Separation determination device, separation determination system, separation determination method, and program

Abstract

To provide a separation determination device, separation determination system, separation determination method, and program capable of performing separation determination over a wide range with high accuracy in a shorter time.SOLUTION: A separation determination device 30 that determines separation between an infrastructure IN and a separation target object O, comprises: a measurement information acquisition unit 311 that acquires a plurality of pieces of image data obtained by measurement of a mobile mapping system 10 and three-dimensional point cloud data associated with the plurality of pieces of image data; a determination image identification unit 313 that identifies, from among the plurality of pieces of image data, determination image data including the infrastructure IN and the separation target object O; and a separation determination unit 316 that determines the separation between the infrastructure IN and the separation target object O on the basis of the determination image data identified by the determination image identification unit 313 and the three-dimensional point cloud data associated with the determination image data.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a distance determination device, a distance determination system, a distance determination method, and a program. [Background technology]

[0002] Conventionally, there is known a technique for determining the distance between infrastructure such as utility poles and power lines and surrounding trees and the like, based on three-dimensional position information obtained by measuring the periphery of the infrastructure using a laser scan or the like. Patent Document 1 is an example of this type of technique. Patent Document 1 describes that model data of the equipment, such as utility poles, is generated based on point cloud data (three-dimensional position information) of the equipment obtained by laser scanning, the distance between the utility poles and the trees is calculated based on this model data, and the calculated distance is superimposed on 3D superimposed image data, making it possible to determine whether the distance between the utility poles and the trees is appropriate. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-195240 Summary of the Invention [Problem to be solved by the invention]

[0004] When distance determination based on three-dimensional position information is performed with higher accuracy and over a wider area, more position information is required for information processing, which poses the problem of longer time required for information processing.

[0005] The present invention aims to provide a distance determination device, a distance determination system, a distance determination method, and a program that can perform distance determination with higher accuracy and over a wider area in a shorter time. [Means for solving the problem]

[0006] (1) The distance determination device of the present invention is a distance determination device that determines the distance between infrastructure and a distant object, and includes a measurement information acquisition unit that acquires multiple image data and three-dimensional point cloud data associated with the multiple image data obtained by measurement of a mobile mapping system, a determination image discrimination unit that discriminates determination image data that includes the infrastructure and the distant object from the multiple image data, and a distance determination unit that determines the distance between the infrastructure and the distant object based on the determination image data discriminated by the determination image discrimination unit and the three-dimensional point cloud data associated with the determination image data.

[0007] The distance determination device (1) can perform distance determination with higher accuracy and over a wider area in a shorter time.

[0008] (2) In the distance determination device described in (1), the infrastructure includes overhead lines for power transmission and utility poles supporting the overhead lines.

[0009] The distance determination device (2) can perform distance determination over a wide area with high accuracy in a short time for overhead wires and utility poles that are placed over a wide area.

[0010] (3) The distance determination device described in (2) further includes an infrastructure candidate point identification unit that identifies utility pole candidate points, which are candidates for points indicating a part of the utility pole, and overhead line candidate points, which are candidates for points indicating a part of the overhead line, in three-dimensional point cloud data, and a virtual overhead line generation unit that extracts an approximate curve passing through three of the overhead line candidate points as a virtual overhead line, and the distance determination unit performs distance determination based on the virtual overhead line and the three-dimensional point cloud data associated with determination image data excluding the overhead line candidate points and the utility pole candidate points.

[0011] The distance determination device (3) can perform distance determination with higher accuracy and over a wider area in a shorter time through simpler information processing.

[0012] (4) The distance determination device described in (1) or (2) further includes a 3D model generation unit that generates a 3D model based on the determination image data determined by the determination image discrimination unit and the 3D point cloud data associated with the determination image data, and the distance determination unit performs distance determination based on the 3D model generated by the 3D model generation unit.

[0013] The distance determination device (4) can perform distance determination with higher accuracy and over a wider area in a shorter time through simpler information processing.

[0014] (5) In the distance determination device described in any one of (1) to (4), the distance determination unit determines the distance between the infrastructure and the distant object based on the three-dimensional point cloud data associated with the determination image data, with points excluding the infrastructure being points of the distant object.

[0015] The distance determination device (5) can perform distance determination with higher accuracy and over a wider area in a shorter time through simpler information processing.

[0016] (6) The distance determination device described in (3) further includes a distance calculation unit that calculates the distance between the virtual overhead line and the distant object based on the virtual overhead line and the three-dimensional point cloud data associated with the determination image data excluding the overhead line candidate points and the utility pole candidate points, and the distance determination unit determines that there is no distance when the distance is less than a predetermined distance.

[0017] The distance determination device (6) can perform distance determination with higher accuracy and over a wider area in a shorter time through simpler information processing.

[0018] (7) The distance determination device described in (3) further includes a distance determination area setting unit that sets an area within a predetermined range from the virtual overhead line as a distance determination area, and the distance determination unit determines that the object is not distant if there is a point in the three-dimensional point cloud data that indicates part of the distant object in the distance determination area, and determines that the object is distant if there is no point in the three-dimensional point cloud data that indicates part of the distant object in the distance determination area.

[0019] The distance determination device (7) can perform distance determination with higher accuracy and over a wider area in a shorter time through simpler information processing.

[0020] (8) The distance determination device described in (4) further includes a distance calculation unit that calculates the distance between the infrastructure and the distant object based on the 3D model, and the distance determination unit determines that there is no distance if the distance is less than a predetermined distance.

[0021] The distance determination device (8) can perform distance determination with higher accuracy and over a wider area in a shorter time through simpler information processing.

[0022] (9) The distance determination device described in (4) further includes a distance determination area setting unit that sets an area within a predetermined range from the infrastructure as a distance determination area in the 3D model, and the distance determination unit determines that the object is not distant if the distant object is present in the distance determination area in the 3D model, and determines that the object is distant if the distant object is not present in the distance determination area.

[0023] The distance determination device (9) can perform distance determination with higher accuracy and over a wider range in a shorter time by using simpler information processing.

