Distance measurement device, method, and program

Abstract

To provide a distance measuring apparatus, or the like, configured to contribute to easy and accurate measurement of shortest distance, horizontal distance, and vertical distance between objects even when the objects have complicated shapes or they are located in places where measurement is physically difficult.SOLUTION: A distance measurement apparatus includes: an object division unit configured to execute processing to divide three-dimensional point cloud data into point clouds for each object; and a distance measurement unit configured to execute processing to calculate two points where two objects are closest to each other, from point clouds of the two objects, out of the point clouds for the objects obtained by the object division unit, and processing to measure one of shortest distance, vertical distance, and horizontal distance between the calculated two points.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present invention relates to a distance measurement device, method, and program, and more particularly, to a distance measurement device, method, and program for measuring the distance between objects using three-dimensional point cloud data.

Background Art

[0002] Power companies need to comply with regulations (wire electrical communication facility ordinance) on the separation distance between electric wires and their surrounding structures (peripheral obstacles) in order to prevent electric shock disasters. The measurement of the separation distance is regularly performed by workers using measuring instruments. In the measurement of the separation distance, there are multiple viewpoints for measurement. For example, in the measurement of the separation distance between an electric wire as the measurement object and its surrounding structures, for example, when measuring the shortest distance between the electric wire and the surrounding structures, or when measuring the horizontal distance or vertical distance between the electric wire and the surrounding structures.

[0003] Since the number of electric wires to be measured is enormous, it is required to facilitate the measurement of the separation distance. In addition, since the measurement results depend on the measurement skills of the workers in manual measurement, an accurate measurement method that does not depend on the skills of the workers is required. One way to facilitate and accurately measure the separation distance is to automate the separation distance measurement using a three-dimensional sensor.

[0004] As a technique for automating the separation distance measurement, Patent Document 1 discloses a measurement object measurement method in which while running a self-propelled machine that travels on an overhead line, the transmission line and trees are synchronously photographed a plurality of times with three or more cameras attached to the self-propelled machine, association is performed on a set of images obtained by the synchronous photography, the three-dimensional coordinate data of the synchronous photographed transmission line and trees are obtained, and the distance between the straight line representing the transmission line and all the corresponding pair determination points of the trees or the corresponding pair determination points within a previously specified range is calculated, and the shortest distance is output as the separation distance between the transmission line and the trees.

[0005] In Patent Document 2, a power transmission line of a known wire type is spanned between power transmission line support structures with known shape dimensions and arrangement, etc., and the position of an object such as a tree close to the power transmission line is specified, and a system for measuring the separation distance between the object and the power transmission line is provided. Two or more pieces of image information taken from two or more imaging positions including the power transmission line support structure and the object are input. Based on the power transmission line support structure in each of the input images, a conversion formula between the coordinates of the image and the actual spatial coordinates is obtained. Based on the object in each image, the direction from each imaging position in the spatial coordinates to the object is obtained. Based on the intersection of the directions to the object obtained for each image, the actual position of the object is obtained. Using the wire type information of the power transmission line, etc., a power transmission line formula is obtained. Based on the position of the object and the power transmission line formula, the separation distance between the object and the power transmission line is obtained. A separation distance measurement system for objects close to a power transmission line is disclosed.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0007] The following analysis is provided by the inventor of the present application.

[0008] There are technical problems in the measurement of these separation distances. For example, in the measurement of the shortest distance, it is necessary to specify and measure the closest point between two objects, but the closest point is not formally determined. For example, when the surrounding structure has a very complex shape with large irregularities like vegetation, it is difficult to specify the point that is the shortest distance to the electric wire with the techniques described in Patent Documents 1 and 2.

[0009] In addition, when measuring the horizontal distance or the vertical distance, it is necessary to measure the distance horizontally or vertically from the electric wire to the surrounding structures. However, with the methods described in Patent Documents 1 and 2, accurate measurement is difficult in an environment where the electric wire and the surrounding structures do not have an orthogonal positional relationship.

[0010] A main object of the present invention is to contribute to easily and accurately measuring the shortest distance, the horizontal distance, and the vertical distance between objects even when the object has a complex shape or exists in a place where physical measurement is difficult, and to provide a distance measurement device, a method, and a program.

