JP7584364B2 - Location determination method, location determination system, and program - Google Patents

Description

This disclosure relates to a location determination method, a location determination system, and a program.

There is a technology that detects the positional relationship with an object with high accuracy and controls a moving body or a robot using the detection result of the positional relationship. LiDAR (Light Detection and Ranging) is known as a technology that detects the positional relationship with an object. LiDAR is a technology that irradiates an object with a laser light while scanning it, and measures the distance and direction to the object based on the brightness of the reflected light. The reflected light is composed of a discrete point cloud, and a two-dimensional or three-dimensional shape indicated by the point cloud can be obtained based on the measurement value up to each point. The measurement value obtained by LiDAR contains errors due to the influence of the manufacturing error of the sensor that detects the reflected light and the installation error of the measuring device. Calibration is performed to correct such errors. For example, Patent Document 1 discloses a method of calibrating a distance measurement sensor that includes a light source that emits a light beam and a light receiver that outputs a signal according to the light receiving position of the light, and measures the distance to the object based on the output signal of the light receiver that receives the light beam reflected by the object.

Japanese Patent Application Publication No. 09-79844

If a specific target position can be set and the measured values of the distance and direction from the sensor to the target position measured by LiDAR can be compared with the exact distance and direction from the sensor to the target position to calculate the error between the two, the measurement accuracy of LiDAR can be improved by correcting the LiDAR measurement value by the calculated error. When performing calibration in this way, it is necessary to accurately identify the target position from the discrete point cloud of reflected light obtained by measurement with LiDAR.

The present disclosure provides a location identification method, a location identification system, and a program that can solve the above problems.

The position identification method disclosed herein includes the steps of extracting a boundary between point groups having different luminance based on the luminance pattern of reflected light when light is irradiated from a light source of an optical detection and ranging device to an object, assigning a line segment or curve to the boundary, and identifying a target position based on the line segment or curve, wherein in the step of identifying the target position, an intersection point of the assigned line segment or curve is extracted, and a predetermined position within an area having a plurality of the intersection points as vertices is identified as the target position.

The position identification system disclosed herein includes a means for extracting a boundary between point groups having different brightness based on the brightness pattern of reflected light when light is irradiated from a light source of an optical detection and ranging device to an object, a means for assigning a line segment or curve to the boundary, and a means for identifying a target position based on the line segment or curve , and the means for identifying the target position extracts an intersection point of the assigned line segment or curve, and identifies a predetermined position within an area having a plurality of the intersection points as vertices as the target position.

The program disclosed herein has a step of causing a computer to execute the steps of: extracting a boundary between point groups with different brightness based on the brightness pattern of reflected light when light is irradiated from a light source of an optical detection and ranging device onto an object; assigning a line segment or curve to the boundary; and identifying a target position based on the line segment or curve. In the step of identifying the target position, the computer is caused to execute a process of extracting an intersection point of the assigned line segment or curve, and identifying a specified position within an area having multiple intersection points as vertices as the target position .

The above-mentioned position identification method, position identification system, and program make it possible to identify a specific target position based on point cloud data measured by LiDAR.

1 is a block diagram showing an example of a proofreading support system according to an embodiment. FIG. 2 is a diagram illustrating an example of a target according to an embodiment. FIG. 1 is a first diagram illustrating a calibration procedure according to an embodiment. FIG. 11 is a second diagram illustrating a calibration procedure according to the embodiment. FIG. 11 is a third diagram illustrating a calibration procedure according to the embodiment. FIG. 4 is a fourth diagram illustrating a calibration procedure according to the embodiment. FIG. 2 is a first diagram showing another example of a target according to an embodiment. FIG. 2 is a second diagram showing another example of the target according to the embodiment. FIG. 11 is a third diagram showing another example of a target according to an embodiment. FIG. 4 is a fourth diagram showing another example of a target according to an embodiment. 4 is a flowchart illustrating an example of an operation of the calibration support device according to the embodiment. FIG. 2 is a diagram illustrating an example of a hardware configuration of a calibration support device according to an embodiment.

