Distance measuring device, distance measuring device control method, and data processing method

Abstract

This distance measuring device comprises: a light source that emits a light beam; a scanning device that carries out a beam scan for changing the emission direction of the light beam; a light detector that receives reflected light from measurement points of an object irradiated with the light beam, and outputs a detection signal; a processing circuit that calculates the distance to the measurement points on the basis of the detection signal; and a control circuit that controls the scanning device. The control circuit determines an angular step of the beam scan to reduce density differences between the measurement points in each region of the object.

Description

Distance measuring device, control method for distance measuring device, and data processing method

[0001] The present disclosure relates to a distance measuring device, a control method for the distance measuring device, and a data processing method.

[0002] 3D measurements using sensors capable of distance measurement are performed to obtain information on the three-dimensional shape of structures. For example, when manufacturing relatively large products such as vehicles, equipment, or home appliances in factories, 3D measurements are sometimes performed to inspect the shape, dents, surface irregularities, and other conditions. 3D measurements of parts or work-in-progress can be performed to evaluate the shape or defects, enabling process management. At construction sites, acquiring 3D measurement information at necessary stages in the construction process allows for data-based progress management or quality control. For example, 3D measurements of the construction site and marking required locations with a projector or other device can automate marking. Furthermore, even if blueprints are not available during building expansion or renovation, obtaining 3D shape information with a sensor allows for the creation of new blueprints. Furthermore, during the construction process, measuring and inspecting the shape of processes such as spraying fireproofing materials or treating concrete joints can enable process management without relying on visual inspection.

[0003] Patent Documents 1 and 2 disclose examples of systems for acquiring information on the surface shape of a structure. Patent Document 1 discloses a surface treatment shape evaluation system that calculates feature quantities of the treated shape of the surface of existing concrete using a distance measuring device such as a laser distance meter or an ultrasonic distance meter. Patent Document 2 discloses a method for scanning a stationary steel plate with a deflected laser beam to acquire data on a detection point cloud on the steel plate and measuring the shape of the steel plate from the detection point cloud data. The method of Patent Document 2 performs a thinning process to uniform the point density of the detection point cloud and a calculation process to analyze a regression curve from the detection point cloud data.

[0004] Japanese Patent Laid-Open No. 11-336017 Japanese Patent Laid-Open No. 2010-156622

[0005] The present disclosure provides techniques for improving the accuracy of 3D measurements.

[0006] A distance measuring device according to an embodiment of the present disclosure includes a light source that emits a light beam, a scanning device that performs beam scanning by changing the emission direction of the light beam, a photodetector that receives reflected light from a measurement point on an object irradiated with the light beam and outputs a detection signal, a processing circuit that calculates a distance to the measurement point based on the detection signal, and a control circuit that controls the scanning device, wherein the control circuit determines an angle step of the beam scanning so as to reduce a difference in density of the measurement points between regions on the object.

[0007] A distance measuring device according to another embodiment of the present disclosure includes a light source, a photodetector that receives light reflected from an object illuminated by the light from the light source and outputs a detection signal, and a processing circuit that calculates distances to each of a plurality of measurement points included in a target area of ​​the object based on the detection signal and generates measurement data that indicates a distribution of distances or positions of the plurality of measurement points, wherein the processing circuit performs a process on the measurement data to change the density of the measurement points in at least one of a plurality of partial areas included in the target area so as to reduce a difference in density of the measurement points among the plurality of partial areas.

[0008] A comprehensive or specific aspect of the present disclosure may be realized by a system, an apparatus, a method, an integrated circuit, a computer program, or a recording medium such as a computer-readable recording disk, or by any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium. The computer-readable recording medium may include a volatile recording medium or a non-volatile recording medium such as a CD-ROM (Compact Disc-Read Only Memory). An apparatus may be composed of one or more devices. When an apparatus is composed of two or more devices, the two or more devices may be located in a single device or may be located separately in two or more separate devices. In this specification and claims, the term "apparatus" may refer not only to a single device but also to a system consisting of multiple devices.

[0009] According to the embodiments of the present disclosure, the accuracy of 3D measurements can be improved.

[0010] FIG. 1A is a diagram schematically illustrating a distance measuring device according to an exemplary embodiment of the present disclosure. FIG. 1B is a diagram illustrating another exemplary configuration of the distance measuring device. FIG. 2 is a block diagram illustrating an exemplary configuration of the distance measuring device. FIG. 3A is a diagram schematically illustrating an exemplary distribution of measurement points when beam scanning is performed at a constant angular step. FIG. 3B is a diagram schematically illustrating an exemplary distribution of measurement points when beam scanning is performed with the angular step corrected according to the emission direction. FIG. 4 is a flowchart illustrating an exemplary measurement procedure using the distance measuring device. FIG. 5A is a diagram schematically illustrating the relationship between a reference surface, an arithmetic mean height, and a root-mean-square height in an evaluation area having an uneven shape. FIG. 5B is a diagram schematically illustrating an example of a reference surface in an uneven shape having low-frequency undulations. FIG. 5C is a diagram schematically illustrating another example of a reference surface in an uneven shape having low-frequency undulations. FIG. 6 is a flowchart illustrating an exemplary flow of distance measurement when pre-measurement is performed. FIG. 7 is a diagram schematically illustrating distance measurement performed by moving the distance measuring device. FIG. 8 is a diagram for explaining a method of making the measurement point density closer to uniform through data processing. FIG. 9A is a diagram for explaining the size of a structure. FIG. 9B is another diagram for explaining the size of a structure. FIG. 10A is a diagram showing an example in which the density of measurement points is insufficient for the structure size. FIG. 10B is a diagram showing an example in which the density of measurement points is appropriate for the structure size. FIG. 10C is a diagram showing an example in which the density of measurement points is excessive for the structure size. FIG. 11 is a block diagram showing an example configuration of a LiDAR sensor. FIG. 12 is a diagram showing an example of time changes in the frequencies of the reference light, reflected light, and interference light when the distance between the LiDAR sensor and the object is constant.

[0011] The embodiments described below are all comprehensive or specific examples. The numerical values, shapes, materials, components, component placement and connection configurations, steps, and step sequences shown in the following embodiments are merely examples and are not intended to limit the technology of the present disclosure. Among the components in the following embodiments, components that are not described in the independent claims that represent the highest concepts are described as optional components. Each figure is a schematic diagram and is not necessarily an exact illustration. Furthermore, in each figure, substantially identical or similar components are denoted by the same reference numerals. Duplicate descriptions may be omitted or simplified.

[0012] In this disclosure, all or part of a circuit, unit, device, component, or part, or all or part of a functional block in a block diagram, may be implemented by one or more electronic circuits, including, for example, a semiconductor device, a semiconductor integrated circuit (IC), or an LSI (large scale integration). The LSI or IC may be integrated on a single chip or may be configured by combining multiple chips. For example, functional blocks other than memory elements may be integrated on a single chip. While the terms LSI and IC are used here, the term may be changed depending on the degree of integration, and may be referred to as a system LSI, a VLSI (very large scale integration), or an ULSI (ultra large scale integration). Field programmable gate arrays (FPGAs), which are programmed after the LSI is manufactured, or reconfigurable logic devices, which can reconfigure connections within the LSI or set up circuit partitions within the LSI, can also be used for the same purpose.

[0013] Furthermore, all or part of the functions or operations of a circuit, unit, device, component, or section can be implemented by software processing. In this case, the software is recorded on one or more non-transitory recording media such as ROMs, optical disks, hard disk drives, etc., and when the software is executed by a processor, the functions specified in the software are performed by the processor and peripheral devices. A system or device may include one or more non-transitory recording media on which the software is recorded, a processor, and necessary hardware devices, such as interfaces.

[0014] In this disclosure, "light" refers to electromagnetic waves including not only visible light (wavelengths of about 400 nm to about 700 nm), but also ultraviolet light (wavelengths of about 10 nm to about 400 nm) and infrared light (wavelengths of about 700 nm to about 1 mm).

[0015] (Foundations on which the present disclosure is based) Before describing embodiments of the present disclosure, the findings on which the present disclosure is based will be described.

[0016] As sensors capable of 3D measurement of structures, various sensors such as contact sensors, imaging sensors, and LiDAR (Light Detection and Ranging) sensors are used.

[0017] The method using a contact sensor requires time to measure the surface shape, and therefore has the problem that when performing 3D measurement of a large structure, measurement cannot be performed in a short time.

[0018] One imaging measurement method is to use a stereo camera containing two cameras to measure the parallax of an object and obtain 3D shape information based on the parallax. The stereo camera method requires a matching process to determine the parallax from the two images. However, it is not possible to measure the surface shape with high accuracy on flat surfaces without feature points or on surfaces with fine random patterns.

