JP7701030B2 - Distance measurement device, method, and program - Google Patents

Description

The present invention relates to a distance measurement device, method, and program, and in particular to a distance measurement device, method, and program that measures the distance between objects using three-dimensional point cloud data.

To prevent electric shock accidents, electric power companies must comply with regulations (Wired Telecommunications Equipment Ordinance) regarding the separation distance between electric wires and surrounding structures (surrounding obstacles). Separation distances are measured periodically by workers using measuring equipment. There are multiple perspectives for measuring separation distances. For example, when measuring the separation distance between the electric wire that is the measurement subject and its surrounding structure, there are cases where the shortest distance between the electric wire and the surrounding structure is measured, and cases where the horizontal distance or vertical distance between the electric wire and the surrounding structure is measured.

Since the number of electric wires to be measured is enormous, there is a demand for facilitating the measurement of separation distance. Furthermore, since the measurement results when measured manually depend on the measurement skills of the worker, there is a demand for an accurate measurement method that is not dependent on the skill of the worker. One way to make separation distance measurement easier and more accurate is to automate the measurement using a 3D sensor.

As a technology for automating distance measurement, Patent Document 1 discloses a method for measuring objects to be measured, which involves taking multiple synchronous images of power lines and trees using three or more cameras attached to a self-propelled machine while the machine is traveling along overhead lines, matching a set of images obtained by synchronous shooting, determining three-dimensional coordinate data of the synchronously photographed power lines and trees, calculating the distance between a straight line representing the power line and all corresponding pair determination points of the trees or corresponding pair determination points within a pre-specified range, and outputting the shortest distance as the distance between the power line and the trees.

Patent Document 2 discloses a system for measuring the distance between objects near power lines, in which power lines of a known type are stretched between power line support structures whose shape, dimensions, and layout are known, and which identifies the position of an object such as a tree close to the power line and measures the distance between the object and the power line. Two or more pieces of image information taken from two or more shooting positions that include the power line support structures and the object are input, and a conversion formula between the image coordinates and the actual spatial coordinates is calculated based on the power line support structures in each input image, the direction from each shooting position to the object in the spatial coordinates is calculated based on the object in each image, the actual position of the object is calculated based on the intersection of the directions to the object calculated for each image, the power line type information is used to calculate the power line type, and the distance between the object and the power line is calculated based on the object's position and the power line type.

JP 2007-107962 A JP 2002-174510 A

The following analysis is provided by the present inventors.

Measuring these separation distances involves technical challenges. For example, when measuring the shortest distance, it is necessary to identify and measure the closest point between two objects, but the closest point is not determined formally. For example, when the surrounding structures have complex shapes with many projections and recesses, such as vegetation, it is difficult to identify the point that is the shortest distance from the electric wire using the techniques described in Patent Documents 1 and 2.

In addition, when measuring horizontal or vertical distances, it is necessary to measure the distance horizontally or vertically from the electric wire to the surrounding structure, but the methods described in Patent Documents 1 and 2 make it difficult to make accurate measurements in environments where the electric wire and the surrounding structure are not in a perpendicular positional relationship.

The main objective of the present invention is to provide a distance measurement device, method, and program that can 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 locations where measurement is physically difficult.

The distance measurement device relating to the first viewpoint includes an object division unit configured to perform a process of dividing three-dimensional point cloud data into point clouds for each object, and a distance measurement unit configured to perform a process of calculating two points at which two objects are closest to each other from each point cloud of two objects among the point clouds for each object divided by the object division unit, and a process of measuring the shortest distance, vertical distance, or horizontal distance between the two calculated points.

The distance measurement method relating to the second viewpoint is a distance measurement method that uses hardware resources to measure distance, and includes the steps of: dividing three-dimensional point cloud data into point clouds for each object; calculating two points at which the two objects are closest to each other from each point cloud of two objects among the divided point clouds for each object; and measuring the shortest distance, vertical distance, or horizontal distance between the two calculated points.

