JP7208708B2 - Shape measurement method, apparatus, and program for three-dimensional measurement object - Google Patents

Description

INDUSTRIAL APPLICABILITY The present invention is a method and apparatus for measuring the shape of a three-dimensional measurement object, which can three-dimensionally capture the object to be surveyed, for example, road surface cracks, ruts, longitudinal and cross-sectional investigations, etc. , as well as programs.

For example, Patent Literature 1 describes a technique of measuring three-dimensional coordinates of an arbitrary position using a surveying instrument such as a total station brought into the field.

According to the technique described in Patent Document 1, a reflecting member such as a prism or reflected light is placed at two reference positions whose coordinates are known, light for measurement is projected from the total station toward the reflecting member, and the light is reflected. The distance to each reference position is measured based on the phase difference of light, and the horizontal angle and vertical angle of the light projection direction for measurement are also measured. Then, the three-dimensional coordinates of the measurement position can be obtained by performing geometrical calculations based on the measured distance, horizontal angle, vertical angle, positional coordinates of the known reference position, and the like.

JP 2013-32983 A

By the way, in the civil engineering and construction industry, more and more accurate survey data are required. For example, accurate surveying that three-dimensionally captures a three-dimensional measurement object, such as road surface crack surveys such as road scratches and damage, rut surveys, longitudinal and cross-sectional surveys (volume of cutting amount), etc. It is necessary to visit the site and visually confirm, take data of the survey point with a survey meter, and create a survey result report. The work is done by specialized companies. For this reason, the time required for the work and the human cost are high. The emergence of tools was hoped for.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems. It is an object of the present invention to provide a method and apparatus for measuring the shape of a three-dimensional measurement object, and a program for reducing the cost.

In order to solve the above-described problems, the present invention provides a method for measuring the shape of a three-dimensional measurement object, wherein a three-dimensional scanning device irradiates a laser beam at a reflection point from the three-dimensional measurement object. A first step of acquiring point cloud data in which each point is three-dimensionally coordinated; analyzing the acquired point cloud data with an analysis device to generate shape confirmation data of the three-dimensional measurement object; a second step of outputting confirmation data to an output device; and in the second step, the shape confirmation data of the three-dimensional measurement object is generated by reflecting observation results from the total station in the point cloud data. obtaining an image including the three-dimensional measurement object obtained by imaging the same area including the effective range of the three-dimensional scanning device at different times by the imaging unit of the UAV, and obtaining the three-dimensional measurement object output from the UAV; generating a composite image excluding non-three-dimensional measurement objects included in the image containing the three-dimensional measurement object, and analyzing the composite image to correspond to the point cloud data Correcting the color information of the shape confirmation data of the three-dimensional measurement object using the color information that is generated so as to be more vivid than the color information of the point cloud data, and the non-three-dimensional measurement object and outputting the shape confirmation data of the three-dimensional measurement object excluding the .
In the present invention, in the second step, an observation result for electronic marking by a total station is reflected in the point cloud data, and the shape confirmation data is generated using the point cloud data to which the electronic marking has been added. It is characterized by

In the present invention, the shape confirmation data of the three-dimensional measurement object is characterized in that it is used for any one of road surface crack investigation, rut investigation, and longitudinal and cross-sectional investigation.

According to the present invention, a series of tasks from surveying a three-dimensional survey object to creating various reports can be accurately realized in one stop, and a three-dimensional measurement object can be measured to reduce time and human costs. A shape measuring method, an apparatus, and a program can be provided.

1 is a block diagram showing the configuration of a shape measuring apparatus for a three-dimensional measurement object according to an embodiment of the present invention; FIG. 4 is a flow chart showing processing operations of the shape measuring apparatus for a three-dimensional measurement object according to the embodiment of the present invention; FIG. 3 is a flow chart showing the processing operation of the shape measuring apparatus for a three-dimensional measurement object according to the embodiment of the present invention (continuation of FIG. 2); FIG. 4 is a diagram showing an example of coordinated and color-mapped point cloud data generated by the shape measuring apparatus for a three-dimensional measurement object according to the embodiment of the present invention; FIG. 2 is a diagram showing an example of a current plane image of a three-dimensional measurement object generated by the three-dimensional measurement object shape measuring apparatus according to the embodiment of the present invention; It is a figure which shows an example of the present condition longitudinal cross-sectional view produced|generated by the shape measuring apparatus of the three-dimensional measurement object which concerns on embodiment of this invention. It is a figure which shows the image at the time of scattering a reflecting material on the road imaged by the imaging part. FIG. 8 is a diagram showing a synthesized image obtained by synthesizing the point cloud data acquired by the three-dimensional scanning device with the image shown in FIG. 7; FIG. 11 is a block diagram showing the configuration of a shape measuring apparatus for a three-dimensional measurement object according to a third embodiment; FIG. 10 is a diagram showing a plurality of images including a road captured in the same area at different times by the imaging unit of the UAV; FIG. 11 is a diagram showing a synthesized image obtained by excluding a vehicle from the image shown in FIG. 10; 12 is a diagram showing three-dimensional point cloud data including color information generated by analyzing the composite image shown in FIG. 11; FIG. It is a figure which shows the point-group data by which color information was correct|amended. FIG. 11 is a block diagram showing the configuration of a shape measuring apparatus for a three-dimensional measurement object according to a fourth embodiment; FIG. 10 is a diagram showing point cloud data with electronic markings added; FIG. 4 is a diagram showing point cloud data of enlarged electronic markings;