[0024] (10) The distance determination system of the present invention comprises the distance determination device described in (1) and a mobile mapping system that acquires image data and three-dimensional point cloud data around the road using a measurement unit mounted on a measurement vehicle traveling on the road.

[0025] The distance determination system (10) can perform distance determination more efficiently, in a shorter time, with higher accuracy, and over a wider area.

[0026] (11) The distance determination method of the present invention is a distance determination method executed by a distance determination device that determines the distance between infrastructure and a distant object, and includes a measurement information acquisition process that acquires multiple image data and three-dimensional point cloud data associated with the multiple image data obtained by measurement of a mobile mapping system, a determination image discrimination process that discriminates determination image data that includes the infrastructure and the distant object from the multiple image data, and a distance determination process that determines the distance between the infrastructure and the distant object based on the determination image data discriminated in the determination image discrimination process and the three-dimensional point cloud data associated with the determination image data.

[0027] The distance determination method (11) can perform distance determination with higher accuracy and over a wider range in a shorter time.

[0028] (12) The program of the present invention causes a processor of a distance determination device that determines the distance between infrastructure and a distant object to execute a measurement information acquisition function that acquires multiple image data and three-dimensional point cloud data associated with the multiple image data obtained by measurement with a mobile mapping system, a determination image discrimination function that discriminates determination image data that includes the infrastructure and the distant object from the multiple image data, and a distance determination function that determines the distance between the infrastructure and the distant object based on the determination image data discriminated by the determination image discrimination function and the three-dimensional point cloud data associated with the determination image data.

[0029] The program (12) can perform distance determination in a shorter time, with higher accuracy and over a wider area. [Brief explanation of the drawings]

[0030] [Figure 1] 1 is a schematic diagram showing a schematic configuration of a distance determination system according to a first embodiment. [Figure 2] 1 is a block diagram showing a hardware configuration of a distance determination device according to a first embodiment. [Figure 3] 1 is a block diagram for explaining the functional configuration of a distance determination device according to a first embodiment. [Figure 4] FIG. 2 is a schematic diagram for explaining generation of virtual overhead lines in the first embodiment. [Figure 5] 4 is a flowchart illustrating the flow of a distance determination method according to the first embodiment. [Figure 6] FIG. 10 is a block diagram for explaining the functional configuration of a distance determination device according to a second embodiment. [Figure 7] 10 is a flowchart illustrating the flow of a distance determination method according to the second embodiment. [Figure 8] FIG. 10 is a block diagram for explaining the functional configuration of a distance determination device according to a third embodiment. [Figure 9] 10 is a flowchart illustrating the flow of a distance determination method according to the third embodiment. [Figure 10] FIG. 10 is a block diagram for explaining the functional configuration of a distance determination device according to a fourth embodiment. [Figure 11] 10 is a flowchart illustrating the flow of a distance determination method according to a fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0031] First Embodiment A distance determination system S according to the first embodiment will be described below with reference to Fig. 1. As shown in Fig. 1, the distance determination system S according to this embodiment is a system that uses a mobile mapping system 10 and performs distance determination between infrastructure IN and a distant object O using a distance determination device 30. The distance determination is to determine whether a predetermined distance D is maintained between the infrastructure and the distant object.

[0032] The infrastructure is, for example, infrastructure such as power transmission and distribution facilities, and FIG. 1 shows overhead wires OW, which are power distribution lines, and utility poles UP as examples of infrastructure IN. Therefore, infrastructure IN includes overhead wires for power transmission and utility poles that support the overhead wires. Note that the overhead wires OW are not limited to power distribution lines, but may also be communication lines, etc. Infrastructure IN as power transmission and distribution facilities is not limited to this and includes, for example, power transmission lines and steel towers. Also, infrastructure IN is not limited to power transmission and distribution facilities. Remote objects O include artificial structures such as private homes and obstacles such as trees. FIG. 1 shows a tree T as an example of a remote object. Remote objects are not limited to this. Note that supports such as guy wires that support utility poles UP are not included in remote objects O.

[0033] In this embodiment, in the case of power transmission and distribution equipment as infrastructure, it is necessary to maintain a predetermined distance between the power transmission and distribution equipment such as overhead lines and utility poles and the objects to be isolated, so as not to cause damage to private houses, trees, etc., as objects to be isolated by the cutting of overhead lines, etc. or the collapse of utility poles, etc., and a separation determination is performed to determine whether the separation distance D is maintained at the predetermined distance.

[0034] As shown in Figure 1, the distance determination system S includes a mobile mapping system 10 that acquires image data and three-dimensional point cloud data of the area around the road using a measurement device 10a mounted on a measurement vehicle 10b (described below) that travels on the road, a server 20, and a distance determination device 30.

[0035] The mobile mapping system 10, the server 20, and the distance determination device 30 are connected to each other so that they can communicate with each other via a network N. The network N is, for example, the Internet, a LAN (Local Area Network), a mobile phone network, or a combination of these.

[0036] <Mobile Mapping System> As shown in Figure 1, the mobile mapping system 10 includes a measurement device 10a and a measurement vehicle 10b equipped with the measurement device 10a. The mobile mapping system 10 is a measurement system that efficiently acquires three-dimensional information about a road and its surroundings using the measurement device 10a while moving using the measurement vehicle 10b. The three-dimensional information is, for example, three-dimensional point cloud data. The three-dimensional point cloud data is a collection of points having three-dimensional coordinates that indicate the measured road and a portion of the road's surroundings.

[0037] The measurement device 10a includes, for example, a measurement control device, a GNSS (Global Navigation Satellite System) device, an IMU (Inertial Measurement Unit) device, multiple image capture devices, multiple laser scanners, and a communication device, all of which are not shown. The measurement vehicle 10b includes, for example, an odometer.

[0038] The measurement control device controls various devices in the mobile mapping system 10. The GNSS device has one or more antennas and is a device that acquires position information of the measurement device 10a based on information transmitted from GNSS satellites. The GNSS device may be a so-called RTK (Real Time Kinematic)-GNSS that corrects errors contained in observations using real-time observation data from electronic reference points, etc. The GNSS device may also acquire position information using network-type RTK. With this configuration, the separation determination system S can perform separation determination with higher accuracy.