A proofreading support system according to the present disclosure will be described below with reference to FIGS.
In the following description, components having the same or similar functions are given the same reference numerals. Furthermore, duplicated descriptions of those components may be omitted. "XX or YY" is not limited to either XX or YY, but may include both XX and YY. This also applies to the case where there are three or more selective elements. "XX" and "YY" are any element (e.g., any information).

<Embodiment>
(composition)
FIG. 1 is a block diagram illustrating an example of a proofreading support system according to an embodiment.
The calibration support system 1 includes a calibration support device 10, a light detection and ranging device 20, and a target 30. The light detection and ranging device 20 has a laser light source capable of scanning a predetermined range, a sensor for detecting reflected light, and the like. The light detection and ranging device 20 is a LiDAR (Light Detection And Ranging) measurement device that irradiates a laser light to the target 30 and measures the distance and direction to the target 30. The target 30 is, for example, a calibration plate that is a target to which the light detection and ranging device 20 irradiates light. A pattern area 31 having a predetermined shape with a reflectance different from the surroundings is provided on the surface of the target 30. The shape of the pattern area 31 is a geometric pattern such as a straight line, a circle, a polygon, or a combination of these, and can be any shape as long as it is easy to assign lines and curves. The light detection and ranging device 20 measures the distance and direction to the target 30 and generates measurement data. The measurement data includes position information for each discrete point and brightness information of the reflected light. The position information is, for example, coordinate information of each point in a three-dimensional coordinate system with the light detection and ranging device 20 (for example, a sensor that detects reflected light) as the origin. The calibration support device 10 and the light detection and ranging device 20 are connected so that they can communicate with each other. The light detection and ranging device 20 outputs the generated measurement data to the calibration support device 10. The calibration support device 10 is composed of a computer, and when it acquires the measurement data from the light detection and ranging device 20, it calculates the correction amount (the "deviation amount" described later) required to calibrate the distance and direction obtained by the LiDAR.

The calibration support device 10 includes a data acquisition unit 11 , a setting reception unit 12 , a control unit 13 , a position identification unit 131 , a deviation amount calculation unit 132 , an output unit 14 , and a storage unit 15 .
The data acquisition unit 11 acquires measurement data from the light detection and distance measuring device 20 .
The setting reception unit 12 receives various setting information input by the user. For example, the setting reception unit 12 receives the setting of known accurate position information (position and direction from the light detection and ranging device 20) of the target position P in the pattern area 31. The target position P is preferably a position that is easy to specify geometrically based on the shape of the pattern area 31, such as the center of gravity or center of the pattern area 31. The target position P is used as a reference point for calibration.

The control unit 13 executes a process of calculating a correction amount for calibrating the measurement data of the light detection and ranging device 20. This process is composed of a process of identifying a target position P and a process of calculating the amount of deviation between true position information of the target position P and position information obtained by LiDAR measurement. The control unit 13 includes a position identification unit 131 and a deviation amount calculation unit 132.
The position specifying unit 131 specifies a target position P in the pattern area 31 based on the measurement data obtained by the light detection and distance measuring device 20, and calculates position information of the specified target position P.
The deviation amount calculation unit 132 calculates the difference between the accurate position information of the target position P accepted by the setting acceptance unit 12 and the position information of the target position P calculated by the position identification unit 131. This difference is the amount of deviation between the true position of the target position P and the measurement result by the LiDAR, so if the measurement result by the LiDAR for an arbitrary point is corrected by the amount of this deviation, the true position information for this point can be obtained.

The output unit 14 outputs the position information of the target position P identified by the position identification unit 131, the amount of deviation calculated by the deviation amount calculation unit 132, and the like to a display device, an electronic file, another device, or the like.
The storage unit 15 stores various information. For example, the storage unit 15 stores accurate position information of the target position P and the like.