(Configuration of the first embodiment)
Hereinafter, a shape measuring apparatus for a three-dimensional measurement object according to an embodiment of the present invention (hereinafter referred to as the present embodiment) will be described in detail with reference to the drawings. The same numbers or symbols are given to the same elements throughout the description of the embodiment.

As shown in FIG. 1, a shape measuring apparatus 100 for a three-dimensional measurement object according to the present embodiment is realized by, for example, a PC (Personal Computer) or the like, and includes an analysis apparatus 30 as a device main body, a keyboard, a mouse, or the like. It is composed of an input device 31 and an output device 32 such as an LCD (Liquid Crystal Display) monitor and a printer. Note that the analysis device 30 is connected offline to the three-dimensional scanning device (3D scanner) 10 and the total station (TS) 20 .

The three-dimensional scanning device 10 irradiates a three-dimensional measurement object such as a road with a laser beam, and a group of points (hereinafter referred to as a point group data) and output to the analysis device 30 .

The total station 20 places reflecting members at two reference positions (reference points) whose position coordinates are known, projects measurement light toward the reflecting members, and measures the distance to each reference position based on the phase difference of the reflected light. Distances are measured to obtain horizontal and vertical angles, which are output to the analysis device 30 as SIMA (Surveying Instruments Manufacturers' Association) data known as a common format for survey data.

The analysis device 30 sequentially reads and executes a program (not shown) to analyze the point cloud data acquired from the three-dimensional scanning device 10 and/or the SIMA data acquired from the total station 20 to generate road shape confirmation data. In addition, it has a function of creating longitudinal and transverse views between any two points input by the input device 31, converting them into design data, and outputting (displaying or printing) them to the output device 32 respectively.

For this reason, the analysis device 30 includes a point cloud data acquisition unit 301, a SIMA data acquisition unit 302, a SIMA integration unit 303, and a plane image synthesis unit, as shown by expanding the program structure in blocks in FIG. 304, plane material creation unit 305, alignment creation unit 306, route calculation unit 307, triangular network longitudinal and cross-section data acquisition unit 308, finished shape management unit 309, and design data and delivery data creation unit 310. Consists of.

A point cloud data acquisition unit 301 acquires point cloud data in which each point of a reflection point from a road, which is a three-dimensional measurement object, is converted into three-dimensional coordinates by laser light irradiated by the three-dimensional scanning device 10, and SIMA Output to the integration unit 303 .

The SIMA data acquisition unit 302 converts SIMA data (point number, point name, X, Y, Z) including reference points output from the total station 20 into data in a CSV (Comma Separated Values) format that can be read by the analysis device 30. File conversion is performed, the XY coordinates are exchanged, and the data is output to the SIMA integration unit 303 .

The SIMA integration unit 303 reflects the CSV data output from the SIMA data acquisition unit 302 in the point cloud data output from the point cloud data acquisition unit 301, and further converts the PTS file of the point cloud generated by the color mapping process. X and Y are exchanged and read, integrated with the reference point SIMA data, and output to the planar image synthesizing unit 304 .

Planar image synthesizing unit 304 synthesizes a current planar image whose scale is fixed with the integrated data output from SIMA integrating unit 303 , and outputs the synthesized TIFF (Tagged Image File Format) data to planar material creating unit 305 .

A planar material creating unit 305 creates a planar material based on the reference point SIMA data and the TIFF data output from the planar image synthesizing unit 304 , and outputs the created planar material to the line creating unit 306 . The planar material creation unit 305 further converts the created planar material into PDF (Portable Document Format) and DWG (Drawing), which is the standard file format of AutoCAD (registered trademark), into a file, and the design data and delivery data creation unit 301 Output to

The alignment creation unit 306 creates IP (Intersection Point) points based on the plane data output from the plane data creation unit 305, outputs the IP coordinates (SIMA data) to the route calculation unit 307, and converts the SIMA data is converted into a PDF file, and the PDF data is output to the design data and delivery data creation unit 310 .

