Point cloud processing system, point cloud processing device, point cloud processing method, and program

Abstract

This invention provides a point cloud processing system, a point cloud processing device, a point cloud processing method, and a program that can reduce the effort required for surveying. [Solution] The point cloud processing system 11 comprises a surveying device 12 for measuring the surroundings, and a point cloud processing device 21 for processing point cloud data D1 generated based on the surveying results from the surveying device. The surveying device includes a laser scanner 13 that irradiates a laser into the surroundings and receives the reflected laser, and a positioning mechanism 15 that measures the position of the surveying device. The point cloud processing device performs the following actions: acquiring point cloud data, acquiring adjustment data D2 that indicates the point cloud to which the adjustment point P1 is associated, matching the adjustment data with the point cloud data, and identifying the adjustment point in the point cloud data based on the matching results.

Description

Technical Field

[0004] , , , ,

[0001] The present disclosure relates to a point cloud processing system, a point cloud processing device, a point cloud processing method, and a program.

Background Art

[0002] Patent Document 1 describes a point cloud processing system including a surveying device that measures the surroundings and a point cloud processing device that processes point cloud data generated based on the measurement results of the surveying device. The surveying device includes a laser scanner that irradiates a laser and receives the reflected laser, and a positioning mechanism that measures the position of the surveying device. The point cloud processing device processes point cloud data in which the reflection points of the laser measured by the laser scanner are represented in three-dimensional coordinates based on the position of the surveying device measured by the positioning mechanism.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In such a point cloud processing system, usually, the coordinate accuracy of the point cloud data is managed based on adjustment points separately measured in the field by total station, satellite positioning, etc. The adjustment points are set at locations where it is easy to measure coordinates in the field and locations where it is easy to identify in the point cloud data. By aligning the adjustment points with the point cloud data, the coordinates of the point cloud data are adjusted. For example, among the point clouds included in the point cloud data, when the points corresponding to the adjustment points are identified, the coordinates of the point clouds included in the point cloud data are adjusted. As a result, the coordinate accuracy of the point cloud data is improved. On the other hand, when processing the point cloud data, in order to improve the accuracy of the point cloud data, it is necessary to separately measure the adjustment points every time of surveying, so there is a problem that the labor required for surveying is large. [Means for solving the problem]

[0005] A point cloud processing system according to one aspect of the present disclosure comprises a surveying device for measuring the surroundings of a moving object, and a point cloud processing device for processing point cloud data generated based on the surveying results of the surveying device, wherein the surveying device includes a laser scanner that irradiates a laser into its surroundings and receives the reflected laser, and a positioning mechanism for measuring the position of the surveying device, and the point cloud processing device performs the following: acquiring the point cloud data, acquiring adjustment data indicating a point cloud to which adjustment points are associated, matching the adjustment data with the point cloud data, and identifying the adjustment points in the point cloud data based on the matching results.

[0006] A point cloud processing device according to one aspect of the present disclosure is a point cloud processing device that processes point cloud data generated based on surveying results from a surveying device, the point cloud processing device comprising a memory for storing a program and a processor for executing processing according to the program, the processor performing the following actions: acquiring the point cloud data, acquiring adjustment data indicating point clouds to which adjustment points are associated, matching the adjustment data with the point cloud data, and identifying the adjustment points in the point cloud data based on the matching results.

[0007] A point cloud processing method according to one aspect of the present disclosure is a computer-based point cloud processing method for processing point cloud data generated based on surveying results from a surveying device, wherein the computer includes acquiring the point cloud data, acquiring adjustment data indicating point clouds to which adjustment points are associated, matching the adjustment data with the point cloud data, and identifying the adjustment points in the point cloud data based on the matching results.

[0008] A program according to one aspect of this disclosure is a program that causes a computer to process point cloud data generated based on surveying results from a surveying device, the program causing the computer to perform the following actions: acquire the point cloud data; acquire adjustment data indicating point clouds to which adjustment points are associated; match the adjustment data with the point cloud data; and identify the adjustment points in the point cloud data based on the matching results. [Brief explanation of the drawing]

[0009] [Figure 1] Figure 1 is a schematic diagram showing an example of a point cloud processing system. [Figure 2] Figure 2 shows the road and its surroundings being surveyed by the mobile unit. [Figure 3] Figure 3 shows the reflection point of the laser by the surveying device. [Figure 4] Figure 4 is a block diagram showing an example of a point cloud processing system. [Figure 5] Figure 5 shows the adjustment points. [Figure 6] Figure 6 is a graph showing the point cloud data and the point cloud data for adjustment. [Figure 7] Figure 7 is a flowchart showing an example of a point cloud processing method. [Modes for carrying out the invention]

[0010] The following describes an embodiment of a point cloud processing system, point cloud processing device, point cloud processing method, and program with reference to the figures. <Point Cloud Processing System> As shown in Figure 1, the point cloud processing system 11 is used in conjunction with the mobile object 99. The point cloud processing system 11 is a so-called mobile mapping system. The mobile object 99 is, for example, an automobile. In addition to an automobile, the mobile object 99 may also be a train, ship, aircraft, trolley, etc. The mobile object 99 may also be a person.