The program according to the third aspect is a program that causes a hardware resource to execute a process of measuring distance, and causes the hardware resource to execute a process of dividing three-dimensional point cloud data into point clouds for each object, a process of calculating, from each point cloud of two objects among the divided point clouds for each object, two points at which the two objects are closest to each other, and a process of measuring either the shortest distance, the vertical distance, or the horizontal distance between the two calculated points.

The program can be recorded on a computer-readable storage medium. The storage medium can be a non-transient medium such as a semiconductor memory, a hard disk, a magnetic recording medium, or an optical recording medium. In the present disclosure, the program can also be embodied as a computer program product. The program is input to the computer device from an input device or an external device via a communication interface, stored in a storage device, and drives the processor according to a predetermined step or process, and can display the processing results, including intermediate states as necessary, at each stage via a display device, or can communicate with the outside via the communication interface. As an example, a computer device for this purpose typically includes a processor, a storage device, an input device, a communication interface, and a display device as necessary, all of which can be connected to each other via a bus.

The first to third aspects can 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 locations that are physically difficult to measure.

1A to 1C are conceptual diagrams showing an example of measuring the shortest distance, horizontal distance, and vertical distance between objects using the distance measuring device according to the first embodiment. 1 is a block diagram illustrating a schematic configuration of a distance measurement device according to a first embodiment. 4 is a flowchart illustrating an example of an operation of the distance measurement device according to the first embodiment. 3A to 3C are conceptual diagrams illustrating an operation relating to distance measurement by the distance measurement device according to the first embodiment. FIG. 11 is a block diagram illustrating a configuration of a distance measurement device according to a second embodiment. FIG. 2 is a block diagram illustrating a schematic configuration of hardware resources.

The following describes the embodiments with reference to the drawings. Note that when reference symbols are used in this application, they are intended to aid understanding and are not intended to limit the invention to the illustrated form. The following embodiments are merely illustrative and do not limit the invention. The connection lines between blocks in the drawings and the like referred to in the following description include both bidirectional and unidirectional lines. One-way arrows are used to diagrammatically indicate the flow of the main signal (data) and do not exclude bidirectionality. Furthermore, although not explicitly shown in the circuit diagrams, block diagrams, internal configuration diagrams, connection diagrams, and the like shown in this disclosure, input ports and output ports exist at the input and output ends of each connection line. The same is true for input/output interfaces. The program is executed via a computer device, which includes, for example, a processor, a storage device, an input device, a communication interface, and a display device as necessary, and the computer device is configured to be able to communicate with devices inside or outside the device (including a computer) via the communication interface, whether wired or wireless.

[Embodiment 1]
A distance measurement device according to the first embodiment 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 the first embodiment. Fig. 2 is a block diagram showing a schematic configuration of the distance measurement device according to the first embodiment.

The distance measurement device 200 is a device that analyzes the three-dimensional point cloud data 100 to measure the distance (shortest distance D, horizontal distance H, vertical distance V in FIG. 1) between objects (for example, 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 an object, and measure the distance (straight-line distance, horizontal distance, vertical distance) between the selected two points. The distance measurement device 200 may also 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 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 connected to a three-dimensional sensor (300 in FIG. 1) so as to be able to communicate (wireless communication, wired communication). The distance measurement device 200 acquires 3D point cloud data 100 relating to the measurement object (such as the electric wire 10 in FIG. 1) from the 3D sensor 300.

Here, the three-dimensional sensor 300 is a device that three-dimensionally senses and photographs the surface of the measurement object (such as the electric wire 10 in FIG. 1) (see FIG. 1). The three-dimensional sensor 300 may be communicably connected to the distance measurement device 200. The three-dimensional sensor 300 generates three-dimensional point cloud data 100 in a predetermined format by photographing the measurement object (such as the electric wire 10 in FIG. 1), and outputs the generated three-dimensional point cloud data 100 to the distance measurement device 200. Note that the three-dimensional point cloud data 100 may be generated by the distance measurement device 200 instead of 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 measurement sensor, a distance camera, etc. may be used. The three-dimensional sensor 300 is operated by an operator. The three-dimensional point cloud data 100 is data generated in a specific format by the three-dimensional sensor 300, and is point cloud data depicted as a point cloud (a collection of many 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 requests.