[0039] The IMU device has a three-axis gyro sensor and a three-directional acceleration sensor, and is a device that detects the attitude, orientation, movement trajectory, etc. of the measurement device 10a by detecting the three-axis angular velocity and acceleration of the measurement device 10a. The imaging device has a plurality of digital cameras, etc. The plurality of digital cameras are preferably high-precision omnidirectional cameras. The image data of the digital cameras according to this embodiment is high-definition image data equivalent to 5K with, for example, 24.5 million pixels.

[0040] The imaging device may have, for example, a digital camera that captures images in front of the measurement vehicle 10b, a digital camera that captures images to the side of the measurement vehicle 10b, and a digital camera that captures images behind the measurement vehicle 10b. By adjusting the imaging frequency and the traveling speed of the measurement vehicle 10b, the mobile mapping system 10 according to this embodiment can capture images of each overhead wire OW, utility pole UP, and distant object O from three directions using the three digital cameras. Depending on the imaging direction, some objects may be hidden by other objects. However, in this embodiment, images are captured from three directions, so it is possible to more reliably capture images in which no object is hidden by other objects. Note that the number and arrangement of cameras in the imaging device are not limited to this.

[0041] A laser scanner is an optical distance meter, also known as a laser range scanner. A laser scanner acquires relative distance and direction information from an object. A laser scanner that is highly sensitive and capable of measuring over a wide range is particularly called a LIDAR (Light Detection and Ranging). The communication device is a device for communicating with the server 20 via the network N, for example.

[0042] During measurement using the mobile mapping system 10, the laser scanner according to this embodiment acquires 3D point cloud data of the road and its surroundings while the measurement vehicle is traveling. Furthermore, during measurement using the mobile mapping system 10, the imaging device according to this embodiment is controlled by the measurement control device to capture an image every 2 meters that the measurement vehicle 10b travels. The timing of capturing images by the imaging device is not limited to this.

[0043] During measurement, the mobile mapping system 10 acquires absolute coordinate information including the latitude, longitude, and altitude of the laser scanner using a GNSS device, an IMU device, and an odometer, and acquires the absolute coordinates of the object measured by the laser scanner based on the absolute coordinate information and attitude information.

[0044] The measurement control device associates image data captured by the imaging device with the 3D point cloud data obtained by the laser scanner when the image data was captured, based on position information from the GNSS unit, IMU device, and odometer at the time of measurement.

[0045] For example, a portion of a utility pole UP shown in an image is associated with a point in the 3D point cloud data that indicates the portion of the utility pole UP shown in the image. Also, a portion of an overhead wire OW shown in an image is associated with a point in the 3D point cloud data that indicates the portion of the overhead wire OW shown in the image. Also, a portion of a remote object O shown in an image is associated with a point in the 3D point cloud data that indicates the portion of the remote object O shown in the image.

[0046] Therefore, for example, when a utility pole UP, overhead wire OW, distant object O, etc. appearing in an image are identified using image recognition, it is possible to identify whether each individual point in the 3D point cloud data associated with the image data is a point of the utility pole UP, overhead wire OW, distant object O, etc.

[0047] The communication device transmits the image information and the three-dimensional point cloud data associated with the image information as measurement information to the server 20 via the network N. Note that the configuration of the mobile mapping system 10 described above is an example of a mobile mapping system, and is not limited to this.

[0048] <server> The server 20 is an information processing device that mainly stores measurement information measured by the mobile mapping system 10. The server 20 has a server control unit (not shown), a server storage device (not shown), and a server communication unit (not shown). The server control unit controls various operations of the server 20. The server storage device is composed of a hard disk drive (HDD), a solid state drive (SSD), etc., and stores various information such as programs and setting values ​​related to various processes, measurement information measured by the mobile mapping system 10 described above, and infrastructure layout information. The server communication unit is a device that communicates with the mobile mapping system 10 and the distance determination device 30 via the network N.

[0049] In this embodiment, the server 20 stores and manages measurement information from the mobile mapping system 10, but the measurement information from the mobile mapping system 10 may be stored and managed by the mobile mapping system 10, or may be stored and managed by the distance determination device 30.

[0050] <Separation determination device> The distance determination device 30 is an information processing device for determining the distance between the infrastructure IN and the distant object O based on multiple image data and the three-dimensional point cloud data associated with the image data acquired by the mobile mapping system 10. The distance determination device 30 may be an information processing device such as a laptop computer, a desktop computer, or a tablet terminal.

[0051] An example of the hardware configuration of the distance determination device 30 will be described with reference to Fig. 2. As shown in Fig. 2, the distance determination device 30 includes a processor 300, a ROM (Read Only Memory) 301, a RAM (Random Access Memory) 302, a bus 303, an input / output interface 304, an input unit 305, an output unit 306, an auxiliary storage device 307, a communication unit 308, and a power supply 309.

[0052] The processor 300 is the central part of a computer that performs various calculations, controls, and other processes required for the operation of the distance determination device 30. The processor 300 is, for example, a central processing unit (CPU), a micro processing unit (MPU), a system on a chip (SoC), a digital signal processor (DSP), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field-programmable gate array (FPGA). Alternatively, the processor 300 may be a combination of two or more of these. The processor 300 may also be a combination of these with a hardware accelerator or the like.

[0053] The processor 300 controls each unit to realize various functions of the distance determination device 30 based on programs such as firmware, system software, and application software stored in the ROM 301 or RAM 302. The processor 300 executes processing based on the programs. Note that part or all of the programs may be incorporated into the circuitry of the processor 300.

[0054] The processor 300, ROM 301, and RAM 302 are connected to one another via a bus 303. An input / output interface 304 is also connected to this bus 303. An input unit 305, an output unit 306, an auxiliary storage device 307, a communication unit 308, and a power supply 309 are connected to the input / output interface 304.

