unit 13 defines the cell points p that are not defined as “core points” or “reachable points” as “noise”. As described above, the allowable distance ε is set to 255 mm in this embodiment. Also, the minimum number of points n can be set to any numerical value, and is set to n=1 in this embodiment.

FIG. 8 is an example of clustering. In FIG. 8, the vertical axis indicates the position in the height direction, and the horizontal axis indicates the position in the horizontal direction. In FIG. 8, the point p1 is a core point because three or more points including the point p1 itself are included within the radius of the distance ε. The core points included within the radius of distance ε form the same cluster. The point p2 is a reachable point because it exists within a radius of ε from the core point, and is in the same cluster as the core point. Point p3 is noise that is neither a core point nor a reachable point, and does not belong to any cluster. As a result, the point cloud is grouped into, for example, cluster A, cluster B, cluster C, cluster D and noise.

After performing the process of step S244, the calculation unit 13 proceeds to step S245.

In step S<b>245 , the calculation unit 13 displays the “point cloud on site” and the “point cloud on road” on the display unit 14 by color-coding each cluster. As shown in FIG. 9( a ), the display unit 14 displays a 3D view of the “point group within the site” and the “point group within the road”. The “point cloud within the site” and the “point cloud within the road” are divided into clusters. As indicated by different hatching in FIG. 9A, each cluster is displayed in a different color. Via the operation input unit 12, the user selects a cluster considered to be a "point cloud on the site" and a "point cloud on the road" from a plurality of clusters of "point cloud on the site" and "point cloud on the road". You can specify clusters that are considered "groups". A user can specify a cluster, for example, by clicking a point displayed within the cluster.

After performing the process of step S245, the calculation unit 13 proceeds to step S246.

In step S246, the calculation unit 13 determines whether or not a cluster of the ground (site surface and road surface) has been designated. If the calculation unit 13 determines that the ground cluster has been specified ("YES" in step S246), the process proceeds to step S247. On the other hand, if the calculation unit 13 determines that no ground cluster is specified ("NO" in step S246), it performs the process of step S246 again.

In step S<b>247 , the calculation unit 13 sets the clusters selected in the “site point group” and “road point group” as the ground point group, and the other clusters as the non-ground point groups. More specifically, as shown in FIG. 9(b), the calculation unit 13 converts the cluster selected in the "site point cloud" in step S246 into the site surface point cloud, and the other clusters other than the site surface point cloud. In step S246, the cluster selected in the "road point group" is set as the road surface point group, and the others are set as the point groups other than the road surface. After performing the process of step S247, the calculation unit 13 proceeds to step S248.

In step S248, the calculation unit 13 integrates the “point cloud other than the site surface” and the “point cloud other than the road surface” with the “point cloud other than the site and road”, and the “point cloud other than the site surface and the road surface”. point cloud”. After performing the process of step S248, the calculation unit 13 ends the process of step S24 shown in FIG.

When the separation of the point cloud data (step S2 shown in FIG. 3) is completed in this way, next, the site surface and the road surface are modeled (step S3 shown in FIG. 3). A specific process of modeling the site surface and the road surface (step S3) will be described below with reference to FIG.

First, in step S31, the calculation unit 13 converts point cloud data other than the site surface and the road surface. Specifically, the calculation unit 13 edits and converts the point cloud data other than the site surface and the road surface into a format that can be processed in steps described later. After performing the process of step S31, the calculation unit 13 proceeds to step S32.

In step S32, the calculation unit 13 arranges the BIM parts and displays the point cloud. Specifically, the calculation unit 13 causes the display unit 14 to display point groups other than the site surface and the road surface. Then, the calculation unit 13 arranges road dividing line BIM parts (BIM parts used for dividing road boundary lines) based on the road boundary lines. After performing the process of step S32, the calculation unit 13 proceeds to step S33.

In step S33, the calculation unit 13 organizes the point group. Specifically, the computing unit 13 acquires bounding boxes for each of the "point group of site surface" and the "point group of road surface", and obtains the "point group of site surface" and the "point group of road surface" in plan view. ' split each into multiple cells. A divided cell is 250 mm×250 mm. Next, the calculation unit 13 selects only cells that include a point group in plan view, and sets the center point (cell point p) of the selected cells (similar to FIG. 6). The height of each cell point p is the average height of the point group included in the cell in plan view. Points in the cell other than the cell point p are deleted. In this way, in each of the "site surface point group" and the "road surface point group", the point groups are organized so that the intervals between the points in a plan view are constant. More specifically, the points are arranged so as to line up in the X direction and the Y direction in a plan view, and the point group is organized so that the points are arranged at regular intervals in the X direction and the Y direction.
After performing the process of step S33, the calculation unit 13 proceeds to step S34.

