WO2022269758A1

WO2022269758A1 - Separation measurement device, separation measurement method, and separation measurement program

Info

Publication number: WO2022269758A1
Application number: PCT/JP2021/023619
Authority: WO
Inventors: 英彰宮西; 幸弘五藤; 充康柳田; 奈月本田
Original assignee: 日本電信電話株式会社
Priority date: 2021-06-22
Filing date: 2021-06-22
Publication date: 2022-12-29
Also published as: JPWO2022269758A1

Abstract

A separation measurement device according to one embodiment of the present invention measures separation between a subject and surrounding objects present in the surroundings of the subject on the basis of a point cloud including position information and height information, the point cloud being acquired by measuring the subject and the surrounding objects, said separation measurement device comprising a refining unit, a superposition unit, a point cloud elimination unit, and a separation measurement unit. The refining unit receives input of a point cloud and a subject model generated from the point cloud, and refines a separation measurement range to a designated range. The superposition unit superposes the model and the point cloud of the refined measurement range. The point cloud elimination unit deems a point cloud present inside the model according to the superposition to be outside of the measurement subject, and deletes said point cloud. The separation measurement unit calculates the distance between the model and the point cloud after deletion, thereby measuring the separation between the subject and the surrounding objects.

Description

Remote measurement device, remote measurement method and remote measurement program

Embodiments of the present invention relate to a distance measurement device, a distance measurement method, and a distance measurement program.

As a method of installing cables such as power transmission cables and communication cables outdoors, aerial overhead wires are widely used, which are installed between poles such as utility poles and traffic lights.

Patent Documents 1 to 3 disclose devices that detect the state of such cables and poles using a Mobile Mapping System (MMS). MMS is equipped with a three-dimensional laser scanner (3D laser survey instrument), camera, GPS (Global Positioning System) receiver, IMU (Inertial Measurement Unit), and odometer (Odometer) on the inspection vehicle. Then, while the inspection vehicle is traveling on the road, comprehensive 3D surveying of the surrounding buildings, roads, bridges, and other outdoor structures is performed, and the 3D (X, It is a system that acquires the three-dimensional shape of an outdoor structure by collecting Y, Z) coordinates. This system uses a laser beam applied to the surface of an outdoor structure to convert the absolute 3D coordinates of the irradiated point into 3D point cloud data within the measurement error range of the MMS and the measurement error of the GPS receiver. to get as Patent Documents 1 to 3 detect the state of an object based on three-dimensional point cloud data of an object such as a cable or pole measured by MMS.

Japanese Patent Application Laid-Open No. 2019-148464 Japanese Patent Application Laid-Open No. 2017-156179 Japanese Patent Application Laid-Open No. 2019-191002

With aerial overhead lines, there is a risk that trees may come into contact with poles and cables due to fallen trees due to storms and snowfall, causing problems such as tilting or overturning of poles and cutting of cables. Therefore, it is desirable to take necessary measures such as trimming branches or replanting other trees in advance for trees that may affect such poles, cables, and the like. Therefore, there is a need for distance measurement between an object such as a pole or cable and surrounding objects such as trees existing around the object.

The present invention seeks to provide a technology that enables distance measurement between an object and peripheral objects existing around the object.

In order to solve the above problems, a distance measuring device according to an aspect of the present invention provides a point cloud having position information and height information obtained by measuring an object and surrounding objects existing around the object. A distance measuring device for measuring the distance between an object and a surrounding object based on the above, comprising a narrowing unit, a superimposing unit, a point group removing unit, and a distance measuring unit. The narrowing-down unit inputs a point cloud and a model of an object generated from the point cloud, and narrows down the distance measurement range to a specified range. The superimposing unit superimposes the point cloud of the narrowed measurement range and the model. The point cloud removing unit removes the point cloud that exists inside the model due to the superimposition as not to be measured. The distance measurement unit measures the distance between the target object and surrounding objects by calculating the distance between the deleted point cloud and the model.

According to one aspect of the present invention, it is possible to provide a technology that enables distance measurement between an object and peripheral objects existing around the object.