[0019] LiDAR sensors measure distances using a light beam such as a laser. For example, 3D measurements can be performed by measuring distances while performing a scanning motion that changes the direction of the light beam. Such LiDAR sensors use a collimated or focused light beam, which allows the light energy to be concentrated at the irradiation point. This allows for highly accurate distance measurements even for distant objects. However, a disadvantage of 3D measurements is that sampling must be performed while scanning the beam, which requires time for measurement. Therefore, 3D measurement using LiDAR can be considered one of the optimal methods when the object does not move during the beam scan or when the object's movement is sufficiently slow compared to the movement of the beam scan.

[0020] There are several other methods for scanning an object with a light beam, such as LiDAR. For example, in the method disclosed in Patent Document 1, scanning is performed by displacing a measuring instrument that emits a fixed beam. However, unless the trajectory of the measuring instrument's displacement is accurately known, it is not possible to accurately obtain information about the object's 3D shape. Another disadvantage is that a mechanism for displacing the measuring instrument is required, which makes the configuration more complex.

[0021] In LiDAR sensors that perform scanning operations, the emission angle of the laser beam is changed by a beam scanning mechanism such as an electric motor rotating a mirror or prism or a MEMS (micro-electromechanical systems) mirror. The driving operation of the beam scan and the sampling rate of the laser beam distance measurement are generally predetermined during product design. In many cases, LiDAR sensor specifications are determined so that the measurement points are spaced at nearly equal angular intervals.

[0022] According to the inventors' research, the following problem occurs when performing 3D measurement of an object using such a LiDAR sensor. The density of measurement points varies depending on the angle at which the beam is incident on the object in the measurement field of view. Specifically, the density of measurement points is lower when the beam is incident obliquely than when it is incident at an angle close to perpendicular. Such variations in the density of measurement points in the measurement data of an object can cause problems when analyzing the measurement results. For example, when determining the general shape of an object based on 3D measurement results by fitting, the fitting is affected by the measurement results of areas with a high density of measurement points, resulting in a large discrepancy in the evaluation results of areas with a low density of measurement points. Furthermore, when evaluating surface area or surface roughness based on 3D measurement results, the evaluation value is affected by the density of measurement points (i.e., the number of measurement points per unit area or unit length). This makes it impossible to evaluate relative changes for each measurement area.

[0023] Patent Document 2 discloses a method for detecting waviness in the shape of a steel plate by thinning out point cloud data acquired by scanning with a laser beam, making the density of measurement points uniform, and determining a regression surface. This method is effective because, in analyzing a macroscopic shape such as waviness, there is no need to increase the density of measurement points in the first place.

[0024] However, when measuring complex shapes or evaluating surfaces such as surface area or roughness, a certain level of measurement point density is required. This means that in some locations, measurements must be taken at a higher density than necessary, which can result in issues such as longer measurement times and a heavier data processing load.

[0025] Based on the above considerations, the inventors have conceived the configurations of the embodiments described below. Exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. However, more detailed description than necessary may be omitted. For example, detailed descriptions of well-known matters and redundant descriptions of substantially identical configurations may be omitted. This is to avoid unnecessary redundancy in the following description and to facilitate understanding by those skilled in the art. Note that the inventors provide the accompanying drawings and the following description to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter recited in the claims.

[0026] (Embodiment) Fig. 1A is a diagram schematically illustrating a distance measuring device 100 according to an exemplary embodiment of the present disclosure. The distance measuring device 100 shown in Fig. 1A measures distances to multiple measurement points on an object while performing a scanning operation that changes the emission direction of a light beam. The distance measuring device 100 can generate three-dimensional point cloud data based on the distances to each measurement point. The three-dimensional point cloud data includes data on the three-dimensional coordinate values ​​of each of the multiple measurement points and represents a three-dimensional distribution of the multiple measurement points. Using the distance measuring device 100, 3D measurement of an object is possible.

[0027] The distance measuring device 100 may be installed on the ground or the floor of a building using a support 300 such as a tripod. In the example of FIG. 1A , the measurement target is the floor. The target may be a structure made of any material, such as the ground, a floor surface, or a concrete surface. Furthermore, the target is not limited to a planar structure, and may be other structures such as the ground with an uneven surface, the wall of a building, or an industrial product.

[0028] The distance measuring device 100 has a beam scanning mechanism and can change the direction of the light beam emitted from the beam emitting unit 110. 3D measurement can be performed by scanning an area within a field of view in the direction in which the beam emitting unit 110 is facing with the light beam. In FIG. 1A, the field of view, which is the scanning range, is illustrated by four dashed lines. The black circles in the figure indicate examples of measurement points.

[0029] The distance measuring device 100 shown in FIG. 1A can adjust the height, horizontal angle, and vertical angle of the beam emitting unit 110. The height of the beam emitting unit 110 is the height from the installation surface of the distance measuring device 100. The horizontal angle is the rotation angle relative to a reference direction around an axis perpendicular to the installation surface. The vertical angle is the rotation angle relative to the vertically downward direction around an axis parallel to the installation surface. The height, horizontal angle, and vertical angle of the beam emitting unit 110 may be fixed at the time of installation or may be adjusted and fixed by the user before measurement. The height of the beam emitting unit 110 can be set to an appropriate height depending on the object, such as 50 cm, 1 m, or 2 m. The horizontal angle and vertical angle are set so that the beam emitting unit 110 faces the measurement target area of ​​the object. Note that the mechanism for adjusting the height, horizontal angle, and vertical angle of the beam emitting unit 110 does not have to be installed in the distance measuring device 100.

[0030] 1B is a diagram showing another example of the configuration of the distance measuring device 100. As shown in Fig. 1B, the distance measuring device 100 may be supported by a support 300 such as a tower. With such a configuration, the distance measuring device 100 can measure in an orientation in which it faces the surface of the object directly (i.e., the vertical angle is 0°).

[0031] The distance measuring device 100 may include a light source such as a laser, an optical system such as a lens, a photodetector, and a scanning device. The scanning device changes the direction of the light beam emitted from the light source. The distance measuring device 100 may also include a control circuit for controlling the scanning device and a processing circuit for processing signals output from the photodetector. The control circuit controls the scanning device to change the horizontal and vertical components of the emission direction of the light beam emitted from the beam emitting unit 110. As a result, multiple measurement points arranged two-dimensionally are sequentially irradiated with the light beam, as indicated by the black circles in FIGS. 1A and 1B. Note that the scanning device may be configured to change only one of the horizontal and vertical components of the emission direction of the light beam. In this case, one-dimensional scanning is possible. The processing circuit calculates the distance to each measurement point based on the detection signal generated by the photodetector upon receiving reflected light from each measurement point. Known distance measurement techniques, such as Time of Flight (ToF) or Frequency Modulation Continuous Wave (FMCW), can be used as a distance measurement method. By beam scanning, distance data for a plurality of measurement points can be generated, and three-dimensional coordinate data for the plurality of measurement points, i.e., point cloud data, can be generated from the distance data for the plurality of measurement points.

[0032] When measuring distances point by point while performing beam scanning using such a distance measuring device 100, the angle of incidence of the light beam on the object within the field of view changes, which causes a change in the density of measurement points per unit area or unit length, resulting in unevenness in the spatial density of the point cloud data, which is the measurement result of the object.

[0033] Therefore, in this embodiment, the variation in the density of measurement points is suppressed by adjusting the angle step of the beam scan according to the emission direction and removing data of some measurement points in areas with a higher density than necessary from the acquired point cloud data. This makes it possible to make the density of measurement points closer to uniform. By making the density of measurement points closer to uniform, it is possible to reduce spatial variations in the accuracy of extraction of the 3D shape of the object. Furthermore, when evaluating a rough surface with a fine pattern or random unevenness, it is possible to suppress a decrease in the reliability of the measurement results due to variations in the density of measurement points.

[0034] Fig. 2 is a block diagram showing an example of the configuration of a distance measuring device 100 according to this embodiment. In Fig. 2, thick arrows illustrate the flow of light, and thin arrows illustrate the flow of signals. The distance measuring device 100 shown in Fig. 2 includes a beam emitting unit 110, a light source 120, a scanning device 130, a photodetector 140, a processing circuit 150, a control circuit 160, a storage device 170, an input interface (I / F) 180, and an output interface 190. The beam emitting unit 110 is a part of the distance measuring device 100 from which a light beam is emitted, and may include an optical system such as a lens therein.

[0035] The light source 120 includes a light emitting element that emits light, such as a laser or an LED, and may be configured to emit a light beam in the infrared or visible wavelength range, for example.