[0055] The input unit 305 and output unit 306 are user interfaces electrically connected to the input / output interface 304 via wire or wirelessly. The input unit 305 is composed of, for example, a keyboard, a mouse, etc., and inputs various information in response to user instructions. The output unit 306 is composed of, for example, a display for displaying images and a speaker for amplifying audio, and outputs images and audio.

[0056] The auxiliary storage device 307 is configured with a hard disk drive (HDD), a solid state drive (SSD), etc. The auxiliary storage device 307 stores various information such as programs related to various processes and setting values. The auxiliary storage device 307 stores, for example, various information such as a reference value for determining distance, programs, etc.

[0057] The communication unit 308 is a device that allows the processor 300 to communicate with other devices, such as the server 20, via the network N. The communication unit 308 may also be able to communicate with the mobile mapping system 10 via the network N.

[0058] The power supply 309 has a battery and is configured to be able to supply power to each part of the distance determination device 30. Note that the configuration capable of supplying power to the power supply is not limited to this, and may be, for example, a battery that is connected to an external power supply and can supply power to the distance determination device 30.

[0059] Next, the functional configuration of the distance determination device 30 will be described with reference to Fig. 3. The control unit 310, which is a functional configuration of the distance determination device 30 that executes various controls of the distance determination device 30, is realized by the processor 300 that executes arithmetic processing by executing programs stored in the ROM 301, RAM 302, auxiliary storage device 307, etc.

[0060] As shown in Figure 3, the control unit 310 of this embodiment has a measurement information acquisition unit (measurement information acquisition function) 311, an infrastructure candidate point identification unit (infrastructure candidate point identification function) 312, a judgment image discrimination unit (judgment image discrimination function) 313, a virtual overhead line generation unit (virtual overhead line generation function) 314, a distance calculation unit (distance calculation function) 315, and a distance judgment unit (distance judgment function) 316.

[0061] The measurement information acquisition unit 311 acquires multiple image data and three-dimensional point cloud data associated with the multiple image data obtained by measurements of the mobile mapping system 10, which are transmitted from the server 20 via the communication unit 308.

[0062] The infrastructure candidate point identifying unit 312 checks whether there is an infrastructure candidate point indicating infrastructure IN in the three-dimensional point cloud data. The infrastructure candidate point identifying unit 312 according to this embodiment identifies utility pole candidate points UPP, which are candidates for points indicating parts of utility poles UP, and overhead line candidate points MP, which are candidates for points indicating parts of overhead lines OW, in the three-dimensional point cloud data. The infrastructure candidate point identifying unit 312 performs image recognition processing using a learning model based on machine learning, which will be described later, to recognize utility poles and overhead lines in the image data. Next, in the three-dimensional point cloud data associated with the image data, points corresponding to images recognized as utility poles UP and overhead lines OW in the image are identified as utility pole candidate points UPP and overhead line candidate points MP, respectively.

[0063] In addition, as the image recognition process, for example, a plurality of image data are used as input data, and utility poles UP and overhead wires OW in determination image data corresponding to the plurality of image data are used as labels, and supervised learning is performed using the pair of the input data and the labels as training data, thereby performing machine learning in advance to construct a learning model for discriminating determination image data from the plurality of image data that are input data, and image recognition is performed using the learning model. At this time, images that include at least the overhead wires OW and utility poles UP are used as determination image data for machine learning.

[0064] The determination image discrimination unit 313 discriminates, from among the plurality of image data, determination image data that includes the infrastructure IN and the distant object O. The determination image discrimination unit 313 according to this embodiment discriminates determination image data that includes the overhead wires OW as the infrastructure IN and the distant object O. Specifically, the determination image discrimination unit 313 performs image recognition processing on the plurality of image data using the learning model based on the above-mentioned machine learning, and identifies an image that includes the overhead wires OW and the distant object O as determination image data.

[0065] Furthermore, the determination image discrimination unit 313 may check whether the distance between the overhead wire OW and the distant object O in the image is equal to or greater than a predetermined distance, and exclude images in which the distance is equal to or greater than the predetermined distance. Further selecting determination images in this manner can further reduce the time required for the distance determination process, enabling distance determination to be performed more quickly, with higher accuracy, and over a wider area. The distance on an image can be calculated from the number of pixels. Although the distance per pixel differs for each image, the distance per pixel can be calculated from the associated 3D point cloud data.

[0066] The virtual overhead line generator 314 extracts and generates, as a virtual overhead line EL, an approximation curve passing through three points SP among the overhead line candidate points MP identified by the infrastructure candidate point identifier 312. If the distance determination were performed using the 3D point cloud data alone, it would be necessary to calculate the distance for every combination between each point included in the 3D point cloud data of the overhead line OW and each point included in the 3D point cloud data of the distant object O, and then compare the respective calculation results to calculate the shortest distance, resulting in a large number of combinations. This results in a large number of calculations and a long time required for the calculation of the shortest distance in the distance determination. However, by using the virtual overhead line EL for the distance determination, it is only necessary to calculate the shortest distance between the virtual overhead line EL and each point included in the 3D point cloud data of the distant object O, thereby reducing the number of calculations. Therefore, by generating the virtual overhead line EL, it is possible to reduce the time required for the calculation of the shortest distance in the distance determination.

[0067] The distance calculation unit 315 calculates the separation distance D between the virtual overhead line EL and the distant object O based on the virtual overhead line EL and points in the three-dimensional point cloud data that indicate the distant object O. In this embodiment, the three-dimensional point cloud data associated with the determination image data excluding the overhead line candidate points MP and the utility pole candidate points UPP is used as the points that indicate the distant object O.

[0068] Note that, in addition to the overhead line candidate points MP and the utility pole candidate points UPP, 3D point cloud data associated with the determination image data excluding infrastructure supports such as utility pole guy wires may also be used as points indicating the distant object O. In other words, infrastructure supports such as utility pole guy wires may not be included in the distant object O. In this case, for example, the supports are detected by image recognition based on a learning model using machine learning, and are not included in the distant object O.