Means for Solving the Problems

[0011] The distance measurement device according to the first aspect includes an object division unit configured to perform a process of dividing three-dimensional point cloud data into point clouds for each object, and among the point clouds for each object divided by the object division unit, a process of calculating two points where two objects are closest to each other from the point clouds of the two objects, and a distance measurement unit configured to perform a process of measuring any one of the shortest distance, the vertical distance, and the horizontal distance between the calculated two points.

[0012] The distance measurement method according to the second aspect is a distance measurement method for measuring a distance using hardware resources, and includes a step of dividing three-dimensional point cloud data into point clouds for each object, a step of calculating two points where two objects are closest to each other from the point clouds of the two objects among the point clouds for each divided object, and a step of measuring any one of the shortest distance, the vertical distance, and the horizontal distance between the calculated two points.

[0013] The program according to the third perspective is a program that causes hardware resources to execute a process of measuring a distance, and includes a process of dividing three-dimensional point cloud data into point clouds for each object, and a process of calculating, from the point clouds for each of the divided objects, two points that are the closest to each other among two objects, and a process of causing the hardware resources to measure any one of the shortest distance, vertical distance, and horizontal distance between the two calculated points.

[0014] Note that the program can be recorded on a computer-readable storage medium. The storage medium can be non-transient, such as a semiconductor memory, a hard disk, a magnetic recording medium, an optical recording medium, etc. Also, in the present disclosure, it is also possible to embody it as a computer program product. The program is input into a computer device via an input device or externally through a communication interface, stored in a storage device, drives a processor according to predetermined steps or processes, and can display the processing result including intermediate states step by step via a display device as needed, or communicate with the outside via a communication interface. A computer device for this purpose typically includes a processor, a storage device, an input device, a communication interface, and a display device that can be connected to each other by a bus as an example.

Advantages of the Invention

[0015] According to the first to third perspectives, it is possible to contribute to easily and accurately measuring the shortest distance, horizontal distance, and vertical distance between objects even when the objects have complex shapes or are located in physically difficult-to-measure locations.

Brief Description of the Drawings

[0016]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Modes for Carrying Out the Invention

[0017] Hereinafter, embodiments will be described with reference to the drawings. In the present application, when reference numerals are attached to the drawings, they are solely for the purpose of assisting understanding and are not intended to be limited to the illustrated embodiments. Also, the following embodiments are merely examples and do not limit the present invention. In addition, the connection lines between the blocks in the drawings and the like referred to in the following description include both bidirectional and unidirectional ones. The one-way arrow schematically shows the flow of the main signal (data) and does not exclude bidirectionality. Furthermore, in the circuit diagrams, block diagrams, internal configuration diagrams, connection diagrams, etc. shown in the present application disclosure, although not explicitly shown, input ports and output ports exist at the input ends and output ends of each connection line respectively. The same applies to the input / output interface. The program is executed via a computer device, and the computer device includes, for example, a processor, a storage device, an input device, a communication interface, and a display device if necessary. The computer device is configured to be able to communicate with devices inside or outside the device (including computers) via the communication interface, whether wired or wireless.

[0018] [Embodiment 1] The distance measurement device according to Embodiment 1 will be described with reference to the drawings. FIG. 1 is an image diagram showing an example of measuring the shortest distance, horizontal distance, and vertical distance between objects using the distance measurement device according to Embodiment 1. FIG. 2 is a block diagram schematically showing the configuration of the distance measurement device according to Embodiment 1.

[0019] The distance measurement device 200 is a device that analyzes the three-dimensional point cloud data 100 to measure the distance (e.g., in FIG. 1, the shortest distance D, horizontal distance H, and vertical distance V) between objects (e.g., between the electric wire 10 and the tree 20 in FIG. 1) (see FIG. 2). The distance measurement device 200 may select any two points from the three-dimensional point cloud data 100 without selecting objects and measure the distance (linear distance, horizontal distance, vertical distance) between the selected two points. Further, the distance measurement device 200 may measure the longest distance between objects by changing the distance measurement process between objects from the shortest distance to the longest distance. The distance measurement device 200 can be used, for example, to measure the distance between electric wires in the power industry, wires in the construction industry, overhead lines in the railway industry, communication lines in the communication industry, etc. and surrounding structures. The distance measurement device 200 may be communicably connected (wireless communication, wired communication) to a three-dimensional sensor (300 in FIG. 1). The distance measurement device 200 acquires the three-dimensional point cloud data 100 related to the object to be measured (the electric wire 10, etc. in FIG. 1) from the three-dimensional sensor 300.