[0011] The point cloud processing system 11 includes a surveying device 12. The surveying device 12 is a device used for surveying. The surveying device 12 is mounted on a mobile unit 99. In one example, the surveying device 12 is loaded onto a car. The surveying device 12 may also be worn by a person. For example, the surveying device 12 may be held by a person or carried on a person's back using a carrying frame.

[0012] The surveying device 12 is configured to measure the area around the moving object 99. The surveying device 12 measures the surrounding area by non-contact distance measurement of the surfaces of surrounding objects. More specifically, the surveying device 12 measures the surrounding area by laser scanning. The surveying device 12 measures the surrounding area while moving together with the moving object 99. Therefore, the surveying device 12 can measure a wide area in a relatively short time.

[0013] The surveying device 12 includes a laser scanner 13. The laser scanner 13 is configured to emit a laser around the mobile body 99. The laser scanner 13 is configured to receive the reflected laser. By receiving the reflected laser, the laser scanner 13 is configured to measure the orientation and distance of the object to which the laser was emitted. Specifically, the laser scanner 13 detects the point of reflection of the laser by receiving the laser reflected off the surface of the object. The laser scanner 13 detects the point of reflection of the laser based on the time elapsed between the emission of the laser and its reception. In other words, the laser scanner 13 detects the point of reflection by time of flight. The laser scanner 13 may also detect the point of reflection by phase shift, for example, rather than time of flight. The mounting position of the laser scanner 13 should be such that it is easy to emit a laser around the mobile body 99. In one example, the laser scanner 13 is mounted on the roof of the mobile body 99.

[0014] The surveying device 12 acquires point cloud information by having the laser scanner 13 detect multiple reflection points from the surroundings. The point cloud information is information about a point cloud composed of multiple reflection points. For example, the point cloud information indicates the position of the reflection points in a three-dimensional coordinate system with the surveying device 12 as the origin. The point cloud information may also include information indicating the reflection intensity of the laser at the reflection points.

[0015] As shown in Figure 2, the surveying device 12 may survey the road and its surroundings. The surveying device 12 may, for example, survey the roadway R1 on which the mobile body 99 travels, the sidewalk R2 along the roadway R1, and buildings R3 located along the roadway R1. White lines R4 indicating the outer edge of the roadway, the center line, the stop line, the pedestrian crossing, etc., may be painted on the roadway R1. Braille blocks R5 may be placed on the sidewalk R2.

[0016] As shown in Figure 3, the laser scanner 13 may irradiate the road and its surroundings with a laser. The black circles in Figure 3 are the reflection points of the laser. The laser scanner 13 acquires a point cloud by detecting the laser reflected from the roadway R1, sidewalk R2, building R3, etc.

[0017] As shown in Figure 1, the surveying device 12 may include a camera 14. The camera 14 is configured to photograph the area around the mobile body 99. The camera 14 may be configured to photograph all directions around the mobile body 99, or it may be configured to photograph only in limited directions, such as in front, behind, or to the side of the mobile body 99. The surveying device 12 acquires a color image by having the camera 14 photograph the surroundings. The color image is an image that contains color information. The color image is, for example, an image represented by RGB. The mounting position of the camera 14 should be such that it is easy to photograph the surroundings from the mobile body 99. In one example, the camera 14 is mounted on the roof of the mobile body 99.

[0018] The measuring device 12 includes a positioning mechanism 15. The positioning mechanism 15 is configured to measure the position of the measuring device 12. The positioning mechanism 15 is configured to measure, for example, the position of the laser scanner 13. The positioning mechanism 15 may be configured to measure the position of the camera 14 in addition to the position of the laser scanner 13. The positioning mechanism 15 may be configured to measure the position of the measuring device 12 in a global coordinate system. That is, the positioning mechanism 15 may be configured to measure the geographical position of the measuring device 12. The positioning mechanism 15 may measure, for example, the position of the measuring device 12 in a coordinate system with the center of gravity of the earth as the origin. The positioning mechanism 15 may be configured to measure the position of the measuring device 12 in a local coordinate system. That is, the positioning mechanism 15 may be configured to measure, for the measuring device 12, the position on a map created based on itself. The positioning mechanism 15 may measure the position of the measuring device 12 by, for example, estimating its own position.