[0069] Therefore, the distance calculation unit 315 in this embodiment calculates the separation distance D between the virtual overhead line EL and the distant object O based on the virtual overhead line EL and the three-dimensional point cloud data associated with the determination image data excluding the overhead line candidate points MP and the utility pole candidate points UPP.

[0070] The distance determination unit 316 determines the distance between the infrastructure IN and the distant object O based on the determination image data determined by the determination image discrimination unit 313 and the three-dimensional point cloud data associated with the determination image data. In this embodiment, the distance determination unit 316 performs the distance determination based on the virtual overhead wire EL and the three-dimensional point cloud data associated with the determination image data excluding the overhead wire candidate points MP and the utility pole candidate points UPP.

[0071] The distance determination unit 316 determines the distance between the overhead wire OW and the distant object O based on the three-dimensional point cloud data associated with the determination image data, with points excluding the overhead wire OW and the utility pole UP being points of the distant object O. The distance determination unit 316 according to this embodiment determines that the overhead wire OW and the distant object O are not separated when the separation distance D calculated by the separation calculation unit 315 is equal to or less than a predetermined distance, and determines that the overhead wire OW and the distant object O are separated when the separation distance D calculated by the separation calculation unit 315 exceeds the predetermined distance. The predetermined distance is set to, for example, 1.2 m. However, the predetermined distance is not limited to this.

[0072] <Separation determination method> Next, a distance determination method according to this embodiment, which uses a distance determination device 30 to determine the distance between the infrastructure IN and a distant object O, will be described with reference to Fig. 6. The distance determination method includes a measurement information acquisition step (step S10), a determination image discrimination step (step S12), and a distance determination step (step S15). The distance determination method may also include an infrastructure candidate point identification step (step S11), a virtual overhead line generation step (step S13), and a distance calculation step (step S14).

[0073] The distance determination method according to this embodiment includes a measurement information acquisition process (step S10), an infrastructure candidate point identification process (step S11), a determination image discrimination process (step S12), a virtual overhead line generation process (step S13), a distance calculation process (step S14), and a distance determination process (step S15).

[0074] The measurement information acquisition step (step S10) is a step of acquiring a plurality of image data acquired by measurement using the mobile mapping system 10 and three-dimensional point cloud data associated with the plurality of image data.

[0075] The infrastructure candidate point identification process (step S11) is a process in which the infrastructure candidate point identification unit 312 of the distance determination device 30 identifies utility pole candidate points UPP, which are candidates for points indicating part of the utility pole UP, and overhead line candidate points MP, which are candidates for points indicating part of the overhead line OW, in the three-dimensional point cloud data.

[0076] The determination image discrimination step (step S12) is a step in which the determination image discrimination unit 313 of the distance determination device 30 discriminates the determination image data that includes the infrastructure IN and the distant object O from among the plurality of image data.

[0077] The virtual overhead line generation process (step S13) is a process in which the virtual overhead line generation unit 314 of the distance determination device 30 extracts, as a virtual overhead line EL, an approximate curve passing through three of the overhead line candidate points MP identified by the infrastructure candidate point identification unit 312 in the infrastructure candidate point identification process (step S11).

[0078] The distance calculation process (step S14) is a process in which the distance calculation unit 315 of the distance determination device 30 calculates the distance D between the virtual overhead line EL and the distant object O based on the virtual overhead line EL and the three-dimensional point cloud data associated with the determination image data excluding the overhead line candidate points MP and the utility pole candidate points UPP.

[0079] The distance determination process (step S15) is a process of determining the distance between the infrastructure IN and the distant object O based on the determination image data determined by the determination image determination unit 313 of the distance determination device 30 in the determination image determination process (step S12) and the three-dimensional point cloud data associated with the determination image data.

[0080] The distance determination device 30 according to the present embodiment described above provides the following advantages. Conventionally, workers have traveled to the site to perform so-called distance determination, determining whether a sufficient distance is maintained between power transmission infrastructure such as utility poles and power lines and surrounding objects such as trees. Because power transmission infrastructure such as utility poles and power lines are installed in large numbers over a vast area, conventional distance determination work, which requires direct travel to the site, requires a huge amount of manpower, cost, and time.

[0081] Therefore, distance determination between infrastructure such as utility poles and power lines and surrounding trees and the like has been performed based on three-dimensional position information obtained by measuring the periphery of the infrastructure using laser scanning or the like. However, when performing distance determination based on three-dimensional position information with higher accuracy and over a wider area, there is a problem that more position information is required for information processing, and the more position information is required, the longer the time required for information processing. According to a distance determination device 30 according to one embodiment of the present invention, distance determination can be performed with higher accuracy and over a wider area in a shorter time.

[0082] <Second embodiment> The distance determination device 30 according to the above embodiment uses a virtual overhead line EL to calculate the separation distance D used for the separation determination, but this is not limited to this. For example, a 3D model may be generated based on three-dimensional point cloud data, and the separation distance D between the infrastructure IN and the separated object O may be calculated on the 3D model to perform the separation determination. Configurations similar to those in the above embodiment may be assigned the same reference numerals and descriptions thereof may be omitted.

[0083] The functional configuration of the distance determination device 30 according to the second embodiment will be described with reference to FIG.

[0084] As shown in FIG. 6, the control unit 310 of this embodiment has a measurement information acquisition unit (measurement information acquisition function) 311, an infrastructure candidate point identification unit (infrastructure candidate point identification function) 312, a judgment image discrimination unit (judgment image discrimination function) 313, a 3D model generation unit (3D model generation function) 314B, a distance calculation unit (distant calculation function) 315, and a distance judgment unit (distant judgment function) 316.

[0085] The 3D model generation unit 314B generates a 3D model based on the determination image data identified by the determination image discrimination unit 313 and the 3D point cloud data associated with the determination image data. For example, the 3D model generation unit 314B generates mesh data or the like by connecting individual points in the 3D point cloud data, thereby generating a 3D model. Mesh data is also referred to as polygon data. The 3D model generation unit 314B may also generate surface data or the like based on the 3D point cloud data. Surface data is also referred to as geometry data. The 3D model generated by the 3D model generation unit 314B can be manipulated on software such as CAD.