The route calculation unit 307 calculates the coordinates based on the position coordinates of the main points of the line obtained by the route survey based on the line shown in the integrated data output from the SIMA integration unit 303 and the IP coordinates output from the line creation unit 306. , the curve parameters, longitudinal elements, width, and arbitrary survey points input from the input device 31 are used to perform route calculation for obtaining three-dimensional coordinate values for the entire route, and the results are output to the triangular network longitudinal and cross section data acquisition unit 308. do.

Based on the three-dimensional coordinate values output from the route calculation unit 307, the triangular network longitudinal and cross-sectional data acquisition unit 308 acquires longitudinal and cross-sectional data (longitudinal and cross-sectional views) between any two specified points as SIMA data for design data and delivery. Output to data creation unit 310 .

The design data and delivery data creation unit 310 outputs current longitudinal and cross-sectional data to the output device 32 based on the cross-sectional SIMA data output from the triangular network longitudinal and cross-sectional data acquisition unit 308 .

The workmanship management unit 309 uses the created basic design data to measure the workmanship at the site, outputs the difference between the design and the workmanship that can determine the quality of the workmanship. The finished product measurement data is read, and a finished product form is created via the design data and delivery data creating unit 310 .

The design data and delivery data creation unit 310 converts the cross-sectional SIMA data into linear data ALG (ER Mapper Algorithm Data), creates a vertical cross-sectional view for a 3D viewer, and displays it on the output device 32 . The design data and delivery data creation unit 310 also creates a general plan view and an area volume calculation sheet in a predetermined format from the planar material in PDF or DWG format output from the planar material creation unit 305, and also creates a line. A route survey calculation sheet in PDF format output from the unit 306 is created and output to the route calculation unit 307. Further, based on the PDF output from the route calculation unit 307 and the three-dimensional coordinate data, cracks and ruts in a predetermined format are generated. Investigation materials are generated and output to the output device 32 respectively.

(Operation of the first embodiment)
Hereinafter, the processing operation of the three-dimensional measurement object shape measuring apparatus 100 according to the present embodiment shown in FIG. 1 will be described with reference to the flowcharts of FIGS. 2 and 3 and the images shown in FIGS. Figure 2 shows the 3D pre-survey, and Figure 3 shows the accuracy of the three-dimensional measurement object constructed based on the basic design data created by the 3D pre-survey against the standards intended by the ordering party. It shows the flow of the finished shape measurement process that manages the degree of construction technology.

Here, reference points are set in advance on the road, which is the object of three-dimensional measurement, and the total station 20, which integrates the light wave rangefinder and the transit, converts the results of die point and principal point observations into SIMA data. Output as certain CAD data. Then, based on this CAD data and the reference point SIMA data, the main points are arranged in a polygonal line, the intersection angle (included angle) and the distance between adjacent points at each point are measured, and the position of the point is calculated by traverse calculation ( Step S101), SIMA data consisting of point numbers, point names, and X, Y, and Z are generated.

On the other hand, the three-dimensional scanning device 10 irradiates a road with laser light and generates point group data in which each point of a large number of reflection points of the laser light is three-dimensionally coordinated. The three-dimensional scanning device 10 calculates the distance from the installation position to the reflection point from the time from laser irradiation to light reception, and calculates the three-dimensional coordinate position (X, Y, Z) of the reflection point in the investigation range. Calculate and output as point cloud data summarizing each position of reflection points in the investigation range. Using this point group data, it is possible to draw a pattern of the road of the three-dimensional measurement object.

The analysis device 30 executes the following processes based on the point cloud data acquired from the three-dimensional scanning device 10 and the SIMA data acquired from the total station 20 . That is, the point cloud data acquisition unit 301 acquires the point cloud data scanned and output by the three-dimensional scanning device 10 and outputs it to the SIMA integration unit 303, and the SIMA data acquisition unit 302 observes and outputs the data by the total station 20. SIMA data is acquired, file-converted into a CSV format, a CSV file in which the X and Y coordinates are exchanged is generated, and output to the SIMA integration unit 303 (step S102).

The SIMA integration unit 303 reflects the CSV data output from the SIMA data acquisition unit 302 in the point cloud data output from the point cloud data acquisition unit 301, and further generates a point cloud PTS file by color mapping (step S103). FIG. 4 shows an example of point cloud data.

Subsequently, the SIMA integration unit 303 reads the generated PTS file by replacing X and Y, integrates it with the reference point SIMA data, and furthermore, the manhole, road width, crack shape, etc. obtained by the traverse calculation in step S101. are converted into DXF data and SIMA data and output to the plane image synthesizing unit 304 (step S104).