FIG. 1 is a block diagram showing an example of the functional configuration of the distance measuring device according to the first embodiment of the invention. FIG. 2 is a diagram showing an example of the hardware configuration of a computer when the distance measuring device according to the first embodiment is configured by a computer. FIG. 3 is a flow chart showing an example of the operation of the distance measuring device. FIG. 4 is a diagram showing an example of point cloud information. FIG. 5 is a diagram showing an example of model information. FIG. 6 is a schematic diagram showing a measurement range narrowed down by an example of a technique for narrowing down the measurement range. FIG. 7 is a schematic diagram showing another example of a technique for narrowing down the measurement range. FIG. 8 is a schematic diagram showing the measurement range narrowed down by the method of FIG. FIG. 9 is a schematic diagram showing superimposition of a model and a point cloud. 10A and 10B are schematic diagrams showing a method of removing a point group not subject to distance measurement from the entire point group. FIG. 11 is a schematic diagram showing distance measurement within the measurement range. FIG. 12 is a schematic diagram showing an example of measured distances. FIG. 13 is a schematic diagram showing an example of the measured separation distance. FIG. 14 is a diagram showing an example of display of distance measurement results. FIG. 15 is a schematic diagram showing distance measurement within the measurement range in the distance measuring device according to the second embodiment of the present invention. FIG. 16 is a schematic diagram showing an example of the measured separation distance. FIG. 17 is a schematic diagram showing distance measurement within the measurement range in the distance measuring device according to the third embodiment of the present invention. FIG. 18 is a graph showing an example of the relationship between the radius of a certain search circle and the total number of points within the search circle. FIG. 19 is a graph showing an example of the relationship between the radius of the search circle and the total points within the search circle, different from FIG. FIG. 20 is a schematic diagram showing an example of the measured distance.

Hereinafter, embodiments according to the present invention will be described with reference to the drawings.

[First Embodiment]
(composition)
FIG. 1 is a schematic diagram showing an example of the functional configuration of a distance measuring device 1 according to the first embodiment of the invention.
The distance measurement device 1 is connected to a laser point cloud data storage unit 2, a management data storage unit 3, and a display unit 4. FIG. Here, "connection" is not limited to a direct wired or wireless connection, but may be an indirect connection via a network such as a LAN (Local Area Network) or the Internet. In addition, the laser point cloud data storage unit 2 and the management data storage unit 3 can store magnetic disks (floppy (registered trademark) disks, hard disks, etc.), optical disks (CD-ROM, DVD, MO, etc.), semiconductor memories (ROM, RAM, If it is configured in the form of a recording medium such as a flash memory, etc., the connection may be via a reading device compatible with the recording medium.

The laser point cloud data storage unit 2 stores laser point cloud data (hereinafter abbreviated as point cloud). A point cloud is a three-dimensional image of a large number of points on the surface of objects such as poles and cables and surrounding objects such as trees existing around the objects, collected while an inspection vehicle equipped with an MMS runs on the road. (X, Y, Z) coordinate data. That is, a point cloud is a set of points with geographical position information (X, Y) and height information (Z).

In addition, the management data storage unit 3 stores management data for each object such as poles and cables. The management data includes, for example, object shape information, geographical position information (X, Y), and height information (Z). The management data may also include shape information and geographical location information (X, Y) about surrounding objects. The management data of these objects and surrounding objects is information at the time of installation of the objects, and information of the surrounding objects is information at an arbitrary point in time. No.

The display unit 4 is, for example, a display device using liquid crystal or organic EL (Electro Luminescence).

The distance measurement device 1 includes a point cloud acquisition unit 11, a modeled data acquisition unit 12, a measurement range narrowing unit 13, a data superimposition unit 14, a non-measurement target point group removal unit 15, a distance measurement unit 16, a measurement result storage unit 17, and A measurement result output unit 18 is provided.

The point cloud acquisition unit 11 acquires the point cloud to be processed from the laser point cloud data storage unit 2. Here, the point cloud acquisition unit 11 can acquire a point cloud at an arbitrary geographical position specified by the operator of the distance measuring device 1, for example.

The modeling data acquisition unit 12 acquires three-dimensional modeling data (hereinafter abbreviated as a model) of the object from the point cloud acquired by the point cloud acquisition unit 11 . A model has position information and height information. Since this model acquisition method is a known technology, the description is omitted here.

The measurement range narrowing unit 13 stores the position and height information (X, Y, Z) of each of the point cloud acquired by the point cloud acquisition unit 11 and the model acquired by the modeling data acquisition unit 12, and the management data storage unit 3 The distance measurement range is specified based on the position information of the object stored by .