The distance measurement device 200 may be a device (computer device) equipped with functional units that constitute a computer (e.g., a processor, a storage device, an input device, a communication interface, and a display device), and may be, for example, a notebook personal computer, a smartphone, or a tablet terminal. By executing a specific program, the distance measurement device 200 realizes a configuration equipped with a preprocessing unit 210, a measuring unit 220, and a user interface unit 230 (see FIG. 2).

The preprocessing unit 210 is a functional unit that performs preprocessing on the input 3D point cloud data 100 (see FIG. 2). The preprocessing unit 210 includes a format conversion unit 211 and a noise removal unit 212.

The format conversion unit 211 is a functional unit that converts the format of the input 3D point cloud data 100 into a common format that can be commonly used in the distance measurement device 200 as preprocessing (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 a common format, the format conversion process in the format conversion unit 211 may be omitted.

The noise removal unit 212 is a functional unit that removes noise (points unnecessary for measurement) from the points in the 3D point cloud data 100 from the format conversion unit 211 as pre-processing (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 processing in the noise removal unit 212 may be omitted. In addition, in the case of noise removal, points other than those extracted by edge detection may be removed as noise.

The measurement unit 220 is a functional unit that measures (calculates) the distance (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.

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 a pre-processing of the 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) is downward. As an angle conversion method for the gravity direction, for example, a method of converting the angle of the inclination of the three-dimensional point cloud data 100 at the time of shooting to match the gravity direction using an IMU (Inertial Measurement Unit) sensor (not shown) can be given. As an angle conversion method for the gravity direction, a wall surface of a 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 surface. As an angle conversion method for the gravity direction, a ground surface (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 surface 30 becomes a horizontal surface. As an angle conversion method for 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 extension direction of the detected utility poles 40, 41 becomes vertical. As an angle conversion method for the gravity direction, angle conversion may be performed by a user operation (manually). The angle conversion unit 221 outputs the angle-converted three-dimensional point cloud data 100 to the object division unit 222.

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). As a division method, for example, the objects may be divided by clustering. As a division method, the objects may be divided using the reflection intensity of the three-dimensional sensor 300. As a division method, the objects may be divided using the RGB (Red Green Blue) values of the three-dimensional sensor 300.

The distance measurement unit 223 is a functional unit that measures the distance (the shortest distance D, horizontal distance H, and vertical distance V in FIG. 1) between objects (between the electric wire 10 and the tree 20 in FIG. 1) (see FIG. 2). The distance measurement unit 223 calculates two points (one point in the point cloud of one object and one point in the point cloud of the other object) at which the two objects are closest to each other from each point cloud of two objects specified by the user's operation of the input unit 232 among the point clouds of the objects divided by the object division unit 222. 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 objects are closest to each other from each point cloud of the detected two objects. When three or more objects are specified, the distance measurement unit 223 may measure the distance between each object. In addition, the distance measurement unit 223 may select a point cloud of one reference object (e.g., an electric wire 10; it may also be an object corresponding to a preset detection model) specified by the user through operation of the input unit 232 from the point clouds for each object divided by the object division unit 222, extract a point cloud of an obstacle object (e.g., a tree 20) that exists within a predetermined distance from the point cloud of the selected reference object, calculate two points at which the reference object and the obstacle object are closest to each other from each point cloud of the reference object and the obstacle object, and measure any of the shortest distance, vertical distance, or horizontal distance between the two calculated points. The distance measurement unit 223 may also select a point cloud of one real object (e.g., electric wire 10; it may also be an object corresponding to a preset detection model) specified by the user through operation of the input unit 232 from among the point clouds for each object divided by the object division unit 222, generate a point cloud of a virtual object (e.g., 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 real object, calculate two points at which the real object and the virtual object are closest to each other from each point cloud of the real object and the virtual object, and measure the shortest distance, vertical distance, or horizontal distance between the two calculated points. The distance measurement unit 223 outputs the measurement result of the distance measured to the user interface unit 230.