(Identification of target position P)
The process of identifying the target position P will be described with reference to FIG. 2 to FIG. 6. FIG. 2 shows an example of the pattern region 31. The pattern region 31 shown in FIG. 2 has a cross shape. The user sets the target position P at the center of the cross. When the light detection and ranging device 20 irradiates a range including the pattern region 31 of the target 30 with laser light, discrete point cloud data as shown in the figure is obtained. Each point constituting the point cloud data is reflected light reflected at a position where the laser light actually hits. The pattern region 31 has a reflectance different from that of the region other than the pattern region 31 of the target 30. Therefore, the light reflected by the pattern region 31 in the point cloud data has a different luminance (brightness, shading) from that reflected by the other regions. For example, if the pattern region 31 is formed of a material with a high reflectance, the luminance of the reflected light from the pattern region 31 will be higher than the luminance of the reflected light from the other regions. By utilizing this property, the pattern region 31 can be distinguished from the other regions based on the luminance of the reflected light, and the shape of the pattern region 31 can be recognized.

First, as shown in FIG. 3, the pattern area 31 is placed within the measurement range of the light detection and ranging device 20, and the measurement range is irradiated with laser light while scanning it. The light detection and ranging device 20 calculates the position information of each point based on the point cloud data of the reflected light, and outputs measurement data including the position information for each point and the brightness information of the reflected light to the calibration support device 10. The data acquisition unit 11 acquires the measurement data.

The control unit 13 maps each point corresponding to the reflected light onto a three-dimensional space based on the position information included in the measurement data, and creates image data 40 showing each mapped point in a different manner based on the brightness information. An example of the created image data 40 is shown in FIG. 4. In FIG. 4, points with different brightnesses of reflected light are shown in different colors, and the shape of the pattern area 31 is displayed in a pseudo-superimposed manner (the shape of the pattern area 31 is not displayed in the image data 40). The position identification unit 131 extracts the boundary of the point group with different brightness based on the image data 40. This allows the geometric shape of the pattern area 31 to be extracted.

The position identification unit 131 assigns a line segment or a curve to the extracted boundary. This is shown in FIG. 5. Line segments 51 to 54 in FIG. 5 are an example of line segments assigned to the luminance boundary line. After the line segments are assigned, the position identification unit 131 calculates the intersection points of the assigned line segments. This is shown in FIG. 6. Points 61 to 64 in FIG. 6 are an example of intersection points. The position identification unit 131 extracts a quadrangle having points 61 to 64 as vertices. The position identification unit 131 then calculates the center of gravity of the extracted quadrangle (the center of gravity of the quadrangle is equal to the center of the cross shape) to identify the position of the target position P on the image data 40. By determining a geometric feature point such as the center of gravity as the target position P, the target position P can be easily identified from the figure (in this example, a quadrangle) identified by extracting the luminance boundary. However, the target position P is not limited to a geometric feature point such as the center of gravity, and any calculable point inside or outside the quadrangle can be set as the target position P.

Next, the position identification unit 131 calculates the position information of the target position P in the coordinate system of the optical detection and ranging device 20 from the positional relationship between each point corresponding to the reflected light on the image data 40 and the identified target position P, and the position information of each point included in the measurement data acquired from the optical detection and ranging device 20. This makes it possible to calculate the position information of the target position P in the actual environment.

The deviation calculation unit 132 calculates the "deviation amount" which is the difference between the accurate position information of the target position P accepted by the setting acceptance unit 12 and the position information of the target position P in the actual environment calculated by the position identification unit 131. The deviation amount may be expressed as an error in each of the XYZ coordinate axis directions, or may be expressed as an error for six parameters, namely, the error in each of the XYZ coordinate axis directions as well as the error in the angle around each of the row, pitch, and yaw coordinate axes. By calculating the deviation amount corresponding to the six degrees of freedom, it is possible to identify the orientation of the optical detection and ranging device 20 to the target 30 and the deviation in the installation position of the optical detection and ranging device 20, and by correcting these, it is possible to improve the measurement accuracy of the optical detection and ranging device 20.

