Mobile body and guiding line detection apparatus

Abstract

To provide a guiding line detection apparatus which can detect a guiding line more properly.SOLUTION: A guiding line detection apparatus 2 includes: an image acquisition unit 11 which acquires a captured image of a front view of a mobile body 1 that moves along a guiding line on a floor surface; an image conversion unit 12 which converts the captured image into an overhead view image; a setting unit 14 which sets parameters to be used for grayscale conversion; a grayscale conversion unit 15 which converts the captured image into a grayscale image, using the parameters, so that a difference from a value of a pixel in a reference color may be increased as a difference in a color from the reference color increases; and a detection unit 16 which detects the guiding line in the captured image converted by the image conversion unit 12 and the grayscale conversion unit 15. The setting unit 14 sets parameters using the captured image. Accordingly, the guiding line can be detected more stably by setting the parameters.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a guiding line detection device that detects a visually recognizable guiding line provided on a floor surface, and a moving body that moves using the detected guiding line.

Background Art

[0002] Conventionally, in factories and the like, a guiding line provided on a floor surface has been detected, and a moving body has been moved along the detected guiding line. As a related technique, a luminance gradient vector of a photographed image of a road has been calculated, and a lane line on the road has been detected using the luminance gradient vector (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, when using luminance, it becomes difficult to stably detect a target guiding line in a photographed image when the lighting changes in the morning or evening, or when the difference in luminance between the guiding line and its surroundings is small.

[0005] The present invention has been made to solve the above problems, and an object thereof is to provide a guiding line detection device that can more stably detect a guiding line when a moving body moves, and a moving body that moves using the detected guiding line.

Means for Solving the Problems

[0006] To achieve the above object, an induction line detection device according to an aspect of the present invention includes an image acquisition unit that acquires a captured image obtained by capturing the front of a moving body that moves according to a visually recognizable induction line provided on a floor surface; an image conversion unit that converts the captured image into a captured image viewed from above; a setting unit that sets one or more parameters related to a reference color that is the color of the induction line and that is used when converting the captured image into grayscale; a grayscale conversion unit that converts the captured image into grayscale such that the difference from the value of the pixel of the reference color becomes larger as the color difference from the reference color that is the color of the induction line becomes larger, using the one or more parameters set by the setting unit; and a detection unit that detects an induction line in the captured image that has been subjected to the image conversion by the image conversion unit and the grayscale conversion by the grayscale conversion unit, wherein the setting unit sets the one or more parameters using the captured image.

Effects of the Invention

[0007] According to an induction line detection device or the like according to an aspect of the present invention, by setting parameters related to the color of the induction line when the moving body moves, it becomes possible to detect the induction line more stably.

Brief Description of the Drawings

[0008]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Embodiment for Carrying out the Invention

[0009] Hereinafter, the moving body and the guiding line detection device according to the present invention will be described using embodiments. In the following embodiments, components and steps denoted by the same reference numerals are the same or corresponding, and repeated descriptions may be omitted. The guiding line detection device according to the present embodiment sets a plurality of parameters when performing grayscale conversion so as to more appropriately detect the guiding line.

[0010] FIG. 1 is a block diagram showing the configuration of the moving body 1 according to the present embodiment. The moving body 1 according to the present embodiment moves according to a visually recognizable guiding line provided on the floor surface, and includes a guiding line detection device 2, a moving mechanism 17 that moves the moving body 1, and a movement control unit 18 that controls the moving mechanism 17 using the detection result of the guiding line by the guiding line detection device 2. The guiding line detection device 2 includes an image acquisition unit 11, an image conversion unit 12, a storage unit 13, a setting unit 14, a grayscale conversion unit 15, and a detection unit 16. The use of the moving body 1 is not particularly limited, but the moving body 1 may be, for example, a moving body that performs transportation, or a moving body for other uses such as security and cleaning.

[0011] It is assumed that a guiding line is provided on the floor surface of the moving environment of the moving body 1. The floor surface of the moving environment is preferably horizontal normally. The guiding line may be provided, for example, to guide the moving body 1, or may be a partition line or the like for partitioning other uses, such as a passage for people or a traveling area for a forklift. The guiding line may be, for example, a tape-like one such as vinyl tape pasted on the floor surface, or may be provided by applying paint to the floor surface. The guiding line is preferably a line with a certain width, for example. The guiding line is visually recognizable. That is, the guiding line can be detected in the image. Since the guiding line is visually recognizable, it is preferably a color different from that of the floor surface. The guiding line may be, for example, a line of a specific color determined in advance. Also, the guiding line may be, for example, a straight line or a curve. In the present embodiment, the case where the guiding line is a straight line will be mainly described.

[0012] FIG. 2 is a plan view showing an example of the situation in a factory where a guiding line 5 is provided on the floor surface. In FIG. 2, it is assumed that the guiding line 5 is a partition line for partitioning the passage for people near the arrangement 7 in the factory and the traveling area for the forklift.

[0013] The image acquisition unit 11 acquires a captured image of the front of the moving body 1. The image acquisition unit 11 may be, for example, an optical device such as a camera that captures an image, or may be one that acquires an image captured by an optical device such as a camera. In the present embodiment, the case where the image acquisition unit 11 is a camera will be mainly described. The captured image is preferably a color image. The image acquisition unit 11 preferably repeats the acquisition of the captured image. The image acquisition unit 11 may, for example, repeatedly acquire the captured image periodically or irregularly. Also, the image acquisition unit 11 may, for example, acquire a moving image. In this case, one frame constituting the moving image may be considered as the captured image.