The planar image synthesizing unit 304 generates images on the screen of Rhinoceras (registered trademark), which is commercial three-dimensional CAD software for the manufacturing industry, specializing in free-form NURBS (Non-Uniform Rational Basis Spline) modeling. The construction area is defined and DXF data is output (step S105), the integrated data output by the SIMA integration unit 303 is synthesized with the current situation planar image with a fixed scale, and output as synthesized TIFF data to the planar material creation unit 305. (Step S106) Fig. 5 shows an example of the current plane image.

The planar material creating unit 305 creates a planar material based on the reference point SIMA data and the TIFF data output from the planar image synthesizing unit 304, and outputs it to the line creating unit 306 (step S106). The planar material creating unit 305 further converts the created planar material into PDF and DWG files, and outputs the files to the design data and delivery data creating unit 310 .

Next, based on the plane data output from the plane data creation section 305, the alignment creation unit 306 creates a plane alignment of the road centerline at the intersection of the extension lines of the two straight sections sandwiching the circular curve and transition curve from both sides. A certain IP point is created (step S107), and its IP coordinates (SIMA data) are output to the route calculation unit 307. FIG. The linear creation unit 306 further converts the SIMA data into a PDF file and outputs the PDF data to the design data and delivery data creation unit 310 .

The route calculation unit 307 combines the position coordinates of the principal points of the line obtained by the route survey on the basis of the line shown in the integrated data output from the SIMA integration unit 303 and the IP coordinates output from the line creation unit 306. Based on this, the curve parameters, longitudinal elements, width, and arbitrary survey points input by the user through the input device 31 are used to calculate the three-dimensional coordinate values for the entire route. Output to the acquisition unit 308 (step S108). The route calculation unit 307 further investigates damage to the road surface (road surface investigation) based on the alignment, converts the results into PDF and 3D data in order to create survey materials for cracks and ruts, and converts the results into design data and delivery. It is output to the data creation unit 310 (step S109). When the route calculation unit 307 converts the data into 3D data, the result of data processing by Rhinoceras (registered trademark) is reflected.

The triangular network longitudinal and transverse data acquisition unit 308 creates triangular network longitudinal and transverse SIMA data between any two points based on the three-dimensional coordinate values output from the route calculation unit 307 (step S110), and creates design data and delivery data. Output to unit 310 . The design data and delivery data creation unit 310 outputs the current longitudinal and cross-sectional data to the output device 32 based on the cross-sectional SIMA data output from the triangular network longitudinal and cross-sectional data acquisition unit 308 (step S111). The current longitudinal and cross-sectional data output here are also used in finished shape measurement, the details of which are shown in FIG. FIG. 6 shows an example of a current longitudinal/cross-sectional view created from the current longitudinal/cross-sectional data.

The design data and delivery data creation unit 310 further converts the transverse SIMA data into linear data ALG, creates basic design data including longitudinal and transverse views for the 3D viewer, and outputs the basic design data to the output device 32 . The design data and delivery data creation unit 310 also creates a general plan view and an area volume calculation sheet in a predetermined format from the planar material in PDF or DWG format output from the planar material creation unit 305, and also creates a line. A route survey calculation sheet in PDF format output from the unit 306 is created and output to the route calculation unit 307. Further, based on the PDF output from the route calculation unit 307 and the three-dimensional coordinate data, cracks and ruts in a predetermined format are generated. Investigation materials are generated and output to the output device 32 respectively.

Next, referring to FIG. 3, longitudinal and cross-section planning finished shape measurement (from 3D preliminary survey to 3D finished shape measurement) will be described. Based on the design data and the basic design data output from the delivery data creation unit 310, the finished shape management unit 309 analyzes the current cross-sectional data, and performs longitudinal and cross-sectional planning to calculate the vertical curve various amounts for each vertical line change point ( Step S201) Based on the input reference point SIMA data, three-dimensional design data is created and an XML (Extensible Markup Language) format file is output (step S202).

Subsequently, the finished shape management unit 309 performs finished shape measurement using the total station 20 based on the XML file (step S203), and converts the results into PDF and XML files via the design data and delivery data creation unit 310. format to the output device 32 .

In addition, the finished shape management unit 309 collects the reference point SIMA data, the linear data (ALG) output from the triangular net vertical and cross data acquisition unit 208, and the data observed and output by the three-dimensional scanning device 10 and the total station 20. Based on the 3D data, data analysis is performed in the same process as the 3D preliminary survey shown in the flowchart of FIG. 2 (step S204). Then, based on the three-dimensional design data of the input XML file, the completed vertical and cross-sectional data is output, and the PDF or The 3D finished product data in DWG format is output to the output device 32 (step S205).

