Distance measurement device, distance measurement method, and distance measurement program

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

[Technical field]

[0001] An embodiment of the present invention relates to a distance measurement device, a distance measurement method, and a distance measurement program. [Background technology]

[0002] 2. Description of the Related Art Aerial cables are widely used as a method for installing cables such as power transmission cables and communication cables outdoors, in which the cables are erected between utility poles, traffic lights, and other poles.

[0003] Patent documents 1 to 3 disclose devices that use a mobile mapping system (MMS) to detect the condition of such cables and poles. The MMS is a system that has an inspection vehicle equipped with a 3D laser scanner (3D laser surveying device), a camera, a global positioning system (GPS) receiver, an inertial measurement unit (IMU), and an odometer, and performs comprehensive 3D surveying of outdoor structures including surrounding buildings, roads, bridges, etc. while the inspection vehicle is traveling on the road, and acquires the 3D shape of the outdoor structure by collecting the 3D (X, Y, Z) coordinates of many points on the surface of the outdoor structure. This system acquires the absolute 3D coordinates of the irradiated points as 3D point cloud data by irradiating the surface of the outdoor structure with laser light within the measurement error of the MMS and the measurement error of the GPS receiver. Patent documents 1 to 3 detect the condition of the object, such as a cable or pole, based on the 3D point cloud data of the object measured by the MMS. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2019-148464 [Patent Document 2] Japanese Patent Publication No. 2017-156179 [Patent Document 3] Japanese Patent Application Publication No. 2019-191002 Summary of the Invention [Problem to be solved by the invention]

[0005] In an aerial cable line, there is a risk that trees may come into contact with the poles or cables due to fallen trees caused by strong winds or snowfall, which may cause the poles to tilt or fall, or the cables to be cut, resulting in other breakdowns. For this reason, it is desirable to take necessary measures in advance, such as pruning branches or replanting trees that may affect such poles or cables. For this reason, there is a need for measuring the distance between objects such as poles and cables and surrounding objects such as trees that are located around the objects.

[0006] The present invention provides a technique that enables measurement of the distance between an object and surrounding objects present around the object. [Means for solving the problem]

[0007] In order to solve the above problem, a distance measurement device according to one aspect of the present invention is a distance measurement device that measures the distance between an object and a peripheral object based on a point cloud having position information and height information acquired by measuring the object and peripheral objects existing around the object, and includes a narrowing down unit, a superimposition unit, a point cloud removal unit, and a distance measurement unit. The narrowing down unit inputs the point cloud and a model of the object generated from the point cloud, and narrows down the distance measurement range to a specified range. The superimposition unit superimposes the point cloud in the narrowed down measurement range and the model. The point cloud removal unit deletes the point cloud existing inside the model due to the superposition as a non-measurement target. The distance measurement unit measures the distance between the object and the peripheral object by calculating the distance between the point cloud after deletion and the model. The distance measurement unit divides the entire space of the measurement range into partial measurement ranges, which are fixed three-dimensional regions, and determines the distance between the partial measurement range with the highest point density within the partial measurement range and the model as the distance between the target object and surrounding objects. Effect of the Invention