In step S34, the calculation unit 13 performs modeling. Specifically, the calculation unit 13 refers to the height of the point group from the point group of the site surface and the point group of the road surface after sorting in step S33. Then, the calculation unit 13 creates a virtual model of the site surface and the road surface based on the height of the point cloud, the site boundary line, and the road boundary line.

Here, in the point cloud data of the site surface and the road surface, when the point cloud data is acquired in step S1 of FIG. Sometimes the surface point cloud is missing. Also, by separating the elements other than the site surface and the road surface, points on the site surface and the road surface may be missing. Therefore, if there is a missing point on the site surface and the road surface after the point group has been organized (after the processing in step S33), the computing unit 13 supplements the missing point with the point cloud and then models the site surface. I do.

First, a method of supplementing the point cloud of the site surface will be described with reference to FIGS. 11 and 12. FIG.

For example, as shown in FIG. 11(a), there may be a point group missing (part indicated by a two-dot chain line) within the site boundary. In this case, as shown in FIG. 11(b), the calculation unit 13 creates a bounding box surrounding the site boundary line. Then, as shown in FIG. 12(a), the calculation unit 13 calculates the coordinates of the missing point based on the coordinates of the existing point, and creates a point at the calculated coordinate position. Then, as shown in FIG. 12(b), the calculation unit 13 creates a virtual model of the site surface from all points, and then cuts out the virtual model of the site surface along the site boundary line. Thus, a virtual model of the site surface is created.

Next, a method for complementing the point cloud on the road surface will be described with reference to FIGS. 13 and 14. FIG.

First, as shown in FIG. 13A, the calculation unit 13 acquires the road contour line based on the vector data of the point group within the road boundary line. Next, as shown in FIG. 13(b), the calculation unit 13 forms a plurality of dividing lines in the road contour line at intervals in the extending direction of the road. Next, as shown in FIG. 14A, the calculation unit 13 creates a quadrangle around the dividing line and obtains the average height of the point group within the quadrangle.

Next, the calculation unit 13 creates a virtual model (BIM part) of a surface formed by road boundary lines and dividing lines. At this time, the calculation unit 13 gives the average height of the point group within the quadrangle to both ends of the dividing line. If the point cloud is missing and no height is given to the dividing line, the difference in height between the dividing lines on both sides of the dividing line is proportionally divided by the length of the road boundary line from the adjacent dividing line. The height of both ends of the dividing line is calculated. For example, in the example shown in FIG. 14B, if the height Z of the dividing line F cannot be obtained, the height of the dividing line F is calculated by the following formula (1).
Z=Z1+(Z2-Z1)×{L1/(L1+L2)} Expression (1)

In equation (1), Z1 and Z2 indicate the heights of the dividing lines on both sides of the dividing line, and L1 and L2 indicate the lengths of the road contour lines from the dividing lines on both sides to the dividing line.

The calculation unit 13 can create a virtual model of the road surface based on the road contour line and the height of the dividing line.

As described above, by supplementing the missing points and creating a virtual model of the site surface and the road surface, even though the site surface and the road surface are actually continuous, the site surface and the road surface It is possible to prevent the virtual model of the road surface from becoming discontinuous. In addition, it is possible to prevent the site surface and the road surface from becoming rough and distorted.

After performing the process of step S34, the calculation unit 13 ends the modeling of the site surface and the road surface.

As described above, in the temporary housing complex design system 1 according to the present embodiment, it is possible to automatically create a virtual model of the site surface and road surface of the temporary housing complex using point cloud data. can be reduced. Also, the design time can be shortened.

In addition, in the temporary housing complex design system 1 according to this embodiment, a virtual model is created after separating the point cloud data, so the site surface and other elements can be modeled as separate members. Therefore, it is possible to easily consider the layout of each element of the temporary housing complex.

Also, hypothetically, if the ground point cloud and the non-ground point cloud are separated based on the height of the point cloud itself, the height difference of the ground is relatively large (for example, the ground is continuous to a relatively high position). ), sometimes the higher parts of the ground may be separated out as other elements. On the other hand, in the temporary housing complex design system 1 according to this embodiment, the point group is separated based on how rapidly the height of the point group changes (the gradient of the straight line E in FIG. 7). Therefore, it is possible to prevent the high ground portion from being separated as another element. In this way, even when the difference in height of the ground is relatively large, it is possible to appropriately separate the ground and point groups other than the ground.