(Effect of the first embodiment)
As described above, the three-dimensional measurement target shape measuring apparatus 100 according to the present embodiment is configured such that the analysis device 30 detects the reflection from the three-dimensional measurement target such as a road by the laser light emitted by the three-dimensional scanning device 10. Each point is acquired as point cloud data in which each point is converted into three-dimensional coordinates, the acquired point cloud data is analyzed, and shape confirmation data of the three-dimensional measurement object is generated. are created, converted into design data, and output to the output device 32 respectively. As a result, a series of operations from surveying a three-dimensional survey object to creating various reports can be accurately realized in one stop, and time and personnel costs can be reduced.

Specifically, conventionally, workers installed a measuring instrument such as a measure or a total station 20 and took time to measure, such as crack investigation, rut investigation, longitudinal and cross-sectional investigation (volume investigation of cutting amount). A field survey can be performed in a short time by the shape measuring device 100 using the three-dimensional scanning device 10, and detailed survey data can be obtained by using the survey data obtained by using the total station 20 together. As a result, it becomes possible to grasp the shape and change of the three-dimensional measurement object, which could not be grasped conventionally, without visiting the site many times. As a result, it was confirmed that, for example, these investigations, which used to take about three days, can be shortened to about two hours. In the past, road rut and longitudinal cross-section surveys were conducted by separate companies, but now this can be done on a one-stop basis, greatly reducing the time and personnel burden of surveying work. In addition, since efficiency can be improved, a significant cost reduction is possible.

In addition, in the three-dimensional measurement object shape measuring apparatus 100 according to the present embodiment, only the road was exemplified as the three-dimensional measurement object, but it is not limited to roads. Alternatively, it can be applied to various uses such as construction planning, execution, area, map creation, and the like.

(Method for measuring the shape of a three-dimensional object)
Further, the method for measuring the shape of a three-dimensional measurement object according to the present embodiment is realized by using at least the three-dimensional scanning device 10 shown in FIG. be done. In this method, for example, as shown in FIG. 2, each point in the reflection point from the three-dimensional measurement target is acquired as point cloud data in which each point is three-dimensionally coordinated by the laser beam irradiated by the three-dimensional scanning device 10. a first step ( S103 ), the acquired point cloud data is analyzed by the analysis device 30 to generate shape confirmation data of the three-dimensional measurement object, and between any two points input by the input device 31 and a second step (S104 to S111) of creating longitudinal and transverse views, converting them into design data, and outputting them to the output device 32, respectively.

Further, in the method for measuring the shape of a three-dimensional measurement object according to the present embodiment, the first step is to convert the observation result by the total station 20 into a file format that can be used by the analysis device 30 and reflect it in the point cloud data, The PTS file generated by the color mapping process and the reference point SIMA data may be integrated and input to the analysis device 30 (steps S101 to S104). In the second step, route calculation is performed based on the position coordinates of the main points of the alignment obtained by route surveying with the alignment as a reference, and the captured intermediate coordinates. A transverse view may be created (steps S105 to S111).

According to the method for measuring the shape of a three-dimensional measurement object according to the present embodiment, a series of operations from surveying the three-dimensional measurement object to creating various reports can be accurately realized in one stop, reducing time and human costs. It is possible to provide a method for measuring the shape of a three-dimensional measurement object that reduces the

Also, the program according to the present embodiment is a program for the shape measuring apparatus 100 for a three-dimensional measurement object. The program causes the analysis device 30 to execute the same processing as each step in the method for measuring the shape of the three-dimensional measurement object according to the present embodiment described above. omitted.

According to the program according to the present embodiment, the analysis device 30 reads out and executes the program according to the present embodiment described above, so that a series of tasks from surveying the three-dimensional survey object to creating various reports can be accurately performed. It is possible to provide the shape measuring apparatus 100 for a three-dimensional measurement object that can be realized as a one-stop shop and that can reduce time and personnel costs.

[Second embodiment]
In the first embodiment, the three-dimensional scanning device 10 irradiates a three-dimensional measurement object such as a road with laser light, converts each point of a large number of reflection points of the laser light into three-dimensional coordinates, and obtains a point cloud. was generating data.
By the way, roads that have just been constructed or roads that are raining or just after the rain stops form a glossy black surface due to the influence of rainwater and the like.

However, the three-dimensional scanning device 10 is not suitable for measuring such glossy black surfaces.
In other words, when the three-dimensional scanning device 10 attempts to measure such a place where rainwater remains on the road, the laser light is not reflected well, and as a result, each point of the small number of reflection points of the laser light is Since the number of points is reduced, the number of point cloud data converted into three-dimensional coordinates is also reduced, and there is a problem that sufficient point cloud data cannot be obtained.
In addition to rainwater, the same problem occurs when water is sprayed on the road, or when a material that is originally difficult to obtain appropriate reflection is used.