[0019] The positioning mechanism 15 may include an antenna 16. The antenna 16 is configured to receive a positioning signal from a satellite. The antenna 16 measures the position of the measuring device 12 by receiving the positioning signal. The antenna 16 is a receiver of GNSS (Global Navigation Satellite System). The positioning mechanism 15 obtains position information when the antenna 16 receives the positioning signal. The position information is information indicating the position of the measuring device 12. The mounting position of the antenna 16 may be any position where it is easy to receive the positioning signal. In one example, the antenna 16 is attached to the roof of the moving body 99.

[0020] The positioning mechanism 15 may include an inertial unit 17. The inertial unit 17 is configured to measure the inertial motion of the surveying device 12. Specifically, the inertial unit 17 measures the inertial motion of the surveying device 12 due to the inertial motion of the moving body 99. The inertial motion includes translational motion and rotational motion. The inertial unit 17 is a so-called IMU (Inertial Measurement Unit). The inertial unit 17 includes a gyro sensor that detects rotational motion, an acceleration sensor that detects translational motion, and the like. The positioning mechanism 15 obtains inertial information when the inertial unit 17 measures the inertial motion of the surveying device 12. The inertial information is information indicating the inertial motion of the surveying device 12. The mounting position of the inertial unit 17 may be a position where it is easy to measure the inertial motion. In one example, the inertial unit 17 is attached to the roof of the moving body 99.

[0021] The positioning mechanism 15 may include an odometry 18. The odometry 18 is configured to measure the movement of the surveying device 12. Specifically, the odometry 18 is configured to measure the movement of the surveying device 12 due to the movement of the moving body 99. The odometry 18 is attached to, for example, the wheel of the moving body 99. The odometry 18 measures the movement of the surveying device 12 based on the rotation angle of the wheel. The positioning mechanism 15 obtains movement information when the odometry 18 measures the movement of the surveying device 12. The movement information is information indicating the movement of the surveying device 12.

[0022] The positioning mechanism 15 measures the position of the surveying device 12 by means of the antenna 16, the inertial unit 17, the odometry 18, etc. The positioning mechanism 15 may measure the position of the surveying device 12 by so-called SLAM (Simultaneous Localization and Mapping), or may measure the position of the surveying device 12 by SLAM and GNSS. The positioning results of the antenna 16, the inertial unit 17, the odometry 18, etc. are synchronized by sensor fusion.

[0023] The surveying device 12 may include a surveying circuit 19. The surveying circuit 19 is connected to a laser scanner 13, a camera 14, a positioning mechanism 15, etc. The surveying circuit 19 may also control the laser scanner 13, the camera 14, the positioning mechanism 15, etc.

[0024] The surveying circuit 19 may include a memory for storing a program and a processor for executing processing according to the program. The memory may include ROM and RAM. The memory may also include storage media such as an HDD or SSD. The processor may consist of a CPU, GPU, MPU, etc. The surveying circuit 19 may also be a hardware circuit configured to execute predetermined processing. The surveying circuit 19 may consist of, for example, an FPGA, CPLD, ASIC, etc.

[0025] The surveying circuit 19 is configured to store the surveying results. The surveying results include various types of information such as point cloud information, positional information, inertial information, movement information, and color images. The surveying circuit 19 accumulates various types of information by saving the surveying results. The surveying circuit 19 stores the various types of information in another device connected to the surveying device 12, for example. The surveying circuit 19 may also store the various types of information itself.

[0026] The surveying circuit 19 may be configured to synchronize various types of information. The surveying circuit 19 may be configured to synchronize point cloud information, position information, inertial information, movement information, and color images, etc. The surveying circuit 19 may synchronize various types of information based on the measurement time. The surveying circuit 19 may store various types of information in a synchronized state. For example, the surveying circuit 19 may store the measurement results of the laser scanner 13 and the measurement results of the positioning mechanism 15 while synchronizing them. For example, the surveying circuit 19 may store the measurement results of the laser scanner 13 and the measurement results of the camera 14 while synchronizing them.

[0027] The surveying circuit 19 may synchronize point cloud information and position information. This allows the reflection points to be represented by their geographical locations. In other words, by synchronizing point cloud information and position information, the reflection points are represented by absolute coordinates.