The data superimposition unit 14 superimposes the point cloud acquired by the point cloud acquisition unit 11 and the model acquired by the modeling data acquisition unit 12 for the measurement range specified by the measurement range narrowing unit 13 based on their position information. Let

The non-measurement target point cloud removal unit 15 removes point groups that are not subject to distance measurement from the entire point cloud with respect to the model and the point cloud superimposed by the data superimposition unit 14 .

The distance measurement unit 16 measures the distance between each model and the point cloud remaining without being removed by the non-measurement target point cloud removal unit 15 .

The measurement result storage unit 17 stores the distance measurement result of the model and the point cloud measured by the distance measurement unit 16 as the distance between the object and the surrounding objects existing therearound.

The measurement result output unit 18 displays on the display unit 4 the distance between the object and the surrounding objects, which is the distance measurement result stored in the measurement result storage unit 17 . Instead of displaying the distance measurement result on the display unit 4, the measurement result output unit 18 prints it on a printing unit such as a printer, records it on a recording medium, or transmits it to an external device via a network. You can also try to

FIG. 2 is a diagram showing an example of the hardware configuration of a computer when the distance measuring device 1 according to the first embodiment is configured by a computer. The distance measurement device 1 has a hardware processor 101 such as a CPU (Central Processing Unit). In the distance measuring device 1 , a program memory 102 , a data memory 103 , a communication interface 104 and an input/output interface 105 are connected to the processor 101 via a bus 106 . By using a multi-core and multi-threaded CPU, it is possible to execute a plurality of information processes at the same time. Also, the processor 101 may include multiple CPUs.

The program memory 102 is a non-temporary tangible computer-readable storage medium, for example, a non-volatile memory such as a HDD (Hard Disk Drive) or SSD (Solid State Drive) that can be written and read at any time, and a non-volatile memory such as a ROM. It is used in combination with a static memory. The program memory 102 stores control programs necessary for the processor 101 to execute various control processes according to this embodiment. For example, a point cloud acquisition unit 11, a modeled data acquisition unit 12, a measurement range narrowing unit 13, a data superimposition unit 14, a non-measurement target point group removal unit 15, a distance measurement unit 16, a measurement result storage unit 17, and a measurement result output unit. 18 can be realized by causing the processor 101 to read and execute the distance measurement program stored in the program memory 102 . Some or all of these processing functions may be implemented in various other forms, including integrated circuits such as Application Specific Integrated Circuits (ASICs) or field-programmable gate arrays (FPGAs). May be.

The data memory 103 is used as a tangible computer-readable storage medium, for example, by combining the above nonvolatile memory and a volatile memory such as RAM (Random Access Memory). This data memory 103 is used to store various data acquired and created in the process of performing various processes. For example, in the data memory 103, storage areas such as a point cloud storage unit 1031, a model storage unit 1032, a measurement range storage unit 1033, a measurement result storage unit 1035, a superposition result storage unit 1034, a temporary storage unit 1036, and the like are secured. .

The point cloud storage unit 1031 is a storage area for storing point cloud information acquired by the processor 101 executing control processing related to the point cloud acquisition unit 11 .

The model storage unit 1032 is a storage area for storing models acquired by the processor 101 executing control processing related to the modeling data acquisition unit 12 .

The measurement range storage unit 1033 is a storage area for storing the measurement range specified by the processor 101 executing control processing related to the measurement range narrowing unit 13 .

The superimposition result storage unit 1034 is a storage area for storing the superimposition results when the processor 101 executes control processing related to the data superimposition unit 14 .

The measurement result storage unit 1035 is a storage area in which the processor 101 executes control processing related to the measurement result storage unit 17 and stores measurement results.

The temporary storage unit 1036 is a storage for temporarily storing various data generated in the course of the processor 101 executing control processing related to the data superimposition unit 14, the non-measurement target point group removal unit 15, and the distance measurement unit 16. area.

The communication interface 104 is a communication module for transmitting and receiving information to and from other devices via a network (not shown). Other devices may include, for example, a storage device, a server device, a personal computer, etc. that function as the laser point cloud data storage unit 2 and/or the management data storage unit 3 .

The input/output interface 105 is an input/output module for connecting the laser point cloud data storage unit 2, the management data storage unit 3, and the display unit 4 by wire or wirelessly. The input/output interface 105 can also be connected to an input unit such as a keyboard (not shown).