[0008] According to one aspect of the present invention, it is possible to provide a technique that enables measurement of the distance between an object and a surrounding object existing around the object. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram showing an example of a functional configuration of a distance measuring device according to a first embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram showing an example of a hardware configuration of a computer when the distance measuring device according to the first embodiment is configured by the computer. [Diagram 3] FIG. 3 is a flowchart showing an example of the operation of the distance measuring device. [Figure 4] FIG. 4 is a diagram illustrating an example of point cloud information. [Diagram 5] FIG. 5 is a diagram illustrating an example of model information. [Figure 6] FIG. 6 is a schematic diagram showing a measurement range narrowed down by an example of a measurement range narrowing technique. [Figure 7] FIG. 7 is a schematic diagram showing another example of a method for narrowing down the measurement range. [Figure 8] FIG. 8 is a schematic diagram showing the measurement range narrowed down by the method of FIG. [Figure 9] FIG. 9 is a schematic diagram showing the superposition of a model and a point cloud. [Figure 10] FIG. 10 is a schematic diagram showing a method for removing points not subject to distance measurement from the entire point cloud. [Figure 11] FIG. 11 is a schematic diagram showing distance measurement within the measurement range. [Figure 12] FIG. 12 is a schematic diagram showing an example of a measured distance. [Figure 13] FIG. 13 is a schematic diagram showing an example of the measured separation distance. [Figure 14] FIG. 14 is a diagram showing an example of a display of the distance measurement result. [Figure 15] FIG. 15 is a schematic diagram showing distance measurement within a measurement range in a distance measurement device according to the second embodiment of the present invention. [Figure 16] FIG. 16 is a schematic diagram showing an example of the measured separation distance. [Figure 17] FIG. 17 is a schematic diagram showing distance measurement within a measurement range in a distance measurement device according to a third embodiment of the present invention. [Figure 18] FIG. 18 is a graph showing an example of the relationship between the radius of a search circle and the total number of points within the search circle. [Figure 19] FIG. 19 is a graph showing an example of the relationship between the radius of a search circle and the total number of points within the search circle, which is different from that shown in FIG. [Figure 20] FIG. 20 is a schematic diagram showing an example of the measured separation distance. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0011] [First embodiment] (composition) FIG. 1 is a schematic diagram showing an example of a functional configuration of a distance measuring device 1 according to a first embodiment of the present 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. Here, the "connection" is not limited to a direct connection by wire or wirelessly, but may be an indirect connection via a network such as a LAN (Local Area Network) or the Internet. In addition, when the laser point cloud data storage unit 2 and the management data storage unit 3 are configured in the form of a recording medium such as a magnetic disk (floppy (registered trademark) disk, hard disk, etc.), an optical disk (CD-ROM, DVD, MO, etc.), or a semiconductor memory (ROM, RAM, flash memory, etc.), the connection may be via a readout device corresponding to the recording medium.

[0012] The laser point cloud data storage unit 2 stores laser point cloud data (hereinafter, abbreviated as point cloud). A point cloud is three-dimensional (X, Y, Z) coordinate data of a large number of points on the surfaces of objects such as poles and cables and surrounding objects such as trees around the objects, collected while an inspection vehicle equipped with an MMS is traveling on the road. In other words, a point cloud is a collection of points having geographical position information (X, Y) and height information (Z).

[0013] The management data storage unit 3 also stores management data for each object such as a pole or cable. The management data includes, for example, shape information and geographical position information (X, Y) and height information (Z) of the object. The management data may also include shape information and geographical position information (X, Y) of surrounding objects. The management data of the object and surrounding objects is information at the time of installation for the object, and is information at any point in time for the surrounding objects, and therefore does not necessarily represent the current state due to changes over time.

[0014] The display unit 4 is, for example, a display device using liquid crystal or organic EL (Electro Luminescence).

[0015] The distance measurement device 1 comprises a point cloud acquisition unit 11, a modeled data acquisition unit 12, a measurement range narrowing unit 13, a data superposition unit 14, a non-measurement target point cloud removal unit 15, a distance measurement unit 16, a measurement result storage unit 17, and a measurement result output unit 18.

[0016] The point cloud acquisition unit 11 acquires a 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 of an arbitrary geographical position designated by an operator of the distance measurement device 1, for example.

[0017] 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. The model has position information and height information. The method of acquiring this model is a known technique, and therefore a description thereof will be omitted here.

[0018] The measurement range narrowing unit 13 identifies the measurement range of the distance based on the position and height information (X, Y, Z) 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 position information of the object stored in the management data storage unit 3.

[0019] The data superposition 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 identified by the measurement range narrowing unit 13 based on their respective position information.

[0020] The non-measurement target point cloud removal unit 15 removes point clouds that are not targets of distance measurement from the entire point clouds regarding the model and point clouds superimposed by the data superimposition unit 14.

[0021] The distance measurement unit 16 measures the distance between each model and the point cloud that has not been removed by the non-measurement target point cloud removal unit 15 and remains.

[0022] The measurement result storage unit 17 stores the distance measurement results between the model and the point cloud measured by the distance measurement unit 16 as the distance between the target object and the surrounding objects existing around it.