[0028] The surveying circuit 19 may synchronize positional information and inertial information with the point cloud information. The surveying circuit 19 may synchronize positional information and movement information with the point cloud information. The surveying circuit 19 may synchronize positional information, inertial information, and movement information with the point cloud information. In such cases, the position of the surveying device 12 is indicated from multiple angles by the positional information, inertial information, and movement information, thereby improving the positional accuracy of the surveying device 12. In addition, for example, if the antenna 16 cannot receive the positioning signal accurately, the position of the surveying device 12 can be estimated accurately based on the inertial information, movement information, etc. By improving the positional accuracy of the surveying device 12, the coordinate accuracy of the reflection point is improved.

[0029] The surveying circuit 19 may synchronize point cloud information and color images. This allows the surveying circuit 19 to assign color information to reflection points. In this case, reflection points are represented not only by 3D coordinates but also by color information consisting of, for example, three RGB colors.

[0030] The point cloud processing system 11 includes a point cloud processing unit 21. The point cloud processing unit 21 is configured to process the point cloud acquired by the surveying device 12. The point cloud processing unit 21 may be connected to the surveying device 12. The point cloud processing unit 21 may be connected to the surveying device 12 by wire or by wireless connection, for example. The point cloud processing unit 21 may communicate with the surveying device 12. The point cloud processing unit 21 may be mounted on a mobile unit 99. In one example, the point cloud processing unit 21 is a personal computer brought into the mobile unit 99. The point cloud processing unit 21 does not have to be mounted on the mobile unit 99. The point cloud processing unit 21 may be a personal computer installed in an office. The point cloud processing unit 21 may acquire the surveying results from the surveying device 12 in real time or retrospectively.

[0031] As shown in Figure 4, the point cloud processing unit 21 includes a processing circuit 22. The processing circuit 22 may include a memory for storing a program and a processor for executing processing according to the program. In addition to the processor and memory, the processing circuit 22 may also include hardware circuits such as an FPGA, CPLD, or ASIC. In this way, the point cloud processing unit 21 is implemented as a computer. The processing circuit 22 may also serve as a surveying circuit 19. The processing circuit 22 may, for example, control a surveying device 12.

[0032] The processing circuit 22 may be configured to acquire survey results. The processing circuit 22 may acquire survey results from the surveying device 12, or it may acquire survey results from an external device where survey results are stored. The processing circuit 22 may store various information by acquiring survey results from the surveying device 12. The processing circuit 22 may acquire various information in a synchronized state.

[0033] The processing circuit 22 may be configured to synchronize various types of information. The processing circuit 22 may synchronize various types of information by processing the acquired measurement results. The processing circuit 22 may acquire various types of information while synchronizing it, or it may synchronize the acquired various types of information.

[0034] The processing circuit 22 is configured to acquire point cloud data D1. Point cloud data D1 is data representing a point cloud. More specifically, point cloud data D1 is data representing the point cloud in three-dimensional coordinates. For example, point cloud data D1 represents the coordinates of the point cloud in a geodetic system. In addition to the coordinates of the point cloud, point cloud data D1 may also represent the color of the point cloud or the reflectance of the point cloud.

[0035] Point cloud data D1 is data generated based on survey results. Point cloud data D1 is data generated based on various types of information. Point cloud data D1 is data generated based on synchronized information. Point cloud data D1 is data generated by analyzing survey results. Point cloud data D1 represents the shape and position of an object using reflection points on the object's surface. Point cloud data D1 is used for mapmaking and for maintenance and inspection of roads, buildings, power lines, slopes, etc.

[0036] The processing circuit 22 may be configured to generate point cloud data D1. In one example, the processing circuit 22 is configured to generate point cloud data D1 by analyzing various synchronized pieces of information. In this way, the processing circuit 22 acquires point cloud data D1. The processing circuit 22 may acquire point cloud data D1 from an external source. For example, the processing circuit 22 may acquire point cloud data D1 from an external device that stores point cloud data D1. For example, the processing circuit 22 may acquire point cloud data D1 from the surveying circuit 19. The point cloud data D1 may be generated by an external device analyzing the surveying results, or by the surveying circuit 19 analyzing the surveying results.

[0037] Point cloud data D1 is data in which the point cloud information has been aligned. In the laser scanner 13, the laser is irradiated while moving together with the moving object 99, so reflection points are measured at multiple locations. Therefore, alignment of the point clouds included in the point cloud information is necessary. In other words, point cloud data D1 is data in which point clouds measured at different locations have been registered and represented in a common coordinate system. Point cloud data D1 may be data in which the point cloud has been aligned by ICP (Iterative Closest Point), for example. Point cloud data D1 may be data in which the point cloud has been aligned by CPD (Coherent Point Drift), or point cloud data D1 may be data in which the point cloud has been aligned by other methods.