[0020] Here, the three-dimensional sensor 300 is a device that three-dimensionally senses and photographs the surface of an object to be measured (such as the electric wire 10 in FIG. 1) (see FIG. 1). The three-dimensional sensor 300 may be communicably connected to the distance measuring device 200. The three-dimensional sensor 300 generates three-dimensional point cloud data 100 in a predetermined format by photographing the object to be measured (such as the electric wire 10 in FIG. 1), and outputs the generated three-dimensional point cloud data 100 to the distance measuring device 200. Note that the three-dimensional point cloud data 100 may be generated by the distance measuring device 200 instead of being generated by the three-dimensional sensor 300. For the three-dimensional sensor 300, for example, a ToF (Time of Flight) camera, a stereo camera, a three-dimensional LIDAR (Laser Imaging Detection And Ranging), a depth sensor, a distance measuring sensor, a distance camera, etc. can be used. The three-dimensional sensor 300 is operated by an operator. Note that the three-dimensional point cloud data 100 is data generated in a predetermined format by the three-dimensional sensor 300, and is point cloud data drawn as a point cloud (a collection of a large number of points having XYZ coordinate (three-dimensional coordinate) information) (see FIG. 2). The three-dimensional sensor 300 can be changed to a sensor device with various output formats according to customer requirements.

[0021] The distance measuring device 200 can use a device (computer device) having functional units (for example, a processor, a storage device, an input device, a communication interface, and a display device) that constitute a computer, and for example, a notebook personal computer, a smartphone, a tablet terminal, etc. can be used. The distance measuring device 200 realizes a configuration including a preprocessing unit 210, a measuring unit 220, and a user interface unit 230 by executing a predetermined program (see FIG. 2).

[0022] The preprocessing unit 210 is a functional unit that performs preprocessing on the input three-dimensional point cloud data 100 (see FIG. 2). The preprocessing unit 210 includes a format conversion unit 211 and a noise removal unit 212.

[0023] The format conversion unit 211 is a functional unit that, as a preprocessing step, converts the format of the input 3D point cloud data 100 into a common format that can be commonly used in the distance measuring device 200 (see Fig. 2). The format conversion unit 211 outputs the converted 3D point cloud data 100 in the common format to the noise removal unit 212. Note that if the format of the 3D point cloud data 100 is originally in the common format, the format conversion process by the format conversion unit 211 may be omitted.

[0024] The noise removal unit 212 is a functional unit that, as a preprocessing step, removes noise (point clouds unnecessary for measurement) from the point clouds in the 3D point cloud data 100 from the format conversion unit 211 (see Fig. 2). The noise removal unit 212 outputs the 3D point cloud data 100 from which noise has been removed to the angle conversion unit 221 of the measurement unit 220. Examples of noise removal methods include smoothing processing, filtering (e.g., moving average filter processing, median filter processing, etc.), and outlier removal processing (e.g., outlier removal processing by chi-square test). Note that if there is almost no noise, the noise removal process by the noise removal unit 212 may be omitted. Also, for noise removal, point clouds other than those extracted by edge detection may be removed as noise.

[0025] The measurement unit 220 is a functional unit that measures (calculates) the distance (such as the shortest distance, horizontal distance, vertical distance, etc.) between objects specified by the user from the preprocessed 3D point cloud data 100. The measurement unit 220 includes an angle conversion unit 221, an object division unit 222, and a distance measurement unit 223.

[0026] The angle conversion unit 221 is a functional unit that performs angle conversion on the three-dimensional point cloud data 100 from the noise removal unit 212 as preprocessing for measurement (see Fig. 2). The angle conversion unit 221 performs angle conversion on the three-dimensional point cloud data 100 so that the gravity direction (vertical direction) faces downward. As a method for angle conversion in the gravity direction, for example, a method of using an IMU (Inertial Measurement Unit) sensor (not shown) to convert the angle of the inclination of the three-dimensional point cloud data 100 at the time of shooting to match the gravity direction can be mentioned. Also, as a method for angle conversion in the gravity direction, the wall surface of the building may be detected based on the three-dimensional point cloud data 100, and angle conversion may be performed so that the detected wall surface becomes a vertical plane. Also, as a method for angle conversion in the gravity direction, the ground (30 in Fig. 1) may be detected based on the three-dimensional point cloud data 100, and angle conversion may be performed so that the detected ground 30 becomes a horizontal plane. Also, as a method for angle conversion in the gravity direction, utility poles (40 or 41 in Fig. 1) may be detected based on the three-dimensional point cloud data 100, and angle conversion may be performed so that the extending directions of the detected utility poles 40 and 41 are perpendicular. Furthermore, as a method for angle conversion in the gravity direction, angle conversion may be performed by a user operation (manual). The angle conversion unit 221 outputs the angle-converted three-dimensional point cloud data 100 toward the object division unit 222.