(motion)
Next, the operation of the distance measuring device 1 according to the first embodiment will be described.
FIG. 3 is a flow chart showing an example of the operation of the distance measuring device 1 according to the first embodiment. 2, the program memory 102 stores a distance measurement program necessary for executing the control processing shown in this flow chart, and the processor 101 By executing the program, the point group acquisition unit 11, the modeled data acquisition unit 12, the measurement range narrowing unit 13, the data superimposition unit 14, and the non-measurement point group removal of the distance measurement device 1 shown in FIG. It can operate as the unit 15 , the distance measurement unit 16 , the measurement result storage unit 17 and the measurement result output unit 18 .

The processor 101 of the distance measuring device 1 receives, for example, an input unit (not shown) via the input/output interface 105, which is specified by the operator of the distance measuring device 1 to perform distance measurement between an object and a peripheral object. The operation shown in this flow chart is started by inputting a geographical position.

First, the processor 101 functions as the point cloud acquisition unit 11 and acquires the point cloud to be processed corresponding to the specified geographical position from the laser point cloud data storage unit 2 through the input/output interface 105 (or the communication interface 104). is acquired (step S11). FIG. 4 is a diagram showing an example of acquired point cloud information DI. In this example, the processor 101 acquires point cloud information DI including a plurality of point clouds. The processor 101 stores the acquired point cloud information DI in the point cloud storage unit 1031 of the data memory 103 .

Next, the processor 101 functions as the modeling data acquisition unit 12 and acquires the model of the object from the point cloud included in the point cloud information DI stored in the point cloud storage unit 1031 (step S12). FIG. 5 is a diagram showing an example of acquired model information MI. In this example, the processor 101 acquires model information MI including two pole models MO1 and MO2 and a cable model MO3 from the point cloud information DI shown in FIG. The processor 101 stores the acquired model information MI in the model storage unit 1032 of the data memory 103 .

Next, the processor 101 functions as the measurement range narrowing unit 13, and performs each point group included in the point cloud information DI stored in the point cloud storage unit 1031 and each point group included in the model information MI stored in the model storage unit 1032. Based on the position and height information of each model and the position information of the object stored in the management data storage unit 3, the distance measurement range is specified (step S13). There are two methods for specifying the measurement range: (1) specification based on the position and height information of the point cloud and model, and (2) specification centered on the model. Or a combination of the two can be used.

FIG. 6 is a schematic diagram showing the measurement range narrowed down by the identification method based on the position and height information of the point cloud and model in (1) as the method of narrowing down the measurement range. The geographical position where the point cloud and the model are likely to exist in the entire measurement area ME is defined by the object position information (X, Y) stored in the management data storage unit 3 . Therefore, the processor 101 acquires the position information of the object from the management data storage unit 3 through the input/output interface 105 (or the communication interface 104) and stores it in the temporary storage unit 1036 of the data memory 103. FIG. In addition, the processor 101 stores position information (X, Y) of each point cloud included in the point cloud information DI stored in the point cloud storage unit 1031 and each model included in the model information MI stored in the model storage unit 1032. A measurement area is designated from all measurement areas ME based on. Among the specified measurement areas, measurement areas that do not correspond to the position information of the object stored in the temporary storage unit 1036 are excluded from the processing targets. In the example of FIG. 6, the measurement areas E1 and E2 are specified because there is position information for the objects corresponding to the models MO11 and MO13. Area not specified. Then, the processor 101 stores each point cloud included in the point cloud information DI stored in the point cloud storage unit 1031 and each point cloud included in the model information MI stored in the model storage unit 1032 for each of the designated measurement areas E1 and E2. The height range to be measured is specified based on each height information (Z: z1, z2) of the model. Thereby, the processor 101 identifies the measurement ranges MR1 and MR2 for the model MO11 and the model MO13. The processor 101 stores the identified measurement ranges MR1 and MR2 in the measurement range storage section 1033 of the data memory 103 .

FIG. 7 is a schematic diagram showing an identification method centered on the model (2) as a method of narrowing down the measurement range. The management data about the object stored in the management data storage unit 3 can include direction designation information that designates the direction of the measurement range in addition to the position information and height information. For example, when an inspection vehicle equipped with an MMS collects point clouds while traveling on the road, this direction designation information can be registered from the conditions of surrounding objects visually confirmed by the collector. Alternatively, a camera image may also be captured at the time of collecting the point cloud, and any operator may register the direction designation information while checking the image. Also, instead of registering it as management data, the operator of the distance measuring device 1 can input an arbitrary geographical position where distance measurement between the target object and the surrounding object is to be performed by an input unit (not shown), and this direction. Designated information may also be entered.