[0038] The point cloud data D1 may be data that has undergone preprocessing. The point cloud data D1 may be data from which noisy points have been removed. The point cloud data D1 may be data from which points unnecessary for surveying have been removed. The point cloud data D1 may be data from which points representing dynamic objects such as people and vehicles have been removed. Preprocessing may be performed automatically by a computer operating with a predetermined algorithm, or it may be performed by the user specifying the points to be removed.

[0039] The processing circuit 22 is configured to adjust the coordinates of the point cloud data D1. In surveying, it is necessary to improve the coordinate accuracy of the point cloud represented by the point cloud data D1. Therefore, the processing circuit 22 adjusts the coordinates of the point cloud data D1 using adjustment point P1. Specifically, the processing circuit 22 adjusts the coordinates of the point cloud data D1 by identifying adjustment point P1 in the point cloud represented by the point cloud data D1. Adjustment point P1 is a point used to adjust the point cloud data D1. Adjustment point P1 is a point that indicates the reference coordinates when adjusting the point cloud data D1.

[0040] Adjustment point P1 is a point surveyed on-site. In one example, adjustment point P1 is a point surveyed on or around the road. Multiple adjustment points P1 may be surveyed on-site. Adjustment point P1 is a point surveyed in conjunction with the surveying by the surveying device 12. Adjustment point P1 is set at a characteristic location when surveying the road or its surroundings. Adjustment point P1 may be set at a location that is easy to survey on-site, a location that is easy to identify in the point cloud data D1, etc. Adjustment point P1 may be set at, for example, the corner of a white line R4, the corner of a tactile paving block R5, or the corner of a grating. In one example, adjustment point P1 is set at the corner of a tactile paving block R5. Adjustment point P1 may be set at a location where the positional accuracy of the surveying device 12 is likely to decrease. Adjustment point P1 may be set at, for example, a location where the antenna 16 has difficulty receiving positioning signals, or a location where the direction of travel of the mobile body 99 changes.

[0041] The position of adjustment point P1 is measured by a device separate from the surveying device 12. Unlike the positioning mechanism 15, which measures position while moving, the position of adjustment point P1 is measured by a total station, GNSS receiver, or other device installed on the ground. In other words, adjustment point P1 is measured while these devices are stationary. Therefore, the positional accuracy of adjustment point P1 is higher than the positional accuracy of the reflection point measured by the surveying device 12.

[0042] The adjustment point P1 is identified in the point cloud data D1. More specifically, the location corresponding to the adjustment point P1 is identified in the point cloud data D1. As a result, the coordinates indicated by the adjustment point P1 are set at the location identified as the adjustment point P1 in the point cloud data D1. The point cloud data D1 is adjusted based on the location identified as the adjustment point P1. As a result, the positional accuracy of the point cloud data D1 is improved. Multiple adjustment points P1 may be identified in the point cloud data D1. In this case, the positional accuracy of the point cloud data D1 is further improved.

[0043] During maintenance inspections, point cloud data D1 of the same area may be acquired repeatedly. For example, when performing maintenance inspections on roads and their surroundings, point cloud data D1 representing the roads and their surroundings may be acquired at predetermined intervals. Specifically, if roads and their surroundings are maintained and inspected annually, point cloud data D1 will be acquired annually. By comparing previously acquired point cloud data D1 with newly acquired point cloud data D1, changes in the roads and their surroundings can be identified. For example, by comparing point cloud data D1, damage to the road surface, tilting of buildings, sagging of power lines, and collapse of slopes can be identified.

[0044] Even when repeatedly acquiring point cloud data D1, adjustment of point cloud data D1 using adjustment points P1 is required each time. When acquiring new point cloud data D1 for the same area, adjusting it based on previously measured adjustment points P1 may degrade the positional accuracy of point cloud data D1. This is because the locations where adjustment points P1 are set may change over time. For example, the corners of white lines R4, corners of tactile paving blocks R5, and corners of gratings where adjustment points P1 are set may change position due to construction or be worn away. Therefore, it is difficult to identify the corners of white lines R4, corners of tactile paving blocks R5, and corners of gratings in newly acquired point cloud data D1. In other words, it is difficult to identify previously measured adjustment points P1 in newly acquired point cloud data D1. Consequently, it is difficult to reuse adjustment points P1 when adjusting newly acquired point cloud data D1. On the other hand, surveying adjustment points P1 every time point cloud data D1 is acquired is cumbersome.