As described above, the temporary housing complex design system 1 according to this embodiment is
A temporary housing complex design system 1 for designing a temporary housing complex,
A point cloud data acquisition unit (communication unit 11, calculation unit 13) that acquires point cloud data of the site of the temporary housing complex and its surroundings (step S1 in FIG. 3);
The acquired point cloud data is separated into at least a point cloud inside the premises and a point cloud outside the premises, the point clouds inside the premises are grouped into a plurality of clusters, and points inside the premises are determined based on the clusters. A point cloud data separation unit (calculation unit 13) that separates the group into at least a point cloud of the site surface and a point group other than the site surface (step S2 in FIG. 3);
a modeling unit (computing unit 13) that creates a virtual model of the site surface using the point group of the site surface (step S3 in FIG. 3);
is provided.

With such a configuration, it is possible to shorten the time required to design a temporary housing complex.
Specifically, since a virtual model of the site of the temporary housing complex can be automatically created, the burden on the user can be reduced, and the design time can be shortened.
In addition, since the virtual model is created after separating the point cloud data, the site surface and other elements can be modeled as separate members, which in turn improves the accuracy of the virtual model of the site surface. , it is possible to facilitate consideration of the arrangement of each element.

Further, the point cloud data separation unit
The obtained point cloud within the site is divided into a plurality of cells in plan view (step S243 in FIG. 5),
In each of the plurality of cells, a point derived from a point group included in the cell in plan view is specified as a cell point (step S243 in FIG. 5),
When the gradient of the straight line connecting the cell points of the adjacent cells is equal to or less than a predetermined value, the point groups in the adjacent cells are grouped into the same cluster, and the cell points of the adjacent cells are grouped into the same cluster. If the gradient of the connecting straight line is not less than a predetermined value, the point groups in the adjacent cells are grouped into separate clusters (step S244 in FIG. 5).

With such a configuration, it is possible to improve the accuracy of the virtual model of the site surface.
Specifically, if the difference in height between point clouds in adjacent cells is relatively large (for example, if the difference in height is so rapid that it cannot be thought of as the slope of the site), the point clouds in adjacent cells are grouped into separate clusters, making it easier to separate the point cloud of the site surface from the point cloud of other elements such as trees and structures. On the other hand, if the height difference between the point clouds in adjacent cells is relatively small (for example, the change is so smooth that it can be considered within the range of the slope of the site), the point clouds in the adjacent cells are the same. By grouping them into clusters, it is possible to suppress modeling of discontinuity even though the site surface is actually continuous.

Further, the point cloud data separation unit
A point set at the same height as the highest point in the point group included in the cell in plan view and at the center of the cell in plan view is designated as the cell point.

With such a configuration, it is possible to improve the accuracy of separating the point group.
Specifically, by setting the position of the cell point in plan view as the center of the cell and measuring the horizontal distance between the cell points of adjacent cells, the gradient of the straight line connecting the cell points is calculated. be able to. Further, by setting the height of the cell point to the same height as the highest point in the group of points included in the cell, the reference of the height of each cell point of adjacent cells can be made the same.

Further, the point cloud data separation unit
The cell is set to a square of 500 mm×500 mm or less.

With such a configuration, it is possible to improve the accuracy of separating the point group.
Specifically, since the point cloud in the site can be divided relatively finely, the point cloud can be separated more precisely.

Further, the point cloud data separation unit
The acquired point cloud data is separated into a point cloud within the site, a point cloud within the road surrounding the site, and a point group outside the site and the road, and the point cloud within the site and the points within the road Each group is grouped into a plurality of clusters, and based on the clusters, the point group in the site and the point group in the road are classified into the point group of the site surface, the point group of the road surface, and the points other than the site surface and the road surface. separated into groups (step S2 in FIG. 3),
The modeling unit
A virtual model of the site surface and the road surface is created using the point group of the site surface and the point group of the road surface (step S3 in FIG. 3).

With such a configuration, it is possible to further shorten the time required for designing a temporary housing complex.
Specifically, a virtual model of the road around the site of the temporary housing complex can be automatically created, so that the burden on the designer can be reduced and the design time can be shortened.
In addition, the site surface, road surface, and other elements can be modeled as separate members, which in turn improves the accuracy of the virtual model of the road surface, and facilitates examination of the arrangement of each element. can be done.

Further, the point cloud data separation unit
Based on the site boundary line and the road boundary line, the point group within the site, the point group within the road, and the point group outside the site and road are separated (step S24 in FIG. 4). .

With such a configuration, it is possible to improve the accuracy of separating the point group.

Further, the point cloud data separation unit
At least one of the site boundary line and the road boundary line is obtained by superimposing a map on the acquired point cloud data (steps S22 and S23 in FIG. 4).