[0036] The scanning device 130 has a beam scanning mechanism, such as a combination of an electric motor and a mirror, a MEMS mirror, or a phased array, and performs beam scanning to change the emission direction of the light beam.

[0037] The photodetector 140 receives reflected light from a measurement point on an object irradiated with a light beam and outputs a detection signal. The photodetector 140 includes one or more light-receiving elements. Each light-receiving element performs photoelectric conversion and outputs an electrical signal corresponding to the intensity of the received light. The photodetector 140 outputs a detection signal based on the electrical signal output from each light-receiving element to the processing circuit 150. The photodetector 140 may include an image sensor. The image sensor has a structure in which multiple light-receiving elements are arranged in a two-dimensional plane. The image sensor outputs an image signal as a detection signal.

[0038] The processing circuit 150 calculates the distance to each measurement point based on the detection signal. The processing circuit 150 may include one or more processors, such as a central processing unit (CPU), a field programmable gate array (FPGA), or a graphics processing unit (GPU). The processing circuit 150 calculates the distance using a distance measurement technique, such as Time of Flight (ToF) or Frequency Modulation Wave (FMCW). When the FMCW technique is used, the photodetector 140 may be configured to detect interference light between emitted light and reflected light, rather than directly detecting reflected light from the target. An example configuration of a distance measurement device using the FMCW technique will be described later.

[0039] The control circuit 160 controls the amount of light emitted from the light source 120 and the scanning operation of the scanning device 130. The control circuit 160 may be realized by a circuit including one or more processors and one or more memories, such as an FPGA or a microcontroller unit (MCU). The control circuit 160 and the processing circuit 150 may be realized by a single integrated circuit. Alternatively, each of the control circuit 160 and the processing circuit 150 may be provided in a device separate from the distance measuring device 100. For example, a processor in a computer connected to the distance measuring device 100 may function as at least one of the control circuit 160 and the processing circuit 150. In this case, the control circuit 160 or the processing circuit 150 is configured to communicate with the distance measuring device 100 via wired or wireless communication.

[0040] The storage device 170 may be any storage device, such as a semiconductor storage device, a magnetic storage device, an optical storage device, etc. The storage device 170 stores computer programs executed by the control circuit 160 and the processing circuit 150, as well as various data generated in the process of processing by these circuits.

[0041] The input interface 180 is an interface for inputting signals from an external device, and the output interface is an interface for outputting signals to an external device.

[0042] In this embodiment, the control circuit 160 determines the angular step of the beam scan (hereinafter also referred to as the "spatial scan step") so as to reduce the difference in density of measurement points between regions of the object. Here, "angular step" refers to the angle between the emission direction of a light beam toward a given measurement point and the emission direction of a light beam toward the next measurement point. The control circuit 160 can reduce the difference in density of measurement points between regions of the object by, for example, changing the angular step of the beam scan depending on the emission direction of the light beam. Alternatively, the control circuit 160 can reduce the difference in density of measurement points between regions of the object by changing the angular step depending on the distance between the beam emitting unit 110 (or the light source 120) and the object. The control circuit 160 may acquire information indicating the distance from the storage device 170 and change the angular step based on that information. For example, the control circuit 160 may reduce the angular step as the distance increases. Note that if the object is placed on a surface on which the distance measuring device 100 is installed, the height of the beam emitting unit 110 (or the light source 120) corresponds to the distance. An example of the operation of the control circuit 160 will now be described in detail.

[0043] FIG. 3A is a diagram schematically illustrating an example of the distribution of measurement points when beam scanning is performed at a constant angular step. FIG. 3B is a diagram schematically illustrating an example of a case where the distribution of measurement points is made uniform by performing beam scanning while correcting the angular step according to the emission direction. FIGS. 3A and 3B illustrate mutually orthogonal X-, Y-, and Z-axes. The X- and Y-axes are set within the installation surface of the distance measuring device 100. The Z-axis is set perpendicular to the installation surface, with the positive direction being the vertically upward direction. In FIGS. 3A and 3B, the position of the beam emission unit 110 is represented by a black circle on the Z-axis. The point cloud data may be, for example, data of three-dimensional coordinate values ​​of each measurement point expressed in the XYZ coordinate system shown in FIGS. 3A and 3B.

[0044] When a beam scanning mechanism uses, for example, a mechanism that rotates a mirror at a constant speed using an electric motor, measurement points are acquired at equal angular intervals by continuously measuring one point at a constant sampling rate. In this case, when measuring an object with a flat surface using beam scanning, the density of measurement points varies depending on the area being measured, as shown in FIG. 3A. When the perpendicular angle of the beam emission direction is θ, the density of surrounding points decreases by cosθ times compared to when the beam is perpendicularly incident (θ = 0°). Even when scanning is performed using a beam scanning mechanism that moves at a non-constant speed, such as a resonant mirror or a MEMS mirror, the density of measurement points generally tends to be sparse in areas with a large irradiation angle θ and dense in areas with a small irradiation angle θ.

[0045] The measurement point density also changes depending on the height h of the beam emission part 110, which is the point where the beam is emitted. For example, if the height is doubled, the measurement point density will decrease to 1 / 4 as long as the same scanning operation is performed.

[0046] When the parameters of the installation angle and height of the beam emission unit 110 are fixed values, or when these parameters can be measured or set using a jig, another sensor, etc., it is possible to predict the distribution of the measurement point density from the parameter values. Therefore, it is effective to correct the spatial scan step by adjusting the beam scanning operation or measurement rate according to the predicted measurement point density.

[0047] Specifically, the control circuit 160 can make the measurement point density within the field of view more uniform by slowing down the beam scanning speed in accordance with the decrease in measurement point density caused by an increase in the irradiation angle θ while keeping the measurement rate, i.e., the number of beam emission times per unit time, fixed. Alternatively, the control circuit 160 can increase the measurement rate in accordance with the decrease in measurement point density caused by an increase in the irradiation angle θ while keeping the beam scanning speed fixed. Alternatively, the control circuit 160 can adjust both the beam scanning speed and the measurement rate to make the measurement point density more uniform. These operations can make the measurement point density more uniform, as shown in FIG. 3B.

[0048] When the surface of the object is substantially flat, the control circuit 160 may adjust the measurement point density to increase by a factor of 1 / cosθ according to the irradiation angle θ of the light beam. Also, when the height of the beam emitting part 110 is h and it is desired to align the measurement point density with the result of measurement at a previous height h1, the control circuit 160 adjusts the measurement point density to (h1 / h) ２ The angle step of the beam scan may be changed so that the beam scanning angle becomes twice as large as the irradiation angle θ. Note that even when the distance measurement of a one-dimensional area is performed by scanning the beam in a one-dimensional direction, the control circuit 160 may change the angle step of the beam scan in accordance with the irradiation angle θ and the height h1.

[0049] If the surface of the object is not flat but has large undulations, the above correction cannot completely correct the density of measurement points, but it can be effective because it reduces density variations compared to no correction at all.

[0050] 4 is a flowchart showing an example of a measurement procedure using the distance measuring device 100. First, in step S101, the distance measuring device 100 is installed in an appropriate location for measuring the distance to the object. For example, if the object is a floor surface as shown in FIG. 1A, the distance measuring device 100 is installed near a portion of the floor whose shape is to be evaluated.

[0051] Next, in step S102, the horizontal angle, vertical angle, and height of the beam emission unit 110 are adjusted. This adjustment may be performed, for example, by an operator performing measurement work. After completing the adjustment, the operator may operate an input device to input information about the angle and height. Alternatively, the device may automatically read the angle and height and input the information. The input information is recorded in the storage device 170 via the input interface 180. This data is used in subsequent steps S103 and S107. The distance measuring device 100 may include one or more sensors that measure the horizontal angle, vertical angle, and height of the beam emission unit 110. In this case, information about the horizontal angle, vertical angle, and height measured by the sensors may be recorded in the storage device 170.

[0052] In step S103, the control circuit 160 determines the scan angle step based on the input or measured horizontal angle, vertical angle, and height so as to obtain a predetermined measurement point density. The control circuit 160 changes the scan angle step according to the light beam emission direction, for example, so that the scan angle step decreases as the angle from the direction of perpendicular incidence increases. In the following step S104, the control circuit 160 controls the scanning device 130 according to the determined angle step to perform 3D measurement. During 3D measurement, the processing circuit 150 calculates the distance to the measurement point each time the light beam is emitted from the beam emission unit 110. During measurement, information indicating that measurement is in progress or the remaining measurement time may be displayed on the display of a personal computer (PC) or mobile computer connected to the distance measuring device 100.

