Surveying data processing device, surveying data processing method, and surveying data processing program

Abstract

To obtain a technology capable of efficiently accurately detecting a position of a measuring target by laser scanning.SOLUTION: A measurement data processing device acquires a laser-scanning point group obtained by first laser scanning, acquires a reflection luminance point group exceeding a threshold value from among the laser-scanning point group, acquires a partial point group, which is a partial point group corresponding to an object causing reflection, from among the reflection luminance point group exceeding the threshold value, acquires a distribution of laser-scanning beams and beam cross-sectional shapes at positions of the partial point group on the basis of ranging values of the partial point group, and identifies reflection estimated areas of the partial point group, which are estimated to be areas causing reflection from reflection prisms 300, 301, on the basis of the distribution of the laser-scanning beams and the beam cross-sectional shapes, and sets second laser-scanning conditions for the reflection prisms 300, 301.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to the technology of laser scanning. [Background technology]

[0002] In laser scanning, a surveying reflector such as a reflecting prism may be used as a target (see, for example, Patent Document 1). In this case, the target is used for purposes such as calculating the exterior orientation parameters of the laser scanning device, assigning coordinates to the laser scan point cloud, and measuring the coordinates of a specific position.

[0003] This can also be thought of as target positioning using a laser scanner device instead of a total station. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 22021-47068 Summary of the Invention [Problem to be solved by the invention]

[0005] In the laser scan using the above-mentioned surveying reflector, a first laser scan with a relatively low scan density is performed to obtain a first laser scan point cloud. Next, points with high reflection intensity (points with a greater amount of reflected light) are detected from this first laser scan point cloud, and the reflector is considered to be located near those points, and a second laser scan with a higher scan density is performed.

[0006] The second laser scan is set to a high scan density to obtain a large number of reflection points on the reflector. In this way, a large number of positioning points are obtained on the reflector used for surveying, and by calculating the average value, precise positioning of the reflector is performed.

[0007] However, because the scanning light from the laser scanning device is emitted radially, the scanning density decreases and the spacing between adjacent scanning lights increases at a distance. Therefore, with the first laser scanner described above, the optical axis (center) of the laser scanning light does not necessarily strike the surveying reflector (especially at a distance). However, the farther the distance, the larger the beam cross section of the scanning light, so when a single scanning light is used, the greater the probability that the reflector will be captured by the scanning light. However, as the beam cross section of the scanning light increases, the energy density decreases, and the received light intensity of the reflected light decreases.

[0008] Conventionally, these points have not been taken into consideration, and the conditions for the second laser scan have been determined by focusing on points with high reflection intensity.

[0009] In this context, an object of the present invention is to provide a technique that can efficiently detect the position of a target for surveying by laser scanning. [Means for solving the problem]

[0010] The present invention includes a laser scan point cloud acquisition unit that acquires a laser scan point cloud, a high-brightness reflection point cloud acquisition unit that acquires a point cloud with reflection brightness exceeding a threshold from the laser scan point cloud, a partial point cloud acquisition unit that acquires a partial point cloud that is a partial point cloud corresponding to an object where reflection occurs from the point cloud with reflection brightness exceeding the threshold, and a partial point cloud identification unit that identifies the partial point cloud corresponding to a reflector used for surveying. a laser scanning light information acquisition unit that acquires the distribution of laser scanning light and the shape of the beam cross section at the position of the partial point cloud based on the distance measurement values ​​of the partial point cloud; and a reflection estimation area acquisition unit that acquires a reflection estimation area that is estimated to be an area where reflection from the object has occurred based on the distribution of laser scanning light and the shape of the beam cross section, wherein the partial point cloud identification unit compares the size and / or shape of the reflector for surveying with the size and / or shape of the reflection estimation area of ​​the partial point cloud, and identifies the partial point cloud that corresponds to the reflector for surveying. A surveying data processing device. The present invention can also be understood as a method invention and a program invention. In the present invention, a preferable aspect includes a laser scan condition setting unit that sets conditions for laser scanning the reflector for surveying based on the identified partial point cloud.

[0011] In the present invention, a preferable aspect is that the reflection estimation region of the partial point group is a region surrounded by a closed line that includes the outer edge of the beam cross section of the laser scanning light at the position of the partial point group.

[0012] In the present invention, it is preferable that the greater the distance from the viewpoint of the laser scan, the lower the luminance points acquired as the point cloud of reflected luminance exceeding the threshold. In the present invention, it is preferable that the greater the distance from the viewpoint of the laser scan, the smaller the threshold.

[0013] The present invention The present invention includes a laser scan point cloud acquisition unit that acquires a laser scan point cloud, a high brightness reflection point cloud acquisition unit that acquires a point cloud with reflection brightness exceeding a threshold from the laser scan point cloud, a partial point cloud acquisition unit that acquires a partial point cloud that is a partial point cloud corresponding to an object where reflection occurs from the point cloud with reflection brightness exceeding the threshold, and a partial point cloud identification unit that identifies the partial point cloud corresponding to a reflector for surveying, and A beam profile indicating the relationship between the distance from the center of the optical axis and the light intensity is acquired in advance for the reflected light of the laser scanning light, and for each of the laser scanning lights, a predicted range for predicting the position of the reflection center in the partial point group is determined based on the detected value of the reflected light and the beam profile, the predicted range having a size inversely proportional to the intensity of the reflected light, and the position of the reflection center in the partial point group is predicted based on the overlap of the predicted ranges of the respective laser scanning lights. The present invention can also be understood as a method invention and a program invention.

[0014] The present invention the system includes a laser scan point cloud acquisition unit that acquires a first laser scan point cloud with lower accuracy than the second laser scan in order to determine conditions for a second laser scan; a high-brightness reflection point cloud acquisition unit that acquires a point cloud with reflection brightness exceeding a threshold from the laser scan point cloud; a partial point cloud acquisition unit that acquires a partial point cloud, which is a partial point cloud corresponding to an object where reflection has occurred, from the point cloud with reflection brightness exceeding the threshold; and a partial point cloud identification unit that identifies the partial point cloud corresponding to a reflector used for surveying, In acquiring the partial point cloud, an estimated separation distance between the target point and another adjacent point, which is estimated based on the distance to the target point, is compared with a calculated separation distance between the target point and the other point, which is calculated based on the distance measurement values ​​of the target point and the other point.If the result of the comparison shows that the target point and the other point are separated in the depth direction when viewed from the viewpoint position of the laser scan point cloud, it is determined that the target point and the other point are not part of the partial point cloud. The present invention can also be understood as a method invention and a program invention. In the present invention, a preferred aspect is to predict the position of the center of the reflector based on the identified partial point group, and set the range of the second laser scan based on the predicted position of the center of the reflector as a condition for the second laser scan. The present invention is a surveying data processing device that includes a laser scan point cloud acquisition unit that acquires a laser scan point cloud, a high-brightness reflection point cloud acquisition unit that acquires a point cloud with reflection brightness exceeding a threshold from the laser scan point cloud, a partial point cloud acquisition unit that acquires a partial point cloud, which is a partial point cloud corresponding to an object where reflection has occurred, from the point cloud with reflection brightness exceeding the threshold, and a partial point cloud identification unit that identifies the partial point cloud that corresponds to a reflector used for surveying, and predicts the position of the center of the reflector based on the identified partial point cloud.