[0023] The measurement result output unit 18 displays the distance between the target object and the surrounding objects, which is the distance measurement result stored in the measurement result storage unit 17, on the display unit 4. Note that instead of displaying the distance measurement result on the display unit 4, the measurement result output unit 18 may print the result on a printing unit such as a printer, record the result on a recording medium, or transmit the result to an external device via a network.

[0024] 2 is a diagram showing an example of a hardware configuration of a computer when the remote measurement device 1 according to the first embodiment is configured by a computer. The remote measurement device 1 has a hardware processor 101 such as a CPU (Central Processing Unit). In the remote measurement 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. The CPU can execute multiple information processes simultaneously by using a multi-core and multi-threaded one. The processor 101 may also be equipped with multiple CPUs.

[0025] The program memory 102 is a non-transient tangible computer-readable storage medium, for example, a combination of a non-volatile memory such as a hard disk drive (HDD) or a solid state drive (SSD) that can be written and read at any time, and a non-volatile memory such as a ROM. The program memory 102 stores control programs required for the processor 101 to execute various control processes according to the present embodiment. For example, the point cloud acquisition unit 11, the modeled data acquisition unit 12, the measurement range narrowing unit 13, the data superposition unit 14, the non-measurement target point cloud removal unit 15, the distance measurement unit 16, the measurement result storage unit 17, and the measurement result output unit 18 can be realized by having the processor 101 read and execute the distance measurement program stored in the program memory 102. Note that some or all of these processing function units may be realized in various other forms, including integrated circuits such as an application specific integrated circuit (ASIC) or a field-programmable gate array (FPGA).

[0026] The data memory 103 is a tangible computer-readable storage medium, for example, a combination of the above-mentioned nonvolatile memory and a volatile memory such as a RAM (Random Access Memory). The data memory 103 is used to store various data acquired and created in the course of various processes. For example, the data memory 103 has storage areas secured for 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.

[0027] 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.

[0028] The model storage unit 1032 is a storage area for storing a model acquired by the processor 101 executing a control process related to the modeling data acquisition unit 12.

[0029] The measurement range storage unit 1033 is a storage area for storing the measurement range specified by the processor 101 executing the control process related to the measurement range narrowing unit 13.

[0030] The superimposition result storage unit 1034 is a storage area for the processor 101 to execute control processing related to the data superimposition unit 14 and store the superimposition result.

[0031] The measurement result storage unit 1035 is a storage area for the processor 101 to execute control processing related to the measurement result storage unit 17 and store the measurement results.

[0032] The temporary memory unit 1036 is a memory area for temporarily storing various data generated in the process in which the processor 101 executes control processing related to the data superposition unit 14, the non-measurement target point cloud removal unit 15, and the distance measurement unit 16.

[0033] The communication interface 104 is a communication module for transmitting and receiving information to and from other devices via a network (not shown). The other devices may include, for example, a storage device, a server device, a personal computer, and the like that function as the laser point cloud data storage unit 2 and / or the management data storage unit 3.

[0034] The input / output interface 105 is an input / output module for connecting, by wire or wirelessly, the laser point cloud data storage unit 2, the management data storage unit 3, and the display unit 4. The input / output interface 105 can further be connected to an input unit such as a keyboard (not shown).

[0035] (operation) Next, the operation of the distance measuring device 1 according to the first embodiment will be described. Fig. 3 is a flowchart showing an example of the operation of the distance measurement device 1 according to the first embodiment. When the distance measurement device 1 is configured by a computer as shown in Fig. 2, a distance measurement program required for executing the control process shown in this flowchart is stored in the program memory 102, and the processor 101 executes the program, thereby allowing the device 1 to operate as the point cloud acquisition unit 11, the modeled data acquisition unit 12, the measurement range narrowing unit 13, the data superposition unit 14, the non-measurement target point cloud removal unit 15, the distance measurement unit 16, the measurement result storage unit 17, and the measurement result output unit 18 of the distance measurement device 1 as shown in Fig. 2.

[0036] The processor 101 of the distance measurement device 1 starts the operation shown in this flowchart, for example, when an arbitrary geographical location where distance measurement between the target object and surrounding objects should be performed is input via an input / output interface 105 by an input unit not shown, as specified by the operator of the distance measurement device 1.

