Construction quality calculation device and construction quality calculation program

Abstract

Even at locations where the point cloud shape of the edge that represents a cross-sectional change cannot be obtained, the completed value of the slope protection structure can be accurately calculated. [Solution] The system includes a plane extraction means 105 that extracts a plane based on the normal vector at each point in the 3D point cloud data, a plane separation means 106 that separates the plane into a slope frame portion and a bottom portion, a center point calculation means 107 that clusters the point cloud data of the bottom portion and calculates a center point for each clustered bottom portion, a selection means 108 that generates cross-sectional clusters for the point cloud data included in the cross-sections that traverse vertically and horizontally from the center point, and selects the cross-sectional slope frame portion and the cross-sectional slope bottom portion based on the average elevation of the cross-sectional clusters, an extraction means 109 that extracts the cross-sectional slope frame portions near the left and right sides of the cross-sectional slope bottom portion that includes the center point, and a completed value calculation means 110 that calculates the completed value based on the extracted cross-sectional slope frame portions.

Description

Technical Field

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[0001] The present invention relates to a formed shape value calculation device and a formed shape value calculation program for calculating formed shape values based on point cloud data.

Background Art

[0002] In order to prevent the collapse of the slope surface, it is necessary to appropriately manage the formed shape at the completion of construction.

[0003] Conventionally, measurements for managing the formed shape of slope work were performed by craftsmen at sites such as high places where rope access was required. However, recently, it has been eagerly desired to irradiate the ground surface with laser light from a laser scanner mounted on a flying object such as a drone or an aircraft, analyze these received light data, obtain three-dimensional point cloud data, and perform measurement of formed shape values based on the obtained point cloud data.

[0004] Patent Document 1 discloses a technique related to a measurement system that divides three-dimensional point cloud data within a measurement range at regular intervals in the horizontal direction with respect to the ground surface, connects the corners of the formwork NB in the vertical direction intersecting the horizontal direction, thereby estimating the vertical edges of the formwork NB, divides the three-dimensional point cloud data within the measurement range at regular intervals in the vertical direction with respect to the ground surface, and connects the corners of the formwork NB in the horizontal direction intersecting the vertical direction, thereby estimating the horizontal edges of the formwork NB.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] However, in the technique described in Patent Document 1, the 3D point cloud data within the measurement range is divided at regular intervals horizontally relative to the ground surface, and the vertical edge of the slope frame NB is estimated. As a result, the horizontal and vertical edges of the slope frame NB are partially estimated as if it were a surface, making it difficult to accurately calculate the completed value of the slope frame in locations where the point cloud shape of the edge that becomes the cross-sectional change point cannot be obtained.

[0007] This invention has been made in view of the above-mentioned problems, and aims to provide a completed work value calculation device and a completed work value calculation program that can accurately calculate the completed work value of a slope protection structure even at locations where the point cloud shape of the edge that becomes a cross-sectional change point cannot be obtained. [Means for solving the problem]

[0008] To solve the above objective, the first feature of the completed work value calculation device according to the present invention is: A device for calculating the completed value of a slope protection structure based on 3D point cloud data, A plane extraction means calculates the normal vector at each point in the three-dimensional point cloud data and extracts a plane based on the normal vector, A plane separation means for separating the plane extracted by the plane extraction means into a slope frame portion and a bottom surface portion, A center point calculation means that clusters the point cloud data of the base portion based on Euclidean distance and calculates a center point for each clustered base portion, A selection means generates cross-sectional clusters by clustering point cloud data contained in cross-sectional areas that are crossed perpendicularly and horizontally to the input slope direction coordinate values ​​from the aforementioned center point, based on Euclidean distance, and selects the cross-sectional slope frame portion and the cross-sectional slope bottom portion based on the average elevation of the cross-sectional clusters. An extraction means for extracting the cross-sectional slope frame portions near the left and right sides of the bottom of the cross-sectional slope including the center point from among the cross-sectional slope frame portions selected by the selection means, A means for calculating the completed work value based on the extracted cross-sectional slope frame portion, It is equipped with this.

[0009] The second feature of the completed work value calculation device according to the present invention is, The aforementioned completion value calculation means is The objective is to calculate the width of the extracted cross-sectional slope frame portion and the width of the bottom of the cross-sectional slope including the center point as the completed value.

[0010] The third feature of the completed work value calculation device according to the present invention is, The aforementioned completion value calculation means is The objective is to calculate the height from both ends of the bottom of the cross-sectional slope including the center point to the cross-sectional slope frame portion extracted by the extraction means as the completed value.

[0011] The fourth feature of the completed work value calculation device according to the present invention is, The aforementioned completion value calculation means is The method involves calculating the midpoints of the left and right vicinity of the bottom of the cross-sectional slope, including the center point extracted by the extraction means, and calculating the distance between the calculated midpoints as the completed value.

[0012] The fifth feature of the completed work value calculation device according to the present invention is: The aforementioned planar extraction means is The process involves calculating the normal vector at each point in the three-dimensional point cloud data, deleting point cloud data where the angle between the normal vector and the Z-axis is greater than or equal to a predetermined threshold, and then extracting a plane based on the remaining point cloud data.

[0013] The sixth feature of the completed work value calculation device according to the present invention is, The aforementioned planar extraction means is The objective is to remove noise from the extracted plane using a noise reduction method based on the spatial distribution of the 3D point cloud data.

[0014] The seventh feature of the completed work value calculation device according to the present invention is: The planar separation means separates the plane extracted by the planar extraction means into a flange portion and a bottom surface portion by a separation method based on the spatial distribution of the three-dimensional point cloud data.