[0086] As described above, if the distance determination is performed using the 3D point cloud data as is, it is necessary to calculate the distance for every combination between each point included in the 3D point cloud data of the overhead wire OW and each point included in the 3D point cloud data of the distant object O, and then compare each calculation result to calculate the shortest distance, which results in a large number of combinations. This results in a large number of calculations, and a long time required for the process of calculating the shortest distance in the distance determination. However, by using a 3D model for the distance determination, it is possible to calculate the shortest distance between the overhead wire OW and the distant object O, for example, on the 3D model, thereby reducing the number of calculations. Therefore, by generating a 3D model, it is possible to reduce the time required for the process of calculating the shortest distance in the distance determination.

[0087] The distance calculation unit 315 calculates the distance D between the infrastructure IN and the separated object O based on the 3D model.

[0088] <Separation determination method> Next, a distance determination method using the distance determination device 30 according to this embodiment will be described with reference to Fig. 7. The distance determination method includes a measurement information acquisition step (step S10), a determination image discrimination step (step S12), and a distance determination step (step S15). The distance determination method may also include an infrastructure candidate point identification step (step S11), a 3D model generation step (step S13B), and a distance calculation step (step S14).

[0089] The distance determination method according to this embodiment includes a measurement information acquisition process (step S10), an infrastructure candidate point identification process (step S11), a determination image discrimination process (step S12), a 3D model generation process (step S13B), a distance calculation process (step S14), and a distance determination process (step S15).

[0090] The 3D model generation process (step S13B) is a process in which the 3D model generation unit 314B of the distance determination device 30 generates a 3D model based on the determination image data discriminated by the determination image discrimination unit 313 and the 3D point cloud data associated with the determination image data.

[0091] The distance calculation step (step S14) is a step in which the distance calculation unit 315 of the distance determination device 30 calculates the distance D between the infrastructure IN and the separated object O based on the 3D model.

[0092] The above-described distance determination device 30 according to the second embodiment can also achieve the effects of the present disclosure. Furthermore, since it is only necessary to calculate the shortest distance between the overhead wire OW and the distant object O on the 3D model, the number of calculations can be reduced, and therefore the time required for the calculation process of the shortest distance in distance determination can be reduced.

[0093] <Third embodiment> The distance determination device 30 according to the above-described embodiment performs the distance determination by comparing the calculated distance D with a predetermined distance, but this is not limited to this. For example, an area within a predetermined range from the generated virtual overhead line may be set as the distance determination area, and the distance determination may be performed based on whether or not 3D point cloud data other than infrastructure IN, such as the virtual overhead line and utility poles, is present in the distance determination area. The same components as those in the above-described embodiment may be assigned the same reference numerals, and descriptions thereof may be omitted.

[0094] The functional configuration of a distance determination device 30 according to the third embodiment will be described with reference to FIG.

[0095] As shown in Figure 8, the control unit 310 of this embodiment has a measurement information acquisition unit (measurement information acquisition function) 311, an infrastructure candidate point identification unit (infrastructure candidate point identification function) 312, a judgment image discrimination unit (judgment image discrimination function) 313, a virtual overhead line generation unit (virtual overhead line generation function) 314, a distance judgment area setting unit (distance judgment area setting function) 315B, and a distance judgment unit (distance judgment function) 316.

[0096] The distance determination area setting unit 315B sets an area within a predetermined range from the virtual overhead line EL as the distance determination area. The predetermined range is, for example, an area at a predetermined distance from the virtual overhead line EL. For example, in the case where the virtual overhead line EL is the example of FIG. 4, the distance determination area setting unit 315B sets an area with a circular cross section extending along the virtual overhead line EL and having a diameter of a predetermined distance centered on the virtual overhead line EL as the distance determination area.

[0097] As described above, when performing distance determination using 3D point cloud data as is, it is necessary to calculate distances for all combinations between each point included in the 3D point cloud data of the overhead wire OW and each point included in the 3D point cloud data of the distant object O, and then compare the respective calculation results to calculate the shortest distance, resulting in a large number of combinations. This results in a large number of calculations, and a long time required for the calculation of the shortest distance in the distance determination. However, as in the present embodiment, it is only necessary to determine whether or not a point representing part of the distant object O in the 3D point cloud data exists in the distance determination region, thereby reducing the number of calculations. Therefore, by setting a distance determination region, the time required for the calculation of the shortest distance in the distance determination can be reduced.

[0098] The distance determination unit 316 determines that the object is not distant if a point representing part of the distant object O in the three-dimensional point cloud data exists in the distance determination area set by the distance determination area setting unit 315B, and determines that the object is distant if a point representing part of the distant object O in the three-dimensional point cloud data does not exist in the distance determination area.

[0099] <Separation determination method> Next, a distance determination method using the distance determination device 30 according to this embodiment will be described with reference to Fig. 9. The distance determination method includes a measurement information acquisition step (step S10), a determination image discrimination step (step S12), and a distance determination step (step S15). The distance determination method may also include an infrastructure candidate point identification step (step S11), a virtual overhead line generation step (step S13), and a distance determination area setting step (step S14B).

[0100] The distance determination method according to this embodiment includes a measurement information acquisition process (step S10), an infrastructure candidate point identification process (step S11), a determination image discrimination process (step S12), a virtual overhead line generation process (step S13), a distance determination area setting process (step S14B), and a distance determination process (step S15).

[0101] The distance determination area setting step (step S14B) is a step in which the distance determination area setting unit 315B of the distance determination device 30 sets an area within a predetermined range from the virtual overhead line EL as the distance determination area.

[0102] The separation determination process (step S15) is a process in which the separation determination unit 316 of the separation determination device 30 determines that the object is not separated if a point representing part of the separated object O in the three-dimensional point cloud data exists in the separation determination area set by the separation determination area setting unit 315B in the separation determination area setting process (step S14B), and determines that the object is separated if a point representing part of the separated object O in the three-dimensional point cloud data does not exist in the separation determination area.