[0053] After the measurement is completed, in step S106, the processing circuitry 150 stores the measurement data including the distance information of each measurement point in the storage device 170 or in a storage device such as a PC or mobile computer connected to the distance measuring device 100.

[0054] In the following step S107, the processing circuitry 150 converts the measurement data into three-dimensional point cloud data in a predetermined coordinate system. The predetermined coordinate system may be, for example, the XYZ coordinate system shown in FIGS. 3A and 3B. Since the origin of the measurement data is the beam emission point, coordinate conversion processing is performed as necessary. The data on the horizontal angle, vertical angle, and height of the beam emission unit 110 input in step S102 is used in the coordinate conversion processing.

[0055] In the next step S108, the processing circuitry 150 extracts data for a partial area to be analyzed from the obtained data, if necessary. The field of view of the distance measuring device 100 may include objects other than the target object. In such cases, the operator can operate a PC or mobile computer to specify which part of the field of view will be the subject of shape analysis. The processing circuitry 150 extracts data for the specified area to be analyzed. This area will be referred to as the "evaluation area" in the following description.

[0056] In step S109, the processing circuitry 150 analyzes the shape of the extracted evaluation region from the point cloud data. For example, the processing circuitry 150 may extract the surface shape by fitting based on the distribution of measurement points, or evaluate the surface roughness. The surface roughness may be evaluated using, for example, roughness parameters described below.

[0057] In step S110, the processing circuitry 150 outputs information indicating the analysis results (e.g., roughness parameters, etc.) to the storage device 170 or an external display device. In this manner, the processing circuitry 150 may generate and output information indicating the surface roughness in an area including multiple measurement points based on distance information of multiple measurement points on the object. In step S110, the processing circuitry 150 may determine whether the surface condition of the object satisfies desired conditions by comparing the calculated roughness parameters, etc. with a predetermined threshold value. If the object's surface is required to be rough, the desired value is determined to be a roughness parameter greater than a predetermined threshold value. If the object's surface is required to be smooth, i.e., not rough, the desired value is determined to be a roughness parameter smaller than a predetermined threshold value. If the object's surface is required to have a moderate roughness, the desired value is determined to be a roughness parameter within a predetermined range.

[0058] By performing the above operations, it is possible to suppress non-uniformity in the density of measurement points for each region of the object, and to evaluate the surface shape of the object with high accuracy.

[0059] [Example of Roughness Parameter] Next, an example of the roughness parameter in the evaluation area calculated in step S109 will be described. The evaluation area may be a two-dimensional area or a one-dimensional area. The size of the evaluation area can be determined, for example, depending on the dimensions of the protrusions or recesses on the surface of the object.

[0060] First, we will explain how to calculate roughness parameters when the evaluation area is a two-dimensional area. The evaluation area can be a two-dimensional area, such as a rectangle, a circle, or an ellipse. Such an evaluation area is effective for the surface of an object having two-dimensionally distributed uneven shapes.

[0061] An example of the roughness parameter is the arithmetic mean height Sa. The arithmetic mean height Sa is calculated by the following formula (1).

[0062] Z(x, y) represents the difference in height of the unevenness from the reference plane Z=0 at positions X=x and Y=y within the evaluation area. The reference plane Z=0 is the average plane of the unevenness height within the evaluation area. "A" in formula (1) represents the area of ​​the evaluation area. The arithmetic mean height Sa is the value obtained by averaging the absolute value of the difference in height of the unevenness from the reference plane Z=0 within the evaluation area. The height of the unevenness can be determined from the distance information of each of multiple measurement points.

[0063] As another example of the roughness parameter, the square root height Sq is calculated by the following equation (2).

[0064] The square root height Sq is obtained by averaging the square of the height difference of the unevenness from the reference plane Z=0 in the evaluation area. The square root height Sq corresponds to the standard deviation of the height difference in the evaluation area and represents the variation of the height difference. The square root height Sq and the arithmetic mean height Sa satisfy the relationship Sq≧Sa. The greater the variation of the height difference, the greater the deviation of Sq / Sa from 1.

[0065] Further examples of roughness parameters include the developed interface area ratio Sdr, which is an index of surface area, the skewness Ssk, which indicates the symmetry of the height distribution of the irregularities, the kurtosis Sku, which indicates the sharpness of the height distribution of the irregularities, and the root-mean-square slope Sdq, which indicates the steepness of the irregularities.

[0066] As described above, the roughness parameter may be, for example, one selected from the group consisting of the arithmetic mean height Sa, the square root height Sq, the developed interface area ratio Sdr, the skewness Ssk, the kurtosis Sku, and the root mean square slope Sdq in a two-dimensional region.

[0067] Next, with reference to Figures 5A to 5C, examples of the arithmetic mean height Sa and the square root height Sq in an evaluation area having an uneven shape, as well as examples of a reference plane, are described. Figure 5A is a diagram schematically showing the relationship between the reference plane Z = 0, the arithmetic mean height Sa, and the square root height Sq in an evaluation area having an uneven shape. The dashed line in Figure 5A represents the reference plane, and the solid line represents the arithmetic mean height Sa and the square root height Sq. In the example shown in Figure 5A, Sq / Sa > 1, and there is some variation in the height difference of the unevenness from the reference plane Z = 0.

[0068] As shown in FIG. 5A , when the uneven shape does not have waviness, the reference surface Z=0 is a flat surface. On the other hand, when the uneven shape has low-frequency waviness, the reference surface may be defined as follows. FIGS. 5B and 5C are schematic diagrams showing examples of reference surfaces for an uneven shape having low-frequency waviness. In the example shown in FIG. 5B , the reference surface is a flat surface obtained by averaging the height of the unevenness in the evaluation area. When the reference surface is a flat surface, a roughness parameter including the waviness is calculated. In contrast, in the example shown in FIG. 5C , the reference surface is a curved surface obtained by dividing the evaluation area into multiple areas, averaging the height of the unevenness in each area, and connecting the averaged heights in the multiple areas. When the reference surface is a curved surface, a roughness parameter with the waviness removed is calculated.

[0069] The evaluation area may be a one-dimensional area. Such an evaluation area is effective for the surface of an object having a one-dimensionally distributed uneven shape. The roughness parameter may be, for example, one selected from the group consisting of the arithmetic mean height Ra, the root-mean-square height Rq, the skewness Rsk, the kurtosis Rku, and the root-mean-square slope Rdq in the one-dimensional area. When the shape of a one-dimensional area is evaluated, the control circuit 160 may cause the scanning device 130 to perform a one-dimensional beam scan.

[0070] [Pre-measurement] Next, an example of the operation of determining the angle step of the beam scan based on the result of pre-measurement performed before the main measurement will be described.

[0071] The preliminary measurement is an operation for measuring the distances to a plurality of measurement points on an object by beam scanning with a constant angle step. Based on the results of the preliminary measurement, the control circuit 160 may adjust the angle step of the beam scanning in the main measurement that is performed after the preliminary measurement. For example, the control circuit 160 may reduce the angle step of the beam scanning in the main measurement in an area where the density of measurement points in the preliminary measurement is lower.

[0072] FIG. 6 is a flowchart showing an example of the flow of distance measurement when preliminary measurement is performed. The flowchart shown in FIG. 6 differs from the flowchart shown in FIG. 4 in that step S111 is added after step S101, and steps S102 and S103 are replaced with steps S112 and S113, respectively. In the example shown in FIG. 4, the measurement point density is corrected using parameters of the installation angle and height of the beam emitter 110. In contrast, in the example shown in FIG. 6, preliminary measurement is performed in step S111, and the measurement point density in the main measurement is corrected based on the point cloud data obtained in the preliminary measurement. In the preliminary measurement, the control circuit 160 measures the distance to each measurement point, for example, by keeping the angle step of the beam scan constant. As a result, the processing circuit 150 generates point cloud data of multiple measurement points. In the subsequent step S112, the processing circuit 150 calculates the distance and vertical angle of the beam emitter 110 from the surface to be measured based on the generated point cloud data. This information is used in the coordinate conversion in the subsequent step S107. In step S113, the control circuit 160 determines the angle step of the beam scan based on the result of the preliminary measurement.

[0073] If the object has a planar surface, the method shown in FIG. 4 can also appropriately correct the measurement point density. However, if the object's surface is not planar, the beam incident angle varies depending on the object's shape, which may prevent effective correction of the measurement point density. Therefore, as shown in the example of FIG. 6, it is effective to perform a preliminary measurement, estimate the overall measurement point density based on the point cloud data obtained in the preliminary measurement, and use the results to determine the scanning angle step. For example, assume that the preliminary measurement results include measurement data such as that shown in FIG. 3A. The measurement data can be used to estimate the measurement point density distribution. To uniformize the density distribution within the field of view of the ranging device 100, the control circuit 160 predetermines the scanning angle step for each emission direction and performs 3D measurement based on the angle step. This enables the object's surface shape to be evaluated with greater accuracy.