[0037] First, the processor 101 functions as the point cloud acquisition unit 11 and acquires point cloud information including a point cloud to be processed corresponding to a specified geographical position from the laser point cloud data storage unit 2 via the input / output interface 105 (or the communication interface 104) (step S11). FIG. 4 is a diagram showing an example of the 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.

[0038] Next, the processor 101 functions as the modeling data acquisition unit 12 and acquires a 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 the 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. 2. The processor 101 stores the acquired model information MI in the model storage unit 1032 of the data memory 103.

[0039] Next, the processor 101 functions as the measurement range narrowing unit 13, and specifies the measurement range of the distance based on the position and height information 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, and the position information of the target object stored in the management data storage unit 3 (step S13). There are two methods for specifying this measurement range: (1) specification based on the position and height information of the point cloud and the model, and (2) specification centered on the model, and either method or a combination of the two can be used.

[0040] FIG. 6 is a schematic diagram showing a measurement range narrowed down by the method of identifying based on the position and height information of the point cloud and the model (1) as a method of narrowing down the measurement range. The geographical positions where the point cloud and the model are likely to exist in the entire measurement area ME are specified by the position information (X, Y) of the object stored in the management data storage unit 3. Then, the processor 101 acquires the position information of the object from the management data storage unit 3 by the input / output interface 105 (or the communication interface 104) and stores it in the temporary storage unit 1036 of the data memory 103. The processor 101 also specifies a measurement area from the entire measurement area ME based on the 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. Then, among the specified measurement areas, the 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 target. In the example of FIG. 6, since there is position information of objects corresponding to the models MO11 and MO13, the measurement areas E1 and E2 are specified, but since there is no position information of objects corresponding to the model MO12, the measurement area is not specified. Then, the processor 101 specifies the height range to be measured for each of the specified measurement areas E1 and E2 based on the height information (Z: z1, z2) of each of the point clouds included in the point cloud information DI stored in the point cloud storage unit 1031 and each of the models included in the model information MI stored in the model storage unit 1032. As a result, the processor 101 specifies the measurement ranges MR1 ​​and MR2 for the models MO11 and MO13. The processor 101 stores the specified measurement ranges MR1 ​​and MR2 in the measurement range storage unit 1033 of the data memory 103.

[0041] FIG. 7 is a schematic diagram showing a method of specifying the measurement range centered on the model (2) as a method of narrowing down the measurement range. The management data for the object stored in the management data storage unit 3 can include, in addition to position information and height information, direction designation information that designates the direction of the measurement range. For example, this direction designation information can be registered from the situation of the surrounding objects visually confirmed by the collection worker when the inspection vehicle equipped with the MMS collects the point cloud while traveling on the road. Alternatively, a camera image may also be taken during the point cloud collection, and an arbitrary worker may register the direction designation information while checking the image. Also, instead of registering it as management data, the operator of the distance measurement device 1 may input this direction designation information together with an arbitrary geographical position where the distance measurement between the object and the surrounding objects should be performed by an input unit (not shown).

[0042] The processor 101 specifies a measurement range MR for each model based on direction designation information indicating the range to be measured, such as the left side (-X direction), right side (+X direction), front side (+Y direction), back side (-Y direction), upper side (+Z direction), lower side (-Z direction), etc., of the model MO with respect to the measurement target range OR centered on the model MO to be processed. The processor 101 stores the specified measurement range MR in the measurement range storage unit 1033.

[0043] Fig. 8 is a schematic diagram showing a measurement range narrowed down by a combination of the method of Fig. 6 and the method of Fig. 7. The processor 101 can specify measurement ranges MR1 ​​and MR2 by further narrowing down the measurement range narrowed down by the specification method based on the position and height information of the point cloud and the model (1) by the specification method centered on the model (2). The model MO12 is not subject to the method of (2) as it is a model outside the measurement area. The processor 101 stores the specified measurement ranges MR1 ​​and MR2 in the measurement range storage unit 1033.

[0044] Next, the processor 101 functions as a data superposition unit 14 and superposes each point cloud contained in the point cloud information DI stored in the point cloud memory unit 1031 and each model contained in the model information MI stored in the model memory unit 1032 on the measurement range stored in the measurement range memory unit 1033 based on their respective position information (X, Y, Z) (step S14).