The processor 101 moves the left side (−X direction), the right side (+X direction), the front side (+Y direction), and the back side (−Y direction) of the model MO with respect to the measurement target range OR centered on the model MO to be processed. , the upper side (+Z direction), the lower side (-Z direction), etc., the measurement range MR for each model is specified based on the direction specifying information indicating the range to be measured. The processor 101 causes the specified measurement range MR to be stored in the measurement range storage unit 1033 .

FIG. 8 is a schematic diagram showing the measurement range narrowed down by the combination of the method of FIG. 6 and the method of FIG. The processor 101 further narrows down the measurement range narrowed down by the identification method (1) based on the position and height information of the point cloud and the model by the identification method (2) centered on the model, thereby obtaining a measurement range MR1. , MR2 can be identified. Model MO12 is not subject to method (2) as a model outside the measurement area. Processor 101 causes measurement range storage section 1033 to store the specified measurement ranges MR1 and MR2.

Next, the processor 101 functions as the data superimposition unit 14, and for the measurement range stored in the measurement range storage unit 1033, each point cloud and model storage unit included in the point cloud information DI stored in the point cloud storage unit 1031 Each model included in the model information MI stored in 1032 is superimposed based on each position information (X, Y, Z) (step S14).

Fig. 9 is a schematic diagram showing the superimposition of this model and the point cloud. The processor 101 causes the superimposition result storage unit 1034 of the data memory 103 to store the superimposition information SI, which is the superimposition result. Since this superimposing process utilizes existing technology, its details are omitted.

Next, the processor 101 functions as the non-measurement target point cloud removal unit 15, and the superimposed model and point cloud in the superimposition information SI stored in the superimposition result storage unit 1034 are excluded from the distance measurement target from the entire point cloud. The point cloud is removed (step S15).

FIG. 10 is a schematic diagram showing a method of removing point clouds not subject to distance measurement from the entire point cloud. As indicated by the dashed line on the left side of FIG. 10, the processor 101 does not measure the point DT that exists in the model MO in the superimposed model and point cloud because it is recognized as a model. , all are deleted as shown on the right side of the figure. Specifically, the processor 101 deletes the points DT existing in the model MO in the superimposition information SI stored in the superimposition result storage unit 1034 .

Next, the processor 101 functions as the distance measuring unit 16, selects one model as a processing target from the models in the superimposition information SI stored in the superimposition result storage unit 1034, and selects the model as a processing target, and selects the model as a remaining model without being removed. The distance between the model and the point group is measured by measuring the distance to each point of the point group (step S16). The processor 101 measures the shortest distance to the point cloud for the model as the distance.

FIG. 11 is a schematic diagram showing distance measurement within the measurement range MR. Here, an example is shown in which the measurement range MR is specified over the entire circumference of the model MO. The processor 101 searches for points DT in the point cloud for each starting point SP on the model MO. FIG. 11 shows a state in which a point DTm whose position information and height information are (Xm, Ym, Zm) is searched from the starting point SPn whose position information and height information is (Xn, Yn, Zn). there is

FIG. 12 is a schematic diagram showing an example of measured distances. When a point DT outside the inside of the model MO is found within the measurement range MR, the processor 101 calculates the distance from the model MO to the point DT. The example of FIG. 12 indicates that points DT1, DT2, and DT3 have been searched and respective distances d1, d2, and d3 have been calculated. In this way, the processor 101 determines whether a point group exists concentrically over 360 degrees with each coordinate of the model MO as the starting point SP, and calculates the distance between the model MO and the point DT. Processor 101 stores the position information of the searched point and the calculated distance in temporary storage section 1036 .

FIG. 13 is a schematic diagram showing an example of the measured separation distance. Among the distances between the model MO and the point DT stored in the temporary storage unit 1036, the processor 101 sets the shortest distance as the separation distance between the model MO and the point group. For example, if the distance d1 to the point DT1 is the shortest, the processor 101 takes this distance d1 as the separation distance.

Then, the processor 101 functions as the measurement result storage unit 17, and converts the separation distance between the model MO and the point group measured in step S16 into the measurement result of the separation distance between the object and objects existing in the vicinity of the object. The data is stored in the measurement result storage unit 1035 of the data memory 103 (step S17).