[0074] 6, when the target object has a known shape, such as a plane, even if the parameters of the angle and height (or distance) of the beam emission unit 110 at the time of installation are unknown or unmeasured, these parameters can be determined from the pre-measurement data. The measurement point density may be further corrected by correcting the angle step of the scan using these parameters.

[0075] [Multiple Measurements] There may be cases where a single measurement can only measure a portion of the area that needs to be evaluated on the surface. In such cases, it is effective to move the distance measuring device 100 and perform measurements multiple times, as shown in FIG. 7, for example. By performing multiple measurements, it is possible to measure the entire area that needs to be evaluated. The distance measuring device 100 may be moved by an operator, for example, or the movement may be automated using a device that moves the distance measuring device 100.

[0076] When measuring multiple times by moving the distance measuring device 100, if the density of measurement points varies from measurement to measurement, the surface shape may not be evaluated appropriately. Therefore, the control circuit 160 may adjust the angle step of the beam scan in each measurement to reduce the difference in the density of measurement points in each measurement. That is, when the distance measuring device 100 measures the distance of a first region of an object and then moves the distance measuring device 100 to measure the distance of a second region of the object, the control circuit 160 may adjust the angle step of the beam scan in measuring the distance of the second region so as to reduce the difference between the density of measurement points in the first region and the second region.

[0077] When the distance measuring device 100 is moved, the installation surface may be tilted or uneven after the movement, which may cause the angle or height parameters of the beam emission unit 110 to change between measurements before and after the movement. Even in such cases, the angle and height of the beam emission unit 110 can be measured after installation, and the measurement point density can be corrected based on these parameters before measurement. This provides the effect of standardizing the measurement conditions each time. Furthermore, the aforementioned pre-measurement may be performed each time the device is moved, and the measurement point density may be corrected based on the pre-measurement before the actual measurement is performed. Even in this case, the effect of leveling the measurement point density can be similarly obtained.

[0078] [Method for Leveling Measurement Point Density by Data Processing] Next, an example of a method for leveling measurement point density by data processing will be described.

[0079] In the above embodiment, the difference in measurement point density between regions is reduced by adjusting the angle step of the beam scan. However, a similar effect can also be achieved by data processing. For example, the processing circuitry 150 may divide the target region occupied by the multiple measurement points whose distances have been measured into multiple virtual partial regions (shown by dotted frames in FIG. 8 ) and change the density of measurement points in some or all of the partial regions to reduce the difference in measurement point density between the partial regions. The change in measurement point density may be performed, for example, by removing some measurement points. For example, the processing circuitry 150 may reduce the difference in measurement point density between multiple regions by bringing the density of measurement points in at least one remaining partial region of the multiple partial regions closer to the density in the partial region with the smallest measurement point density. Furthermore, the processing circuitry 150 may reduce the difference in measurement point density between multiple regions by bringing the density of measurement points in some or all of the remaining partial regions approximately equal to the density in the partial region with the smallest measurement point density.

[0080] The multiple partial regions may be set by the processing circuitry 150, for example, so that the difference in the number of angular steps or area between the partial regions is small. Alternatively, the user may be allowed to set the partial regions arbitrarily. In this case, setting information for the multiple partial regions may be input from a computer used by the user via the input interface 180. The processing circuitry 150 may divide the target region into multiple partial regions according to the information input via the input interface 180. The multiple partial regions may be set by combining multiple methods described above. Furthermore, the processing circuitry 150 may limit the density of measurement points in each of the multiple partial regions to a specified density or less.

[0081] The processing circuitry 150 may refer to the density of measurement points in each of a plurality of partial regions and level the density of measurement points by removing data on measurement points in other partial regions so that the density is the same as the density of the partial region with the lowest density. For example, the point density of other partial regions may be reduced so that the point density is the same as the point density of the partial region with the furthest average distance from the beam emission unit 110 to each measurement point. If the surface of the object is flat, the beam incident angle will be larger in partial regions that are farther away from the beam emission unit 110.

[0082] Furthermore, if the density of measurement points in all of the set partial regions is equal to or greater than the specified density required for surface evaluation, the measurement point data may be removed from all of the multiple partial regions. The specified density required for surface evaluation may be, for example, the number of points required to determine the surface by fitting the measurement points. Furthermore, when evaluating a rough or patterned surface, for example, a density that covers the typical structural size of the surface with two or more measurement points may be set as the specified density. The typical structural size may be, for example, the width of the protrusions or recesses of the structure, the period of the protrusions and recesses, the height of the protrusions, or the depth of the recesses, as shown in FIG. 9A . Alternatively, the typical structural size may be the average width or average height of the rough surface, as shown in FIG. 9B .

[0083] FIG. 10A shows an example in which the density of measurement points is insufficient relative to the structure size. FIG. 10B shows an example in which the density of measurement points is appropriate relative to the structure size. FIG. 10C shows an example in which the density of measurement points is excessive relative to the structure size. In these figures, measurement points are indicated by circles. As shown in FIG. 10A, if the point density is too low, the shape obtained by 3D measurement deviates from the actual shape, reducing the reliability of the structure evaluation. As shown in FIG. 10B, if the structure size is covered by approximately two to five measurement points, 3D measurement results close to the true shape value can be obtained. On the other hand, as shown in FIG. 10C, if the number of measurement points is greater than necessary, the amount of data processing increases, which can lead to processing delays. Furthermore, because measurements contain noise, the measurement results vary around the true value. As a result, when results measured under conditions with different measurement point densities are evaluated, the evaluation results will vary. By introducing a process to uniformly distribute the measurement point density for each partial region, as in this embodiment, the variation in evaluation results can be reduced and the reliability of the evaluation can be improved.

[0084] If the object is concrete, for example, the typical structure size can be determined based on the size of the aggregate contained in the concrete. Alternatively, the typical structure size can be estimated by preliminary measurement. The specified density can be determined based on the information on the typical structure size thus obtained. For example, the processing circuit 150 may determine the specified density based on information on the scale of the irregularities on the surface of the object (e.g., one of the structure sizes exemplified above) input via the input interface 180. By limiting the density of measurement points in each partial area to the specified density or less, the load on the calculation process can be reduced while ensuring the minimum measurement accuracy required for surface evaluation.

[0085] The processing circuitry 150 may determine the plurality of partial regions and the predetermined density for the main measurement based on the results of a preliminary measurement that measures the distances of the plurality of measurement points in the target region without changing the density of the measurement points. The processing circuitry 150 may also limit the density of the measurement points in each of the plurality of partial regions for the main measurement to a predetermined density or less. In this way, the processing circuitry 150 may perform preliminary measurement to capture a rough overall image of the target, and then perform processing to set the partial regions and reduce the density difference of the measurement points. By performing such processing, it is possible to set appropriate partial regions and reduce the density difference even when the identity of the target is unknown.

[0086] Furthermore, if the required density was not achieved in some partial regions in the previous measurement or pre-measurement, an additional measurement may be performed on those partial regions to add more measurement points. That is, the processing circuitry 150 may increase the density of measurement points in at least one of the partial regions in the main measurement based on the results of the previous measurement or pre-measurement. By employing such a method, the measurement can be completed in a shorter time than if the measurement were to be performed again from scratch.

[0087] After measuring the distances of the multiple partial regions using the method described above, the processing circuitry 150 may extract data for an evaluation region, the region to be analyzed for shape, from the obtained data. The processing circuitry 150 may then analyze the shape from the data and output the results as needed. The shape analysis may be performed, for example, by extracting the shape using fitting or by evaluating the surface roughness. The data may be output, for example, by displaying the evaluation results for each partial region on a display device or by outputting the results as numerical data or other data.

[0088] In the above embodiment, the distance measuring device 100 acquires distance data for multiple measurement points by performing beam scanning. Instead of performing beam scanning, a distance measuring device may be used that acquires distance data for multiple measurement points using a light source 120 that emits diffused light, such as a laser or LED, and an image sensor. In this case, the scanning device 130 is not provided. In such a distance measuring device, the photodetector 140 includes an image sensor that outputs an image signal as a detection signal. The processing circuit 150 calculates the distance for each of multiple pixels in the image signal or each of multiple pixel regions in the image signal and outputs the calculated distance as the distance for the multiple measurement points. Even with such a configuration, a similar effect can be achieved by performing data processing to level the measurement point density.