[0015] The first feature of the formed value calculation program according to the present invention is a formed value calculation program executed by a formed value calculation device that calculates a formed value of a flange work based on three-dimensional point cloud data, a plane extraction step of calculating a normal vector at each point of the three-dimensional point cloud data and extracting a plane based on the normal vector, a plane separation step of separating the plane extracted by the plane extraction step into a flange portion and a bottom surface portion, a center point calculation step of clustering the point cloud data of the bottom surface portion based on the Euclidean distance and calculating a center point for each of the clustered bottom surface portions, a selection step of generating a cross-sectional cluster by clustering the point cloud data included in a cross-section that crosses in the vertical and horizontal directions with respect to the input normal surface direction coordinate value from the center point, and selecting a cross-sectional flange portion and a cross-sectional normal surface bottom based on the average elevation of the cross-sectional cluster, an extraction step of extracting cross-sectional flange portions in the left and right vicinities of the cross-sectional normal surface bottom including the center point among the cross-sectional flange portions selected in the selection step, a formed value calculation step of calculating the formed value based on the extracted cross-sectional flange portions, and having the above.

Effect of the Invention

[0016] According to the formed value calculation device and the formed value calculation program according to the present invention, even at a point where the point cloud shape of an edge that is a cross-section change point cannot be obtained, the formed value of the flange work can be accurately calculated.

Brief Description of the Drawings

[0017] [Figure 1]This is a schematic diagram showing the general configuration of a slope framing support system to which a completed work value calculation device, which is one embodiment of the present invention, is applied. [Figure 2] This is an explanatory diagram illustrating the processing of the pre-processing means provided in a slope frame construction support system 1, which is one embodiment of the present invention. [Figure 3] This is an explanatory diagram illustrating the processing of the pre-processing means provided in a slope frame construction support system 1, which is one embodiment of the present invention. [Figure 4] This is an explanatory diagram illustrating the processing of the plane extraction means provided in a slope frame construction support system 1, which is one embodiment of the present invention. [Figure 5] This is an explanatory diagram illustrating schematically the processing of the planar separation means provided in a slope protection support system 1, which is one embodiment of the present invention. [Figure 6] This is an explanatory diagram illustrating the processing of the center point calculation means included in a slope frame construction support system 1, which is one embodiment of the present invention. [Figure 7] This is an explanatory diagram illustrating the processing of the selection means provided in a slope frame construction support system 1, which is one embodiment of the present invention. [Figure 8] This is an explanatory diagram illustrating the processing of the selection means provided in a slope frame construction support system 1, which is one embodiment of the present invention. [Figure 9] This is an explanatory diagram illustrating schematically the processing of the extraction means and the completed value calculation means included in the slope frame construction support system 1, which is one embodiment of the present invention. [Figure 10] This is an explanatory diagram illustrating schematically the processing of the completed work value calculation means included in the slope frame construction support system 1, which is one embodiment of the present invention. [Figure 11] This is an explanatory diagram illustrating schematically the processing of the completed work value calculation means included in the slope frame construction support system 1, which is one embodiment of the present invention. [Figure 12] This is a flowchart illustrating the processing steps of a slope framing support system 1, which is one embodiment of the present invention. [Figure 13] This is a schematic diagram illustrating the processing of the midpoint selection means provided in a slope frame construction support system 1, which is one embodiment of the present invention. [Figure 14]This is a schematic diagram illustrating the processing of the midpoint selection means provided in a slope frame construction support system 1, which is one embodiment of the present invention. [Figure 15] This is an explanatory diagram illustrating schematically the processing of the first filtering means provided in a slope protection support system 1, which is one embodiment of the present invention. [Figure 16] This is an explanatory diagram illustrating schematically the processing of the first filtering means provided in a slope protection support system 1, which is one embodiment of the present invention. [Figure 17] This is an explanatory diagram illustrating schematically the processing of the second filtering means provided in a slope framing support system 1, which is one embodiment of the present invention. [Figure 18] This is an explanatory diagram illustrating schematically the processing of the connection means provided in a slope frame construction support system 1, which is one embodiment of the present invention. [Figure 19] This is an explanatory diagram illustrating schematically the processing of the connection means provided in a slope frame construction support system 1, which is one embodiment of the present invention. [Figure 20] This is a flowchart illustrating the processing steps of a slope framing support system 1, which is one embodiment of the present invention. [Modes for carrying out the invention]

[0018] Embodiments of the present invention will be described below with reference to the drawings. Throughout the drawings, identical or equivalent parts and components are denoted by the same or equivalent reference numerals. However, it should be noted that the drawings are schematic and may differ from reality. Furthermore, there are parts where the dimensional relationships and proportions differ between drawings.

[0019] Furthermore, the embodiments shown below are illustrative examples of devices and the like for realizing the technical concept of this invention, and the technical concept of this invention is not limited to the arrangement of each component as described below. The technical concept of this invention can be modified in various ways within the scope of the claims.

[0020] The following describes a slope framing support system to which a completed work value calculation device, which is one embodiment of the present invention, is applied.

[0021] Figure 1 is a schematic diagram showing the general configuration of a slope frame construction support system to which a completed value calculation device, which is one embodiment of the present invention, is applied.