After that, the processor 101 determines whether all the models in the superimposition information SI stored in the superimposition result storage unit 1034 have been processed (step S18). If it is determined that all models have not been processed yet (NO in step S18), the processor 101 proceeds to the process of step S16. Then, the processes of steps S16 and S17 are repeated.

In this way, when it is determined that all models have been processed (YES in step S18), the processor 101 functions as the measurement result output unit 18, and the distance measurement results stored in the measurement result storage unit 1035 are stored in the measurement result storage unit 1035. The separation distance from the object is displayed on the display unit 4 via the input/output interface 105 (step S19). Then, the processing shown in the flowchart is terminated.

FIG. 14 is a diagram showing an example of display of distance measurement results. The processor 101 displays the models MO1, MO2 and MO3 representing the object and the point group DO representing the surrounding objects, and displays the respective shortest distances SD1, SD2 and SD3. The processor 101 can display the distances SD1, SD2, and SD3 as specific numerical values.

Instead of displaying the distance measurement result on the display unit 4, the distance measurement device 1 prints the distance measurement result on a printing unit such as a printer, records it on a recording medium, or transmits it to an external device via a network. You can make it work.

In the first embodiment as described above, based on a point group having position information and height information acquired by measuring an object such as a pole and surrounding objects such as trees existing around the object, A distance measuring device 1 for measuring the distance between a target object and a surrounding object, comprising a measurement range narrowing unit 13, a data superimposing unit 14, a point group removing unit 15 outside the measurement target, a distance measuring unit 16, Prepare. The measurement range narrowing unit 13 inputs a point group and a model of an object generated from the point group, and narrows down the distance measurement range to a designated range. The data superimposition unit 14 superimposes the point cloud of the narrowed measurement range and the model. The non-measuring target point cloud removing unit 15 deletes the point cloud existing inside the model due to superimposition as non-measuring target. The distance measurement unit 16 measures the distance between the object and the surrounding objects by calculating the distance between the deleted point cloud and the model. Therefore, it is possible to provide a technique that enables distance measurement between an object and peripheral objects existing around the object.

In addition, the non-measurement target point group removal unit 15 removes the point groups not subject to distance measurement from the entire point cloud, thereby reducing the number of points in the point cloud to be processed by the distance measurement unit 16. In addition, the speed of the distance measurement process can be increased, and the amount of information stored in the data memory 103 during the process can be reduced.

Also, in the first embodiment, the measurement range narrowing unit 13 narrows down the measurement range to a range designated based on the position information and height information of the point cloud and model. Therefore, the speed of the distance measurement process can be increased, the amount of information stored in the data memory 103 during the process can be reduced, the capacity of the data memory 103 can be suppressed, and the cost can be reduced.

Alternatively, in the first embodiment, the measurement range narrowing unit 13 narrows down the measurement range to a specified range centered on the model. Therefore, the speed of the distance measurement process can be increased, the amount of information stored in the data memory 103 during the process can be reduced, the capacity of the data memory 103 can be suppressed, and the cost can be reduced.

Furthermore, the measurement range narrowing unit 13 narrows down the measurement range to a range specified based on the position information and height information of the point cloud and the model, and narrows down the measurement range to a range specified centering on the model. By combining , it is possible to further increase the speed of the distance measurement process, reduce the amount of information, and lower the price.

In the first embodiment, the distance measurement unit 16 calculates the distance between each point in the point cloud after deletion and the model, and the minimum value of the calculated distance is taken as the distance between the object and the surrounding objects. do. Therefore, a highly accurate distance measurement result can be obtained.

For example, in visual distance measurement, the accuracy of distance measurement is poor due to variations among people, and it takes a long time to measure. On the other hand, in the case of distance measurement based on a photographed image, it is not possible to accurately measure the distance in the depth direction using the image. Furthermore, manual calculation of the distance from the point cloud also causes variations among people, resulting in poor distance measurement accuracy and long measurement time. On the other hand, the distance measuring device 1 according to the first embodiment can greatly reduce the inspection time, can increase the speed and reduce the data size, can perform distance measurement without on-site inspection, and improves the measurement accuracy. It is possible to achieve an excellent effect.

[Second embodiment]
The configuration of the distance measuring device 1 according to the second embodiment of the invention is the same as that of the first embodiment. This embodiment differs from the first embodiment in the method of measuring the distance between the model and the point cloud.