[0103] The effects of the present disclosure can also be obtained with the distance determination device 30 according to the third embodiment described above. Furthermore, by setting a distance determination region, it is only necessary to determine whether or not a point representing a part of the distant object O in the 3D point cloud data exists in the distance determination region, which reduces the number of calculations and shortens the time required for calculating the shortest distance in distance determination.

[0104] <Fourth embodiment> In the distance determination device 30 according to the third embodiment, a region a predetermined distance from the generated virtual overhead line EL is set as the distance determination region, and the distance determination is performed based on whether or not 3D point cloud data other than the virtual overhead line EL and infrastructure IN, such as utility poles UP, exists in the distance determination region. However, the present invention is not limited to this. For example, a region a predetermined distance from the overhead line OW on the generated 3D model may be set as the distance determination region, and the distance determination may be performed based on whether or not 3D models other than the infrastructure IN, such as the overhead line OW and utility poles UP, exist in the distance determination region. Components similar to those in the above-described embodiments may be assigned the same reference numerals, and descriptions thereof may be omitted.

[0105] The functional configuration of a distance determination device 30 according to the fourth embodiment will be described with reference to FIG.

[0106] As shown in FIG. 10, the control unit 310 of this embodiment has a measurement information acquisition unit (measurement information acquisition function) 311, an infrastructure candidate point identification unit (infrastructure candidate point identification function) 312, a judgment image discrimination unit (judgment image discrimination function) 313, a 3D model generation unit (3D model generation function) 314B, a separation judgment area setting unit (separation judgment area setting function) 315B, and a separation judgment unit (separation judgment function) 316.

[0107] The distance determination region setting unit 315B sets a region within a predetermined range from the overhead wire OW as the distance determination region on the 3D model. The predetermined range is, for example, a region at a predetermined distance from the overhead wire OW.

[0108] As described above, when performing distance determination using 3D point cloud data as is, it is necessary to calculate distances for all combinations between each point included in the 3D point cloud data of the overhead wire OW and each point included in the 3D point cloud data of the distant object O, and then compare the respective calculation results to calculate the shortest distance, resulting in a large number of combinations. This results in a large number of calculations, and a long time required for calculating the shortest distance in the distance determination. However, as in the present embodiment, by setting an area within a predetermined distance from the overhead wire OW as a distance determination area on the generated 3D model and determining whether the distant object O is present in the distance determination area, the number of calculations can be reduced. Therefore, by setting a distance determination area, the time required for calculating the shortest distance in the distance determination can be reduced.

[0109] The distance determination unit 316 determines that the object is not distant if a distant object O exists in the distance determination area on the 3D model, and determines that the object is distant if a distant object O does not exist in the distance determination area.

[0110] <Separation determination method> Next, a distance determination method using the distance determination device 30 according to this embodiment will be described with reference to Fig. 11. The distance determination method includes a measurement information acquisition step (step S10), a determination image discrimination step (step S12), and a distance determination step (step S15). The distance determination method may also include an infrastructure candidate point identification step (step S11), a 3D model generation step (step S13B), and a distance determination area setting step (step S14B).

[0111] The distance determination method according to this embodiment includes a measurement information acquisition process (step S10), an infrastructure candidate point identification process (step S11), a determination image discrimination process (step S12), a 3D model generation process (step S13B), a distance determination area setting process (step S14B), and a distance determination process (step S15).

[0112] The distance determination region setting step (step S14B) is a step in which the distance determination region setting unit 315B of the distance determination device 30 sets, on the 3D model, a region within a predetermined range from the overhead wire OW as a distance determination region.

[0113] The separation determination process (step S15) is a process in which the separation determination unit 316 of the separation determination device 30 determines that the object is not separated if a separated object O exists in the separation determination area on the 3D model, and determines that the object is separated if a separated object O does not exist in the separation determination area.

[0114] The effects of the present disclosure can also be obtained with the distance determination device 30 according to the fourth embodiment described above. Furthermore, by setting a distance determination region on a 3D model, it is only necessary to determine whether or not the distant object O exists in the distance determination region, which reduces the number of calculations and therefore reduces the time required for calculating the shortest distance in distance determination.

[0115] <Other variations> In the above-described embodiment, information is transmitted between the mobile mapping system 10 and the server 20 via the network N. However, the method of transmitting information between the mobile mapping system 10 and the server 20 is not limited to this, and information may be transmitted between the mobile mapping system 10 and the server 20 via a storage medium or the like.

[0116] Furthermore, in the above-described embodiment, the method of transmitting information between the server 20 and the distance determination device 30 is via the network N. However, the method of transmitting information between the server 20 and the distance determination device 30 is not limited to this, and the method of transmitting information between the server 20 and the distance determination device 30 may be via a storage medium or the like.

[0117] In the above embodiment, the distance determination device 30 and the mobile mapping system 10 are separate structures, but this is not limiting. For example, the distance determination device 30 may include the mobile mapping system 10.

[0118] The series of processes according to the above-described method can be executed by hardware or software. In other words, the functional configurations of Figures 3, 6, 8, and 10 are merely examples and are not particularly limited. In other words, it is sufficient if the functions capable of executing the series of processes described above as a whole are provided, and the functional blocks used to realize these functions are not particularly limited to the examples of Figures 3, 6, 8, and 10.

[0119] Furthermore, one functional block may be configured as a hardware unit, a software unit, or a combination thereof. The functional configuration in this embodiment is realized by a processor that executes arithmetic processing, and processors that can be used in this embodiment include those configured as various processing units such as single processors, multiprocessors, and multicore processors, as well as those that combine these various processing units with processing circuits such as ASICs (Application Specific Integrated Circuits) and FPGAs (Field-Programmable Gate Arrays).

[0120] When a series of processes is executed by software, the programs that make up the software are installed into a computer or the like from a network or a recording medium. The computer may be a computer built into dedicated hardware. Alternatively, the computer may be a computer that can execute various functions by installing various programs, such as a general-purpose personal computer.