[0022] As shown in Figure 1, the slope protection support system 1 includes a laser point cloud data acquisition means 101, a set coordinate acquisition means 102, a preprocessing means 103, a laser point cloud data storage means 104, a plane extraction means 105, a plane separation means 106, a center point calculation means 107, a selection means 108, an extraction means 109, a completed value calculation means 110, a completed value storage means 111, a beam length calculation means 120, and a beam length storage means 125.

[0023] The laser point cloud data acquisition means 101 acquires 3D point cloud data. 3D point cloud data is measurement data obtained by combining coordinate data calculated based on reflected light from a laser scanner or similar device mounted on a flying object such as a drone or airplane, and the time information of the received light. While the 3D point cloud data here is described as measurement data from an airplane or drone, it is not limited to measurement data acquired by irradiation from an airplane or drone; laser light may also be emitted from a high position on the ground. Furthermore, while laser light is used here, the method is not limited to this; 3D point cloud data may also be acquired by photogrammetry without using laser light. At least the data should include 3D coordinate data.

[0024] The setting coordinate acquisition means 102 acquires slope range coordinate values ​​and slope direction coordinate values ​​from user input from an input device such as a keyboard or mouse (not shown). The slope range coordinate values ​​are coordinate values ​​that indicate the range of the target slope in the three-dimensional space of the three-dimensional point cloud data, and the slope direction coordinate values ​​are coordinate values ​​that indicate the direction in which the slope on the three-dimensional point cloud data is facing.

[0025] The preprocessing means 103 performs slope range extraction processing and rotation processing on the 3D point cloud data acquired by the laser point cloud data acquisition means 101.

[0026] Figures 2 and 3 are schematic diagrams illustrating the processing of the pre-processing means 103 included in the slope frame construction support system 1, which is one embodiment of the present invention.

[0027] As shown in Figure 2, once the setting coordinate acquisition means 102 acquires the slope range coordinate values, the preprocessing means 103 sets the slope range on the 3D point cloud data based on the slope range coordinate values. In the example shown in Figure 2, for example, the area encompassing the slope range coordinate values ​​P101 to P104 is set as slope range A101.

[0028] Furthermore, once the slope direction coordinates are obtained by the setting coordinate acquisition means 102, the preprocessing means 103 sets the slope direction on the 3D point cloud data based on the slope direction coordinates. In the example shown in Figure 2, for example, if the starting point P101 and ending point P102 are set as slope direction coordinate values, the preprocessing means 103 sets the direction from the starting point P101 to the ending point P102 as the slope direction.

[0029] Furthermore, the preprocessing means 103 generates an approximate plane from the 3D point cloud data and rotates the approximate plane so that its normal direction is oriented in the Z-axis direction.

[0030] Specifically, as shown in Figure 3, an approximate plane A102 is generated from the 3D point cloud data, and the approximate plane A102 is rotated so that the normal direction Z101 of the plane of this approximate plane A102 is oriented along the Z-axis in the 3D space of the 3D point cloud data.

[0031] The laser point cloud data storage means 104 stores the 3D point cloud data from which slope range extraction processing and rotation processing have been performed by the preprocessing means 103.

[0032] The plane extraction means 105 first thins out the point cloud at predetermined intervals set in advance to suppress the characteristics of each device, then calculates the normal vector at each point in the thinned 3D point cloud data, and extracts a plane based on the normal vector.

[0033] Figure 4 is an explanatory diagram illustrating the processing of the plane extraction means 105 included in the slope frame construction support system 1, which is one embodiment of the present invention.

[0034] The plane extraction means 105 calculates the normal vector at each point in the 3D point cloud data. Point cloud data where the angle between the normal vector and the Z-axis in 3D space is greater than or equal to a predetermined threshold Thθ1 will have an inclined surface that cannot be a frame or a base. Therefore, the plane extraction means 105 deletes the point cloud data where the angle between the normal vector and the Z-axis is greater than or equal to the predetermined threshold Thθ1, and extracts a plane based on the remaining point cloud data.

[0035] In the example shown in Figure 4, the plane extraction means 105 deletes point cloud data such as point cloud data D102, where the angle between the normal vector and the Z-axis is greater than or equal to a predetermined threshold Thθ1. Then, the plane extraction means 105 extracts a plane based on the remaining point cloud data such as point cloud data D101, where the angle between the normal vector and the Z-axis is less than the predetermined threshold Thθ1.

[0036] Furthermore, the plane extraction means 105 removes noise from the extracted plane using the SOR (Statistical Outlier Removal) method, for example, by using the number of neighboring points and the maximum distance as SOR parameters, and then removes point cloud data that does not possess planarity using the neighboring distance and planarity threshold as dimensional features. Here, noise is removed using the SOR method, but this is not the only method; noise can also be removed using a pass-through filter that uses a simple neighboring distance or a voxel grid filter that uses a grid. In other words, the plane extraction means 105 can remove noise from the extracted plane using a noise reduction method based on the spatial distribution of the 3D point cloud data.

[0037] The plane separation means 106 separates the plane extracted by the plane extraction means 105 into a slope frame portion and a bottom portion. For example, the plane separation means 106 separates the plane extracted by the plane extraction means 105 into a slope frame portion and a bottom portion using a cloth simulation method. Here, the cloth simulation method is a technique for simulating the movement of cloth, and in this case, when a cloth is placed over the plane extracted by the plane extraction means 105 from above in three-dimensional space, the portion that comes into contact with the cloth becomes the slope frame portion, and the portion that does not come into contact with the cloth becomes the bottom portion.

[0038] In this example, the slope frame and base were separated using the cloth simulation method. However, the planar separation means 106 may also be used to separate the slope frame and base using separation methods based on the spatial distribution of point clouds, such as clustering methods based on point distances or object recognition methods using deep learning.