[0015] The present invention may include an aspect in which the average position of multiple points constituting the partial point cloud is predicted as the position of the center of the reflector.The present invention may include an aspect in which the position of the center of gravity of multiple points constituting the partial point cloud, weighted by the intensity of laser scan light, is predicted as the position of the center of the reflector.The present invention may include an aspect in which the partial point cloud identification unit identifies the partial point cloud corresponding to the reflector for surveying based on a comparison of the size and / or shape of the reflector for surveying with the partial point cloud.

[0016] The present invention provides a method for obtaining a laser scan point cloud, obtaining a point cloud having a reflection brightness exceeding a threshold value from the laser scan point cloud, obtaining a partial point cloud that is a partial point cloud corresponding to an object where reflection occurs from the point cloud having a reflection brightness exceeding the threshold value, and identifying the partial point cloud that corresponds to a reflector for surveying. 、 and A surveying data processing method for predicting the position of the center of the reflector based on the identified partial point cloud.

[0017] The present invention is a program that is read and executed by a computer, the program including the steps of: acquiring a laser scan point cloud; acquiring a point cloud having a reflection brightness exceeding a threshold value from the laser scan point cloud; acquiring a partial point cloud, which is a partial point cloud corresponding to an object where reflection has occurred, from the point cloud having a reflection brightness exceeding the threshold value; and identifying the partial point cloud corresponding to a reflector for surveying. 、 Run and a surveying data processing program for predicting the position of the center of the reflector based on the identified partial point cloud. [Effects of the Invention]

[0018] According to the present invention, a technique is provided that can efficiently detect the position of a target for surveying by laser scanning. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 is a schematic diagram of an embodiment. [Figure 2] FIG. 1 is an external view of a laser scanning device. [Figure 3] FIG. 1 is a block diagram of a laser scanning device. [Figure 4] FIG. 2 is a block diagram of a survey data processing device. [Figure 5] 10 is a flowchart illustrating an example of a processing procedure. [Figure 6] FIG. 10 is a conceptual diagram showing a method for evaluating the size of a partial point group. [Figure 7] FIG. 1A shows the beam shape of laser scanning light, and FIG. 1B shows the distribution profile of light intensity. [Figure 8] FIG. 10 is a diagram illustrating an example of a beam profile of a laser scanning light. [Figure 9] FIG. 1 is a conceptual diagram showing a predicted range. DETAILED DESCRIPTION OF THE INVENTION

[0020] (overview) FIG. 1 shows a laser scanning device (laser scanner) 100, a surveying data processing device 200, reflecting prisms 300 and 301, and a building 400 to be laser scanned. In this example, the laser scanning device 100 is installed at a position determined to be appropriate as the viewpoint for laser scanning. The reflecting prisms 300 and 301 are examples of reflectors used for surveying, and are installed at positions with known coordinates. Here, an example is shown in which two reflecting prisms are used, but three or more reflecting prisms can also be used.

[0021] The reflecting prisms 300 and 301 have the function of reflecting incident light by inverting it by 180 degrees. There are two types of reflecting prisms: one that can accommodate light incident from a specific direction and one that can accommodate light incident from all directions. Either type can be used, but here, the reflecting prism that can accommodate light incident from a specific direction is used.

[0022] In this example, the laser scanning device 100 is installed in a location whose coordinates are unknown. Then, the position of two reflecting prisms 300, 301, whose positions are known, is measured by laser scanning. The position and attitude of the laser scanning device 100 are then determined by resection, with the positions of the reflecting prisms 300, 301 used as control points. The coordinate system used is, for example, an absolute coordinate system. An absolute coordinate system is a coordinate system used in GNSS and maps, and its position (coordinates) are described by, for example, latitude, longitude, and altitude. Note that the present invention is not limited to the above example and can be widely applied to technologies for measuring the position of reflecting prisms by laser scanning.

[0023] The survey data processing device 200 processes the laser scan data obtained by the laser scanning device 100. The processing of the laser scan data includes (1) determining the conditions for a relatively dense second laser scan based on the results of a relatively coarse first laser scan, (2) determining the position of the reflecting prism with high precision based on the second laser scan, and (3) processing the laser scan point cloud of the survey object obtained by the laser scan.

[0024] Here, we will explain the process of (1). The processes of (2) and (3) are well known processes, so we will not explain them here. Examples of the process of (3) include matching a first laser scan point cloud and a second laser scan point cloud obtained from different viewpoints, and creating a three-dimensional model based on the laser scan point clouds.

[0025] In this example, the survey data processing device 200 is configured as a PC (personal computer). The survey data processing device 200 can also be configured as dedicated hardware. The survey device 200 can also be incorporated into the laser scanning device 100.

[0026] The reflecting prisms 300 and 301 are the same and are commercially available for surveying. Reflectors for surveying other than reflecting prisms can also be used. Examples of reflectors for surveying other than reflecting prisms include those using retroreflective materials. The building 400 is an example of a target for laser scanning. The target for laser scanning is not particularly limited.

[0027] (laser scanning device) 2 shows a laser scanning device 100. The laser scanning device 100 includes a tripod 111, a base unit 112 fixed to the top of the tripod 111, a horizontal rotation unit 113 that can rotate horizontally on the base unit 112, and a vertical rotation unit 114 that can rotate vertically relative to the horizontal rotation unit 113.

[0028] The vertical rotation unit 114 includes an optical unit 115 that emits and receives laser scanning light. Laser scanning is performed by irradiating pulses of laser scanning light from the optical unit 105 and receiving the reflected light while rotating the horizontal rotation unit 113 horizontally and the vertical rotation unit 114 vertically. The horizontal rotation unit 113 and the vertical rotation unit 114 are rotated by motors. The horizontal rotation angle of the horizontal rotation unit 113 and the vertical rotation angle of the vertical rotation unit 114 are precisely measured by encoders.

[0029] The laser scanning light is a single beam of pulsed ranging light, and one laser scanning light measures the distance to a scanning point, which is a reflection point where the laser scanning light hits. The position of the scanning point relative to the laser scanner 100 is calculated from this measured distance value and the direction of the laser scanning light. Here, if the exterior orientation parameters (position and orientation) of the laser scanner 100 in the absolute coordinate system are known, the position of the scanning point in the absolute coordinate system can be determined. Then, a laser scanning point cloud can be obtained by determining the position of each scanning point.

[0030] The laser scan point cloud output from the laser scanning device 100 can be in the form of outputting distance and direction data for each point (scan point). It is also possible to calculate the position of each point in a specific coordinate system within the laser scanning device 100 and output the three-dimensional coordinate position of each point as point cloud data. Note that the laser scanner point cloud data also includes information on the brightness (intensity of reflected light) of the scan point.