[0045] 9 is a schematic diagram showing the superimposition of this model and a point cloud. The processor 101 stores the superimposition information SI, which is the result of the superimposition, in the superimposition result storage unit 1034 of the data memory 103. This superimposition process utilizes existing technology, so details thereof will be omitted.

[0046] Next, the processor 101 functions as the non-measurement target point cloud removal unit 15 and removes point clouds that are not the target of distance measurement from the entire point cloud for the superimposed model and point cloud in the superimposition information SI stored in the superimposition result memory unit 1034 (step S15).

[0047] Fig. 10 is a schematic diagram showing a method for removing points that are not targets of distance measurement from the entire point cloud. As shown by the dashed line on the left side of Fig. 10, the processor 101 deletes all points DT that exist within the model MO in the superimposed model and point cloud, as shown on the right side of the figure, since they are points recognized as models and are not targets of measurement. Specifically, the processor 101 deletes points DT that exist within the model MO in the superimposition information SI stored in the superimposition result storage unit 1034.

[0048] Next, the processor 101 functions as the distance measurement unit 16, selects one model from the models in the overlay information SI stored in the overlay result storage unit 1034 as a processing target, and measures the distance between the selected model and each point of the point cloud that has not been removed, thereby measuring the distance between the model and the point cloud (step S16). The processor 101 measures the shortest distance to the point cloud for the selected model as the distance.

[0049] Fig. 11 is a schematic diagram showing distance measurement within a 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 a point DT of the point cloud for each start point SP on the model MO. Fig. 11 shows a state in which a point DTm with position information and height information (Xm, Ym, Zm) is searched for from a start point SPn with position information and height information (Xn, Yn, Zn).

[0050] FIG. 12 is a schematic diagram showing an example of a measured distance. If a point DT other than inside 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 shows that points DT1, DT2, and DT3 are found, and their respective distances d1, d2, and d3 are calculated. In this way, the processor 101 determines whether or not a group of points exists concentrically around 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. The processor 101 stores the position information of the found point and the calculated distance in the temporary storage unit 1036.

[0051] 13 is a schematic diagram showing an example of the measured separation distance. The processor 101 determines the shortest distance between the model MO and the point cloud among the distances between the model MO and the point DT stored in the temporary storage unit 1036. For example, if the distance d1 between the model MO and the point DT1 is the shortest, the processor 101 determines this distance d1 as the separation distance.

[0052] Then, the processor 101 functions as the measurement result storage unit 17 and stores the separation distance between the model MO and the point cloud measured in step S16 above in the measurement result memory unit 1035 of the data memory 103 as the measurement result of the separation distance between the target object and objects existing around it (step S17).

[0053] After that, the processor 101 judges whether or not all the models in the superimposition information SI stored in the superimposition result storage unit 1034 have been processed (step S18). If it is judged that all the 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.

[0054] When it is determined that all models have been processed in this way (YES in step S18), the processor 101 functions as the measurement result output unit 18 and causes the display unit 4 to display the separation distance between the target object and the object, which is the separation measurement result stored in the measurement result storage unit 1035, via the input / output interface 105 (step S19). Then, the process shown in the flowchart ends.

[0055] 14 is a diagram showing an example of display of the distance measurement result. The processor 101 displays the models MO1, MO2, and MO3 representing the target object and the point cloud DO representing the surrounding objects, and displays the distances SD1, SD2, and SD3 which are the shortest distances between them. The processor 101 can display the distances SD1, SD2, and SD3 as specific numerical values.

[0056] In addition, instead of displaying the distance measurement results on the display unit 4, the distance measurement device 1 may print the distance measurement results on a printing unit such as a printer, record them on a recording medium, or transmit them to an external device via a network.

[0057] In the first embodiment described above, the distance measuring device 1 measures the distance between an object and a peripheral object based on a point cloud having position information and height information acquired by measuring an object such as a pole and peripheral objects such as trees around the object, and includes a measurement range narrowing unit 13, a data superimposition unit 14, a non-measurement target point cloud removal unit 15, and a distance measuring unit 16. The measurement range narrowing unit 13 inputs a point cloud and a model of the object generated from the point cloud, and narrows the measurement range of the distance to a specified range. The data superimposition unit 14 superimposes the point cloud of the narrowed measurement range and the model. The non-measurement target point cloud removal unit 15 deletes the point cloud existing inside the model by superimposition as a non-measurement target. The distance measuring unit 16 measures the distance between the object and the peripheral object by calculating the distance between the deleted point cloud and the model. Thus, a technology that enables measurement of the distance between an object and peripheral objects existing around the object can be provided.