[0039] Figure 5 is an explanatory diagram illustrating the processing of the planar separation means 106 included in the slope frame construction support system 1, which is one embodiment of the present invention.

[0040] As shown in Figure 5, using the Cloth Simulation method, for example, the plane separation means 106 sets the portion that comes into contact with the cloth when the cloth is placed over the plane extracted from above by the plane extraction means 105 in three-dimensional space, such as D201, as the slope frame portion. On the other hand, the plane separation means 106 sets the portion that does not come into contact with the cloth when the cloth is placed over the plane extracted from above by the plane extraction means 105 in three-dimensional space, such as D202, as the bottom surface portion.

[0041] The center point calculation means 107 clusters the point cloud data of the base surface based on Euclidean distance and calculates a center point for each clustered base surface.

[0042] Figures 6(a) and 6(b) are schematic diagrams illustrating the processing of the center point calculation means 107 included in the slope frame construction support system 1, which is one embodiment of the present invention.

[0043] As clustering is performed by the center point calculation means 107, the point cloud data of the bottom surface is recognized as point cloud data of different bottom surfaces. Therefore, as shown in Figure 6(a), the clustered point cloud data D301 to D303 of the bottom surface are recognized as point cloud data (clusters) of different bottom surfaces. In this case, if the width of a cluster exceeds a predetermined range, that is, if it is less than a predetermined threshold width WTh1 or exceeds a predetermined threshold width WTh2, the center point calculation means 107 may determine that the point cloud data of the bottom surface has not been properly clustered and delete the cluster.

[0044] As shown in Figure 6(b), the center point calculation means 107 calculates the center points D301a to D303a for each of the clustered bottom point cloud data D301 to D303.

[0045] The selection means 108 generates cross-sectional clusters by clustering point cloud data contained in the cross-sections that are crossed in the XY direction (vertical and horizontal) with respect to the input slope direction coordinate values ​​from the center point, based on Euclidean distance, and selects the cross-sectional slope frame portion and the cross-sectional slope bottom portion based on the average elevation of the cross-sectional clusters.

[0046] Figures 7(a),(b) and 8(a),(b) are schematic diagrams illustrating the processing of the selection means 108 included in the slope frame construction support system 1, which is one embodiment of the present invention.

[0047] As shown in Figure 7(a), from the center point D302a of the bottom surface point cloud data (cluster) D302, a cross-section R101 is generated that crosses horizontally (X direction) with respect to the slope direction B101, based on the input slope direction coordinate values ​​P101~P102, and a cross-section R102 is generated that crosses perpendicularly (Y direction) with respect to the slope direction B101.

[0048] As a result, as shown in Figure 7(b), it is possible to extract point cloud data D401 corresponding to the bottom portion included in the cross section R101 with center point D302a, point cloud data D402 corresponding to the slope frame included in the cross section R101, point cloud data D403 corresponding to the bottom portion included in the cross section R102 with center point D302a, and point cloud data D404 corresponding to the slope frame included in the cross section R102.

[0049] As shown in Figure 8(a), the selection means 108 generates cross-sectional clusters D501-D506 and D511-D516 by clustering the point cloud data included in cross-sectional R101 and cross-sectional R102 based on Euclidean distance.

[0050] The selection means 108 selects the cross section slope frame and the cross section slope bottom based on the average elevation (average height in the Z-axis direction) of each of the generated cross section clusters D501 to D506 and D511 to D516.

[0051] In the example shown in Figure 8(b), the selection means 108 sets an elevation threshold Th1 by adding a predetermined height to the elevation (height in the Z-axis direction) of the center point D514a, and sets the cross-sectional clusters with an average elevation lower than this elevation threshold Th1 as the bottom of the cross-sectional slope. Here, cross-sectional clusters D511 to D516 are set as the bottom of the cross-sectional slope.

[0052] Furthermore, the selection means 108 sets a cross-sectional cluster as a cross-sectional slope frame section if the average elevation is higher than the elevation threshold Th1 and the width (lateral length) of the cross-sectional cluster is longer than a predetermined width threshold. In this case, cross-sectional clusters D501 to D506 are set as cross-sectional slope frame sections.

[0053] The extraction means 109 extracts the cross-sectional slope frame portions selected by the selection means 108 that are located near the left and right sides of the bottom of the cross-sectional slope including the center point.

[0054] The completed work value calculation means 110 calculates the completed work value based on the cross-sectional slope frame portion extracted by the extraction means 109.

[0055] Figures 9(a) and 9(b) are schematic diagrams illustrating the processing of the extraction means 109 and the completed value calculation means 110 of the slope frame construction support system 1, which is one embodiment of the present invention.

[0056] As shown in Figure 9(a), the extraction means 109 extracts the cross-sectional slope frame portions D503 and D504 as cross-sectional slope frame portions near the left and right sides of the bottom portion D514 of the cross-sectional slope including the center point D514a.

[0057] As shown in Figure 9(b), the completed value calculation means 110 calculates the width L1 of the extracted cross section slope frame D503, the width L2 of the extracted cross section slope frame D504, and the width L3 of the cross section slope frame D514 including the center point D514a as the completed value.

[0058] Furthermore, the completed value calculation means 110 calculates the height from both ends of the bottom of the cross-sectional slope including the center point D514a to the cross-sectional slope frame sections D503 and D504 extracted by the extraction means 109 as the completed value.