With such a configuration, it is possible to improve the accuracy of separating the point group.
Specifically, even if it is difficult to acquire site boundaries and road boundaries from point cloud data, site boundaries and road boundaries can be easily acquired.

In addition, the temporary housing complex design system 1 according to the present embodiment is configured so that in each of the point group of the site surface and the point group of the road surface, the points of the site surface are arranged so that the intervals between the points in a plan view are constant. A sorting unit (computing unit 13) for sorting out the group and the point group of the road surface is provided (step S33 in FIG. 10).

With such a configuration, it is possible to improve the accuracy of the virtual model of the site surface and the road surface.

Further, the modeling unit
If points are missing in the point group of the site surface and the point group of the road surface after being organized by the organizing unit, a virtual model of the site surface is created after supplementing the missing points with points (Fig. 9 step S34).

With such a configuration, it is possible to improve the accuracy of the virtual model of the site surface and the road surface.
Specifically, the virtual model of the site surface and the road surface becomes discontinuous even though the site surface and the road surface are actually continuous, and the site surface and the road surface become rough and distorted. can be suppressed.

Although the embodiments according to the present invention have been described above, the present invention is not limited to the above configurations, and various modifications are possible within the scope of the invention described in the claims.

For example, in the present embodiment, a BIM model is used as a virtual model to plan the layout of temporary housing. may be

Also, in the present embodiment, the point cloud data is obtained by flying a drone, but the method for obtaining the point cloud data is not limited to this, and any method can be used.

Further, in the present embodiment, the user selects a cluster of "point cloud on site surface" from a plurality of clusters of "point cloud on site" and "point cloud on road" via operation input unit 12. and clusters of "point cloud of road surface" are designated, but the calculation unit 13 may automatically designate them based on a predetermined condition.

1 Temporary housing complex design system 11 Communication unit 13 Calculation unit

Claims (9)

A temporary housing complex design system for designing a temporary housing complex, comprising:
a point cloud data acquisition unit that acquires point cloud data of the site of the temporary housing complex and its surroundings;
The acquired point cloud data is separated into at least a point cloud inside the premises and a point cloud outside the premises, the point clouds inside the premises are grouped into a plurality of clusters, and points inside the premises are determined based on the clusters. a point cloud data separation unit that separates the group into at least a point cloud of the site surface and a point group other than the site surface;
a modeling unit that creates a virtual model of the site surface using the point cloud of the site surface;
comprising a
Temporary housing complex design system. The point cloud data separation unit
The acquired point cloud within the site is divided into multiple cells in a plan view,
In each of the plurality of cells, a point derived from a point group included in the cell in plan view is designated as a cell point;
When the gradient of the straight line connecting the cell points of the adjacent cells is equal to or less than a predetermined value, the point groups in the adjacent cells are grouped into the same cluster, and the cell points of the adjacent cells are grouped into the same cluster. If the gradient of the connecting straight line is not less than a predetermined value, grouping the point clouds in the adjacent cells into separate clusters;
The temporary housing complex design system according to claim 1. The point cloud data separation unit
Designating a point set at the center of the cell in a plan view and at the same height as the highest point of the point group included in the cell in a plan view as the cell point;
The temporary housing complex design system according to claim 2. The point cloud data separation unit
setting the cell to a square of 500 mm x 500 mm or less;
The temporary housing complex design system according to claim 2 or 3. The point cloud data separation unit
The acquired point cloud data is separated into a point cloud within the site, a point cloud within the road surrounding the site, and a point group outside the site and the road, and the point cloud within the site and the points within the road Each group is grouped into a plurality of clusters, and based on the clusters, the point group in the site and the point group in the road are classified into the point group of the site surface, the point group of the road surface, and the points other than the site surface and the road surface. separate into groups,
The modeling unit
Creating a virtual model of the site surface and the road surface using the point group of the site surface and the point group of the road surface;
The temporary housing complex design system according to any one of claims 1 to 3. The point cloud data separation unit
Based on the site boundary line and the road boundary line, separating the point group within the site, the point group within the road, and the point group other than within the site and road;
The temporary housing complex design system according to claim 5. The point cloud data separation unit
Acquiring at least one of the site boundary line or the road boundary line by superimposing a map on the acquired point cloud data;
The temporary housing complex design system according to claim 6. A sorting unit that sorts out the point group of the site surface and the point group of the road surface so that the intervals between the points in the plan view are constant in each of the point group of the site surface and the point group of the road surface. do,
The temporary housing complex design system according to claim 5. The modeling unit
If there is a missing point in the point group of the site surface and the point group of the road surface after being organized by the organizing unit, a virtual model of the site surface is created after supplementing the missing point with the point.
The temporary housing complex design system according to claim 8.

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