[0058] In addition, by using the non-measurement point cloud removal unit 15 to remove point clouds that are not subject to distance measurement from the entire point cloud, the number of points in the point cloud that the distance measurement unit 16 processes is reduced, which not only speeds up the distance measurement process, but also reduces the amount of information stored in the data memory 103 during processing, thereby reducing the capacity of the data memory 103 and lowering the price.

[0059] In the first embodiment, the measurement range narrowing unit 13 narrows the measurement range to a range specified based on the position information and height information of the point cloud and the model. This increases the speed of the distance measurement process, reduces the amount of information stored in the data memory 103 during the process, and reduces the capacity of the data memory 103, resulting in a lower price.

[0060] Alternatively, in the first embodiment, the measurement range narrowing unit 13 narrows the measurement range to a range specified with the model at the center. This increases the speed of the distance measurement process, reduces the amount of information stored in the data memory 103 during the process, and reduces the capacity of the data memory 103, resulting in a lower price.

[0061] Furthermore, the measurement range narrowing unit 13 can combine narrowing the measurement range to a range specified based on the position information and height information of the point cloud and the model, and narrowing the measurement range to a range specified with the model at the center, thereby further speeding up the distance measurement process, reducing the amount of information, and reducing the cost.

[0062] In the first embodiment, the distance measurement unit 16 calculates the distance between each point of the deleted point cloud and the model, and sets the minimum value of the calculated distances as the distance between the target object and the surrounding objects. Therefore, accurate distance measurement results can be obtained.

[0063] For example, when measuring the distance visually, there is variation among people, the distance measurement accuracy is poor, and it takes a lot of time to measure. On the other hand, when measuring the distance based on a photographed image, the image cannot measure the distance accurately in the depth direction, and there are cases where the image cannot be sufficiently identified when photographed against the light or at night, making it impossible to measure the distance. Furthermore, when calculating the distance manually from a point cloud, there is also variation among people, the distance measurement accuracy is poor, and it takes time to measure. In contrast, the distance measurement device 1 according to the first embodiment has excellent effects such as a significant reduction in inspection time, high speed and light data volume, distance measurement without on-site inspection, and improved measurement accuracy.

[0064] [Second embodiment] The configuration of a distance measuring device 1 according to the second embodiment of the present invention is similar to that of the first embodiment. This embodiment differs from the first embodiment in the method of measuring the distance between a model and a point cloud.

[0065] FIG. 15 is a schematic diagram showing distance measurement within a measurement range MR in the remote measurement device 1 according to the second embodiment. The points near the model are plotted due to measurement errors when collecting a point cloud by the MMS, and the measurement errors are present randomly and at low density. Therefore, in this embodiment, when measuring the distance between the model and each point of the point cloud in step S16, the processor 101 of the remote measurement device 1 performs measurement by dividing the entire space of the measurement range MR and taking into account the point density. 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 a certain cube. Then, the processor 101 counts the number of points DT present in each divided partial measurement range PR.

[0066] 16 is a schematic diagram showing an example of a measured separation distance. The processor 101 deletes the points in a partial measurement range PR that has a smaller number of points DT in the partial measurement range PR, i.e., a lower point density, compared to other partial measurement ranges PR. In this way, the distance to the partial measurement range PR that is finally left and has a larger number of points DT, i.e., a higher point density, is calculated as the separation distance d.

[0067] As described above, in the second embodiment, the distance measurement unit 16 divides the entire measurement range into partial measurement ranges, which are fixed three-dimensional regions, and determines the distance between the partial measurement range with the highest point density and the model as the distance between the target object and the surrounding objects. Therefore, accurate distance measurement results can be obtained.

[0068] [Third embodiment] The configuration of a distance measurement device 1 according to the third embodiment of the present invention is similar to that of the first embodiment. This embodiment differs from the first and second embodiments in the method of measuring the distance between a model and a point cloud.