[0027] The object division unit 222 is a functional unit that divides (extracts) the angle-converted three-dimensional point cloud data 100 into point clouds for each object (see Fig. 2). Examples of the division method include object division by clustering. Also, regarding the division method, the object may be divided using the reflection intensity of the three-dimensional sensor 300. Furthermore, regarding the division method, the object may be divided using the RGB (Red Green Blue) values of the three-dimensional sensor 300.

[0028] The distance measurement unit 223 is a functional unit that measures the distance between objects (in FIG. 1, between the electric wire 10 and the tree 20) (see FIG. 2). The distance measurement unit 223 calculates, from the point clouds of two objects specified by the operation of the input unit 232 by the user among the point clouds of the objects divided by the object division unit 222, the two points at which the two objects are closest to each other (the closest points) (one point in the point cloud of one object and one point in the point cloud of the other object). The distance measurement unit 223 may detect the point clouds of two objects corresponding to a preset detection model among the point clouds of each object divided by the object division unit 222, and calculate the two points at which the two detected objects are closest to each other from the point clouds of the two objects. When three or more objects are specified, the distance measurement unit 223 may measure the distance between each object. Further, the distance measurement unit 223 selects the point cloud of one reference object (for example, the electric wire 10; it may also be an object corresponding to a preset detection model) specified by the operation of the input unit 232 by the user among the point clouds of each object divided by the object division unit 222, extracts the point cloud of an obstacle object (for example, the tree 20) existing within a predetermined distance from the selected point cloud of the reference object, calculates the two points at which the reference object and the obstacle object are closest to each other from the point clouds of the reference object and the obstacle object, and may measure any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points.Further, the distance measurement unit 223 selects a point cloud of one actual object (for example, the electric wire 10; it may also be an object corresponding to a preset detection model) specified by the operation of the input unit 232 by the user from among the point clouds of each object divided by the object division unit 222, generates a point cloud of a virtual object (for example, a point cloud of a building that will be built in the future) in the three-dimensional point cloud data 100 including the point cloud of the selected actual object, calculates two points where the actual object and the virtual object are closest to each other from the point clouds of the actual object and the virtual object, and may measure any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points. The distance measurement unit 223 outputs the measurement result of the measured distance toward the user interface unit 230.

[0029] The user interface unit 230 is a functional unit that mediates between the user and the distance measurement device 200 (see FIG. 2). The user interface unit 230 includes a display unit 231 and an input unit 232.

[0030] The display unit 231 is a functional unit that displays information such as the division result of the object division unit 222 and the measurement result of the distance measurement unit 223 (see FIG. 2). The display unit 231 may display, as a separation violation area, an area within a predetermined distance from the reference object (for example, the electric wire 10), which is the measurement target object specified by the operation of the input unit 232 by the user, as a reference.

[0031] The input unit 232 is a functional unit that inputs information operated by the user (see FIG. 2). The input unit 232 inputs designation information related to the object designated by the user from among the division results of the objects by the operation. Regarding the method of selecting an object, instead of the user's operation, the object may be automatically detected and selected using a preset detection model.

[0032] As described above, in the example of FIG. 1, the distance measuring device 200 photographs an object (such as the electric wire 10, the tree 20, etc.) to be measured using the three-dimensional sensor 300 at the measurement site, and acquires the three-dimensional point cloud data 100 of the electric wire 10. The distance measuring device 200 reads the acquired three-dimensional point cloud data 100, divides the three-dimensional point cloud data 100 for each object in internal processing, and displays the division result. From the division result, the user designates (or selects) the object for which the distance is to be measured. The distance measuring device 200 automatically measures (calculates) the distance (shortest distance, horizontal distance, vertical distance) between the designated objects, and displays the calculation result on the screen. As described above, the distance between objects (between the electric wire 10 and the tree 20 in FIG. 1) can be measured non-contact.