[0031] An optical system 116 of a camera 110 (see FIG. 3) is arranged in front of the horizontal rotation unit 113. This camera 110 can capture an image of the laser scan target. The exterior orientation parameters (position and attitude) of the camera 110 in the laser scanning device 100 are known, and the image captured by the camera 110 can be associated with the laser scan point cloud. For example, a point cloud image can be obtained in which the laser scan point cloud is superimposed on the image captured by the camera 110.

[0032] The density of the laser scan is set and adjusted by adjusting the horizontal and vertical rotation speeds and the interval between laser scan light emissions. Note that the farther away the object is, the wider the interval between the laser scan light (the interval between the center positions of the laser scan points) and the larger the beam cross-sectional area of ​​the laser scan light.

[0033] The optical axis of the optical unit 115 is the optical axis of the laser scanning light. This optical axis is understood to be the direction of the center of the beam of the laser scanning light. The extension of this optical axis is the laser scanning point, i.e., the point of the reflection center of the laser scanning light.

[0034] 3 is a block diagram of the laser scanning device 100. The laser scanning device 100 includes a light emitting unit 101, a light receiving unit 102, a distance measuring unit 103, a direction obtaining unit 104, a scan control unit 105, a drive control unit 106, a scan condition setting unit 107, a communication unit 108, a touch panel display 109, and a camera 110.

[0035] The light-emitting unit 101 has a light-emitting element that emits laser scanning light, an optical system related to light emission, and peripheral circuits. The light-receiving unit 102 has a light-receiving element that receives laser scanning light, an optical system related to light reception, and peripheral circuits.

[0036] Although it depends on the type of light receiving element, in this example, the light receiving element outputs an output signal proportional to the amount of light. Therefore, the intensity of the reflected light is used to evaluate the amount of light. Since the pulse width of the laser scanning light is fixed, the intensity of the reflected light is proportional to the amount of light.

[0037] The distance measuring unit 103 calculates the distance from the laser scanning device 100 to the reflection point of the laser scanning light. In this example, a reference optical path is provided inside the laser scanning device 100. The laser scanning light output from the light emitting unit is split into two beams, one of which is irradiated onto the target from the optical unit 115 as laser scanning light, and the other is guided to the reference optical path as reference light.

[0038] The laser scanning light reflected from the object and taken in by the optical unit 105 and the reference light propagating through the above-mentioned reference optical path are combined and input to the light receiving unit 201. The laser scanning light and the reference light have different propagation distances, and the reference light is first detected by the light receiving element, and then the laser scanning light is detected by the light receiving element.

[0039] Looking at the output waveform of the light receiving element, the detected waveform of the reference light is output first, followed by the detected waveform of the laser scanning light after a time lag. The distance to the reflection point of the laser scanning light is calculated from the phase difference (time difference) between these two waveforms. Note that it is also possible to calculate the distance from the flight time of the laser scanning light.

[0040] The direction acquisition unit 104 acquires the direction of the optical axis of the laser scanning light. By measuring the horizontal angle of the horizontal rotation unit 113 and the vertical rotation angle of the vertical rotation unit 115, the direction of the optical axis of the laser scanning light as seen from the laser scanning device 100, i.e., the direction of the scan point, can be determined.

[0041] The data for each scan point, including distance and direction, is collected and becomes the laser scanner point cloud data.

[0042] The scan control unit 105 controls the horizontal rotation of the horizontal rotation unit 113 during laser scanning, controls the vertical rotation of the vertical rotation unit 115, and controls the timing of emission of laser scanning light from the light emitting unit 101.

[0043] The drive control unit 106 controls the drive of the motor for horizontally rotating the horizontal rotation unit 113 and the drive of the motor for vertically rotating the vertical rotation unit 115. The scan condition setting unit 107 sets various conditions related to laser scanning. The communication device 108 communicates with external devices. In this example, the communication device 108 communicates with the survey data processing device 200. The communication is performed using, for example, a wireless LAN standard. Wired, mobile phone line, or optical communication can also be used.

[0044] The touch panel display 109 functions as a UI (user interface) for the laser scanning device 100. Various operations and settings of the laser scanning device 100 are performed using the touch panel display 109. In addition, various information related to the operation of the laser scanning device 100 is displayed on the touch panel display 109.

[0045] The camera 110 is a digital camera that can capture still images and moving images.

[0046] (Survey data processing device) 4 is a block diagram of the surveying data processing device 200. The surveying data processing device 200 includes a laser scan point cloud acquisition unit 201, a high-brightness reflection point cloud acquisition unit 202, a partial point cloud acquisition unit 203, a laser scan light interval and beam cross-sectional shape acquisition unit 204, a partial point cloud reflection estimation area acquisition unit 205, a partial point cloud identification unit 206, a detailed scan condition setting unit 207, a memory unit 208, and a communication unit 209.

[0047] The storage unit 208 and communication device 209 utilize the functions of the PC being used. The other functional units are realized by the CPU of the PC executing application software for realizing each functional unit. It is also possible to realize some or all of the functional units using dedicated hardware or a microcomputer. The application software that realizes the survey data processing device 200 is stored in an appropriate storage medium or storage area and is downloaded to the PC being used for use.

[0048] For example, it is possible to use an internet line to connect the laser scanning device 100 to a processing server, and to have some or all of the functions of the survey data processing device 200 executed on this processing server.

[0049] The laser scan point cloud acquisition unit 201 executes the process of step S101 in Fig. 5. The high brightness reflection point cloud acquisition unit 202 executes the process of step S102 in Fig. 5. The partial point cloud acquisition unit 203 executes the process of step S103 in Fig. 5. The laser scan light interval and beam cross-sectional shape acquisition unit 204 acquires the distribution of laser scan light and the shape of the beam cross-section at the position of the partial point cloud based on the distance measurement value of the partial point cloud. The laser scan light interval and beam cross-sectional shape acquisition unit 204 executes the process of step S105 in Fig. 5.

[0050] The partial point cloud reflectance estimation area acquisition unit 205 executes the process of step S106 in Fig. 5. The partial point cloud identification unit 206 executes the process of step S107 in Fig. 5. The detailed scan condition setting unit 207 executes the process of step S108 in Fig. 5. The memory unit 208 stores data and programs necessary for the operation of the survey data processing device 200, and data obtained by the operation of the survey data processing device 200. The communication device 209 communicates with the laser scanning device 100 and other devices.

[0051] (Example of processing) First, the laser scanning device 100 and the reflecting prisms 300 and 301, which are reflectors for surveying, are installed at the site where laser scanning will be performed. Here, the position and orientation of the laser scanning device 100 are unknown, and the reflecting prisms 300 and 301 are installed at known positions in the absolute coordinate system.

[0052] Here, we will explain the procedure up to setting the conditions for detailed scanning of the reflecting prisms 300 and 301. The processing after detailed scanning is the same as the processing that has been performed up to now, so the explanation will be omitted.

[0053] After the laser scanning device 100 and the reflecting prisms 300 and 301 are installed, a first laser scan of the surroundings is performed by the laser scanning device 100. Here, a laser scan of the surroundings 360° (2π space) is performed. Laser scanning of a narrower range is also possible.