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.

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

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 an object designated by the user from among the object segmentation results. Note that, regarding the method of selecting an object, instead of a user operation, a preset detection model may be used to automatically detect and select the object.

In the example of FIG. 1, the distance measurement device 200 as described above uses a 3D sensor 300 to capture an image of an object (such as an electric wire 10 or a tree 20) to be measured at the measurement site, and acquires 3D point cloud data 100 of the electric wire 10. The distance measurement device 200 reads the acquired 3D point cloud data 100, divides the 3D point cloud data 100 into objects by internal processing, and displays the division results. From the division results, the user specifies (or selects) an object for which distance measurement is to be performed. The distance measurement device 200 automatically measures (calculates) the distance (shortest distance, horizontal distance, vertical distance) between the specified objects, and displays the calculation results 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 without contact.

Next, the operation of the distance measurement device according to the first embodiment will be described with reference to the drawings. FIG. 3 is a flow chart that shows the operation of the distance measurement device according to the first embodiment. Please refer to FIG. 2 and its description for the configuration of the distance measurement device.

First, the preprocessing unit 210 of the distance measurement device 200 acquires three-dimensional point cloud data 100 relating to an object to be measured (e.g., an electric wire 10, a tree 20) that has been photographed and generated by the three-dimensional sensor 300 (step A1).

Next, as preprocessing, the format conversion unit 211 of the preprocessing unit 210 of the distance measurement device 200 converts the format of the acquired 3D point cloud data 100 into a common format that can be commonly used in the distance measurement device 200 (step A2).

Next, as preprocessing, the noise removal unit 212 of the preprocessing unit 210 of the distance measurement device 200 removes noise from the point cloud in the 3D point cloud data 100 whose format has been converted by the format conversion unit 211 (step A3).

Next, the angle conversion unit 221 of the measurement unit 220 of the distance measurement device 200 converts the angle of the 3D point cloud data 100 preprocessed by the preprocessing unit 210 so that the direction of gravity is vertically downward (step A4).

Next, the object division unit 222 of the measurement unit 220 of the distance measurement device 200 divides (extracts) the angle-converted 3D point cloud data 100 into objects (step A5).

Next, the distance measurement device 200 acquires designation information relating to the object to be measured, which is designated from the object segmentation results, by the user operating the input unit 232 of the user interface unit 230 (step A6).

Next, the distance measurement unit 223 of the measurement unit 220 of the distance measurement device 200 measures the distances (the shortest distance D, the horizontal distance H, and the vertical distance V in FIG. 1) between the objects related to the acquired specification information (between the power line 10 and the tree 20 in FIG. 1) (step A7).

Next, the display unit 231 of the user interface unit 230 of the distance measurement device 200 displays the measurement results (step A8), and then the process ends.

Next, the operation of distance measurement by the distance measurement device according to the first embodiment will be described with reference to the drawings. FIG. 4 is an image diagram that shows a schematic diagram of the operation related to distance measurement by the distance measurement device according to the first embodiment.

Figure 4 shows an example of measuring the distance between objects in step A7 of Figure 3.

In distance measurement, first, the two closest points between two objects to be measured (power line 10 and tree 20 in FIG. 4) are calculated from the point clouds that make up each object. Examples of calculation methods include nearest neighbor search using KDTree (K-Dimensional Tree) and nearest neighbor decision rules.

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 Equation 1, the horizontal distance H between the two points can be expressed as Equation 2, and the vertical distance V between the two points can be expressed as Equation 3.

[Formula 1]

[Formula 2]

[Formula 3]

According to the first embodiment, even if an object has a complex shape or is located in a place where it is physically difficult to measure, measurement points are identified using nearest neighbor search or the like for the point group that constitutes the cluster of the measurement target, which can contribute to easily and accurately measuring the shortest distance, horizontal distance, vertical distance, etc. between objects.