[0033] Next, the operation of the distance measuring device according to Embodiment 1 will be described with reference to the drawings. FIG. 3 is a flowchart schematically showing the operation of the distance measuring device according to Embodiment 1. For the configuration of the distance measuring device, refer to FIG. 2 and its description.

[0034] First, the preprocessing unit 210 of the distance measuring device 200 acquires the three-dimensional point cloud data 100 related to an object (for example, the electric wire 10, the tree 20) to be measured, which is photographed and generated by the three-dimensional sensor 300 (step A1).

[0035] Next, the format conversion unit 211 of the preprocessing unit 210 of the distance measuring device 200 converts the format of the acquired three-dimensional point cloud data 100 into a common format that can be commonly used in the distance measuring device 200 as preprocessing (step A2).

[0036] Next, the noise removal unit 212 of the preprocessing unit 210 of the distance measuring device 200 removes noise from the point cloud in the three-dimensional point cloud data 100 whose format has been converted by the format conversion unit 211 as preprocessing (step A3).

[0037] Next, the angle conversion unit 221 of the measurement unit 220 of the distance measurement device 200 performs angle conversion on the three-dimensional point cloud data 100 preprocessed by the preprocessing unit 210 so that the gravitational direction is vertically downward (step A4).

[0038] Next, the object division unit 222 of the measurement unit 220 of the distance measurement device 200 divides (extracts) the angle-converted three-dimensional point cloud data 100 for each object (step A5).

[0039] Next, the distance measurement device 200 acquires designation information related to the object designated as the measurement target from among the object division results by operating the input unit 232 of the user interface unit 230 by the user (step A6).

[0040] Next, the distance measurement unit 223 of the measurement unit 220 of the distance measurement device 200 measures the distance (the shortest distance D, horizontal distance H, and vertical distance V in FIG. 1) between the objects related to the acquired designation information (between the electric wire 10 and the tree 20 in FIG. 1) (step A7).

[0041] Next, the display unit 231 of the user interface unit 230 of the distance measurement device 200 displays the measurement result (step A8), and then ends.

[0042] Next, the distance measurement operation of the distance measurement device according to Embodiment 1 will be described with reference to the drawings. FIG. 4 is an image diagram schematically showing the operation related to the distance measurement of the distance measurement device according to Embodiment 1.

[0043] An image of the distance measurement between objects in step A7 of FIG. 3 is shown in FIG. 4.

[0044] In distance measurement, first, for two objects (the electric wire 10 and the tree 20 in FIG. 4) to be the measurement targets, two points that are closest to each other are calculated from the point clouds constituting the respective objects. Examples of the calculation method include nearest neighbor search using a KDTree (K-Dimensional Tree) and nearest neighbor decision rules.

[0045] Next, distance measurement is performed. In the distance measurement, if two points corresponding to the shortest distance between objects are (x1, y1, z1) and (x2, y2, z2) as shown in FIG. 4, the shortest distance D between the two points can be expressed as in Equation 1, the horizontal distance H between the two points can be expressed as in Equation 2, and the vertical distance V between the two points can be expressed as in Equation 3.

[0046] [Equation 1] TIFF0007701030000001.tif777

[0047] [Equation 2] TIFF0007701030000002.tif854

[0048] [Equation 3] TIFF0007701030000003.tif724

[0049] According to Embodiment 1, even when the object has a complex shape or is present in a place where physical measurement is difficult, since the measurement points are specified using nearest neighbor search or the like for the point cloud constituting the cluster of the measurement object, it is possible to contribute to easily and accurately measuring the shortest distance, horizontal distance, vertical distance, etc. between objects.

[0050] Also, according to Embodiment 1, an object can be automatically detected from three-dimensional point cloud data, and the shortest distance, horizontal distance, and vertical distance between specific objects can be automatically measured. Note that Patent Document 2 describes which part of the object should be used as the measurement point for measuring the shortest distance between objects, such as the top or the tip of a branch for a tree, and the top or a corner for a structure, but does not specify a specific method for specifying the measurement point.

[0051] Further, according to Embodiment 1, by using the three-dimensional point cloud data 100 of the object captured by the three-dimensional sensor 300, the shortest distance between objects can be measured non-contact, and the distance measurement cost can be reduced. In the technology described in Patent Document 1, although distance measurement can be performed non-contact, it is necessary to run a self-propelled machine from one end to the other end of the overhead transmission line in order to acquire the coordinates of the overhead transmission line and the object, which incurs a high distance measurement cost.