Figures 7 to 10 show other examples of the shape of the pattern area 31. Figure 7 shows an example in which areas with different reflectance are arranged in a range other than the cross in a rectangular pattern area 31. In this case, too, the target position P is set at the center of the cross. In the example of Figure 7, as in the examples of Figures 2 to 6, the position identification unit 131 extracts the boundaries of the point groups with different luminance, assigns line segments 51a to 54a to the boundaries, extracts intersections 61a to 64a of the assigned line segments 51a to 54a, and identifies the center of gravity of a rectangle with these intersections 61a to 64a as vertices as the target position P.

Figure 8 shows an example in which a circular area with different reflectance is provided as the pattern area 31. The target position P is set at the center of the circle. In the example of Figure 8, the position identification unit 131 extracts the boundary between the point groups with different brightness, assigns a curve 51b to the boundary, and identifies the center of the area formed by the assigned curve 51b as the target position P.

Figure 9 shows an example of a pattern area 31 in which two triangles with opposing top-to-bottom orientations are arranged so that one vertex of each triangle overlaps, and the reflectance of the two triangular areas is made different from that of the other areas. Target position P is set at the point where the vertices of the two triangles overlap. In the example of Figure 9, position identification unit 131 extracts the boundary of the point group with different luminance, assigns line segments 51c to 54c to the boundary, extracts the intersection of the assigned line segments 51c to 54c, and identifies the intersection as target position P.

9, the target position P may be set at the center of gravity of each triangle, the position identification unit 131 may identify two target positions, and the deviation calculation unit 132 may calculate the deviation for each of the two target positions. By calculating the deviation for a plurality of target positions, it may be possible to perform more precise calibration. In the examples of FIGS. 7 and 8, the target position P is set inside a certain figure, but the target position P may be set outside the figure if the position can be identified. FIG. 10 shows an example of setting the target position P outside the pattern area 31. For example, for the pattern area 31 in FIG. 10, the center of gravity of the triangle formed by the straight line 53d assigned to the boundary, the straight line 54d, and the straight line 52d or the line extended from the straight line 54d is set as the target position P. In this example, the position identification unit 131 can identify the target position P based on the geometric characteristics of the figure formed using the assigned line segments and the extended line segments. The pattern area 31 may also be configured three-dimensionally.

(Operation)
Next, the operation of the calibration support device 10 will be described with reference to FIG.
FIG. 11 is a flowchart illustrating an example of the operation of the calibration support device according to the embodiment.
The target 30 provided with the pattern area 31 is placed in the measurement range of the light detection and ranging device 20. The user inputs true position information (distance and direction) from the light detection and ranging device 20 to the target position P in a state where the target 30 is placed to the calibration support device 10. The setting reception unit 12 acquires the true position information (step S1) and records it in the storage unit 15. Next, the user operates the light detection and ranging device 20 to measure the position information for the range including the pattern area 31 (step S2). The light detection and ranging device 20 generates measurement data and outputs it to the calibration support device 10. The measurement data includes position information and luminance information of each point that constitutes the point cloud. In the calibration support device 10, the data acquisition unit 11 acquires the measurement data (step S3) and records it in the storage unit 15. Next, the control unit 13 reads out the measurement data from the storage unit 15 and creates image data 40 in which points corresponding to the point cloud of reflected light are mapped in a three-dimensional space based on the position information of each point included in the measurement data (step S4). Based on the luminance information of each point included in the measurement data, the control unit 13 creates image data 40 in which the reflected light from the pattern area 31 and the reflected light from other areas are displayed in different modes, for example by setting a color corresponding to the luminance of the mapped points ( FIG. 4 ). For example, the image data 40 may be a distance image that includes depth information and luminance information for each pixel.