[0089] Thus, the distance measuring device 100 that processes data includes a light source 120, a photodetector 140 that receives light irradiated by light from the light source 120 and reflected from the object and outputs a detection signal, and a processing circuit 150. The processing circuit 150 calculates the distance to each of multiple measurement points included in the target area of ​​the object based on the detection signal and generates measurement data that indicates the distribution of the distances or positions of the multiple measurement points. The processing circuit 150 performs processing on the measurement data to change the density of the measurement points in at least one of the multiple partial areas included in the target area so as to reduce the difference in density of the measurement points among the multiple partial areas, and outputs the measurement data with the changed density. This makes the density of the measurement points in the multiple partial areas closer to uniform, thereby improving the accuracy of analysis or evaluation of the shape of the object.

[0090] [Confirming Measurement Point Density Leveling Operation] In 3D measurement, a method for confirming whether a LiDAR sensor (i.e., a ranging device) is performing an operation to level the measurement point density by adjusting the scan angle step or processing data will be described. If the measurement point density leveling operation is not performed, when the same measurement object is measured from different angles or different distances, the measurement point density changes depending on the change in the angle of the beam emitted for measurement. In contrast, if the measurement point density leveling operation is performed, the amount of change in the measurement point density distribution within the measurement field of view or between different measurements can be reduced when the same measurement object is measured under different conditions. Therefore, it is possible to determine whether the ranging device is performing an operation to level the measurement point density based on the amount of change in the measurement point density distribution when measurements are performed under different conditions.

[0091] [Switching ON / OFF of the measurement point density leveling operation] In this system, the user may be able to switch ON / OFF the measurement point density leveling operation. By allowing the user to select ON / OFF of this operation, it becomes possible to acquire data without leveling the measurement point density. This makes it possible to compare results with and without leveling and to select the appropriate mode depending on the situation.

[0092] In this way, in a distance measuring device 100 equipped with a function for adjusting the angle step of the beam scan, the control circuit 160 may be configured to switch between a first mode in which the angle step of the beam scan is determined so as to reduce the difference in density of measurement points between regions of the object, and a second mode in which the angle step of the beam scan is kept constant, in response to operation by the user.

[0093] In addition, in a distance measuring device 100 having a function of leveling the density of measurement points through data processing, the processing circuit 150 may be configured to switch between a first mode in which a process for changing the density of measurement points in at least one of a plurality of partial areas is performed on the measurement data so as to reduce the density difference of measurement points in the plurality of partial areas, and a second mode in which a process for changing the density of measurement points is not performed, in response to an operation from the user.

[0094] [Range Measurement Using FMCW-LiDAR] Next, as an example of the distance measuring device 100, a specific example of the configuration and distance measurement operation of a LiDAR sensor that performs distance measurement using FMCW technology will be described.

[0095] Fig. 11 is a block diagram showing an example of the configuration of a LiDAR sensor 200, which is an example of a distance measuring device. In Fig. 11, thick arrows represent the flow of light, and thin arrows represent the flow of signals or data. Fig. 11 also shows an object to which distance is to be measured. The object may be, for example, an object with fine irregularities on its surface, such as a concrete surface or a wall.

[0096] The LiDAR sensor 200 shown in FIG. 11 includes a light source 210, an interference optical system 220, a photodetector 230, a processor 240, and a scanning device 250. In the example shown in FIG. 11, the processor 240 functions as both the processing circuit 150 and the control circuit 160. The light source 210 can change the frequency or wavelength of the emitted light in response to a control signal output from the processor 240. The interference optical system 220 separates the light emitted from the light source 210 into a reference light and an output light, and generates interference light by causing the reference light to interfere with the reflected light generated when the output light is reflected by an object. The interference light is incident on the photodetector 230.

[0097] The photodetector 230 receives the interference light and generates and outputs an electrical signal corresponding to the intensity of the interference light. This electrical signal is called a "detection signal." The photodetector 230 includes one or more light-receiving elements. The light-receiving elements include photoelectric conversion elements such as photodiodes. The photodetector 230 may be a sensor in which a plurality of light-receiving elements are two-dimensionally arranged, such as an image sensor.

[0098] The processor 240 controls the light source 210 and performs processing based on the detection signal output from the photodetector 230. The processor 240 functions as a control circuit that controls the light source 210 and the scanning device 250, and as a processing circuit that performs signal processing based on the detection signal. The processor 240 may be configured as a single circuit or may be a collection of multiple separate circuits. The processor 240 sends a control signal to the light source 210. The control signal causes the light source 210 to periodically change the frequency of the emitted light within a predetermined range. The processor 240 also sends a control signal to the scanning device 250 to change the emission direction of the light beam. The processor 240 further calculates the distance to each measurement point based on the detection signal output from the photodetector 230.

[0099] The light source 210 in this example includes a drive circuit 211 and a light-emitting element 212. The drive circuit 211 receives a control signal output from the processor 240, generates a drive current signal according to the control signal, and inputs the drive current signal to the light-emitting element 212. The light-emitting element 212 may be an element that emits laser light with high coherence, such as a semiconductor laser element. The light-emitting element 212 emits laser light whose frequency is modulated in response to the drive current signal.

[0100] The frequency of the laser light emitted from the light-emitting element 212 is modulated at a constant period. The frequency modulation period may be, for example, 1 microsecond (μs) or more and 10 milliseconds (ms) or less. The frequency modulation amplitude may be, for example, 100 MHz or more and 1 THz or less. The wavelength of the laser light may be, for example, in the near-infrared wavelength range of 700 nm or more and 2000 nm or less. In sunlight, the amount of near-infrared light is less than the amount of visible light. Therefore, by using near-infrared light as the laser light, the effects of sunlight can be reduced. Depending on the application, the wavelength of the laser light may be in the visible light wavelength range of 400 nm or more and 700 nm or less, or in the ultraviolet light wavelength range.

[0101] The control signal input from the processor 240 to the drive circuit 211 is a signal whose voltage fluctuates at a predetermined cycle and a predetermined amplitude. The voltage of the control signal can be modulated, for example, into a triangular wave or a sawtooth wave. A control signal whose voltage repeatedly changes linearly, such as a triangular wave or a sawtooth wave, can sweep the frequency of the light emitted from the light-emitting element 212 in a manner that is close to linear.

[0102] 11 includes a splitter 221, a mirror 222, and a collimator 223. The splitter 221 splits the laser light emitted from the light emitting element 212 of the light source 210 into reference light and output light, and combines the light reflected from the object with the reference light to generate interference light. The mirror 222 reflects the reference light back to the splitter 221. The collimator 223 includes a collimating lens and irradiates the output light at a nearly parallel divergence angle onto the object.

[0103] 11, the interference optical system 220 may be, for example, a fiber optical system. In this case, a fiber coupler may be used as the splitter 221. The reference light does not necessarily have to be reflected by the mirror 222, and the reference light may be returned to the splitter 221 by routing an optical fiber, for example.

[0104] The scanning device 250 may include, for example, a MEMS mirror or a galvanometer mirror. The scanning device 250 can change the output direction of the output light 22 by changing the angle of the mirror according to a command from the processor 240. This enables wide-range ranging by beam scanning. The scanning device 250 is not limited to the above configuration and may be, for example, a beam scanning device using an optical phased array and a slow-light waveguide, as described in International Publication No. WO 2019 / 230720.

[0105] Next, distance measurement using FMCW-LiDAR will be described. Distance measurement using FMCW-LiDAR is performed based on the frequency of interference light generated by interference between frequency-modulated reference light and reflected light.

[0106] FIG. 12 shows an example of the time changes in the frequencies of the reference light, reflected light, and interference light when the distance between the LiDAR sensor 200 and the object is constant (e.g., when both are stationary). Here, an example is described in which the frequency f of the light emitted from the light source 210 changes in a triangular wave shape, and the rate of change of the frequency per unit time is the same during the period when the frequency increases and the period when the frequency decreases. In the following description, the period when the frequency increases is referred to as the "up-chirp period," and the period when the frequency decreases over time is referred to as the "down-chirp period." In FIG. 12 , the dotted line represents the reference light, the dashed line represents the reflected light, and the thick solid line represents the interference light. The reflected light from the object is subject to a time delay depending on the distance relative to the reference light. Therefore, a certain difference occurs between the frequency of the reflected light and the frequency of the reference light depending on the distance, except immediately after the turnaround point of the frequency modulation. The interference light has a frequency corresponding to the frequency difference between the reference light and the reflected light. Therefore, the frequency f of the interference light during the up-chirp period is 1 / 2 s. Except immediately after the turnaround point of the frequency modulation, ｕｐ and the frequency f of the interference light during the down-chirp period ｄｏｗｎ is equal to . The photodetector 230 outputs a detection signal indicating the intensity of the interference light. This detection signal is called a beat signal, and the frequency of the beat signal is called the beat frequency. The beat frequency is equal to the frequency difference between the reference light and the reflected light. This frequency difference depends on the distance from the LiDAR sensor 200 to the object. Therefore, the distance from the LiDAR sensor 200 to the object can be calculated based on the beat frequency.