[0054] The first laser scan serves both as a search for the reflecting prisms 300 and 301 and as a full-circle scan for normal measurement. This full-circle scan for normal measurement can be used to search for the reflecting prisms 300 and 301, but the scan density is set to be too coarse for precise positioning.

[0055] Increasing the scan density of the first laser scan increases the accuracy of capturing the reflecting prisms 300 and 301, but it also lengthens the scan time and increases power consumption. The former is a disadvantage in terms of improving work efficiency. The latter is undesirable when considering battery operation outdoors. Therefore, it is preferable to perform the first laser scan at a scan density that allows the reflecting prisms 300 and 301 to be captured without missing any.

[0056] Furthermore, in the first laser scan, since we want to obtain distance data from the light reflected from the reflecting prisms 300 and 301, we must ensure that the light receiving section of the laser scanning device 100 is not saturated with the light reflected from the reflecting prisms 300 and 301, resulting in a state where distance information cannot be obtained.

[0057] If the reflection from the reflecting prism is too strong and distance information cannot be obtained, the output of the scanning light is adjusted, and the output of the scanning light and / or the intensity of the detection light are adjusted using a neutral density filter so that distance information can be obtained. Note that the distance information from the reflecting prisms 300 and 301 at this stage does not require high accuracy.

[0058] After obtaining laser scan data by the laser scanning device 100, the process of Fig. 5 is started. The program that executes the process of Fig. 5 is stored in an appropriate storage medium and executed by a PC that constitutes the survey data processing device 200. The program can also be stored in a server and downloaded to a PC via the Internet. It is also possible to execute the process of Fig. 5 on a server.

[0059] When the process starts, first, a first laser scan point cloud is obtained by a first laser scan using the laser scanning device 100 (step S101). Next, a high-brightness reflection point cloud is obtained from the first laser scan point cloud obtained in step S101 (step S102).

[0060] In the process of step S102, a point cloud with a reflection intensity equal to or greater than a threshold is extracted from the laser scan point cloud obtained in step S101. A preset value is used as the threshold. The reason for extracting points with a reflection intensity equal to or greater than the threshold is to obtain a laser scan point cloud resulting from reflected light from reflecting prisms 300 and 301, which have high reflectivity, i.e., a laser scan point cloud of reflecting prisms 300 and 301.

[0061] The light reflected from the reflecting prisms 300 and 301 is reflected from a specular surface, and the intensity of the reflected light is relatively strong compared to the intensity of light reflected from reflective surfaces other than specular surfaces. By utilizing this, point cloud data based on the reflected light from the reflecting prisms 300 and 301 is extracted by extracting point cloud data of reflected light having an intensity equal to or greater than a threshold value.

[0062] Furthermore, in the processing of step S102, the reflection intensity is corrected according to distance. That is, due to the spread of the scanning light beam, the intensity of the reflected light decreases as the distance increases. Furthermore, the laser scanning light attenuates as the distance increases due to scattering and absorption by dust and moisture in the air. In anticipation of this decrease, the threshold value for acquiring a high-brightness reflection point cloud is reduced for long distances. That is, the threshold value used in step S102 is variably set so that it is large at short distances and small at long distances.

[0063] This process is performed as follows. First, let Th0 be the reference threshold. Let x be the distance from the laser scanning device 100 to the scan point. Then, let f(x) be a decreasing function that decreases as x increases. The threshold Th to be used is expressed as Th=f(x)Th0. f(x) can be obtained by examining in advance the relationship between distance and the intensity (amount of light) of reflected light.

[0064] According to the above formula, the farther the point, the smaller the threshold value Th. In this case, if the distance x is large, even points with weak reflected light can be extracted as high-brightness reflection points. On the other hand, if the distance x is small, points with a relatively strong reflection will not be extracted as high-brightness reflection points.

[0065] Here, instead of varying the threshold value according to distance, it is also possible to vary the evaluation value of the intensity of reflected light according to distance. In this case, the reflection intensity (amount of light) at the detected point is defined as I, and the intensity of reflected light is evaluated using the above function f(x), or I / f(x). In this way, the detected intensity of reflected light from a close position is estimated to be low, and the detected intensity of reflection from a distant position is estimated to be high. The effect obtained is the same as when the threshold value is varied as described above.

[0066] In either case, the greater the distance from the viewpoint of the laser scan, the lower the points of brightness that are captured as high-brightness reflection points. This reduces false detection of reflections from sources other than reflecting prisms at close range, and the failure to capture reflected light from reflecting prisms at long range.

[0067] The number of high-brightness reflection point groups acquired in step S102 is at least two, because the amount of reflected light from the reflecting prisms 300 and 301 is at least two. Normally, there is a high possibility that multiple reflections of scanning light will be obtained from one reflecting prism, and there is also the possibility of reflections from sources other than the reflecting prism, so the number of high-brightness reflection point groups will be two or more.

[0068] Next, a partial point cloud, which is a partial point cloud corresponding to an object where reflection occurs, is obtained from the high-brightness reflection point cloud obtained in step S102 (step S103). High-brightness reflection points are reflection points on an object with high reflectivity, such as a reflecting prism. Therefore, the reflection points can be classified by reflector. The partial point cloud classified by this reflector is the partial point cloud.

[0069] There are several methods for obtaining partial point clouds. The first method is to separate the partial point clouds based on the distribution of the point clouds as seen from the viewpoint of the laser scan (the optical origin of the laser scanning device 100). This method makes use of the fact that the partial point clouds are distributed in clusters as seen from the viewpoint. However, since depth information (distance information) is not used, differences in the depth direction cannot be used for separation.

[0070] The second method for obtaining a partial point cloud is to also use distance information of the points. The laser scan point cloud contains data on the direction and distance of the points as seen from the laser scanning device 100. Therefore, by examining the three-dimensional distribution of the high-brightness reflection point cloud, the high-brightness point cloud that exists in a cluster in three dimensions can be recognized as a partial point cloud based on reflection from a specific object.

[0071] For example, the laser scanning device 100 estimates the separation distance, which is the distance between adjacent points in the point cloud, from the point resolution of the distance to the measured point, and eliminates points that deviate significantly from that separation distance as outliers.

[0072] The point cloud obtained by scanning a target is considered to be on a plane (target plane) at approximately the same distance from the laser scanning device 100, so the actual separation distance between each point of the point cloud on the target plane does not significantly deviate from the separation distance estimated from the point resolution at the distance to the point measured by the laser scanning device 100. Therefore, the above processing makes it possible to distinguish between the partial point cloud and the rest.

[0073] Points with a large deviation in distance can be determined to be points that are closer or further away from the target surface in the depth direction.Then, the distance between candidates is determined starting from an arbitrary point.By doing this, a partial point cloud corresponding to each target can be obtained.

[0074] The distance to a point measured by the laser scanning device 100 can be a representative point distance (the distance between the laser scanning device 100 and the point) that uses the point distance to a representative point selected under specified conditions from among the points in the point cloud measured by the laser scanning device 100, or a point cloud average distance that is the average of the distances to each point in the point cloud.