[0059] Figures 10(a) and 10(b) are schematic diagrams illustrating the processing of the completed work value calculation means 110 included in the slope frame construction support system 1, which is one embodiment of the present invention.

[0060] As shown in Figure 10(a), the completed value calculation means 110 extracts the coordinates of both ends D514b and D514c of the bottom of the cross section slope D514, which includes the center point D514a. Then, as shown in Figure 10(b), the completed value calculation means 110 calculates the height from the extracted ends D514b and D514c to the cross section slope frame D503 and D504 as the completed value. Specifically, the completed value calculation means 110 calculates the difference H1 between the Z-axis coordinate value of end D514b and the Z-axis coordinate value of end D503c of the cross section slope frame D503 as the completed value, and also calculates the difference H2 between the Z-axis coordinate value of end D514c and the Z-axis coordinate value of end D504b of the cross section slope frame D504 as the completed value.

[0061] Furthermore, the completed work value calculation means 110 calculates the midpoints of the left and right vicinity of the cross section slope frame portion D514, which includes the center point D514a extracted by the extraction means 109, and calculates the distance between the calculated midpoints as the completed work value.

[0062] Figures 11(a) and (b) are schematic diagrams illustrating the processing of the completed work value calculation means 110 included in the slope frame construction support system 1, which is one embodiment of the present invention.

[0063] As shown in Figure 11(a), the completed work value calculation means 110 extracts the cross section slope frame portions D503 and D504 near the left and right sides of the bottom of the cross section slope D514, which includes the center point D514a. The completed work value calculation means 110 then extracts the coordinates of both ends D503b and D503c of the extracted cross section slope frame portion D503, and also extracts the coordinates of both ends D504b and D504c of the extracted cross section slope frame portion D504.

[0064] As shown in Figure 11(b), the completed value calculation means 110 calculates the coordinates of the midpoint D503a, which is located midway between the ends D503b and D503c, based on the coordinates of the extracted ends D503b and D503c, and also calculates the coordinates of the midpoint D504a, which is located midway between the ends D504b and D504c, based on the coordinates of the extracted ends D504b and D504c.

[0065] The completed work value calculation means 110 then calculates the distance L4 between midpoints, which is the Euclidean distance between midpoints D503a and D504a, as the completed work value.

[0066] The completed work storage means 111 stores the completed work values ​​calculated by the completed work value calculation means 110. Specifically, the completed work storage means 111 stores the width L1 of the cross section slope frame D503, the width L2 of the cross section slope frame D504, the width L3 of the cross section slope frame D514, the difference H1, the difference H2, and the distance L4 between the midpoints of the frame.

[0067] Figure 12 is a flowchart showing the processing steps of the slope framing support system 1, which is one embodiment of the present invention.

[0068] In step S101, the slope protection support system 1 performs slope range extraction processing. Specifically, the preprocessing means 103 sets the slope range on the 3D point cloud data based on the slope range coordinate values ​​input by the user.

[0069] In step S103, the slope protection support system 1 performs a rotation process. Specifically, the preprocessing means 103 generates an approximate plane from the 3D point cloud data based on the slope direction coordinate values ​​input by the user, and rotates the approximate plane so that its normal direction is oriented in the Z-axis direction.

[0070] In step S105, the slope protection support system 1 performs slope protection separation processing. Specifically, the plane extraction means 105 thins out the point cloud at predetermined intervals set in advance to suppress the characteristics of each piece of equipment, then calculates the normal vector at each point in the thinned 3D point cloud data, and extracts a plane based on the normal vector. Subsequently, the plane separation means 106 separates the plane extracted by the plane extraction means 105 into a slope protection section and a bottom section.

[0071] In step S107, the slope protection support system 1 executes a cross-section generation process. Specifically, the center point calculation means 107 clusters the point cloud data of the bottom surface based on Euclidean distance and calculates a center point for each clustered bottom surface. The selection means 108 generates cross-section clusters by clustering the point cloud data included in the cross-sections that are crossed perpendicularly and horizontally to the input slope direction coordinate values ​​from the center point based on Euclidean distance. Then, the selection means 108 selects the cross-section slope protection section and the cross-section slope bottom based on the average elevation of the cross-section clusters, and the extraction means 109 extracts the cross-section slope protection sections near the left and right sides of the cross-section slope bottom containing the center point from among the cross-section slope protection sections selected by the selection means 108.

[0072] In step S109, the slope protection support system 1 performs width calculation processing. Specifically, the completed value calculation means 110 calculates the width L1 of the extracted cross-sectional slope protection section, the width L2 of the extracted cross-sectional slope protection section, and the width L3 of the cross-sectional slope protection section including the center point as completed values.

[0073] In step S111, the slope protection support system 1 performs a height calculation process. Specifically, the completed value calculation means 110 extracts the coordinates of both ends of the bottom of the cross-sectional slope including the center point, and calculates the heights H1 and H2 from the extracted ends to the cross-sectional slope protection section as completed values.

[0074] In step S113, the slope frame construction support system 1 performs a process to calculate the distance between frame centers. Specifically, the completed value calculation means 110 calculates the midpoints of the left and right vicinity of the bottom of the cross-sectional slope frame containing the center point extracted by the extraction means 109, and calculates the calculated distance L4 between the midpoints as the completed value.

[0075] As described above, according to the slope protection support system 1, which is one embodiment of the present invention, since it has a laser point cloud data acquisition means 101, a set coordinate acquisition means 102, a preprocessing means 103, a plane extraction means 105, a plane separation means 106, a center point calculation means 107, a selection means 108, an extraction means 109, and a completed value calculation means 110, even if the acquired 3D point cloud data includes points where the point cloud shape of the edge that becomes a cross-sectional change point cannot be obtained, it is possible to accurately calculate the completed value of the slope protection work.