Next, the position identification unit 131 extracts the boundary between the point groups with different luminance based on the luminance pattern of the reflected light displayed in the image data 40 (step S5). The position identification unit 131 identifies the points corresponding to the reflected light from the pattern area 31 and the points corresponding to the reflected light from other areas based on the colors assigned to each point in the image data 40, and extracts the boundary between them.

Next, the position identification unit 131 assigns a line segment or the like to the extracted boundary (step S6). For example, if the extracted boundary is a straight line, the position identification unit 131 assigns a line segment along the extracted boundary (for example, line segments 51 to 54 in FIG. 5). For example, if the extracted boundary is a curved line, the position identification unit 131 assigns a line segment along the extracted boundary (for example, curve 51b in FIG. 8).

Next, the position identification unit 131 identifies the target position P based on the assigned line segments or curves (step S7). For example, the position identification unit 131 may identify a position within an area formed by the assigned line segments, etc. as the target position P (Figure 8). For example, the position identification unit 131 may extract intersections of the assigned line segments, etc., and identify a position within an area having multiple intersections as vertices as the target position P (Figures 6, 7, and 10). For example, the position identification unit 131 may extract intersections of the assigned line segments, etc., and identify the intersections as the target position P (Figure 9). For example, the position identification unit 131 may extend the assigned line segments, etc., and identify a position within an area formed by the extended line segments, etc. as the target position P (Figure 10).

When the target position P is identified on the image data 40, the position identification unit 131 calculates position information of the target position P in the actual environment (step S8). For example, the position identification unit 131 calculates the positional relationship between the target position P in the image data 40 and one or more points P' existing around it, and applies the calculated positional relationship to the positional information indicated by the reflected light corresponding to point P' included in the measurement data measured by the light detection and ranging device 20, thereby calculating the positional information of the target position P as seen by the light detection and ranging device 20.

Next, the deviation amount calculation unit 132 calculates the difference between the position information of the target position P calculated in step S7 and the true position information of the target position P set in step S1 to calculate the deviation amount (step S9). The output unit 14 outputs the information on the deviation amount calculated by the deviation amount calculation unit 132 to a display device or the like.

For example, the optical detection and ranging device 20 is installed on a robot (not shown) equipped with a manipulator. The robot's control device uses the optical detection and ranging device 20 to measure the position information of obstacles and work objects within the range in which the manipulator operates, and moves the manipulator to the work object while avoiding the obstacles to perform the work. In such a case, by using the deviation amount output in step S8, it is possible to correct the tilt or deviation of the installation position that occurred when the optical detection and ranging device 20 was installed on the robot. After redoing the installation, steps S1 to S8 may be performed again to check whether the deviation amount has been corrected, and the installation position may be corrected repeatedly until the deviation amount is within the allowable range. In addition, the deviation amount that cannot be corrected by correcting the installation position may be due to a manufacturing error of the optical system of the optical detection and ranging device 20. For example, the user can configure the robot's control device to incorporate software that corrects the deviation amount output in step S8, correct the measurement result of the optical detection and ranging device 20 using this software, and control the operation of the manipulator based on the corrected position information. For example, in a nuclear power plant where a robot equipped with a manipulator is remotely operated to perform work, mounting the light detection and ranging device 20 calibrated using the calibration support system 1 of this embodiment on the robot makes it possible to accurately grasp the surrounding environment in three dimensions, improving maneuverability and interference prevention (safety) performance.

(effect)
As described above, according to this embodiment, an arbitrary target position P in the target 30 can be identified using the measurement results of the LiDAR. If the target position P can be identified, the amount of deviation of the measurement position obtained by the LiDAR can be grasped by comparing the position information based on the LiDAR measurement of the identified target position P with the true position information of the target position P. By grasping the amount of deviation, the installation of the light detection and ranging device 20 can be corrected to reduce the amount of deviation and improve the measurement accuracy. Alternatively, by grasping the amount of deviation, a method for correcting the measurement results by the LiDAR can be known, and the measurement accuracy of the LiDAR can be improved by using software that corrects the measurement results.