[0121] The recording medium containing such a program may be a removable medium distributed separately from the device main body to provide the program to the user, or may be a recording medium provided to the user in a state where it is pre-installed in the device main body. Removable media may be, for example, a magnetic disk (including a floppy disk), an optical disk, or a magneto-optical disk. Optical disks may be, for example, CD-ROMs (Compact Disk-Read Only Memory), DVDs (Digital Versatile Disks), Blu-ray (registered trademark) Discs, etc. Magneto-optical disks may be, for example, MDs (Mini-Disks), etc. Furthermore, recording media provided to the user in a state where it is pre-installed in the device main body may be, for example, the ROM shown in FIG. 2 on which the program is recorded, or a hard disk included in the storage unit shown in FIG. 2.

[0122] In this specification, the steps of describing a program to be recorded on a recording medium include not only processes that are performed chronologically in accordance with the order, but also processes that are not necessarily performed chronologically but are performed in parallel or individually.

[0123] Although several embodiments of the present invention have been described above, these embodiments are merely illustrative and do not limit the technical scope of the present invention. The present invention can take on various other embodiments, and various modifications such as omissions and substitutions can be made without departing from the spirit of the present invention. These embodiments and their modifications are included within the scope and spirit of the invention described in this specification, etc., and are also included in the invention described in the claims and their equivalents. [Explanation of symbols]

[0124] 10 Mobile Mapping System 30 Separation determination device 311 Measurement information acquisition unit (measurement information acquisition function) 313 Image discrimination unit for judgment (image discrimination function for judgment) 316 Separation judgment section (separation judgment function) IN Infrastructure O Separation object S10 Measurement information acquisition process S12 Image discrimination process for judgment S15 Separation judgment process

Claims

1. A distance determination device for determining distance between an infrastructure and a distance object, a measurement information acquisition unit that acquires a plurality of image data and three-dimensional point cloud data associated with the plurality of image data, the image data being acquired by measurement using a mobile mapping system; a determination image discrimination unit that discriminates determination image data that includes the infrastructure and the separated object from among the plurality of image data; A distance determination device comprising: a distance determination unit that determines the distance between the infrastructure and the distant object based on the determination image data determined by the determination image discrimination unit and three-dimensional point cloud data associated with the determination image data.

2. The distance determination device according to claim 1 , wherein the infrastructure includes overhead lines for transmitting electricity and utility poles supporting the overhead lines.

3. an infrastructure candidate point identifying unit that identifies utility pole candidate points that are candidates for points indicating a portion of the utility pole and overhead line candidate points that are candidates for points indicating a portion of the overhead line in the three-dimensional point cloud data; a virtual overhead line generating unit that extracts an approximate curve that passes through three of the overhead line candidate points as a virtual overhead line, 3. The distance determination device according to claim 2, wherein the distance determination unit performs the distance determination based on the virtual overhead line and the three-dimensional point cloud data associated with the determination image data excluding the overhead line candidate points and the utility pole candidate points.

4. a 3D model generation unit that generates a 3D model based on the determination image data determined by the determination image determination unit and the 3D point cloud data associated with the determination image data, The distance determination device according to claim 1 , wherein the distance determination unit performs the distance determination based on the 3D model generated by the 3D model generation unit.

5. The distance determination device according to claim 1 or 2, wherein the distance determination unit determines the distance between the infrastructure and the distant object based on the three-dimensional point cloud data associated with the determination image data, with points excluding the infrastructure being considered as points of the distant object.

6. a distance calculation unit that calculates a separation distance between the virtual overhead line and the separated object based on the virtual overhead line and the three-dimensional point cloud data associated with the determination image data excluding the overhead line candidate points and the utility pole candidate points, The distance determination device according to claim 3 , wherein the distance determination unit determines that the object is not distant when the distance is equal to or less than a predetermined distance.

7. a distance determination area setting unit that sets an area within a predetermined range from the virtual overhead line as a distance determination area; 4. The distance determination device according to claim 3, wherein the distance determination unit determines that the object is not distant if the distance determination region contains a point representing a part of the distant object in the three-dimensional point cloud data, and determines that the object is distant if the distance determination region does not contain a point representing a part of the distant object in the three-dimensional point cloud data.

8. a separation calculation unit that calculates a separation distance between the infrastructure and the separated object based on the 3D model; The distance determination device according to claim 4 , wherein the distance determination unit determines that the object is not distant when the distance is equal to or less than a predetermined distance.

9. a distance determination area setting unit that sets an area within a predetermined range from the infrastructure as a distance determination area in the 3D model; The distance determination device according to claim 4, wherein the distance determination unit determines that the object is not distant when the distant object is present in the distance determination area in the 3D model, and determines that the object is distant when the distant object is not present in the distance determination area.

10. The distance determination device according to claim 1 ; A distance determination system comprising: a mobile mapping system that acquires the image data and three-dimensional point cloud data of the area around the road using a measurement unit mounted on a measurement vehicle traveling on the road.

11. A distance determination method executed by a distance determination device that determines the distance between an infrastructure and a distance object, comprising: a measurement information acquisition step of acquiring a plurality of image data and three-dimensional point cloud data associated with the plurality of image data, the image data being acquired by measurement using a mobile mapping system; a determination image discrimination step of discriminating determination image data including the infrastructure and the separated object from among the plurality of image data; A distance determination method including a distance determination process for determining the distance between the infrastructure and the distant object based on the determination image data determined in the determination image discrimination process and three-dimensional point cloud data associated with the determination image data.

12. A processor of a distance determination device that determines the distance between the infrastructure and the distance object, a measurement information acquisition function that acquires a plurality of image data and three-dimensional point cloud data associated with the plurality of image data acquired by measurement using a mobile mapping system; a determination image discrimination function for discriminating, from among the plurality of image data, determination image data that includes the infrastructure and the separated object; A program that executes a distance determination function that determines the distance between the infrastructure and the distant object based on the judgment image data determined by the judgment image discrimination function and three-dimensional point cloud data associated with the judgment image data.

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