[0045] As shown in Figure 4, the processing circuit 22 is configured to acquire adjustment data D2. Adjustment data D2 is data indicating the adjustment point P1. Adjustment data D2 indicates the three-dimensional coordinates of the adjustment point P1. For example, adjustment data D2 indicates the coordinates of the adjustment point P1 in a geodetic system. The processing circuit 22 may acquire adjustment data D2 from an external device separate from the point cloud processing device 21, or it may acquire adjustment data D2 from a storage medium it possesses.

[0046] Adjustment data D2 is data that indicates reusable adjustment points P1. More specifically, adjustment data D2 is data that makes it easy to identify adjustment points P1 in point cloud data D1. Therefore, when adjusting newly acquired point cloud data D1 using adjustment data D2, adjustment points P1 can be reused. In other words, the lifespan of adjustment points P1 is extended. As a result, it is not necessary to survey adjustment points P1 every time point cloud data D1 is acquired, thus reducing the effort required for surveying.

[0047] As shown in Figure 5, adjustment data D2 is data representing a point cloud. More specifically, adjustment data D2 is data representing a point cloud to which adjustment points P1 are associated. Adjustment data D2 represents a point cloud composed of multiple reflection points measured by a device other than the laser scanner 13. For example, adjustment data D2 represents a point cloud composed of multiple reflection points measured by a ground-based laser scanner L1. The black circles shown in Figure 5 represent the reflection points of the laser emitted by the ground-based laser scanner L1. The ground-based laser scanner L1 measures the point cloud with itself as the origin. Adjustment data D2 is generated when a computer associates the adjustment points P1 measured by a total station, GNSS receiver, etc., with the point cloud measured by the ground-based laser scanner L1.

[0048] The adjustment point P1 is associated with the point cloud so as to indicate the position of the point cloud indicated by the adjustment data D2. In one example, the adjustment point P1 is associated with the origin of the point cloud indicated by the adjustment data D2. That is, the adjustment point P1 indicates the origin of the coordinate system representing the point cloud indicated by the adjustment data D2. In this case, the adjustment point P1 indicates the installation position of the ground-based laser scanner L1. The adjustment point P1 may also indicate the centroid of the point cloud indicated by the adjustment data D2. The adjustment point P1 may also indicate the position of one of the reflection points in the point cloud indicated by the adjustment data D2.

[0049] The processing circuit 22 is configured to adjust the point cloud data D1 based on the adjustment data D2. Based on the adjustment data D2, the processing circuit 22 identifies the location in the point cloud data D1 that corresponds to the adjustment point P1.

[0050] As shown in Figure 6, the processing circuit 22 is configured to match point cloud data D1 and adjustment data D2. More specifically, the processing circuit 22 matches the point cloud indicated by adjustment data D2 with the point cloud indicated by point cloud data D1. That is, the processing circuit 22 matches point cloud data D1 and adjustment data D2 with each other. The processing circuit 22 may match the point cloud indicated by adjustment data D2 with the point cloud indicated by point cloud data D1 using ICP. The processing circuit 22 may match the point cloud indicated by adjustment data D2 with the point cloud indicated by point cloud data D1 using CPD. The processing circuit 22 may match the point cloud indicated by adjustment data D2 with the point cloud indicated by point cloud data D1 using other methods.

[0051] The processing circuit 22 identifies the location in the point cloud data D1 that corresponds to the adjustment point P1, based on the matching results. For example, the processing circuit 22 identifies the adjustment point P1 in the point cloud data D1 at the location with the highest matching rate with the adjustment data D2. The processing circuit 22 adjusts the point cloud data D1 based on the location where the adjustment point P1 was identified in the point cloud data D1. This improves the positional accuracy of the point cloud data D1.

[0052] Since adjustment data D2 represents adjustment point P1 as a point cloud, it is easy to identify adjustment point P1 in point cloud data D1. This is because even if the location where adjustment point P1 was set changes over time, for example, if the corner of the tactile paving block R5 is worn down or its position changes due to construction, the matching accuracy between point cloud data D1 and adjustment data D2 does not easily decrease. Because point cloud data D1 and adjustment data D2 are matched using point clouds, the matching accuracy does not easily decrease even if the location where adjustment point P1 was set changes. In other words, even if the location where adjustment point P1 was set changes, it is easy to identify adjustment point P1 in newly acquired point cloud data D1. Therefore, even if previously measured adjustment point P1 is reused, the positional accuracy of point cloud data D1 is easily improved. In addition, since the processing circuit 22 can automatically identify adjustment point P1 in point cloud data D1 using methods such as ICP and CPD, the effort required to adjust point cloud data D1 is reduced. If adjustment data D2 represents adjustment point P1 as a single point, then in identifying adjustment point P1 in point cloud data D1, the user must manually specify the location corresponding to adjustment point P1. Therefore, if the location where adjustment point P1 is set changes, it becomes difficult to identify adjustment point P1 in newly acquired point cloud data D1. Furthermore, because the user must manually specify adjustment point P1 in point cloud data D1, adjusting point cloud data D1 is time-consuming.