FIG. 12 is a diagram showing an example of the hardware configuration of a calibration support device according to an embodiment. The computer 900 includes a CPU 901, a main memory device 902, an auxiliary memory device 903, an input/output interface 904, and a communication interface 905. The above-mentioned calibration support device 10 is implemented in the computer 900. The above-mentioned functions (data acquisition unit 11, setting reception unit 12, control unit 13, position identification unit 131, and deviation amount calculation unit 132) are stored in the auxiliary memory device 903 in the form of a program. The CPU 901 reads the program from the auxiliary memory device 903, expands it in the main memory device 902, and executes the above-mentioned processing according to the program. The CPU 901 secures a storage area in the main memory device 902 according to the program. The CPU 901 secures a storage area in the auxiliary memory device 903 for storing data being processed according to the program.

A program for realizing all or part of the functions of the proofreading support device 10 may be recorded on a computer-readable recording medium, and the program recorded on the recording medium may be read into a computer system and executed to perform processing by each functional unit. The term "computer system" here includes hardware such as an OS and peripheral devices. In addition, if a WWW system is used, the term "computer system" also includes a homepage providing environment (or display environment). In addition, the term "computer-readable recording medium" refers to portable media such as CDs, DVDs, and USBs, and storage devices such as hard disks built into a computer system. In addition, if the program is distributed to a computer 900 via a communication line, the computer 900 that receives the program may expand the program into the main storage device 902 and execute the above processing. In addition, the above program may be for realizing part of the functions described above, and may further be capable of realizing the functions described above in combination with a program already recorded in the computer system.

As described above, several embodiments of the present disclosure have been described, but all of these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents as described in the claims, as well as in the scope and gist of the invention.

<Additional Notes>
The location identification method, the location identification system, and the program described in each embodiment can be understood, for example, as follows.

(1) The position identification method according to the first aspect includes a step (S4) of extracting a boundary between point groups having different luminance based on the luminance pattern of reflected light when light is irradiated from a light source of the optical detection and ranging device 20 to an object, a step (S5) of assigning a line segment or a curve to the boundary, and a step (S6) of identifying a target position based on the line segment or the curve.
This makes it possible to identify a reference position for calculating the amount of correction (amount of deviation) required for the configuration of the light detection and distance measuring device 20.

(2) A position identification method according to a second aspect is the position identification method of (1), in which in the step of identifying the target position, a predetermined position within an area formed by the assigned line segment or curve is identified as the target position.
By assigning lines or curves and extracting an area (figure, geometric pattern) formed by the lines, etc., it is possible to identify a target position P set within the area based on the shape and outer edge of the area.

(3) A position identification method according to a third aspect is the position identification method of (1), in which, in the step of identifying the target position, an intersection point of the assigned line segment or curve is extracted, and a specified position within an area having a plurality of the intersection points as vertices is identified as the target position.
By extracting the intersections of lines or curves and extracting areas (figures, geometric patterns) with those intersections as vertices, it is possible to identify a target position P set within the area based on the shape and outer edges of the extracted area.

(4) A position specifying method according to a fourth aspect is the position specifying method according to (2) or (3), in which the target position is a center of gravity or a center of the area.
By setting the target position P at the center of gravity or the center of the area, even if the square to be extracted is distorted and extracted as a parallelogram or trapezoid due to the influence of measurement errors, etc., it is possible to specify an approximation of the target position P (if it is the center of gravity or the center, it is not greatly affected by such distortions or errors). By setting the target position P at the center of gravity or the center of the area, it is possible to specify the target position P by geometric calculation.

(5) A position identification method according to a fifth aspect is the position identification method of (1), in which in the step of identifying the target position, an intersection of the assigned line segment or curve is extracted, and the intersection is identified as the target position.
This makes it possible to specify the target position P when a vertex of a figure or the like is set as the target position P.