Therefore, in the second embodiment, a method for obtaining good point cloud data even in such a situation will be described below with reference to FIGS. 7 and 8. FIG.
In addition, below, description shall be abbreviate|omitted about the same point as 1st Embodiment, and mainly a different point from 1st Embodiment shall be demonstrated.
Further, in the following description, a portion where appropriate laser light reflection cannot be obtained may be referred to as a laser light unsuitable surface.
FIG. 7 is a diagram showing an image captured by the imaging unit when the reflecting material 50 is scattered on the road, and FIG. 8 is an image obtained by synthesizing the point cloud data acquired by the three-dimensional scanning device 10 with the image shown in FIG. FIG. 10 is a diagram showing a synthesized image;

As shown in FIG. 7, a reflecting material 50 made of wheat flour or the like is sprinkled on the laser beam unsuitable surface where appropriate laser beam reflection cannot be obtained due to the influence of rainwater or the like.
The reflecting material 50 is not limited to wheat flour or the like, and may be a liquid material made of paint mixed with glass beads, for example.

Then, when the three-dimensional scanning device 10 is used after the reflecting material 50 is dispersed in this manner, the laser light is effectively reflected by the reflecting material 50, and as shown in FIG. A reflection point can be obtained.
As a result, as shown in FIG. 8, a large number of point cloud data in which each point of the reflection point is three-dimensionally coordinated can be obtained, and good point cloud data can be generated.
Incidentally, such a point group acquisition method of a laser beam unsuitable surface by scattering a reflecting material may be called an MRP method.

[Third embodiment]
In the first embodiment, the SIMA integration unit 303 reflects the CSV data output from the SIMA data acquisition unit 302 in the point cloud data output from the point cloud data acquisition unit 301, and further converts the point cloud by color mapping. Although the PTS file was generated, in the third embodiment, in order to obtain point cloud data with clearer colors, a method for correcting color information in point cloud data will be described below with reference to FIGS. 9 to 13. Description will be made with reference to this.
In the description of the third embodiment as well, the description of the same points as in the first embodiment may be omitted.

FIG. 9 is a block diagram showing the configuration of a shape measuring apparatus 100 for a three-dimensional measurement object according to the third embodiment.
10A and 10B are diagrams showing a plurality of images including the road captured in the same area at different times by the imaging unit of the UAV 40. FIG. 10A shows an image including the road captured in the same area at the first time. FIG. 10(b) is a diagram showing an image including the road taken in the same region at a second time later than the first time.
FIG. 11 is a diagram showing a synthesized image obtained by excluding the vehicle from the image shown in FIG.
FIG. 12 is a diagram showing three-dimensional point cloud data that is generated by analyzing the composite image shown in FIG. 11 and includes color information.
FIG. 13 is a diagram showing point cloud data in which color information has been corrected.

As shown in FIG. 9, a shape measuring apparatus 100 for three-dimensional measurement according to the third embodiment includes an analysis device 30, an input device 31, and an output device 32. The analysis device 30 includes a three-dimensional A scanning device 10, a total station 20, and a UAV (Unmanned Aerial Vehicle) 40 are connected offline.
Note that the analysis device 30 and the UAV 40 are used for correcting the color information of the point cloud data as described below.

The UAV 40 is connected offline to the analysis device 30 and is an unmanned aerial vehicle that can fly by remote control.
The UAV 40 has an imaging unit (not shown) for capturing an image of a three-dimensional measurement object such as a road.

Images captured by the imaging unit of the UAV 40 are shown in FIGS. 10(a) and 10(b).
Specifically, FIGS. 10A and 10B show three-dimensional measurement objects such as roads captured at different times by the imaging unit of the UAV 40 in the same area including the effective range of the three-dimensional scanning device 10. is an image containing
As described above, the UAV 40 is connected offline to the analysis device 30, and the plurality of images captured by the UAV 40 can be output to the image synthesizing unit 311, which will be described later.

The analysis device 30 of the third embodiment has the same configuration as the analysis device 30 of the first embodiment except that it includes an image synthesis unit 311, an image survey analysis unit 312, and a color information correction unit 313. are doing.

The image synthesizing unit 311 synthesizes a plurality of images output from the UAV 40, including roads and other 3D measurement objects, to generate a synthesized image excluding non-3D measurement target vehicles, as shown in FIG. and output to the image survey analysis unit 312 .