[0053] <Point Cloud Processing Method> Next, we will explain the computer-based point cloud processing method. The point cloud processing method is a method by which a computer processes point cloud data D1. The computer operates as a point cloud processing unit 21 that processes point cloud data D1 by executing processing according to a program. The point cloud processing unit 21 performs point cloud processing by executing processing according to a program. For example, the point cloud processing unit 21 performs point cloud processing when a user starts point cloud processing software.

[0054] As shown in Figure 7, in step S11, the point cloud processing unit 21 acquires point cloud data D1. At this time, the point cloud processing unit 21 may acquire point cloud data D1 from the surveying device 12, from another device, or from its own storage medium. The point cloud processing unit 21 expands the point cloud data D1 into the memory of the processing circuit 22 so that it can process the point cloud data D1.

[0055] In step S12, the point cloud processing unit 21 acquires adjustment data D2. At this time, the point cloud processing unit 21 may acquire adjustment data D2 from another device or from its own storage medium. The point cloud processing unit 21 expands the adjustment data D2 into the memory of the processing circuit 22 so that it can process the adjustment data D2.

[0056] In step S13, the point cloud processing device 21 matches the adjustment data D2 with the point cloud data D1. At this time, the point cloud processing device 21 aligns the point cloud indicated by the adjustment data D2 with the point cloud indicated by the point cloud data D1.

[0057] In step S14, the point cloud processing device 21 identifies the adjustment point P1 in the point cloud data D1 based on the matching result. At this time, the point cloud processing device 21 sets the coordinates of the adjustment point P1 at the location where the adjustment data D2 matches the point cloud data D1. In this way, the point cloud processing device 21 identifies the adjustment point P1 in the point cloud data D1. The point cloud processing device 21 may also adjust the point cloud data D1 based on the identified adjustment point P1.

[0058] <Effects and Effects of the Examples> Next, the operation and effects of the above-described embodiment will be explained. (1) The point cloud processing unit 21 acquires point cloud data D1. The point cloud processing unit 21 acquires adjustment data D2 which shows the point cloud to which the adjustment point P1 is associated. The point cloud processing unit 21 matches the adjustment data D2 with the point cloud data D1. Based on the matching result, the point cloud processing unit 21 identifies the adjustment point P1 in the point cloud data D1. With the above configuration, since the adjustment point P1 is associated with the point cloud in the adjustment data D2, it is easy to identify the adjustment point P1 that was measured in the past in the point cloud data D1 by matching the point cloud data D1 and the adjustment data D2. More specifically, since the point cloud processing unit 21 matches the point cloud shown by the adjustment data D2 with the point cloud shown by the point cloud data D1, the matching accuracy of the point cloud data D1 and the adjustment data D2 does not easily decrease even if the location where the adjustment point P1 is set changes. The position where the adjustment data D2 is matched in the point cloud data D1 corresponds to the adjustment point P1. Thus, since the adjustment points P1 are associated with the point cloud in the adjustment data D2, it is easy to identify previously measured adjustment points P1 in the point cloud data D1. In other words, previously measured adjustment points P1 can be reused. Therefore, the effort required for surveying is reduced.

[0059] (2) Adjustment data D2 is data in which the adjustment point P1 is associated with the origin. With the above configuration, the adjustment point P1 can be easily identified in point cloud data D1 based on the matching result of point cloud data D1 and adjustment data D2.