(6) A position identification method according to a sixth aspect is a position identification method according to any one of (1) to (5), further comprising a step of calculating an amount of deviation between the identified target position and a position where the target position should actually be detected.
By calculating the amount of deviation, the light detection and distance measuring device 20 can be calibrated.

(7) A position identification method according to a seventh aspect is a position identification method according to any one of (1) to (6), in which an area (pattern area 31) of a known shape having a reflectance different from that of its surroundings is provided on the object (target 30), and the object is placed at a position whose positional relationship with the light source is known.
By providing an area of a known shape with reflectance, it becomes possible to extract the boundary between point groups with different brightness, and by installing it at a position with a known positional relationship to the light source, it becomes possible to calculate the amount of deviation.

(8) The position identification system (calibration support system 1) relating to the eighth aspect includes a means (position identification unit 131) for extracting a boundary between point groups with different luminance based on the luminance pattern of reflected light when light is irradiated from a light source of the light detection and ranging device 20 to an object (target 30), a means (position identification unit 131) for assigning a line segment or curve to the boundary, and a means (position identification unit 131) for identifying a target position based on the line segment or curve.

(9) The position identification system (calibration support system 1) according to the ninth aspect is the position identification system of (9), further comprising an object (target 30) having an area (pattern area 31) with a reflectance different from that of the surrounding area, and a light detection and ranging device 20 that irradiates light onto the object to measure the distance to the object.

(10) A program according to the tenth aspect causes a computer to execute the steps of extracting a boundary between point groups with different luminance based on the luminance pattern of reflected light when a light source of a light detection and ranging device shines light on an object, assigning a line segment or a curve to the boundary, and identifying a target position based on the line segment or the curve.

1: Calibration support system 10: Calibration support device 11: Data acquisition unit 12: Setting reception unit 13: Control unit 131: Position identification unit 132: Deviation amount calculation unit 14: Output unit 15: Memory unit 20: Light detection and ranging device 30: Target 31: Pattern area 900: Computer 901: CPU
902: Main memory device 903: Auxiliary memory device 904: Input/output interface 905: Communication interface

Claims (7)

extracting a boundary between point groups having different luminance based on a luminance pattern of reflected light when a light source of the light detection and ranging device is irradiated onto the target object;
assigning lines or curves to the boundary;
identifying a target position based on the line segment or the curve;
having
In the step of identifying the target position,
extracting intersections of the assigned line segments or curves, and specifying a predetermined position within an area having a plurality of the intersections as vertices as the target position;
Location method. the target location is a location based on a geometric feature of the area or a centroid or center of the area;
The method of claim 1 . calculating a deviation amount between the specified target position and a position where the target position should be detected;
The method of claim 1 , further comprising: The object is provided with a region of a known shape having a reflectance different from that of the surrounding area, and the object is placed at a position with a known positional relationship with the light source.
The method for identifying a position according to any one of claims 1 to 3 . A means for extracting a boundary between point groups having different luminance based on a luminance pattern of reflected light when a light source of the light detection and ranging device is irradiated onto an object;
means for assigning lines or curves to said boundary;
A means for identifying a target position based on the line segment or the curve;
Equipped with
The means for identifying the target position includes:
extracting intersections of the assigned line segments or curves, and specifying a predetermined position within an area having a plurality of the intersections as vertices as the target position;
Location system. An object having an area having a reflectance different from that of its surroundings;
a light detection and ranging device that irradiates light onto the object and measures the distance to the object;
The location system of claim 5 further comprising: On the computer,
extracting a boundary between point groups having different luminance based on a luminance pattern of reflected light when a light source of the light detection and ranging device is irradiated onto the target object;
assigning lines or curves to the boundary;
identifying a target position based on the line segment or the curve;
having
In the step of identifying the target position,
A process of extracting intersections of the assigned line segments or curves, and specifying a predetermined position within an area having a plurality of the intersections as vertices as the target position;
A program that executes the following.

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