Furthermore, according to the first embodiment, it is possible to automatically detect objects from three-dimensional point cloud data and automatically measure the shortest distance, horizontal distance, and vertical distance between specific objects. Note that Patent Document 2 describes which parts of an object should be used as measurement points for measuring the shortest distance between objects, such as the tops or branch tips of trees, and the tops or corners of structures, but does not specify a specific method for identifying the measurement points.

Furthermore, according to the first embodiment, by using the three-dimensional point cloud data 100 of the object photographed by the three-dimensional sensor 300, it is possible to measure the shortest distance between objects in a non-contact manner, thereby reducing distance measurement costs. Note that the technology described in Patent Document 1 allows for non-contact distance measurement, but requires a self-propelled vehicle to travel from one end of the overhead power line to the other in order to obtain the coordinates of the overhead power line and the target object, which increases distance measurement costs.

In addition, according to embodiment 1, the measurement process is automated, allowing even users who are unfamiliar with measurement tasks to easily perform measurements.

Furthermore, according to embodiment 1, measurements can be easily performed even in an environment where it is physically difficult to measure the shortest distance, horizontal distance, and vertical distance due to, for example, a shield placed between the power line 10 and the tree 20.

Furthermore, according to the first embodiment, since a three-dimensional sensor is used, for example, if the shape of an object is symmetrical from the front to the back, the point cloud coordinates of the rear half can be estimated from the point cloud coordinates of the front half, and the shortest distance between the estimated rear half and the overhead power line can be calculated. Note that the techniques described in Patent Documents 1 and 2 can only calculate the shortest distance within the range captured by the camera.

[Embodiment 2]
A distance measurement device according to the second embodiment will be described with reference to the drawings. Fig. 5 is a block diagram showing a schematic configuration of the distance measurement device according to the second embodiment.

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.

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 is configured to perform a process of calculating, from each point cloud of two objects among the point clouds for each object divided by the object division unit 222, two points at which the two objects are closest to each other, and a process of measuring the shortest distance, vertical distance, or horizontal distance between the two calculated points.

According to the second embodiment, even if an object has a complex shape or is located in a place where it is physically difficult to measure, measurement points are identified using nearest neighbor search or the like for the point cloud that constitutes the cluster of the measurement target, which can contribute to easily and accurately measuring the shortest distance, horizontal distance, vertical distance, etc. between objects.

The distance measurement device according to the first and second embodiments can be configured with so-called hardware resources (information processing device, computer), and a device having the configuration shown in FIG. 6 can be used. For example, the hardware resource 1000 includes a processor 1001, a memory 1002, a network interface 1003, and the like, which are interconnected by an internal bus 1004.

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 (e.g., an input/output interface) that is not shown. Furthermore, 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, and for example, multiple processors 1001 may be included in the hardware resource 1000. For example, a CPU (Central Processing Unit), an MPU (Micro Processor Unit), a GPU (Graphics Processing Unit), etc. may be used as the processor 1001.

The memory 1002 may be, for example, a random access memory (RAM), a read only memory (ROM), a hard disk drive (HDD), or a solid state drive (SSD).

The network interface 1003 may be, for example, a LAN (Local Area Network) card, a network adapter, a network interface card, etc.

The functions of the hardware resource 1000 are realized by the above-mentioned processing module. The processing module is realized, for example, by the processor 1001 executing a program stored in the memory 1002. The program can be downloaded via a network or updated using a storage medium on which the program is stored. Furthermore, the processing module may be realized by a semiconductor chip. In other words, it is sufficient that the functions performed by the processing module can be realized by the execution of software on some kind of hardware.