[0052] Further, according to Embodiment 1, by automating the measurement process, even a user who is not familiar with the measurement work can easily perform the measurement.

[0053] Further, according to Embodiment 1, for example, even in an environment where it is physically difficult to measure the shortest distance, horizontal distance, and vertical distance due to a shielding object provided between the electric wire 10 and the tree 20, the measurement can be easily performed.

[0054] Furthermore, according to Embodiment 1, since a three-dimensional sensor is used, for example, when the shape of the object is front-back symmetric, the point cloud coordinates of the latter half can be estimated from the point cloud coordinates of the first half, and the shortest distance between the estimated latter half and the overhead transmission line can be calculated. In the technologies described in Patent Documents 1 and 2, the shortest distance can be calculated only within the range captured by the camera.

[0055] [Embodiment 2] The distance measurement device according to Embodiment 2 will be described with reference to the drawings. FIG. 5 is a block diagram schematically showing the configuration of the distance measurement device according to Embodiment 2.

[0056] The distance measurement device 200 is a device that measures the distance between two objects based on the three-dimensional point cloud data 100. The distance measurement device 200 includes an object division unit 222 and a distance measurement unit 223.

[0057] The object division unit 222 is configured to perform a process of dividing the three-dimensional point cloud data 100 into point clouds for each object. The distance measurement unit 223 performs a process of calculating, from the point clouds of each object divided by the object division unit 222, two points where the two objects are closest to each other among the point clouds of two objects, and a process of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points.

[0058] According to the second embodiment, even when the object has a complex shape or is present in a place where physical measurement is difficult, measurement points are specified for the point cloud constituting the cluster of the measurement object using nearest neighbor search or the like. Therefore, it is possible to contribute to easily and accurately measuring the shortest distance, horizontal distance, vertical distance, etc. between objects.

[0059] Note that the distance measurement device according to the first and second embodiments can be configured by so-called hardware resources (information processing devices, computers), and those having the configuration illustrated in FIG. 6 can be used. For example, the hardware resource 1000 includes a processor 1001, a memory 1002, a network interface 1003, etc., which are interconnected by an internal bus 1004.

[0060] Note that the configuration shown in FIG. 6 is not intended to limit the hardware configuration of the hardware resource 1000. The hardware resource 1000 may include hardware not shown (for example, an input / output interface). Alternatively, the number of units such as the processor 1001 included in the device is not intended to be limited to the example shown in FIG. 6. For example, a plurality of processors 1001 may be included in the hardware resource 1000. For the processor 1001, for example, a CPU (Central Processing Unit), an MPU (Micro Processor Unit), a GPU (Graphics Processing Unit), etc. can be used.

[0061] For the memory 1002, for example, RAM (Random Access Memory), ROM (Read Only Memory), HDD (Hard Disk Drive), SSD (Solid State Drive), etc. can be used.

[0062] For the network interface 1003, for example, a LAN (Local Area Network) card, a network adapter, a network interface card, etc. can be used.

[0063] The functions of the hardware resources 1000 are realized by the above-described processing modules. The processing modules are realized, for example, by the processor 1001 executing a program stored in the memory 1002. Also, the program can be downloaded via a network or updated using a storage medium storing the program. Furthermore, the above processing modules may be realized by semiconductor chips. That is, the functions performed by the above processing modules may be realized as long as software is executed in some hardware.

[0064] Some or all of the above embodiments may be described as follows in the appended claims, but are not limited thereto.