[0076] Returning to Figure 1, the beam length calculation means 120 calculates the midpoints of the left and right vicinity of the bottom of the cross-sectional slope, including the center point extracted by the extraction means 109, and calculates the beam length based on the linear point cloud data connecting the multiple midpoints. Functionally, the beam length calculation means 120 includes a midpoint selection means 121, a first filtering means 122, a second filtering means 123, and a connection means 124.

[0077] The midpoint selection means 121 calculates the midpoints of the left and right vicinity of the bottom of the cross-sectional slope containing the center point extracted by the extraction means 109, and narrows down the two midpoints calculated based on adjacent bottoms of the cross-sectional slope to one point by clustering.

[0078] Figures 13 and 14 are schematic diagrams illustrating the processing of the midpoint selection means 121 of the slope frame construction support system 1, which is one embodiment of the present invention.

[0079] As shown in Figures 13 and 14, the midpoint selection means 121 calculates the midpoints of the left and right vicinity of the bottom of the cross-sectional slope containing the center point extracted by the extraction means 109. Here, for one slope frame, a midpoint D601a is calculated in relation to the cross-sectional slope frame located to the right, and a midpoint D602a is calculated in relation to the cross-sectional slope frame located to the left, based on the slope frame width coordinate values ​​D602b and D602c.

[0080] In this case, the midpoint selection means 121 calculated the midpoints of the left and right vicinity of the bottom of the cross-sectional slope containing the center point extracted by the extraction means 109. However, it is also possible to calculate the midpoint D601a of the cross-sectional slope by determining the center point between the input slope width coordinate value D601b and the slope width coordinate value D601c, and to calculate the midpoint D602a of the cross-sectional slope by determining the center point between the input slope width coordinate value D602b and the slope width coordinate value D602c.

[0081] Then, the midpoint selection means 121 narrows down the two calculated midpoints D601a and D602a to one point through clustering.

[0082] The first filtering means 122, when an arbitrary midpoint calculated is selected as the point of interest, will not recognize the linear point cloud data as beam length if, in the cross-section formed by connecting two other midpoints within a predetermined range from the point of interest, there exists point cloud data where the Z coordinate value of adjacent point cloud data is greater than or equal to a predetermined Z threshold, or where adjacent point cloud data are separated by a predetermined XY threshold or more in the XY direction.

[0083] Figures 15 and 16 are schematic diagrams illustrating the processing of the first filtering means 122 included in the slope protection support system 1, which is one embodiment of the present invention.

[0084] As shown in Figure 15, here, the calculated arbitrary midpoint is designated as the point of interest D601a. ​​The first filtering means 122 sets a predetermined range C101 that is contained within a predetermined radius centered on the point of interest D601a.

[0085] This predetermined range C101 includes numerous midpoints, such as midpoint D605a. On the other hand, midpoints such as D611a, which are located more than a predetermined distance from the point of interest D601a, are not included within the predetermined range C101.

[0086] The first filtering means 122 generates a cross-section connecting two midpoints for all midpoints included within the predetermined range C101.

[0087] In the example shown in Figure 16(a), the first filtering means 122 generates a cross-section F601 that includes midpoints D601a and 603a, and also generates a cross-section F602 that includes midpoints D601a and 604a.

[0088] Figure 16(b) shows the cross-section F601 generated by the first filtering means 122, and Figure 16(c) shows the cross-section F601 generated by the first filtering means 122.

[0089] The first filtering means 122 determines whether, in the point cloud data included in a cross-section containing a straight line connecting two midpoints within a predetermined range C101, the Z coordinate values ​​of adjacent point cloud data are greater than or equal to a predetermined Z threshold, and whether there are point cloud data where adjacent point cloud data are separated by a predetermined XY threshold or more in the XY direction.

[0090] As shown in Figure 16(b), in the cross-section F601, the point cloud data is continuous, and there are no adjacent point cloud data points whose Z coordinate values ​​are greater than or equal to a predetermined Z threshold Zth. Also, since the point cloud data is continuous in the cross-section F601, there are no adjacent point cloud data points that are separated by a predetermined XY threshold XYTh or more in the XY direction. Therefore, the first filtering means 122 recognizes the point cloud data included in the cross-section F601 as candidates for beam length.

[0091] On the other hand, as shown in Figure 16(c), in the cross-section F602, the point cloud data is continuous, and there are no data points where the Z coordinate value of adjacent point cloud data is greater than or equal to a predetermined Z threshold Zth. However, in the cross-section F602, there are point cloud data points that are discontinuous and separated by L5 on the XY plane, that is, adjacent point cloud data points that are separated by a predetermined XY threshold XYTh or more on the XY plane. Therefore, the first filtering means 122 determines that the slope frame is interrupted in the cross-section F602 and recognizes the point cloud data included in the cross-section F602 as being outside the scope of beam length.

[0092] The second filtering means 123 calculates the angle between the midpoint in the vicinity of the point of interest and the point of interest when an arbitrary midpoint calculated is taken as the point of interest, clusters based on the calculated angle, and extracts the midpoint closest to the point of interest from the clustered neighboring point clusters as the corresponding point.

[0093] Figure 17 is a schematic diagram illustrating the processing of the second filtering means 123 included in the slope frame construction support system 1, which is one embodiment of the present invention.