[0075] The separation distance between adjacent points in a point cloud is defined as follows: When a point cloud obtained by laser scanning is viewed from the laser scanning device 100, it appears as if the points (scanned points) are arranged in a grid pattern. Adjacent points in this grid pattern are considered to be adjacent points. The three-dimensional distance between these adjacent points is the separation distance between the adjacent points.

[0076] A specific example will be described below. For example, suppose there are two adjacent points A and B. Here, the estimated separation distance between points A and B estimated from the distance (measured distance) of point A is set to D0. Then, the calculated separation distance, which is the actual separation distance between points A and B obtained from the laser scan data, is set to D1.

[0077] In this case, if D0 ≒ D1, points A and B are on the same plane directly facing the laser scanning device when viewed from the laser scanning device (the distances from the laser scanning device are approximately the same), and it is determined that they are a partial point cloud. On the other hand, if D0 ≠ D1, points A and B are not on the same plane directly facing the laser scanning device when viewed from the laser scanning device (the viewpoint position of the laser scanning point cloud) (they are separated in the depth direction), and it is determined that they are not a partial point cloud. This method is used to find the points that make up the partial point cloud.

[0078] In this way, high-brightness reflection point clouds that exist in three-dimensional space with varying shading are classified for each object, and partial point clouds are obtained. For example, the high-brightness reflection point clouds are classified into multiple partial point clouds, such as a first partial point cloud centered on a first three-dimensional position, a second partial point cloud centered on a second three-dimensional position, etc. The center of a partial point cloud is calculated as the average position of the points that make up the partial point cloud.

[0079] In this example, the first laser scan is performed on an area including the reflecting prisms 300 and 301, so at least two groups of partial point clouds are obtained.

[0080] After obtaining the partial point clouds in step S103, distance information for each partial point cloud is acquired (step S104). Here, the average value of the distance from the position (optical origin) of the laser scanning device 100 to each point constituting the partial point cloud is acquired as the distance information for each partial point cloud.

[0081] Next, the interval D of the scanning light and the cross-sectional shape of the scanning light beam (shape and dimensions of the beam cross section) for each partial point cloud are obtained (step S105). The relationship between the distance L from the laser scanning device 100 and the interval D of the scanning light, and the relationship between this distance L and the cross-sectional shape of the scanning light are known and have been acquired in advance. Therefore, if the distance L to the center position of the partial point cloud is known, the interval D of the scanning light and the cross-sectional shape and dimensions of the scanning light beam at the position of the partial point cloud can be obtained. The processing of step S105 acquires the distribution of laser scan points and the shape of the beam cross section at the position of the partial point cloud.

[0082] Figure 7(A) shows an example of the cross-sectional shape of a laser scanning light beam as viewed from the direction of the optical axis. Figure 7(A) shows a case where the cross-sectional shape of the laser scanning light beam is a horizontally elongated ellipse. The cross-sectional shape of a laser scanning light beam can be a circle, a vertically elongated ellipse, an ellipse with a long axis in an oblique direction, a polygon with rounded corners, etc. The cross-sectional shape of the laser scanning light beam is determined by the structure and specifications of the light-emitting element of the laser scanning light, the light-emitting unit, and the optical system of the laser scanner device.

[0083] The beam diameter (beam width) is defined as the dimension of the region where the intensity is more than half of the peak. Therefore, the cross-sectional shape of the beam is the shape of the region where the intensity is more than half of the peak when viewed from the direction of the optical axis. Figure 7(B) shows an example of the intensity distribution corresponding to the beam in Figure 7(A).

[0084] Next, a reflection estimation region of the partial point group is acquired based on the interval between adjacent scanning beams, the beam cross-sectional shape and its dimensions, and the shapes and dimensions of the reflecting prisms 300 and 301 (step S106).

[0085] The reflection estimation region of a partial point group is a region where reflection is likely to have occurred somewhere. Therefore, the size of the reflection estimation region of the partial point group corresponds to the actual size of the reflector.

[0086] The reflection estimation region of a partial point group is defined, for example, as a region surrounded by a closed line that encloses the outer edges of the beam cross-sections related to the points constituting the partial point group (in this case, inscribed). In this example, a rectangular region that fits into the region occupied by the beam cross-sections related to the points constituting the partial point group is obtained as the reflection estimation region of the partial point group.

[0087] When the area of the reflection estimation region of the partial point group (the area seen from the viewpoint) is S1 and the area of the portion filled by the cross-sections of the beams related to the points constituting the partial point group (the area occupied by the beam cross-sections) is S0, a relationship where S0 < S1 < 1.2S0 is preferably satisfied. This is because the reflection estimation region of the partial point group is a region for estimating the region occupied by the beam cross-sections, and it is not preferable to have a deviation in the difference in their areas.

[0088] FIG. 6 shows the shape of the beam cross-section of the laser scan light in the partial point group as viewed from the direction of the optical axis. The black dot in the center indicates the optical axis of the laser scan light.

[0089] FIG. 6(A) shows a case where the cross-section of the laser scan light constituting the partial point group is a horizontally long ellipse and the partial point group is constituted by 10 points of 2×5. In this case, the reflection estimation region of the partial point group is obtained as a square region that fits into the collection of 2×5 elliptical beam cross-sections.

[0090] FIG. 6(B) shows the reflection estimation region of the partial point group in the case where the cross-section of the laser scan light is circular and the partial point group is constituted by 9 points of 3×3. In this case, a square region that encloses the 3×3 circular beam cross-section inside becomes the reflection estimation region of the partial point group. In FIG. 6, the interval between the points is the interval between the optical axes of adjacent laser scan lights.

[0091] If there is only one point in the horizontal or vertical direction, the shape of the beam cross section at that position is used to determine the range of the reflectance estimation area of ​​the partial point cloud in the corresponding direction. The range of the reflectance estimation area of ​​the partial point cloud does not have to be a rectangle, but can also be a trapezoid, a polygon with five or more sides, or a shape surrounded by curves. As shown in Figure 6, the reflectance estimation area of ​​the partial point cloud depends on the spacing between points and the shape of the beam cross section.

[0092] Next, the partial point groups corresponding to the reflecting prisms 300 and 301 are identified (step S107). The partial point groups may include point groups resulting from reflections from other than the reflecting prisms 300 and 301. In step S107, the partial point groups resulting from reflections from other than the reflecting prisms 300 and 301 are excluded, and the partial point groups resulting from reflections from the reflecting prisms 300 and 301 are selected.

[0093] In step S107, the size of the reflection estimation region of the partial point group obtained in step S106 is compared with the sizes of the reflecting prisms 300 and 301. Here, the sizes of the reflecting prisms 300 and 301 are the sizes when the reflecting surface is viewed from the front, and are checked in advance and stored in the storage unit 208. Note that if the sizes of the reflecting prisms 300 and 301 are different, a comparison is made for each reflecting prism.

[0094] Here, the horizontal dimension of the reflection estimation region of the partial point group is Hn and the vertical dimension is Vn, and the horizontal dimension of the reflecting prisms 300, 301 is H0 and the vertical dimension is V0. In this case, a partial point group having an Hn whose difference from H0 is less than a threshold and a Vn whose difference from V0 is less than a threshold is selected as the partial point group corresponding to the reflecting prism. Here, an appropriate value for the threshold is set by conducting experiments in advance.