A part or all of the above embodiments may be described as follows, but is not limited to the following:

[Appendix 1]
An object division unit configured to perform a process of dividing the three-dimensional point cloud data into point clouds for each object;
a distance measurement unit configured to perform a process of calculating two points at which the two objects are closest to each other from each point cloud of the two objects among the point clouds for each object divided by the object division unit, and a process of measuring the shortest distance, the vertical distance, or the horizontal distance between the two calculated points;
A distance measuring device comprising:
[Appendix 2]
In the process of calculating the two points, a process of calculating the two points is performed by nearest neighbor search using a KDT tree.
2. The distance measuring device of claim 1.
[Appendix 3]
In the dividing process,
A process of dividing the points into object-specific point clouds by clustering.
A process of dividing the image into point clouds for each object using the reflection intensity of the three-dimensional sensor; and
A process of dividing the image into point clouds for each object using RGB values from a 3D sensor;
Perform one of the following processes:
3. The distance measuring device according to claim 1 or 2.
[Appendix 4]
An input unit for inputting information operated by a user is further provided,
In the process of calculating the two points,
selecting, based on designation information input to the input unit, each point group of two objects from among the point groups for each object divided by the object dividing unit;
calculating the two points from the point clouds of the two selected objects;
To carry out
4. A distance measuring device according to claim 1.
[Appendix 5]
In the process of calculating the two points,
A process of detecting point clouds of two objects corresponding to a preset detection model from among the point clouds of each object divided by the object division unit;
calculating the two points from point clouds of the two detected objects;
[0023]
4. A distance measuring device according to claim 1.
[Appendix 6]
The distance measurement unit is
A process of selecting a point cloud of one reference object from the point clouds of each object divided by the object dividing unit;
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 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;
A process of measuring any one of the shortest distance, the vertical distance, and the horizontal distance between the two points calculated;
and further configured to:
6. A distance measuring device according to claim 1 .
[Appendix 7]
The distance measurement unit is
A process of selecting a point cloud of one real object from the point clouds of each object divided by the object dividing unit;
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 at which 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, the vertical distance, and the horizontal distance between the two points calculated;
It is further configured to
7. A distance measuring device according to claim 1.
[Appendix 8]
An angle conversion unit configured to perform angle conversion on the three-dimensional point cloud data so that the direction of gravity is downward,
the object division unit is configured to perform processing using the three-dimensional point cloud data angle-converted by the angle conversion unit.
8. A distance measuring device according to claim 1 .
[Appendix 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;
calculating two points at which the two objects are closest to each other from each point cloud of the two objects among the point clouds of the divided objects;
measuring any one of the calculated shortest distance, vertical distance, and horizontal distance between the two points;
A distance measurement method comprising:
[Appendix 10]
A program for causing a hardware resource to execute a process for measuring a distance,
A process of dividing the three-dimensional point cloud data into point clouds for each object;
A process of calculating two points at which the two objects are closest to each other from each point cloud of two objects among the point clouds of each divided object;
A process of measuring any one of the shortest distance, the vertical distance, and the horizontal distance between the two points calculated;
A program for causing the hardware resource to execute the above.

The disclosures of the above patent documents are incorporated herein by reference and may be used as the basis or part of the present invention as necessary. Within the framework of the entire disclosure of the present invention (including the claims and drawings), and further based on the basic technical ideas, modifications and adjustments of the embodiments and examples are possible. Furthermore, within the framework of the entire disclosure of the present invention, various combinations or selections (or non-selection as necessary) of various disclosed elements (including each element of each claim, each element of each embodiment or example, each element of each drawing, etc.) are possible. In other words, the present invention naturally includes various modifications and corrections that a person skilled in the art would be able to make in accordance with the entire disclosure, including the claims and drawings, and the technical ideas. Furthermore, with regard to the numerical values and numerical ranges described in this application, any intermediate value, lower numerical value, and small range are considered to be described even if not specified. Furthermore, the disclosures of the above cited documents may be used in part or in whole in combination with the descriptions in this document as part of the disclosure of the present invention as necessary, in accordance with the spirit of the present invention, and are considered to be included (belong) to the disclosures of this application.