[0094] As shown in Figure 17, the second filtering means 123 calculates the angle on the XY plane between the midpoint in the vicinity of the point of interest D701 and the point of interest D701, assuming that the calculated midpoint is the point of interest D701. By clustering based on the calculated angle, a neighboring point cluster G701 is generated that includes the midpoints D702 and D703 in the vicinity of the point of interest D701, and a neighboring point cluster G702 is generated that includes the midpoints D704 and D705 in the vicinity of the point of interest D701.

[0095] The second filtering means 123 then extracts the midpoints closest to the point of interest D701 from the midpoints included in the clustered neighbor point clusters G701 and G702, respectively, as corresponding points. Here, the midpoint closest to the point of interest D701 from the midpoints included in the clustered neighbor point cluster G701 is extracted as corresponding point D703. Also, the midpoint closest to the point of interest D701 from the midpoints included in the clustered neighbor point cluster G702 is extracted as corresponding point D704, and the extracted corresponding points are stored as provisional beam length coordinate values.

[0096] The connection means 124 calculates a straight line connecting the corresponding points, calculates the coordinates of the intersection points of the calculated straight lines, and calculates the beam length as the straight line connecting the intersection points.

[0097] Figures 18 and 19 are schematic diagrams illustrating the processing of the connection means 124 provided in the slope frame construction support system 1, which is one embodiment of the present invention.

[0098] As shown in Figure 18(a), for example, the second filtering means 123 calculates a straight line R801 connecting corresponding points D801 and D802, or calculates a straight line R802 connecting corresponding points D811 and D812. Here, although not shown, there are other corresponding points in the direction extending from corresponding point D802 to corresponding point D801, and by connecting these corresponding points, the straight line R801 is generated. The same applies to the straight line R802.

[0099] On the other hand, there are no other corresponding points in the direction extending from corresponding point D801 to corresponding point D802, and the line does not intersect with any other lines, ending at corresponding point D801. This can occur, for example, when the number of points acquired in the 3D point cloud data is small.

[0100] Therefore, as shown in Figure 18(b), the connection means 124 extends the line R801 from corresponding point D802 in the direction extending from corresponding point D801 to corresponding point D802 until it intersects with the line R803, and the point where it intersects with the line R803 is designated as corresponding point D803. Similarly, the connection means 124 extends the line R802 from corresponding point D812 in the direction extending from corresponding point D811 to corresponding point D812 until it intersects with the line R803, and the point where it intersects with the line R803 is designated as corresponding point D813.

[0101] As shown in Figure 19(a), the connection means 124 calculates the straight lines R801 to R805 connecting each corresponding point, and calculates the coordinates of the intersection points of the calculated straight lines R801 to R805. Here, the coordinates of the intersection points D901 to D906 are calculated. Here, the Z-axis coordinates of the intersection points D901 to D906 are taken from arbitrary point cloud data close to the intersection points.

[0102] As shown in Figure 19(b), the connection means 124 recalculates the straight line connecting the calculated intersection points D901 to D906 as the straight line R801 to R805, and stores this calculated straight line R801 to R805 as the beam length in the beam length storage means 125.

[0103] Figure 20 is a flowchart showing the processing steps of the slope framing support system 1, which is one embodiment of the present invention.

[0104] In step S201, the slope protection support system 1 executes a midpoint list generation process. Specifically, the midpoint selection means 121 calculates the midpoints of the left and right vicinity of the bottom of the cross-sectional slope containing the center point extracted by the extraction means 109. The midpoint selection means 121 may also calculate the midpoints of the cross-sectional slope protection based on the input slope protection width coordinate values.

[0105] In step S203, the slope protection support system 1 performs midpoint list filtering. Specifically, the midpoint selection means 121 narrows down two midpoints calculated based on adjacent cross-sectional slope bottoms to one point through clustering.

[0106] In step S205, the slope protection support system 1 performs a process to acquire neighboring points of the point of interest. Specifically, the first filtering means 122 sets a predetermined range that is included in a predetermined radius centered on the point of interest, assuming that an arbitrary midpoint calculated is the point of interest.

[0107] In step S207, the slope protection support system 1 performs filtering based on the cross-sectional view. Specifically, the first filtering means 122 generates a cross-section connecting two midpoints for all midpoints within a predetermined range, and determines whether the Z coordinate values ​​of adjacent point cloud data are greater than or equal to a predetermined Z threshold, or whether there are point cloud data points that are separated by a predetermined XY threshold or more in the XY direction from adjacent point cloud data points. If the Z coordinate values ​​of adjacent point cloud data are greater than or equal to a predetermined Z threshold, or if there are point cloud data points that are separated by a predetermined XY threshold or more in the XY direction from adjacent point cloud data points, the first filtering means 122 does not recognize the point cloud data included in the cross-section as beam length.

[0108] In step S209, the slope protection support system 1 performs distance filtering. Specifically, the second filtering means 123 calculates the angle between the midpoint in the vicinity of the midpoint in the vicinity of the midpoint in the vicinity of the midpoint in the vicinity of the midpoint in the vicinity of the midpoint in the vicinity of the midpoint, clusters based on the calculated angle, and extracts the midpoint closest to the midpoint in the vicinity of the midpoint in the clustered neighboring point cluster as the corresponding point.

[0109] In step S211, the slope protection support system 1 performs beam length registration processing. Specifically, the second filtering means 123 stores the extracted corresponding points as temporary beam length coordinate values ​​in the beam length storage means 125.