[0065] [Appended Note 1] An object division unit configured to perform a process of dividing 3D point cloud data into point clouds for each object, Among the point clouds for each object divided by the object division unit, a process of calculating two points where the two objects are closest to each other from the point clouds of the two objects, and a process of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, and a distance measurement unit configured to perform the processes, A distance measurement device comprising the above. [Appended Note 2] In the process of calculating the two points, the process of calculating the two points is performed by nearest neighbor search using a KDTree. The distance measurement device described in Supplementary Note 1. [Supplementary Note 3] In the process of the division, a process of dividing into point clouds for each object by clustering, a process of dividing into point clouds for each object using the reflection intensity of the three-dimensional sensor, and a process of dividing into point clouds for each object using the RGB values of the three-dimensional sensor, any one of the processes is performed. The distance measurement device described in Supplementary Note 1 or 2. [Supplementary Note 4] Further comprising an input unit for inputting information operated by the user, In the process of calculating the two points, Based on the specified information input to the input unit, among the point clouds for each object divided by the object division unit, a process of selecting the point clouds of two objects, a process of calculating the two points from the point clouds of the two selected objects, is performed. The distance measurement device described in any one of Supplementary Notes 1 to 3. [Supplementary Note 5] In the process of calculating the two points, Among the point clouds for each object divided by the object division unit, a process of detecting the point clouds of two objects corresponding to a preset detection model, a process of calculating the two points from the point clouds of the two detected objects, is configured to perform. The distance measurement device described in any one of Supplementary Notes 1 to 3. [Supplementary Note 6] The distance measurement unit Among the point clouds for each object divided by the object division unit, a process of selecting the point cloud of one reference object, a process of extracting the point cloud of an obstacle object existing within a predetermined distance from the point cloud of the selected reference object, A process of calculating two points from each point cloud of the reference object and the obstacle object, where the reference object and the obstacle object are closest to each other, A process of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, is further configured to perform, The distance measuring device according to any one of Appendices 1 to 5. [Appendix 7] The distance measuring unit, A process of selecting a point cloud of one real object from the point clouds of each object divided by the object dividing unit, A process of generating a point cloud of a virtual object in the three-dimensional point cloud data including the point cloud of the real object, A process of calculating two points from each point cloud of the real object and the virtual object, where the real object and the virtual object are closest to each other, A process of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, is further configured to perform, The distance measuring device according to any one of Appendices 1 to 6. [Appendix 8] The distance measuring device further includes an angle conversion unit configured to perform angle conversion on the three-dimensional point cloud data so that the gravity direction is downward, The object dividing unit is configured to process using the three-dimensional point cloud data angle-converted by the angle conversion unit. The distance measuring device according to any one of Appendices 1 to 7. [Appendix 9] A distance measuring method for measuring a distance using hardware resources, A step of dividing three-dimensional point cloud data into point clouds for each object, A step of calculating two points from each point cloud of two objects among the point clouds of each object divided, where the two objects are closest to each other, A step of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, A distance measurement method including [Appendix 10] A program for causing hardware resources to execute a process of measuring a distance, a process of dividing three-dimensional point cloud data into point clouds for each object, a process of calculating, from the point clouds of each of two objects among the point clouds of the divided objects for each object, two points at which the two objects are closest to each other, a process of measuring any one of the shortest distance, the vertical distance, and the horizontal distance between the calculated two points, and causing the hardware resources to execute the above, a program.

[0066] Note that each disclosure of the above patent documents is incorporated herein by reference and can be used as the basis or part of the present invention as necessary. Within the scope of the entire disclosure of the present invention (including the claims and the drawings), further modifications and adjustments of the embodiments or examples can be made based on the basic technical idea. Also, within the scope of the entire disclosure of the present invention, various combinations or selections (including non-selections if necessary) of various disclosure elements (including each element of each claim, each element of each embodiment or example, each element of each drawing, etc.) are possible. That is, the present invention naturally includes various modifications and corrections that a person skilled in the art could make according to the entire disclosure including the claims and the drawings and the technical idea. Also, regarding the numerical values and numerical ranges described in the present application, even if not explicitly stated, any intermediate value, lower numerical value, and small range are considered to be described. Furthermore, each disclosure item of the above-cited documents is, if necessary, considered to be included in (belong to) the disclosure of the present application as part of the disclosure of the present invention and can be used in combination with the description items of this document, either in part or in whole, in accordance with the spirit of the present invention.

Explanation of Signs

[0067] 10 Electric wire 20 Tree 30 Ground 40, 41 Utility pole 100 Three-dimensional point cloud data 200 Distance Measurement Device 210 Preprocessing Unit 211 Format Conversion Unit 212 Noise Removal Unit 220 Measurement Unit 221 Angle Conversion Unit 222 Object Division Unit 223 Distance Measurement Unit 230 User Interface Unit 231 Display Unit 232 Input Unit 300 3D Sensor 1000 Hardware Resources 1001 Processor 1002 Memory 1003 Network Interface 1004 Internal Bus

Claims

1. An object division unit configured to perform a process of dividing three-dimensional point cloud data into point clouds for each object, Among the point clouds for each object divided by the object division unit, a process of calculating two points where two objects are closest to each other from the point clouds of the two objects, and a process of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, and a distance measurement unit configured to perform the process, Comprising, In the process of calculating the two points, Among the point clouds for each object divided by the object division unit, a process of detecting point clouds of two objects corresponding to a preset detection model, A process of calculating the two points from the point clouds of the detected two objects, A distance measurement device configured to perform the process.