REFERENCE SIGNS LIST 10 Power wire 20 Tree 30 Ground 40, 41 Utility pole 100 3D 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 (11)

An object division unit configured to perform a process of dividing the three-dimensional point cloud data into point clouds for each object;
a distance measurement unit configured to perform a process of calculating two points at which the two objects are closest to each other from each point cloud of the two objects among the point clouds for each object divided by the object division unit, and a process of measuring the shortest distance, the vertical distance, or the horizontal distance between the two calculated points;
Equipped with
In the process of calculating the two points,
A process of detecting point clouds of two objects corresponding to a preset detection model from among the point clouds of each object divided by the object division unit;
calculating the two points from point clouds of the two detected objects;
A distance measurement device configured to perform the following : An object division unit configured to perform a process of dividing the three-dimensional point cloud data into point clouds for each object;
a distance measurement unit configured to perform a process of calculating two points at which the two objects are closest to each other from each point cloud of the two objects among the point clouds for each object divided by the object division unit, and a process of measuring the shortest distance, the vertical distance, or the horizontal distance between the two calculated points;
Equipped with
The distance measurement unit is
A process of selecting a point cloud of one reference object from the point clouds of each object divided by the object dividing unit;
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 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;
A process of measuring any one of the shortest distance, the vertical distance, and the horizontal distance between the two points calculated;
The distance measurement device is further configured to perform the following : An object division unit configured to perform a process of dividing the three-dimensional point cloud data into point clouds for each object;
a distance measurement unit configured to perform a process of calculating two points at which the two objects are closest to each other from each point cloud of the two objects among the point clouds for each object divided by the object division unit, and a process of measuring the shortest distance, the vertical distance, or the horizontal distance between the two calculated points;
Equipped with
The distance measurement unit is
A process of selecting a point cloud of one real object from the point clouds of each object divided by the object dividing unit;
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 at which 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, the vertical distance, and the horizontal distance between the two points calculated;
The distance measurement device is further configured to : In the process of calculating the two points, a process of calculating the two points is performed by nearest neighbor search using a KDT tree.
4. A distance measuring device according to claim 1. In the dividing process,
A process of dividing the points into object-specific point clouds by clustering.
A process of dividing the image into point clouds for each object using the reflection intensity of the three-dimensional sensor; and
A process of dividing the image into point clouds for each object using RGB values from a 3D sensor;
Perform one of the following processes:
5. A distance measuring device according to claim 1. An input unit for inputting information operated by a user is further provided,
In the process of calculating the two points,
selecting, based on designation information input to the input unit, each point group of two objects from among the point groups for each object divided by the object dividing unit;
calculating the two points from point clouds of the two selected objects;
To carry out
6. A distance measuring device according to claim 1. An angle conversion unit configured to perform angle conversion on the three-dimensional point cloud data so that the direction of gravity is downward,
the object division unit is configured to perform processing using the three-dimensional point cloud data angle-converted by the angle conversion unit.
7. A distance measuring device according to claim 1. 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;
calculating two points at which the two objects are closest to each other from each point cloud of the two objects among the point clouds of the divided objects;
measuring any one of the calculated shortest distance, vertical distance, and horizontal distance between the two points ;
The step of calculating the two points includes:
detecting point clouds of two objects corresponding to a preset detection model from among the point clouds of each divided object;
calculating the two points from each point cloud of the two detected objects . 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;
calculating two points at which the two objects are closest to each other from each point cloud of the two objects among the point clouds of the divided objects;
measuring any one of the calculated shortest distance, vertical distance, and horizontal distance between the two points;
selecting a point cloud of one reference object from the point clouds of each divided object;
A step of extracting a point cloud of an obstacle object existing within a predetermined distance from the point cloud of the selected reference object;
calculating 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 measuring any one of the calculated shortest distance, vertical distance, and horizontal distance between the two points . 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;
calculating two points at which the two objects are closest to each other from each point cloud of the two objects among the point clouds of the divided objects;
measuring any one of the calculated shortest distance, vertical distance, and horizontal distance between the two points;
selecting a point cloud of one real object from the point clouds of each divided object;
generating a point cloud of a virtual object in the three-dimensional point cloud data including a point cloud of the real object;
calculating, from each point cloud of the real object and the virtual object, two points at which the real object and the virtual object are closest to each other;
and measuring any one of the calculated shortest distance, vertical distance, and horizontal distance between the two points . A program for causing hardware resources to execute the distance calculation method according to any one of claims 8 to 10 .

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