[0110] In step S213, the slope protection support system 1 performs the extension process of the end line segments. Specifically, the connection means 124 calculates a straight line connecting the corresponding points and extends the straight line from the corresponding point that needs to be extended.

[0111] In step S215, the slope protection support system 1 performs the intersection calculation process. Specifically, the connection means 124 calculates a straight line connecting each corresponding point and calculates the coordinates of the intersection of the calculated straight lines.

[0112] In step S217, the slope frame construction support system 1 performs a process to acquire neighboring points of interest. Specifically, the connection means 124 recalculates the straight line connecting the calculated intersection points as a straight line, and stores this calculated straight line as the beam length in the beam length storage means 125.

[0113] The processes in steps S219 to S223 are identical to those in steps S207 to S211, so their explanation will be omitted.

[0114] As described above, according to the slope protection support system 1, which is one embodiment of the present invention, since it has a laser point cloud data acquisition means 101, a set coordinate acquisition means 102, a preprocessing means 103, a plane extraction means 105, a plane separation means 106, a center point calculation means 107, a selection means 108, an extraction means 109, and a beam length calculation means 120, the beam length of the slope protection structure can be accurately calculated even when the acquired 3D point cloud data includes points where the point cloud shape of the edge that becomes a cross-sectional change point cannot be obtained.

[0115] Furthermore, the above-described embodiment can also be realized by running a program installed on a computer. [Explanation of symbols]

[0116] 1. Slope Retaining Frame Construction Support System 101 Laser point cloud data acquisition means 102 Means for acquiring set coordinates 103 Pre-treatment means 104 Laser point cloud data storage means 105 Plane extraction means 106 Plane separation means 107 Center point calculation means 108 Selection method 109 Extraction means 110 Means for calculating completed work value 111. Method for storing completed work 120 Beam length calculation method 121 Midpoint Selection Method 122 First filtering means 123 Second filtering means 124 Connection methods 125 Beam length storage means

Claims

1. A device for calculating the completed value of a slope protection structure based on 3D point cloud data, A plane extraction means calculates the normal vector at each point in the three-dimensional point cloud data and extracts a plane based on the normal vector, A plane separation means for separating the plane extracted by the plane extraction means into a slope frame portion and a bottom surface portion, A center point calculation means that clusters the point cloud data of the base portion based on Euclidean distance and calculates a center point for each clustered base portion, A selection means generates a cross-sectional cluster by clustering point cloud data contained in a cross-section that is crossed perpendicularly and horizontally to the input slope direction coordinate values ​​from the aforementioned center point, based on Euclidean distance, and selects the cross-sectional slope frame portion and the cross-sectional slope bottom portion based on the average elevation of the cross-sectional cluster. An extraction means for extracting the cross-sectional slope frame portions near the left and right sides of the bottom of the cross-sectional slope including the center point from among the cross-sectional slope frame portions selected by the selection means, A means for calculating the completed work value based on the extracted cross-sectional slope frame portion, A device for calculating completed work values, characterized by being equipped with the following features.

2. The aforementioned completion value calculation means is The width of the extracted cross-sectional slope frame and the width of the bottom of the cross-sectional slope including the center point are calculated as the completed value. The device for calculating the completed work value according to claim 1.

3. The aforementioned completion value calculation means is The height from both ends of the bottom of the cross-sectional slope including the center point to the cross-sectional slope frame extracted by the extraction means is calculated as the completed value. The device for calculating the completed work value according to claim 1.

4. The aforementioned completion value calculation means is The midpoints of the left and right vicinity of the bottom of the cross-sectional slope, including the center point extracted by the extraction means, are calculated, and the distance between the calculated midpoints is used as the completed value. The device for calculating the completed work value according to claim 1.

5. The aforementioned planar extraction means is The normal vector at each point in the three-dimensional point cloud data is calculated, point cloud data where the angle between the normal vector and the Z-axis is greater than or equal to a predetermined threshold is deleted, and a plane is extracted based on the remaining point cloud data. The device for calculating the completed work value according to claim 1.

6. The aforementioned planar extraction means is Noise is removed from the extracted plane using a noise reduction method based on the spatial distribution of the 3D point cloud data. The device for calculating the completed work value according to claim 1.

7. The plane separation means separates the plane extracted by the plane extraction means into a slope frame portion and a bottom surface portion using a separation method based on the spatial distribution of the three-dimensional point cloud data. The device for calculating the completed work value according to claim 1.

8. A program for calculating completed work values, which is executed by a device that calculates the completed work value of a slope protection structure based on three-dimensional point cloud data, A plane extraction step is performed to calculate the normal vector at each point in the three-dimensional point cloud data and to extract a plane based on the normal vector, A plane separation step is performed to separate the plane extracted by the plane extraction step into a slope frame portion and a bottom surface portion. A center point calculation step involves clustering the point cloud data of the base portion based on Euclidean distance and calculating the center point for each clustered base portion. A selection step is to generate a cross-sectional cluster by clustering point cloud data contained in the cross-sections that are crossed perpendicularly and horizontally to the input slope direction coordinate values ​​from the aforementioned center point, based on Euclidean distance, and to select the cross-sectional slope frame portion and the cross-sectional slope bottom portion based on the average elevation of the cross-sectional cluster, An extraction step is performed to extract the cross-sectional slope frame portions near the left and right sides of the bottom of the cross-sectional slope, including the center point, from among the cross-sectional slope frame portions selected in the selection step, A step of calculating the completed value based on the extracted cross-sectional slope frame portion, A program for calculating completed work values, characterized by having the following features.

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