[0107] Here, the speed of light is c and the modulation frequency of the emitted light is f ＦＭＣＷ , the width of the frequency modulation of the emitted light (i.e., the difference between the highest and lowest frequencies) is Δf, and the beat frequency is f ｂ (=f ｕｐ = f ｄｏｗｎ ), and the distance from the LiDAR sensor 200 to the object is d. The modulation frequency f ＦＭＣＷ is the reciprocal of the period of the frequency modulation of the emitted light. The distance d can be calculated based on the following formula (1): d = c × f ｂ / (Δf × f ＦＭＣＷ ) × (1 / 4) (1)

[0108] The processing circuitry 150 can generate distance data for multiple measurement points by performing the above calculation for each measurement point. The processing circuitry 150 can further convert the distance data for the multiple measurement points into three-dimensional point cloud data based on information indicating the position and orientation of the beam emission unit of the LiDAR sensor 200.

[0109] The FMCW-LiDAR can measure not only the distance but also the speed of the target object. However, since the target object in this embodiment is a stationary object, the description of the speed measurement process will be omitted.

[0110] 11 , the processor 240 may change the step angle of the beam scan performed by the scanning device 250 in accordance with parameters such as the angle of the emitted light. In addition, the processor 240 may suppress variations in the density of the measurement points between regions by removing data of some of the measurement points from the generated three-dimensional point cloud data.

[0111] The distance measuring device is not limited to the LiDAR sensor 200 described above, but may be a sensor that measures distance using ToF technology. A distance measuring device using ToF technology measures the time from when light is emitted until the reflected light is received, and calculates the distance based on that time. The technology disclosed herein is applicable regardless of the type of distance measuring device.

[0112] As described above, a distance measuring device according to an embodiment of the present disclosure includes a light source that emits a light beam, a scanning device that performs beam scanning by changing the emission direction of the light beam, a photodetector that receives reflected light from a measurement point on an object irradiated with the light beam and outputs a detection signal, a processing circuit that calculates the distance to the measurement point based on the detection signal, and a control circuit that controls the scanning device. The control circuit determines an angle step for the beam scan so as to reduce the difference in density of the measurement points between regions on the object. This reduces variation in the density of the measurement points between regions, thereby improving the reliability of surface condition evaluation based on acquired data.

[0113] The control circuit may vary the angle step depending on the emission direction of the light beam. For example, the control circuit may reduce the angle step as the incident angle of the light beam on the object increases. This makes it possible to suppress changes in the density of measurement points caused by changes in the incident angle of the light beam on the object.

[0114] The control circuit may acquire information indicating a distance between the light source and the object, and change the angle step according to the distance. For example, the control circuit may decrease the angle step as the distance increases. This makes it possible to suppress changes in the density of measurement points due to changes in the distance between the light source and the object.

[0115] The control circuit may adjust the angle step of the beam scan in the main measurement that is performed after the pre-measurement based on the result of a pre-measurement that measures distances to a plurality of measurement points on the object by the beam scan. This makes it possible to estimate the overall measurement point density based on the data obtained in the pre-measurement, even if the surface of the object is not flat, and therefore makes it possible to appropriately determine the angle step of the scan in the main measurement.

[0116] The control circuit may set the angle step of the beam scan in the main measurement to be smaller in an area where the density of the measurement points in the preliminary measurement is lower, thereby reducing the difference in density of the measurement points between areas.

[0117] After the distance measuring device measures the distance to a first region of the object, the distance measuring device may be moved to measure the distance to a second region of the object. In this case, the control circuit may adjust the angle step of the beam scan in measuring the distance to the second region so as to reduce the difference between the density of the measurement points in the first region and the density of the measurement points in the second region. This reduces the difference in density of the measurement points between the first region and the second region.

[0118] The processing circuit may generate and output information indicating the surface roughness of a region including the plurality of measurement points based on the distance from the distance measuring device to each of the plurality of measurement points on the object. The information indicating the surface roughness may be, for example, one or more selected from the group consisting of arithmetic mean height Ra, root mean square height Rq, skewness Rsk, kurtosis Rku, and root mean square slope Rdq in a one-dimensionally extending region or a two-dimensionally extending region. By generating the information indicating the surface roughness, the surface condition of the object can be evaluated.

[0119] The control circuit may switch between a first mode in which the angle step of the beam scan is determined so as to reduce the density difference of the measurement points for each region of the object, and a second mode in which the angle step of the beam scan is constant, in response to a user operation. The user can switch between the first mode and the second mode, for example, via a user interface. This allows the user to compare data acquired by performing an operation to reduce the density difference of the measurement points for each region with data acquired without performing the operation, or to select either the first mode or the second mode depending on the purpose.

[0120] A distance measuring device according to another embodiment of the present disclosure includes a light source, a photodetector that receives light reflected from an object illuminated by the light from the light source and outputs a detection signal, and a processing circuit that calculates distances to each of a plurality of measurement points included in a target area of ​​the object based on the detection signal and generates measurement data indicating a distribution of distances or positions of the plurality of measurement points. The processing circuit performs processing on the measurement data to change the density of the measurement points in at least one of a plurality of partial areas included in the target area so as to reduce a difference in density of the measurement points among the plurality of partial areas. This suppresses variation in the density of the measurement points between areas and improves the reliability of surface condition evaluation based on the acquired data.

[0121] The light source may be configured to emit a light beam. The distance measuring device may further include a scanning device that performs beam scanning by changing the emission direction of the light beam. By beam scanning, information on the distance to each of a plurality of measurement points within a target area can be obtained with high accuracy.

[0122] The light source may be configured to emit diffused light. The photodetector may include an image sensor that outputs an image signal as the detection signal. The processing circuit may calculate the distance for each of a plurality of pixels in the image signal or for each of a plurality of pixel regions in the image signal, and output the calculated distance as the distance to the plurality of measurement points. This makes it possible to simultaneously obtain information on the distance to each of a plurality of measurement points within a target region.

[0123] The distance measuring device may further include an input interface for inputting information for setting the plurality of partial regions. The processing circuit may divide the target region into the plurality of partial regions according to the information input via the input interface. This allows, for example, a user to arbitrarily set the plurality of partial regions.

[0124] The processing circuit may reduce the difference in density of the measurement points among the plurality of partial regions by making the density of the measurement points in at least one remaining partial region of the plurality of partial regions closer to the density of the measurement points in the partial region with the smallest density of the measurement points. For example, the processing circuit may make the density of the measurement points in all remaining partial regions of the plurality of partial regions closer to or equal to the density of the measurement points in the partial region with the smallest density of the measurement points. Such processing makes it possible to equalize the density of the measurement points among the partial regions, thereby further improving the reliability of the surface shape evaluation.

[0125] The processing circuit may limit the density of the measurement points in each of the plurality of partial regions to a predetermined density or less. The predetermined density may be set, for example, to a density equal to or greater than the minimum density required for surface evaluation of the object. By limiting the density of the measurement points in each partial region to the predetermined density or less, the load of calculation processing can be reduced while ensuring the minimum measurement accuracy required for surface evaluation.

[0126] The distance measuring device may further include an input interface for inputting information regarding the scale of the unevenness of the surface of the object. The processing circuit may change the predetermined density in response to the input information. This allows, for example, a user to appropriately set the predetermined density depending on the object.

[0127] The processing circuit may determine the plurality of partial regions in the main measurement performed after the preliminary measurement based on a result of a preliminary measurement that measures the distances of the plurality of measurement points in the target region without changing the density of the measurement points, thereby making it possible to appropriately determine the plurality of partial regions based on data obtained in the preliminary measurement.

[0128] The processing circuit may determine the predetermined density based on the results of the preliminary measurement and limit the density of the measurement points in each of the partial regions in the main measurement to equal to or less than the predetermined density, thereby making it possible to set the predetermined density to an appropriate value based on the data obtained in the preliminary measurement.

[0129] The processing circuit may increase the density of the measurement points in at least one of the plurality of partial regions in the main measurement based on the results of the preliminary measurement. This makes it possible to supplement data for partial regions in which the density required for surface evaluation is not achieved by the main measurement alone with data obtained by the preliminary measurement. This makes it possible to obtain the necessary data with a reduced number of measurements.