[0095] For example, if the shape of the reflectance estimation region of the partial point cloud viewed from the front is rectangular, the length of its horizontal side is Hn and the length of its vertical side is Vn. Alternatively, if the shape of the reflectance estimation region of the partial point cloud viewed from the front is circular, the horizontal diameter is Hn and the vertical diameter is Vn. Alternatively, if the shape of the reflectance estimation region of the partial point cloud viewed from the front is a horizontally elongated ellipse, the horizontal diameter (major axis) is Hn and the vertical diameter (minor axis) is Vn.

[0096] If the outer edge of the reflectance estimation region of the partial point group is uneven, a rectangle, circle, or ellipse that fits it is selected, and the above-mentioned Vn and Hn are obtained.

[0097] The following method can also be used as the process in step S107, that is, the process of comparing the size of the reflection estimated region of the partial point group obtained in step S106 with the size of the reflecting prisms 300 and 301.

[0098] In this method, the beam spread and point pitch at that distance are calculated from the distance information of the partial point cloud, and the theoretical number of points (how many points) returned by the target prism is estimated from these and the prism size.

[0099] In other words, assuming that the reflecting prism is at the distance of the partial point group of interest, predict the number of reflection points (X0 points, Y0 points) on this reflecting prism. Here, X0 is the maximum number of points in the horizontal direction, and Y0 is the maximum number of points in the vertical direction. If the reflecting prism is circular, then X0 = Y0. Also, if the reflecting prism is rectangular, X0 is the number of points in the horizontal direction, and Y0 is the number of points in the vertical direction.

[0100] For example, suppose the reflecting prism is circular with a diameter of 10 cm, the cross section of the scanning light beam is circular, the interval between the scanning lights at the distance of the target partial point cloud is 5 cm, and the beam diameter (diameter) is 15 cm. In this case, the maximum number of scanning lights that can produce effective reflection is estimated to be 5 x 5, and the number of reflection points is estimated to be (X0 point, Y0 point) = (5 points x 5 points).

[0101] These points (X0 point, Y0 point) are compared with the points of the partial point cloud (X1 point, Y1 point). Here, X1 is the maximum number of points in the horizontal direction, and Y1 is the maximum number of points in the vertical direction. For example, if the shape of the partial point cloud when viewed from the front is a rectangle and the number of points is (5 points x 5 points), then X1 = 5 points and Y1 = 5 points.

[0102] Here, if (point X0, point Y0) = (point X1, point Y1), the partial point group is determined to be a point group based on reflection from a reflecting prism, that is, the partial point group is determined to be a partial point group corresponding to a reflecting prism. Taking error into consideration, a difference of about 1 to 2 points is allowed, and if (point X0, point Y0) ≒ (point X1, point Y1), the partial point group is determined to be a point group based on reflection from a reflecting prism.

[0103] If (X0 point, Y0 point)≠(X1 point, Y1 point), it is determined that the partial point group is not a point group based on reflection from a reflecting prism, that is, the partial point group does not correspond to a reflecting prism. This method can be seen as a technique for comparing sizes using the number of points.

[0104] In addition, if the number of identified partial point groups is greater than the number of reflecting prisms, in this case, if there are three or more identified partial point groups, the partial point groups caused by reflection from the reflecting prisms 300, 301 are identified by image judgment based on the image captured by the camera 110 (see Figure 3) provided in the laser scanning device 100.

[0105] After step S107, the process proceeds to step S108. In step S108, the scan conditions for a detailed laser scan (second laser scan), which is a second laser scan targeting the partial point cloud identified as a reflective prism in step S107, are set.

[0106] Here, the conditions are set so that laser scanning is performed at a density of 5 mm intervals vertically and horizontally at the positions of the reflecting prisms 300 and 301. The center of the scan range, i.e., the position where the reflecting prism is estimated to be, is calculated as the estimated center position, which is the position of the center of gravity (weighted average position) weighted by the intensity of reflected light for each point that makes up the partial point cloud.

[0107] For example, suppose the target partial point cloud consists of four points (2x2). In this case, the positions of the four points as seen from the laser scanning device 100 are (X1, Y1), (X2, Y2), (X3, Y3), and (X4, Y4), and the intensities of the reflected light at each point are I1, I2, I3, and I4. In this case, the estimated center position (X0, Y0) can be calculated using the following formula for calculating the weighted average position: X0=(I1X1+I2X2+I3X3+I4X4) / (I1+I2+I3+I4) Y0=(I1Y1+I2Y2+I3Y3+I4Y4) / (I1+I2+I3+I4)

[0108] After determining the estimated center position, a laser scan range is set with a density of 5 mm vertically and horizontally centered on that position. The scan range is the rectangular range of the target partial point cloud described in relation to Figure 6.

[0109] The laser scan interval is not limited to 5 mm, but narrowing this interval increases the positioning accuracy of the reflecting prism, but on the other hand, it becomes necessary to acquire more laser scan point clouds, which increases the processing time and power consumption.

[0110] The positioning of the reflecting prisms 300 and 301 using detailed scanning is the same as the conventional method. That is, the position of the center of gravity of the position data of the laser scan point clouds of the reflecting prisms 300 and 301 obtained is determined, and this is set as the position of the reflecting prisms 300 and 301. In this way, the positions of the reflecting prisms 300 and 301 relative to the laser scanning device 100 are determined.

[0111] Once the positions of the reflecting prisms 300, 301 relative to the laser scanning device 100 have been determined, the exterior orientation parameters of the laser scanning device 100 are determined using the resection method. Here, the positions of the reflecting prisms 300, 301 in the absolute coordinate system are known. Therefore, the exterior orientation parameters of the laser scanning device 100 in the absolute coordinate system can be determined using the resection method described above.

[0112] By determining the exterior orientation parameters of the laser scanning device 100 in the absolute coordinate system, the laser scanning point cloud obtained in the first laser scan can be handled in the absolute coordinate system. In this way, a laser scanning point cloud around the laser scanning device 100 that can be handled in the absolute coordinate system is obtained.

[0113] (superiority) The density of the laser scan varies depending on the distance, and the size of the cross section of the laser scanning light beam also varies depending on the distance. By taking this into consideration when setting the detailed scan conditions, it is possible to reduce unnecessary laser scans and set detailed scans with higher accuracy.

[0114] In step S102, the threshold value serving as the extraction standard for high-brightness reflection points is varied depending on the distance, thereby preventing unnecessary reflection points from close range from being detected and necessary reflection points from long range from being missed.

[0115] In step S107, partial point groups corresponding to reflecting prisms are identified taking into consideration the intervals between points at the positions of the partial point groups and the cross-sectional shape of the beam, thereby making it possible to suppress adverse effects of reflections other than those from reflecting prisms.

[0116] Furthermore, in step S107, when the density of points is sparse, particularly at a distance, the size of the partial point cloud can be estimated based on the cross-sectional shape of the laser scanning light beam rather than the spacing between points, thereby enabling efficient detailed scanning settings.