2. An object division unit configured to perform a process of dividing three-dimensional point cloud data into point clouds for each object, Among the point clouds for each object divided by the object division unit, a process of calculating two points where two objects are closest to each other from the point clouds of the two objects, and a process of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, and a distance measurement unit configured to perform the process, Comprising, The distance measurement unit, Among the point clouds for each object divided by the object division unit, a process of selecting a point cloud of one reference object, A process of extracting a point cloud of an obstacle object existing within a predetermined distance from the point cloud of the selected reference object, A process of calculating two points where the reference object and the obstacle object are closest to each other from the point clouds of the reference object and the obstacle object, A process of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, A distance measurement device configured to further perform the process.

3. An object division unit configured to perform a process of dividing three-dimensional point cloud data into point clouds for each object, Among the point clouds for each object divided by the object division unit, a process of calculating two points where two objects are closest to each other from the point clouds of the two objects, and a process of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, and a distance measurement unit configured to perform the process, Comprising, The distance measurement unit, Among the point clouds for each object divided by the object division unit, a process of selecting a point cloud of one real object; A process of generating a point cloud of a virtual object in the three-dimensional point cloud data including the point cloud of the real object; A process of calculating two points where the real object and the virtual object are closest to each other from the point clouds of the real object and the virtual object; A process of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points; A distance measuring device configured to further perform.

4. In the process of calculating the two points, the process of calculating the two points is performed by nearest neighbor search using a KDTree. The distance measuring device according to any one of claims 1 to 3.

5. In the process of dividing, A process of dividing into point clouds for each object by clustering, A process of dividing into point clouds for each object using the reflection intensity of the three-dimensional sensor, and A process of dividing into point clouds for each object using the RGB value of the three-dimensional sensor, Any one of the processes is performed. The distance measuring device according to any one of claims 1 to 4.

6. Further comprising an input unit for inputting information operated by a user, In the process of calculating the two points, Based on the specified information input to the input unit, among the point clouds for each object divided by the object division unit, a process of selecting the point clouds of two objects; A process of calculating the two points from the point clouds of the selected two objects; is performed. The distance measuring device according to any one of claims 1 to 5.

7. Further comprising an angle conversion unit configured to perform angle conversion on the three-dimensional point cloud data so that the gravity direction is downward, The object division unit is configured to process using the three-dimensional point cloud data angle-converted by the angle conversion unit. The distance measuring device according to any one of claims 1 to 6.

8. A distance measuring method for measuring a distance using hardware resources, comprising: A step of dividing three-dimensional point cloud data into point clouds for each object; A step of calculating two points where the two objects are closest to each other from the point clouds of the two objects among the point clouds for each divided object; A step of measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, and The step of calculating the two points is Among the point clouds for each of the segmented objects, detecting the point clouds of two objects corresponding to a preset detection model; Calculating the two points from the point clouds of the two detected objects, the distance measurement method comprising:

9. A distance measurement method for measuring a distance using hardware resources, comprising: Dividing the three-dimensional point cloud data into point clouds for each object; Among the point clouds for each of the segmented objects, calculating two points where the two objects are closest to each other from the point clouds of the two objects; Measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points; Among the point clouds for each of the segmented objects, selecting the point cloud of one reference object; Extracting the point cloud of an obstacle object existing within a predetermined distance from the point cloud of the selected reference object; Calculating two points where the reference object and the obstacle object are closest to each other from the point clouds of the reference object and the obstacle object; Measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, the distance measurement method comprising:

10. A distance measurement method for measuring a distance using hardware resources, comprising: Dividing the three-dimensional point cloud data into point clouds for each object; Among the point clouds for each of the segmented objects, calculating two points where the two objects are closest to each other from the point clouds of the two objects; Measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points; Among the point clouds for each of the segmented objects, selecting the point cloud of one actual object; Generating a point cloud of a virtual object in the three-dimensional point cloud data including the point cloud of the actual object; Calculating two points where the actual object and the virtual object are closest to each other from the point clouds of the actual object and the virtual object; Measuring any one of the shortest distance, vertical distance, and horizontal distance between the calculated two points, the distance measurement method comprising:

11. A program for causing a hardware resource to execute the distance calculation method according to any one of Claims 8 to 10.

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