[0130] The processing circuit may switch between a first mode in which a process of changing the density of the measurement points in at least one of the plurality of partial regions is executed on the measurement data so as to reduce a density difference of the measurement points in the plurality of partial regions, and a second mode in which the process of changing the density is not executed, in response to a user operation. This makes it possible to compare data acquired by performing an operation of reducing the density difference of the measurement points for each region with data acquired without performing the operation, or to select either the first mode or the second mode depending on a purpose.

[0131] According to yet another embodiment of the present disclosure, there is provided a method for controlling a distance measuring device including a light source that emits a light beam and a scanning device that performs beam scanning by changing the emission direction of the light beam, the method including: acquiring information regarding the emission direction of the light beam and / or the distance between the object and the light source based on the information, determining an angle step of the beam scanning based on the information so as to reduce a difference in density of measurement points between regions of the object, and performing the beam scanning based on the angle step.

[0132] According to yet another embodiment of the present disclosure, there is provided a data processing method for a distance measuring device including a light source and a photodetector that receives light reflected from an object illuminated by the light from the light source and outputs a detection signal, the method including: calculating distances to each of a plurality of measurement points included in a target area of ​​the object based on the detection signal; generating measurement data indicating a distribution of distances or positions of the plurality of measurement points; and performing a process on the measurement data to change the density of the measurement points in at least one of a plurality of partial areas included in the target area so as to reduce a difference in density of the measurement points among the plurality of partial areas.

[0133] In the above-described embodiment, information indicating surface roughness is calculated as an index for evaluating the surface condition of the object. However, the index for evaluating the surface condition is not limited to roughness. For example, when it is desired to evaluate the flatness of the surface of the object, the calculated evaluation index may be the degree of inclination of the surface in the target area.

[0134] The evaluation index may also be the size or surface area of ​​the target region.

[0135] The techniques of the present disclosure may be used in applications for making 3D measurements of structures such as buildings or industrial products made from materials such as concrete, metal, wood, or plastic.

[0136] 100 Distance measuring device 110 Beam emitting unit 120 Light source 130 Scanning device 140 Photodetector 150 Processing circuit 160 Control circuit 170 Storage device 180 Input device 190 Display device 200 LiDAR sensor 210 Light source 211 Drive circuit 212 Light emitting element 220 Interference optical system 221 Splitter 222 Mirror 223 Collimator 230 Photodetector 240 Processor 250 Scanning device

Claims

1. A distance measuring device comprising: a light source that emits a light beam; a scanning device that performs beam scanning by changing the emission direction of the light beam; a photodetector that receives reflected light from a measurement point on an object illuminated by the light beam and outputs a detection signal; a processing circuit that calculates the distance to the measurement point based on the detection signal; and a control circuit that controls the scanning device, wherein the control circuit determines the angle step of the beam scan so as to reduce the difference in density of the measurement points for each region on the object.

2. The distance measuring device according to claim 1, wherein said control circuit changes said angle step in accordance with the direction of emission of said light beam.

3. The distance measuring device according to claim 2, wherein the control circuit reduces the angle step as the incident angle of the light beam on the object increases.

4. A distance measuring device according to any one of claims 1 to 3, wherein the control circuit acquires information indicating the distance between the light source and the object, and changes the angle step in accordance with the distance.

5. The distance measuring device according to claim 4, wherein the control circuit reduces the angle step as the distance increases.

6. A distance measuring device as described in any one of claims 1 to 3, wherein the control circuit adjusts the angle step of the beam scan in the main measurement performed after the preliminary measurement based on the results of a preliminary measurement that measures the distances to multiple measurement points on the object using the beam scan.

7. The distance measuring device according to claim 6, wherein the control circuit reduces the angle step of the beam scan in the main measurement in an area where the density of the measurement points in the preliminary measurement is lower.

8. A ranging device as described in any one of claims 1 to 3, wherein, after the ranging device measures the distance of a first area of ​​the object, the ranging device is moved to measure the distance of a second area of ​​the object, the control circuit adjusts the angle step of the beam scan in measuring the distance of the second area so as to reduce the difference between the density of the measurement points in the first area and the density of the measurement points in the second area.

9. A distance measuring device as described in any one of claims 1 to 3, wherein the processing circuit generates and outputs information indicating the surface roughness in an area including the plurality of measurement points based on the distance from the distance measuring device to each of the plurality of measurement points on the object.

10. A distance measuring device as described in any one of claims 1 to 3, wherein the processing circuit generates and outputs information indicating the flatness of the surface in an area including the plurality of measurement points based on the distance from the distance measuring device to each of the plurality of measurement points on the object.

11. A distance measuring device as described in any one of claims 1 to 3, wherein the control circuit switches between a first mode in which the angle step of the beam scan is determined so as to reduce the density difference of the measurement points for each region of the object, and a second mode in which the angle step of the beam scan is kept constant, in response to operation by the user.

12. A distance measuring device comprising: a light source; a photodetector that receives reflected light from an object illuminated with light from the light source and outputs a detection signal; and a processing circuit that calculates the distance to each of a plurality of measurement points included in a target area of ​​the object based on the detection signal and generates measurement data that indicates the distribution of distances or positions of the plurality of measurement points, wherein the processing circuit performs a process on the measurement data that changes the density of the measurement points in at least one of the plurality of partial areas included in the target area so as to reduce the difference in density of the measurement points in the plurality of partial areas.

13. The distance measuring device according to claim 12, wherein the light source emits a light beam, and the distance measuring device further comprises a scanning device that performs beam scanning to change the emission direction of the light beam.

14. A distance measuring device as described in claim 12, wherein the light source emits diffused light, the photodetector includes an image sensor that outputs an image signal as the detection signal, and the processing circuit calculates the distance for each of a plurality of pixels in the image signal or each of a plurality of pixel regions in the image signal, and outputs the calculated distance as the distance to the plurality of measurement points.

15. A distance measuring device according to any one of claims 12 to 14, further comprising an input interface for inputting information for setting the plurality of partial regions, wherein the processing circuit divides the target region into the plurality of partial regions in accordance with the information input via the input interface.

16. A distance measuring device as described in any one of claims 12 to 14, wherein the processing circuit reduces the difference in density of the measurement points in the plurality of regions by bringing the density of the measurement points in at least one remaining partial region among the plurality of partial regions closer to the density in the partial region among the plurality of partial regions having the smallest density of the measurement points.

17. A distance measuring device according to any one of claims 12 to 14, wherein the processing circuit limits the density of the measurement points in each of the plurality of partial regions to a specified density or less.

18. The distance measuring device according to claim 17, further comprising an input interface for inputting information relating to the scale of the unevenness of the surface of the object, and wherein the processing circuit changes the specified density in accordance with the input information.

19. A distance measuring device according to any one of claims 12 to 14, wherein the processing circuit determines the plurality of partial areas in the main measurement performed after the pre-measurement based on the results of a pre-measurement that measures the distances to the plurality of measurement points in the target area without changing the density of the measurement points.

20. The distance measuring device according to claim 19, wherein the processing circuit determines the specified density based on the results of the preliminary measurement, and limits the density of the measurement points in each of the plurality of partial regions in the main measurement to be equal to or less than the specified density.

21. The distance measuring device according to claim 19, wherein the processing circuit increases the density of the measurement points in at least one of the plurality of partial regions in the main measurement based on the result of the pre-measurement.

22. A distance measuring device as described in any one of claims 12 to 14, wherein the processing circuit switches between a first mode in which a process for changing the density of the measurement points in at least one of the plurality of partial regions is performed on the measurement data so as to reduce the density difference of the measurement points in the plurality of partial regions, and a second mode in which the process for changing the density is not performed, in response to an operation from a user.

23. A control method for a distance measuring device equipped with a light source that emits a light beam and a scanning device that performs beam scanning to change the emission direction of the light beam, the control method including: acquiring information regarding the emission direction of the light beam and / or the distance between the object and the light source; determining an angle step for the beam scan based on the information so as to reduce the difference in density of measurement points between regions on the object; and performing the beam scan based on the angle step.

24. A data processing method for a distance measuring device equipped with a light source and a photodetector that receives reflected light from an object illuminated by light from the light source and outputs a detection signal, the data processing method including: calculating the distance to each of a plurality of measurement points included in a target area of ​​the object based on the detection signal; generating measurement data that indicates the distribution of distances or positions of the plurality of measurement points; and performing a process on the measurement data that changes the density of the measurement points in at least one of the plurality of partial areas included in the target area so as to reduce the difference in density of the measurement points in the plurality of partial areas.

Images