FIG. 15 is a schematic diagram showing distance measurement within the measurement range MR in the distance measurement device 1 according to the second embodiment. Points in the vicinity of the model are points plotted due to measurement errors when collecting the point cloud by MMS, and the measurement errors exist randomly and at low density. Therefore, in this embodiment, the processor 101 of the distance measuring device 1 divides the entire space of the measurement range MR when measuring the distance between the model and each point of the point group in step S16, and The point density is taken into consideration when performing the measurement. Specifically, the processor 101 divides the entire space of the measurement range MR into partial measurement ranges PR, which are three-dimensional areas such as fixed cubes. The processor 101 then counts the number of points DT existing within each of the divided partial measurement ranges PR.

FIG. 16 is a schematic diagram showing an example of the measured separation distance. The processor 101 deletes the point cloud inside a partial measuring range PR in which the number of points DT in the partial measuring range PR is smaller than that in other partial measuring ranges PR, that is, the point density is low. Thus, the distance to the final remaining partial measurement range PR with a large number of points DT, that is, with a high point density is calculated as the separation distance d.

As described above, in the second embodiment, the distance measurement unit 16 divides the entire space of the measurement range into partial measurement ranges that are fixed three-dimensional areas, and the portion of the partial measurement range with the highest point density Let the distance between the measurement range and the model be the distance between the object and the surrounding objects. Therefore, a highly accurate distance measurement result can be obtained.

[Third embodiment]
The configuration of the distance measuring device 1 according to the third embodiment of the invention is the same as that of the first embodiment. This embodiment differs from the first and second embodiments in the method of measuring the distance between the model and the point cloud.

In this embodiment, the processor 101 of the distance measuring device 1 uses the point cloud distribution for finding surrounding objects when measuring the distance between the model and each point of the point cloud in step S16. It is for measuring.

FIG. 17 is a schematic diagram showing distance measurement within the measurement range in the distance measuring device 1 according to the third embodiment. As described in the second embodiment, points in the vicinity of the model are points plotted by measurement errors, and the measurement errors exist randomly and at low density. Therefore, in the present embodiment, the processor 101 of the distance measuring device 1, when measuring the distance between the model and each point of the point group in step S16, measures each starting point on the model MO within the measurement range. Set the search circle to . The example in FIG. 17 shows search circles SS1 and SS2 for two starting points. That is, the processor 101 counts the number of points DT in the point cloud around the model MO with respect to a certain direction.

FIG. 18 is a graph showing an example of the relationship between the radius of the search circle SS1 and the total points within the search circle SS1, and FIG. 19 is an example of the relationship between the radius of the search circle SS2 and the total points within the search circle SS2. is a graph showing That is, these graphs show the point cloud distribution on the search circle, and the slope of this point cloud distribution represents the point density of the point cloud within the search circle. Therefore, when the inclination is large as shown in FIG. 18, it can be determined that the point cloud is due to the surrounding objects, and when the inclination is not large as shown in FIG. 19, it can be determined that the point cloud is due to measurement error. .

Therefore, the processor 101 determines whether or not the point cloud is due to a peripheral object based on the threshold value determined for the slope of the point cloud distribution. Calculate the radial distance of . Then, the processor 101 measures the shortest distance among the calculated radial distances as the separation distance. FIG. 20 is a schematic diagram showing an example of the measured distance. In this example, the processor 101 measures the distance d1 to the point DT1 of the point group as the separation distance based on the graph of FIG.

As described above, in the third embodiment, the distance measurement unit 16 calculates the point cloud distribution by counting the number of points around the model in the measurement range from each starting point set in the model in a certain direction. , the shortest distance among the distances to the point where the slope in the point cloud distribution has changed by a threshold value or more is taken as the distance between the object and the surrounding objects. Therefore, a highly accurate distance measurement result can be obtained.

The method described in each embodiment can be executed by a computer (computer) as a distance measurement program (software means), such as a magnetic disk (floppy (registered trademark) disk, hard disk, etc.), an optical disk (CD-ROM). , DVD, MO, etc.), a semiconductor memory (ROM, RAM, flash memory, etc.), or the like, or may be transmitted and distributed via a communication medium. The programs stored on the medium also include a setting program for configuring software means (including not only execution programs but also tables and data structures) to be executed by the computer. A computer that realizes this apparatus reads a program recorded on a recording medium, and in some cases, builds software means by a setting program, and executes the above-described processes by controlling the operation by this software means. The term "recording medium" as used herein is not limited to those for distribution, and includes storage media such as magnetic disks, semiconductor memories, etc. provided in computers or devices connected via a network.