[0117] Furthermore, by comparing the apparent size and shape of the partial point cloud with the size and shape of the reflecting prism and selecting the partial point cloud that corresponds to the reflecting prism, point clouds resulting from reflections other than those of the reflecting prism can be effectively eliminated, allowing the target of the detailed scan to be efficiently narrowed down.

[0118] The technology described above acquires a laser scan point cloud obtained by a first laser scan, acquires a point cloud with a reflection brightness exceeding a threshold from the laser scan point cloud, acquires a partial point cloud that is a partial point cloud corresponding to an object where reflection occurred from the point cloud with a reflection brightness exceeding the threshold, acquires the distribution of the laser scan light and the shape of the beam cross section at the position of the partial point cloud based on the distance measurement values ​​of the partial point cloud, identifies an estimated reflection area of ​​the partial point cloud that is estimated to be an area where reflection from reflecting prisms 300, 301 occurred based on the distribution of the laser scan light and the shape of the beam cross section, and sets conditions for a second laser scan for reflecting prisms 300, 301 based on the identified partial point cloud. This technology allows for efficient and accurate detection of the position of a surveying target by laser scanning.

[0119] 2. Second embodiment Below, we will explain an example of predicting the position of the reflection center (position of the reflecting prism) by weighting multiple reflected lights using the beam profile of a laser scanning light. For example, suppose a partial point cloud of four 2x2 points (A, B, C, D) is obtained. In this case, suppose the intensity of the detected reflected light is point A > point B ≒ C ≒ D. In this case, the reflection center is estimated to be located closer to point A.

[0120] An example of quantitatively performing the above estimation will be described below. Here, the horizontal direction is defined as the X direction, and the vertical direction is defined as the Y direction. Figure 8 shows an example of the beam profile of the reflected light of the laser scanning light in the horizontal direction (X direction). The beam profile in Figure 8 is a beam pattern that shows the relationship between the distance from the center of the optical axis and the light intensity. This beam profile is obtained in advance according to the distance to the reflector to be used.

[0121] Here, a predicted range indicating the probability that a reflection center exists for each point is set in accordance with the value on the vertical axis of the beam profile in Figure 8. For example, if the beam profile in the X and Y directions is the same, this predicted range will be a circular predicted circle.

[0122] Here, we will explain the case where the predicted range is a circle (predicted circle). The predicted circle is centered on the position of the point (the position of the optical axis of the laser scanning light). The diameter of the predicted circle is set as follows: First, the distance from the laser scanning device to the point of interest is obtained, and a beam profile corresponding to this distance (see Figure 8) is obtained. Next, the detected value of the reflected light is applied to the vertical axis of the obtained beam profile, and the length corresponding to the width of the range of intensity above the detected value is obtained as the diameter of the predicted circle.

[0123] In this way, when the light intensity of the detected reflected light is high, the diameter of the predicted circle is set small, and conversely, when the light intensity of the reflected light is low, the diameter of the predicted circle is set large. In other words, the predicted range is set to a size that is inversely proportional to the intensity of the reflected light.

[0124] This predicted circle is created for each point that makes up the partial point cloud. Figure 9 shows an example of a partial point cloud consisting of four points A, B, C, and D. In this case, it is assumed that the target reflecting prism is located near point A. It is also assumed that the peripheral parts of the beam cross section of the laser scanning light at points A, B, C, and D overlap without any gaps at the position of the partial point cloud.

[0125] In this case, the laser scanning light whose optical axis is at point A has a reflecting prism near the peak of its beam profile. On the other hand, the laser scanning light associated with points B, C, and D has a reflecting prism at a position on the beam profile where the intensity is lower than that of point A.

[0126] Therefore, the reflected light from point A is relatively intense, while the reflected light from points B, C, and D is relatively weak. Correspondingly, the predicted circle for point A is set small, while the predicted circles for points B, C, and D are set large. The diameters of adjacent predicted circles are set so that they overlap partially to prevent gaps.

[0127] Here, the area where the four predicted circles overlap is the predicted location of the center of the reflecting prism. In this way, if the detected reflected light intensity for four points A, B, C, and D is point A > point B ≒ C ≒ D, it can be quantitatively estimated that the reflection center is located closer to point A.

[0128] If the beam profile differs between the horizontal and vertical directions, the predicted circle may be, for example, an ellipse. Also, the predicted range may be a closed shape other than a circle or an ellipse.

[0129] Note that if the reflecting prism overlaps with the optical axis of the laser scanning light, the predicted range for the corresponding point becomes extremely small. In this case, the method of this embodiment and the method of selecting the point with the strongest reflection intensity produce similar results. Therefore, this embodiment is more effective in distant areas where the scanning density is sparse than in close areas where the scanning density is dense and the optical axis of the laser scanning light is likely to overlap with the reflecting prism.

[0130] A set of predicted ranges (prediction circles in this case) can be considered as an example of a reflection estimation region of a partial point cloud. In this case, the reflection estimation region of a partial point cloud is composed of multiple predicted ranges related to each point, and the position of the reflection center is determined from the overlapping state of the predicted ranges.

[0131] 3. Other Embodiments A method based on shape comparison can also be used in the process of identifying the partial point group corresponding to the reflecting prisms 300, 301 in step S107. For example, the aspect ratio is used as a parameter that characterizes the shape. In this case, the aspect ratio of the reflecting prisms 300, 301 is compared with the aspect ratio of the reflection estimation region of the partial point group obtained in step S103. Then, the partial point group having the aspect ratio of the reflection estimation region that is similar to the aspect ratio of the reflecting prisms 300, 301 is determined to be the partial point group corresponding to the reflecting prisms 300, 301.

[0132] For example, let the horizontal dimension of the reflection estimation region of the partial point group be Hn and the vertical dimension be Vn, and let the horizontal dimension of the reflecting prisms 300 and 301 be H0 and the vertical dimension be V0. In this case, the partial point group with Hn / Vn, a value close to H0 / V0, is selected as the partial point group corresponding to the reflecting prism.

[0133] It is also possible to use the aspect ratio of the figure to be fitted as a parameter characterizing the shape of the reflecting prism or partial point cloud. It is also possible to categorize the shapes of the reflecting prism or partial point cloud into shapes such as square, circle, or ellipse, and select those of the same type. Another example of size comparison is a method based on area comparison. In this case, the area is evaluated by counting the total number of points, for example. Another example of size comparison is a method based on the perimeter of the figure to be fitted. It is also possible to identify a partial point cloud corresponding to a reflecting prism by combining size comparison and shape comparison. [Explanation of symbols]

[0134] 100...laser scanning device, 111...tripod, 112...base part, 113...horizontal rotation part, 114...vertical rotation part, 115...optical part for emitting and receiving laser scanning light, 116...camera optical system, 300...reflecting prism, 301...reflecting prism.