The image survey analysis unit 312 analyzes the synthesized image output from the image synthesis unit 311 to generate three-dimensional point cloud data including color information as shown in FIG. .

Then, the color information correction unit 313 uses the 3D point cloud data including the color information output from the image survey analysis unit 312 to convert the 3D point cloud data into the PTS file of the point cloud output from the SIMA engagement unit 303 . The color information of the data is corrected, and the PTS file of the point cloud is output to the plane image synthesizing unit 304 and the route calculation unit 307 as three-dimensional point cloud data having clearer color information.

Specifically, the three-dimensional point cloud data including the color information of the PTS file of the point cloud output from the SIMA engagement unit 303 is based on the data acquired by the three-dimensional scanning device 10. While the color information such as the white lines drawn on the road may be unclear, the 3D point cloud data including the color information based on the image acquired by the UAV 40 has the color information such as the white lines drawn on the road. Since the image is clear, the color information correction unit 313 performs processing for correcting color information such as white lines on the road.

Thus, in the third embodiment, by correcting the color information of the PTS file of the point cloud using the UAV 40 and the analysis device 30, point cloud data with clearer colors can be obtained. For example, as shown in FIG. 13, details such as white lines drawn on the road can be clearly confirmed.

[Fourth embodiment]
In the above-described third embodiment, the case of correcting the color information by using the UAV 40 has been described. For this range, the 3D point cloud data based on the data acquired by the 3D scanning device 10 may be used to supplement the point cloud where the point cloud is insufficient. Referring to FIG. 14, a method of supplementing point cloud data from the three-dimensional scanning device 10 using the UAV 40 will be described.

FIG. 14 is a block diagram showing the configuration of a shape measuring apparatus 100 for a three-dimensional measurement object according to the fourth embodiment.
Although the fourth embodiment will be specifically described below with reference to FIG. 14, the description of the same points as those of the first embodiment may be omitted in the fourth embodiment as well.
In addition, the contents of the UAV 40 that have already been explained in the third embodiment may also be omitted.

As shown in FIG. 14, a shape measuring apparatus 100 for three-dimensional measurement according to the fourth embodiment includes an analysis device 30, an input device 31, and an output device 32. The analysis device 30 includes a three-dimensional The scanning device 10, total station 20, and UAV 40 are connected offline.
Note that the UAV 40 and the analysis device 30 are used to supplement the point cloud data by the three-dimensional scanning device 10 as described below.

The UAV 40 is connected offline to the analysis device 30 and is an unmanned aerial vehicle capable of flying by remote control. It is as described in the third embodiment.
Then, in the same manner as described in the third embodiment, the imaging unit of the UAV 40 captures the same area including the area outside the effective range of the three-dimensional scanning device 10 at different times. A plurality of images are output to the image synthesizing unit 311 .

The analysis device 30 of the fourth embodiment has the same configuration as the analysis device 30 of the first embodiment, except that it includes an image synthesis unit 311, an image survey analysis unit 312, and a point cloud data synthesis unit 314. have.

As in the third embodiment, the image synthesizing unit 311 synthesizes a plurality of images including a three-dimensional measurement object such as a road output from the UAV 40, thereby excluding a non-three-dimensional measurement object vehicle and performing a three-dimensional measurement. A composite image including areas outside the effective range of the source scanning device 10 is generated and output to the image survey analysis unit 312 .

Then, the image survey analysis unit 312 analyzes the composite image including the area outside the effective range of the three-dimensional scanning device 10 output from the image survey analysis unit 312, thereby determining the area outside the effective range of the three-dimensional scanning device 10. , and outputs it to the point cloud data synthesizing unit 314 .

Then, the point cloud data synthesizing unit 314 synthesizes the three-dimensional points output from the image survey analysis unit 312 so as to supplement the points where the point cloud of the point cloud data output from the point cloud data acquisition unit 301 is insufficient. The point cloud of the cloud data is partially synthesized, and the three-dimensional point cloud data in which the partial point cloud is supplemented is output to the SIMA integration unit 303 .

As described above, in the fourth embodiment, the UAV 40 is used to supplement the point cloud in the three-dimensional point cloud data based on the data acquired by the three-dimensional scanning device 10, where the point cloud is insufficient. A complete 3D point cloud data can be generated.

[Fifth embodiment]
The total station 20 described in the first embodiment may be used to make the boundaries of the three-dimensional point cloud data based on the data acquired by the three-dimensional scanning device 10 easier to understand. In the embodiment, a method for making such boundaries easier to understand using the total station 20 will be described.

In other words, since the amount of information is enormous in current situation observation using point clouds, the 3D point cloud data based on the data acquired by the 3D scanning device 10, when partially enlarged, shows the boundary between the roadway and the sidewalk. However, it is possible to use the total station 20 to add electronic markings so that the boundaries can be seen. Explain marking.
In addition, also in the fifth embodiment, the description of the same points as in the first embodiment may be omitted.