In short, the present invention is not limited to the above embodiments, and can be modified in various ways without departing from the gist of the invention at the implementation stage. Moreover, each embodiment may be implemented in combination as much as possible, and in that case, the combined effect can be obtained. Furthermore, the above-described embodiments include inventions at various stages, and various inventions can be extracted by appropriately combining a plurality of disclosed constituent elements.

REFERENCE SIGNS LIST 1 distance measuring device 2 laser point cloud data storage unit 3 management data storage unit 4 display unit 11 point cloud acquisition unit 12 modeling data acquisition unit 13 measurement range narrowing unit 14 data superimposition unit 15 measurement Non-target point group removal unit 16 Distance measurement unit 17 Measurement result storage unit 18 Measurement result output unit 101 Processor 102 Program memory 103 Data memory 1031 Point cloud storage unit 1032 Model storage unit 1033 Measurement range storage Unit 1034 Superimposition result storage unit 1035 Measurement result storage unit 1036 Temporary storage unit 104 Communication interface 105 Input/output interface 106 Bus DI Point group information DO Point group DT, DT1, DT2, DT3, DTm Points E1, E2...Measurement area ME...Full measurement area MI...Model information MO, MO1, MO2, MO3, MO11, MO12, MO13...Model MR, MR1, MR2...Measurement range OR...Measurement target range PR...Partial measurement range SD1, SD2, SD3 -- Separation SI -- Superimposition information SP, SPn -- Start point SS1, SS2 -- Search circle d -- Separation distance d1, d2, d3 -- Distance

Claims

Distance measurement for measuring the distance between an object and surrounding objects based on a point cloud having position information and height information obtained by measuring the object and surrounding objects existing around the object a device,
a narrowing unit for inputting the point group and the model of the object generated from the point group and narrowing down the measurement range of the distance to a specified range;
a superimposition unit that superimposes the point cloud of the measurement range after the narrowing down and the model;
a point cloud removal unit that removes the point cloud existing inside the model by the superimposition as not to be measured;
a distance measuring unit that measures the distance between the target object and the peripheral object by calculating the distance between the deleted point cloud and the model;
a distance measuring device.
The distance measuring device according to claim 1, wherein the narrowing-down unit narrows down the measurement range to a range designated based on the position information and the height information of the point cloud and the model.
The distance measuring device according to claim 1 or 2, wherein the narrowing-down unit narrows down the measurement range to a range specified centering on the model.
The distance measurement unit calculates a distance between each point of the point group after the deletion and the model, and sets the minimum value of the calculated distance as the distance between the object and the surrounding object. 4. A distance measuring device according to any one of claims 1 to 3.
The distance measurement unit divides the entire space of the measurement range into partial measurement ranges that are fixed three-dimensional areas, and measures the distance between the partial measurement range having the highest point density among the partial measurement ranges and the model as follows: 4. The distance measuring device according to any one of claims 1 to 3, wherein said distance between said object and said peripheral object is defined as said distance.
The distance measurement unit calculates a point cloud distribution by counting the number of points around the model in the measurement range from each starting point set in the model with respect to a certain direction, 4. The distance measuring device according to any one of claims 1 to 3, wherein the distance between said object and said peripheral object is the shortest distance among distances to a point where there is a change in .
Equipped with a processor and a memory, and based on a point group having position information and height information obtained by measuring a target and peripheral objects existing around the target, the target and the peripheral objects A distance measurement method in a distance measurement device for measuring the distance of
said processor inputting said point cloud and a model of said object generated from said point cloud and narrowing the range of measurement of said separation to a specified range;
the processor superimposing the point cloud of the narrowed measurement range and the model, and storing the result in the memory;
the processor deletes from the memory the point cloud that exists inside the model due to the superimposition as a non-measurement object;
the processor measuring the distance between the target object and the surrounding object by calculating the distance between the point cloud after the deletion and the model;
A method of distance measurement, comprising:
7. A distance measuring program causing a processor to function as the narrowing-down unit, the superimposing unit, the point group removing unit, and the distance measuring unit of the distance measuring device according to claim 1.