[0060] <Note> The embodiments understood based on the above examples are listed below. [1] The point cloud processing system comprises a surveying device for measuring the surroundings and a point cloud processing device for processing point cloud data generated based on the surveying results from the surveying device. The surveying device includes a laser scanner that irradiates a laser into the surroundings and receives the reflected laser, and a positioning mechanism that measures the position of the surveying device. The point cloud processing device performs the following actions: acquiring the point cloud data, acquiring adjustment data that indicates the point cloud to which the adjustment points are associated, matching the adjustment data with the point cloud data, and identifying the adjustment points in the point cloud data based on the matching results. In the point cloud processing system, when surveying, adjustment points are set at locations where the coordinates are easy to measure on site and where they are easy to identify in the point cloud data. For example, in the point cloud processing system, when surveying a road, adjustment points are set at the corners of white lines, corners of tactile paving blocks, corners of gratings, etc. These locations may change over time. For example, the corners of white lines may wear down, or the position of tactile paving blocks may change due to construction. Therefore, it is difficult to identify previously measured adjustment points in point cloud data. In other words, it is difficult to reuse previously measured adjustment points. With the above configuration, since the adjustment points are associated with the point cloud in the adjustment data, it is easy to identify previously measured adjustment points in the point cloud data by matching the point cloud data and the adjustment data. Specifically, since the point cloud processing unit matches the point cloud indicated by the adjustment data with the point cloud indicated by the point cloud data, the matching accuracy of the point cloud data and the adjustment data does not decrease even if the location where the adjustment points are set changes. In the point cloud data, the location where the adjustment data matches corresponds to the adjustment point. In this way, since the adjustment points are associated with the point cloud in the adjustment data, it is easy to identify previously measured adjustment points in the point cloud data. In other words, previously measured adjustment points can be reused. Therefore, the effort required for surveying is reduced.

[0061] [2] In the point cloud processing system described above, the adjustment data may be data in which the adjustment points are associated with the origin. With the above configuration, it is easy to identify the adjustment points in the point cloud data based on the matching result of the point cloud data and the adjustment data.

[0062] [3] The point cloud processing device is a point cloud processing device that processes point cloud data generated based on surveying results from a surveying device, the point cloud processing device comprises a memory for storing a program and a processor for executing processing according to the program, the processor performing the following: acquiring the point cloud data, acquiring adjustment data indicating the point cloud to which the adjustment points are associated, matching the adjustment data with the point cloud data, and identifying the adjustment points in the point cloud data based on the matching results. With the above configuration, the same effects as the point cloud processing system described above can be obtained.

[0063] [4] The point cloud processing method is a computer-based point cloud processing method that processes point cloud data generated based on surveying results from a surveying device, wherein the computer includes acquiring the point cloud data, acquiring adjustment data indicating point clouds to which adjustment points are associated, matching the adjustment data with the point cloud data, and identifying the adjustment points in the point cloud data based on the matching results. The above method provides the same effects as the point cloud processing system described above.

[0064] [5] The program is a program that causes a computer to process point cloud data generated based on the surveying results of a surveying device, the program causing the computer to perform the following actions: acquire the point cloud data, acquire adjustment data indicating the point cloud to which the adjustment points are associated, match the adjustment data with the point cloud data, and identify the adjustment points in the point cloud data based on the matching results. The above program provides the same effect as the point cloud processing system described above. [Explanation of symbols]

[0065] 11...Point cloud processing system, 12...Surveying device, 13...Laser scanner, 15...Positioning mechanism, 21...Point cloud processing device, 99...Mobile device, D1...Point cloud data, D2...Adjustment data, P1...Adjustment point.

Claims

1. A surveying device for measuring the surroundings, The system includes a point cloud processing device that processes point cloud data generated based on the surveying results from the aforementioned surveying device, The aforementioned surveying device is A laser scanner that emits a laser into the surroundings and receives the reflected laser, It has a positioning mechanism for measuring the position of the aforementioned surveying device, The point cloud processing device is The acquisition of the aforementioned point cloud data, This involves obtaining adjustment data that shows the point cloud to which the adjustment points are associated, Matching the adjustment data with the point cloud data, A point cloud processing system that performs the following: identifying the adjustment points in the point cloud data based on the matching results.

2. The point cloud processing system according to claim 1, wherein the adjustment data is data to which the adjustment points are associated with the origin.

3. A point cloud processing device that processes point cloud data generated based on surveying results from a surveying device, The point cloud processing device is Memory for storing programs, A processor that performs processing according to the aforementioned program, The aforementioned processor, The acquisition of the aforementioned point cloud data, This involves obtaining adjustment data that shows the point cloud to which the adjustment points are associated, Matching the adjustment data with the point cloud data, A point cloud processing device that performs the following: identifying the adjustment points in the point cloud data based on the matching results.

4. A computer-based point cloud processing method for processing point cloud data generated based on surveying results from a surveying device, The aforementioned computer, The acquisition of the aforementioned point cloud data, Obtain adjustment data that shows the point cloud to which the adjustment points are associated, Matching the adjustment data with the point cloud data, A point cloud processing method comprising identifying the adjustment points in the point cloud data based on the matching results.

5. A program that causes a computer to process point cloud data generated based on surveying results from a surveying device, The aforementioned program, The acquisition of the aforementioned point cloud data, Obtain adjustment data that shows the point cloud to which the adjustment points are associated, Matching the adjustment data with the point cloud data, A program that causes the computer to identify the adjustment points in the point cloud data based on the matching results.

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