FIG. 15 is a diagram showing point cloud data to which electronic markings have been added, and FIG. 16 is a diagram showing enlarged point cloud data of electronic markings.
For example, the total station 20 outputs the observation result of the marking points at the boundary between the roadway and the sidewalk (the boundary between the roadway and the sidewalk) as SIMA data for electronic marking to the SIMA data acquisition unit 302 of the analysis device 30. .

Then, the SIMA data acquisition unit 302 converts the SIMA data for electronic marking output by the total station 20 into CSV-format data for electronic marking that can be read by the analysis device 30, replaces the XY coordinates, and integrates SIMA. Output to unit 303 .

Then, the SIMA integration unit 303 reflects the CSV data for electronic marking output from the SIMA data acquisition unit 302 in the point cloud data output from the point cloud data acquisition unit 301, and performs electronic marking by color mapping processing. Generate a PTS file of the added point cloud.

For example, FIG. 15 shows an example of point cloud data to which electronic markings M have been added so as to indicate white line boundaries, and the line connecting the electronic markings M is the white line boundary.
Then, when the periphery of the electronic marking M is enlarged, the state of the white line that was vaguely visible in FIG. 15 becomes blurred, and the state of the white line becomes unclear as shown in FIG. As shown in FIG. 16, since the boundary of the white line exists on the line connecting the electronic markings M, it is possible to know where the boundary is by the electronic marking M even if the state of the white line is unknown.

As described above, in the fifth embodiment, by adding the electronic marking to the point cloud data, even if the boundary becomes unclear due to the enlargement, as shown in FIG. To speedily and accurately distinguish a boundary between a carriageway and a sidewalk of a road.
Furthermore, if the distance between the added electronic marking and the carriageway-sidewalk boundary of the road shown in the point cloud data exceeds a predetermined threshold, it can be inferred that there is an error in the point cloud data.

Although the present invention has been described using the embodiments, it goes without saying that the technical scope of the present invention is not limited to the scope described in the above embodiments. It is obvious to those skilled in the art that various modifications or improvements can be made to the above embodiments. Moreover, it is clear from the description of the scope of the claims that the forms with such modifications or improvements can also be included in the technical scope of the present invention.

10 three-dimensional scanning device 20 total station 30 analysis device 31 input device 32 output device 40 UAV
50 Reflector 100 Shape measuring device 301 Point cloud data acquisition unit 302 SIMA data acquisition unit 303 SIMA integration unit 304 Planar image synthesizing unit 305 Planar material creation unit 306 Line creation unit 307 Route calculation unit 308 Triangular network vertical cross-section data acquisition unit 309 Done Shape management unit 310 Design data and delivery data creation unit 311 Image composition unit 312 Imaging survey analysis unit 313 Color information correction unit 314 Point cloud data composition unit M Electronic marking

Claims (3)

A method for measuring the shape of a three-dimensional measurement object,
a first step of acquiring point cloud data in which each point in the reflection point from the three-dimensional measurement object is three-dimensionally coordinated by irradiating a laser beam with a three-dimensional scanning device;
a second step of analyzing the acquired point cloud data by an analysis device, generating shape confirmation data of the three-dimensional measurement object, and outputting the shape confirmation data to an output device;
In the second step,
generating shape confirmation data of the three-dimensional measurement object by reflecting observation results from the total station in the point cloud data;
Acquiring images including the three-dimensional measurement object obtained by imaging the same area including the effective range of the three-dimensional scanning device at different times by the imaging unit of the UAV,
synthesizing a plurality of images including the three-dimensional measurement object output from the UAV to generate a synthesized image excluding non-three-dimensional measurement objects included in the image including the three-dimensional measurement object;
Shape confirmation of the three-dimensional measurement object using color information generated by analyzing the synthesized image so as to correspond to the point cloud data and clearer than the color information of the point cloud data. A method for measuring the shape of a three-dimensional measurement object, comprising correcting color information of data and outputting shape confirmation data of the three-dimensional measurement object excluding non-three-dimensional measurement objects. In the second step,
2. The method according to claim 1, wherein observation results for electronic marking by a total station are reflected in the point cloud data, and the shape confirmation data are generated using the point cloud data to which the electronic marking has been added. A method for measuring the shape of a three-dimensional object. 3. The shape of the three-dimensional measurement object according to claim 1 or 2, wherein the shape verification data of the three-dimensional measurement object is used for any one of road surface crack investigation, rut investigation, and longitudinal and cross-sectional investigation. Measuring method.

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