Claims

1. a laser scan point cloud acquisition unit that acquires a laser scan point cloud; a high-brightness reflection point cloud acquisition unit that acquires a point cloud having reflection brightness exceeding a threshold from the laser scan point cloud; a partial point cloud acquisition unit that acquires a partial point cloud, which is a partial point cloud corresponding to an object where reflection occurs, from the point cloud having reflection luminance exceeding the threshold value; a partial point cloud identification unit for identifying the partial point cloud corresponding to a reflector for surveying; a laser scanning light information acquisition unit that acquires a distribution of laser scanning light and a shape of a beam cross section at the position of the partial point cloud based on the distance measurement values ​​of the partial point cloud; a reflection estimation area acquisition unit that acquires a reflection estimation area that is estimated as an area where reflection from the object occurs based on the distribution of the laser scanning light and the shape of the beam cross section; Equipped with In the partial point group identification unit, A surveying data processing device that compares the size and / or shape of the surveying reflector with the size and / or shape of the reflection estimation area of ​​the partial point cloud, and identifies the partial point cloud that corresponds to the surveying reflector.

2. 2. The surveying data processing device according to claim 1, further comprising a laser scan condition setting unit that sets conditions for laser scanning the surveying reflector based on the identified partial point cloud.

3. 2. The surveying data processing device according to claim 1, wherein the reflection estimation area of ​​the partial point cloud is an area surrounded by a closed line that includes the outer edge of the beam cross section of the laser scanning light at the position of the partial point cloud.

4. a laser scan point cloud acquisition unit that acquires a laser scan point cloud; a high-brightness reflection point cloud acquisition unit that acquires a point cloud having reflection brightness exceeding a threshold from the laser scan point cloud; a partial point cloud acquisition unit that acquires a partial point cloud, which is a partial point cloud corresponding to an object where reflection occurs, from the point cloud having reflection luminance exceeding the threshold value; a partial point cloud identification unit for identifying the partial point cloud corresponding to a reflector for surveying; Equipped with a beam profile indicating a relationship between a distance from the center of the optical axis and a light intensity of the reflected light of the laser scanning light from the plurality of points constituting the partial point group is acquired in advance; For each of the laser scanning beams, a predicted range for predicting the position of a reflection center in the partial point cloud is determined based on the detected value of the reflected light and the beam profile; the predicted range has a magnitude inversely proportional to the intensity of the reflected light; A surveying data processing device that predicts the position of the reflection center in the partial point cloud based on the overlap of the predicted ranges of each of the laser scanning lights.

5. A surveying data processing device as described in claim 1 or 4, wherein the greater the distance from the viewpoint position of the laser scan point cloud, the lower the brightness points are acquired as a point cloud with reflected brightness exceeding the threshold.

6. A surveying data processing device as described in claim 1 or 4, wherein the threshold value becomes smaller as the distance from the viewpoint position of the laser scan point cloud increases.

7. In acquiring the partial point cloud, comparing an estimated separation distance between the target point and another adjacent point, which is estimated based on the distance to the target point, with a calculated separation distance between the target point and the other adjacent point, which is calculated based on the distance measurement values ​​between the target point and the other adjacent point; A surveying data processing device as described in claim 1 or 4, wherein, as a result of the comparison, if the target point and the other point are spaced apart in the depth direction when viewed from the viewpoint position of the laser scan point cloud, it is determined that the target point and the other point are not part of the partial point cloud.

8. 5. The surveying data processing apparatus according to claim 1, wherein the position of the center of the reflector is predicted based on the identified partial point cloud.

9. 9. The surveying data processing device according to claim 8, wherein the position of the center of gravity obtained by weighting the plurality of points constituting the partial point cloud by the intensity of the laser scanning light is predicted as the position of the center of the reflector.

10. Acquisition of laser scan point clouds and Acquiring a point cloud having a reflection brightness exceeding a threshold from the laser scan point cloud; Acquiring a partial point cloud, which is a partial point cloud corresponding to an object where reflection occurs, from the point cloud having reflection brightness exceeding the threshold value; Identifying the partial point cloud corresponding to a surveying reflector; Acquiring a distribution of laser scanning light and a shape of a beam cross section at the position of the partial point cloud based on the distance measurement values ​​of the partial point cloud; acquiring a reflection estimation area that is estimated as an area where reflection from the object occurs based on the distribution of the laser scanning light and the shape of the beam cross section; and In identifying the partial point group, A surveying data processing method that compares the size and / or shape of the surveying reflector with the size and / or shape of the reflection estimation area of ​​the partial point cloud, and identifies the partial point cloud that corresponds to the surveying reflector.

11. Acquisition of laser scan point clouds and Acquiring a point cloud having a reflection brightness exceeding a threshold from the laser scan point cloud; Acquiring a partial point cloud, which is a partial point cloud corresponding to an object where reflection occurs, from the point cloud having reflection brightness exceeding the threshold value; Identifying the partial point cloud corresponding to a surveying reflector; and a beam profile indicating a relationship between a distance from the center of the optical axis and a light intensity of the reflected light of the laser scanning light from the plurality of points constituting the partial point group is acquired in advance; For each of the laser scanning beams, a predicted range for predicting the position of a reflection center in the partial point cloud is determined based on the detected value of the reflected light and the beam profile; the predicted range has a magnitude inversely proportional to the intensity of the reflected light; A surveying data processing method in which the position of the reflection center in the partial point cloud is predicted based on the overlap of the predicted ranges of each of the laser scanning lights.

12. A program to be read and executed by a computer, To the computer Acquisition of laser scan point clouds and Acquiring a point cloud having a reflection brightness exceeding a threshold from the laser scan point cloud; Acquiring a partial point cloud, which is a partial point cloud corresponding to an object where reflection occurs, from the point cloud having reflection brightness exceeding the threshold value; Identifying the partial point cloud corresponding to a surveying reflector; Acquiring a distribution of laser scanning light and a shape of a beam cross section at the position of the partial point cloud based on the distance measurement values ​​of the partial point cloud; acquiring a reflection estimation area that is estimated as an area where reflection from the object occurs based on the distribution of the laser scanning light and the shape of the beam cross section; Execute In identifying the partial point group, A surveying data processing program that compares the size and / or shape of the surveying reflector with the size and / or shape of the reflection estimation area of ​​the partial point cloud, and identifies the partial point cloud that corresponds to the surveying reflector.

13. A program to be read and executed by a computer, To the computer Acquisition of laser scan point clouds and Acquiring a point cloud having a reflection brightness exceeding a threshold from the laser scan point cloud; Acquiring a partial point cloud, which is a partial point cloud corresponding to an object where reflection occurs, from the point cloud having reflection brightness exceeding the threshold value; Identifying the partial point cloud corresponding to a surveying reflector; Execute a beam profile indicating a relationship between a distance from the center of the optical axis and a light intensity of the reflected light of the laser scanning light from the plurality of points constituting the partial point group is acquired in advance; For each of the laser scanning beams, a predicted range for predicting the position of a reflection center in the partial point cloud is determined based on the detected value of the reflected light and the beam profile; the predicted range has a magnitude inversely proportional to the intensity of the reflected light; A surveying data processing program that predicts the position of the reflection center in the partial point cloud based on the overlap of the predicted ranges of each of the laser scanning lights.

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