[0069] In this embodiment, the processor 101 of the distance measurement device 1 measures the distance between the model and each point of the point cloud in step S16 above, by using a point cloud distribution for finding surrounding objects.

[0070] FIG. 17 is a schematic diagram showing distance measurement within a measurement range in the distance measurement device 1 according to the third embodiment. As described in the second embodiment, points near the model are plotted due to measurement errors, and the measurement errors are random and low-density. Therefore, in this embodiment, the processor 101 of the distance measurement device 1 sets a search circle within the measurement range for each start point on the model MO when measuring the distance between the model and each point of the point cloud in the above step S16. The example of FIG. 17 shows search circles SS1 and SS2 for two start points. That is, the processor 101 counts the number of points DT of the point cloud around the model MO in a certain direction.

[0071] Fig. 18 is a graph showing an example of the relationship between the radius of the search circle SS1 and the total number of points in the search circle SS1, and Fig. 19 is a graph showing an example of the relationship between the radius of the search circle SS2 and the total number of points in the search circle SS2. That is, these graphs show the point cloud distribution in the search circle, and the slope of this point cloud distribution represents the point density of the point cloud in the search circle. Therefore, when the slope is large as shown in Fig. 18, the point cloud is due to a surrounding object, and when the slope is not large as shown in Fig. 19, it can be determined that the point cloud is due to a measurement error.

[0072] Therefore, the processor 101 judges whether the point cloud is caused by a peripheral object based on a threshold value determined for the inclination of the point cloud distribution, and if it is a peripheral object, calculates the radial distance of the search circle to the point where the point cloud distribution has changed. Then, the processor 101 measures the shortest distance among the calculated radial distances as the separation distance. Figure 20 is a schematic diagram showing an example of the measured separation distance. In this example, the processor 101 measures the distance d1 to the point DT1 of the point cloud as the separation distance based on the graph of Figure 18.

[0073] As described above, in the third embodiment, the distance measurement unit 16 calculates a point cloud distribution by counting the number of points around the model in the measurement range in a certain direction from each start point set in the model, and determines the shortest distance among the distances to a point where the slope of the point cloud distribution has changed by more than a threshold value as the distance between the target object and the surrounding objects. Therefore, a highly accurate distance measurement result can be obtained.

[0074] The methods described in each embodiment can be stored as a distance measurement program (software means) that can be executed by a calculator (computer) on a recording medium such as a magnetic disk (floppy (registered trademark) disk, hard disk, etc.), optical disk (CD-ROM, DVD, MO, etc.), semiconductor memory (ROM, RAM, flash memory, etc.), and can also be distributed by transmitting it via a communication medium. The program stored on the medium side also includes a setting program that configures the software means (including not only execution programs but also tables and data structures) that the computer executes. The computer that realizes this device reads the program recorded on the recording medium, and in some cases, constructs the software means by the setting program, and executes the above-mentioned processing by controlling the operation of the software means. The recording medium referred to in this specification is not limited to a recording medium for distribution, but also includes a storage medium such as a magnetic disk or semiconductor memory provided inside the computer or in a device connected via a network.

[0075] In short, this invention is not limited to the above-mentioned embodiment, and various modifications can be made in the implementation stage without departing from the gist of the invention. Moreover, each embodiment may be implemented in combination as appropriate as possible, in which case the combined effect can be obtained. Furthermore, the above-mentioned embodiment includes inventions at various stages, and various inventions can be extracted by appropriate combinations of the disclosed constituent elements. [Explanation of symbols]

[0076] 1... Distance measurement device 2...Laser point cloud data storage unit 3...Management data storage section 4...Display section 11...Point cloud acquisition section 12…Modeling data acquisition section 13…Measuring range narrowing section 14...Data superimposition section 15…Non-measurement point cloud removal section 16… Distance measurement section 17...Measurement result storage section 18…Measurement result output section 101…Processor 102…Program memory 103...Data memory 1031...Point cloud storage unit 1032…Model memory section 1033…Measuring range memory section 1034...Superposition result storage unit 1035…Measurement result storage unit 1036...Temporary storage 104...Communication interface 105... Input / Output Interface 106…Bus DI: Point cloud information DO…Point cloud DT, DT1, DT2, DT3, DTm... points E1, E2…Measurement area ME: All measurement areas MI…Model Information MO, MO1, MO2, MO3, MO11, MO12, MO13…Models MR, MR1, MR2…Measuring range OR…Measurement range PR…Partial measurement range SD1, SD2, SD3…separation SI: Superimposed information SP,SPn…starting point SS1, SS2...Search circle d…Separation distance d1,d2,d3...distance

Claims

1. A distance measurement device that measures a distance between an object and a peripheral object based on a point cloud having position information and height information obtained by measuring the object and peripheral objects present around the object, a narrowing-down unit that receives the point cloud and a model of the object generated from the point cloud and narrows down the measurement range of the distance to a specified range; a superimposing unit that superimposes the point cloud of the narrowed-down measurement range and the model; a point cloud removal unit that removes a point cloud that exists inside the model due to the superposition as a non-measurement target; a distance measurement unit that measures the distance between the target object and the peripheral object by calculating a distance between the point cloud after the deletion and the model; Equipped with The distance measurement unit divides the entire space of the measurement range into partial measurement ranges, which are fixed three-dimensional regions, and determines the distance between the partial measurement range with the highest point density within the partial measurement range and the model as the distance between the target object and the surrounding object.

2. A distance measurement device that measures a distance between an object and a peripheral object based on a point cloud having position information and height information obtained by measuring the object and peripheral objects present around the object, a narrowing-down unit that receives the point cloud and a model of the object generated from the point cloud and narrows down the measurement range of the distance to a specified range; a superimposing unit that superimposes the point cloud of the narrowed-down measurement range and the model; a point cloud removal unit that removes a point cloud that exists inside the model due to the superposition as a non-measurement target; a distance measurement unit that measures the distance between the target object and the peripheral object by calculating a distance between the point cloud after the deletion and the model; Equipped with The distance measurement unit calculates a point cloud distribution by counting the number of points around the model in the measurement range in a certain direction from each starting point set on the model, and determines the shortest distance among the distances to a point where there is a change in slope in the point cloud distribution that is equal to or greater than a threshold value as the distance between the target object and the surrounding object.

3. The distance measurement device according to claim 1 , wherein the narrowing unit narrows down the measurement range to a range specified based on the position information and the height information of the point cloud and the model.

4. 4. The distance measurement device according to claim 1, wherein the narrowing unit narrows the measurement range to a specified range centered on the model.

5. A method for measuring a distance between an object and a peripheral object, the method comprising the steps of: The processor inputs the point cloud and a model of the object generated from the point cloud, and narrows down a measurement range of the separation to a specified range; The processor superimposes the point cloud of the narrowed-down measurement range on the model and stores the result in the memory; and The processor deletes a point cloud existing inside the model due to the superposition from the memory as a non-measurement target; The processor measures the distance between the target object and the surrounding objects by calculating a distance between the point cloud after the deletion and the model; The processor divides the entire space of the measurement range into partial measurement ranges that are certain three-dimensional regions, and determines the distance between the partial measurement range with the highest point density within the partial measurement range and the model as the separation between the target object and the surrounding object; A distance measurement method comprising:

6. A method for measuring a distance between an object and a peripheral object, the method comprising the steps of: The processor inputs the point cloud and a model of the object generated from the point cloud, and narrows down a measurement range of the separation to a specified range; The processor superimposes the point cloud of the narrowed-down measurement range on the model and stores the result in the memory; and The processor deletes a point cloud existing inside the model due to the superposition from the memory as a non-measurement target; The processor measures the distance between the target object and the surrounding objects by calculating a distance between the point cloud after the deletion and the model; The processor calculates a point cloud distribution by counting the number of points around the model in the measurement range in a certain direction from each start point set in the model, and determines the distance between the target object and the surrounding object as the shortest distance among distances to a point where a change in slope in the point cloud distribution is equal to or exceeds a threshold value; A distance measurement method comprising:

7. 5. A distance measurement program that causes a processor to function as the narrowing-down unit, the superimposing unit, the point cloud removing unit, and the distance measurement unit of the distance measurement device according to claim 1.

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