[0014] The optical axis of the camera for taking the captured image is preferably usually directed forward in the traveling direction of the moving body 1. The optical axis may, for example, extend in the horizontal direction, or may be directed toward the floor side so that the depression angle has a positive value. Even in the latter case, it is preferable that an area far in the traveling direction is also included in the captured image. Also, for example, the captured image may be taken so that the left-right direction of the captured image is the horizontal direction of the real space. FIG. 3 is a diagram showing an example of the captured image taken when the moving body 1 exists at the position shown in FIG. 2. As shown in FIG. 3, the captured image becomes an image with perspective.

[0015] The image conversion unit 12 converts the captured image acquired by the image acquisition unit 11 into a captured image viewed from above. Note that the converted captured image may also be referred to as a planar image. The planar image, which is a captured image viewed from above, may be, for example, an image viewed from a direction perpendicular to the floor surface, for example, the vertical direction. The image conversion unit 12 may, for example, convert the captured image into a planar image by a homography transformation. Note that a method for converting a captured image into a planar image is known, and a detailed description thereof will be omitted. FIG. 4 is a diagram showing an example of the planar image obtained by converting the captured image shown in FIG. 3. As shown in FIG. 4, the planar image becomes an image without perspective. The image conversion unit 12 may, for example, repeatedly convert each of the acquired captured images into a planar image, which is a captured image viewed from above.

[0016] In the storage unit 13, a plurality of parameters regarding the reference color, which is the color of the guiding line used when converting the captured image to grayscale, are stored. This reference color is the color of the guiding line in the captured image. As described above, the color of the guiding line provided on the floor surface of the moving environment of the moving body 1 is usually a predetermined color, but in the captured image in which it is captured, the color of the guiding line will vary depending on changes in lighting and the like. Therefore, the reference color changes according to the light conditions at the time of capturing the guiding line and the like. The plurality of parameters may include, for example, a parameter indicating the reference color. These plurality of parameters will be described later. The storage unit 13 is preferably realized by a non-volatile recording medium, but may also be realized by a volatile recording medium. The recording medium may be, for example, a semiconductor memory or a magnetic disk. The plurality of parameters stored in the storage unit 13 may be, for example, those accumulated by the setting unit 14.

[0017] The setting unit 14 sets a plurality of parameters using the captured image. The captured image used for setting the plurality of parameters may be, for example, a planar image after grayscale conversion or a color planar image. The setting unit 14 may set a plurality of parameters each time the moving body 1 starts moving. In this case, each time the movement of the moving body 1 from the departure point to the destination starts, a plurality of parameters can be set according to the situation at that time. In this way, appropriate parameters according to the lighting at the start of movement can be set, and more appropriate detection of the guiding line can be performed during movement. Further, the setting unit 14 may, for example, also set a plurality of parameters at predetermined time intervals. That is, the setting unit 14 may set a plurality of parameters each time movement starts and also set a plurality of parameters at predetermined time intervals after the start of movement. In this case, for example, after the start of movement, the plurality of parameters may be set at predetermined time intervals such as every 10 minutes or every 30 minutes. In this way, by setting a plurality of parameters at predetermined time intervals, for example, even when the lighting changes according to the movement, a plurality of parameters can be set according to the lighting at that time. Note that the setting of the plurality of parameters will be described later.

[0018] The grayscale conversion unit 15 uses a plurality of parameters set by the setting unit 14 to perform grayscale conversion on the captured image such that the difference from the value of the pixel of the reference color, which is the color of the guiding line, becomes larger as the color difference from the reference color becomes larger. That is, when converting a pixel of a certain color to grayscale, the closer the color is to the reference color, the closer the value of the pixel after grayscale conversion is to the value of the pixel of the reference color after grayscale conversion, and the farther the color is from the reference color, the farther the value of the pixel after grayscale conversion is from the value of the pixel of the reference color after grayscale conversion. For example, when converting to 8-bit grayscale, the value of the pixel of the reference color may be set to 255, and the grayscale conversion may be performed such that the value becomes closer to 0 as the color difference from the reference color becomes larger. By doing so, the guiding line can be detected more stably in the converted grayscale planar image. In this case, as an example, the grayscale conversion may be performed such that pixels closer to the reference color have larger luminance values. For example, the guiding line of the reference color may be converted to white by grayscale conversion. A more specific method of grayscale conversion will be described later. Note that the grayscale conversion unit 15 may, as an example, perform grayscale conversion on the captured image after conversion by the image conversion unit 12. In the present embodiment, this case will be mainly described. FIG. 5 is a diagram showing an example of a captured image obtained by performing grayscale conversion on the planar image shown in FIG. 4. For example, as shown in FIG. 5, in the captured image after grayscale conversion, the luminance value of the guiding line 5 may be the largest value. The grayscale conversion unit 15 may, for example, convert each of the repeatedly acquired planar images into a grayscale image.

[0019] Note that the order of performing the image conversion by the image conversion unit 12 and the grayscale conversion by the grayscale conversion unit 15 on the captured image is not limited. For example, grayscale conversion may be performed after converting the captured image into a planar image, or the captured image may be converted into a planar image after performing grayscale conversion. In the present embodiment, the former case will be mainly described.

[0020] The detection unit 16 detects the guiding line in the captured image that has been subjected to image conversion by the image conversion unit 12 and grayscale conversion by the grayscale conversion unit 15. As an example, the detection unit 16 may detect the guiding line by a Hough transform in the captured image after conversion by the image conversion unit 12 and the grayscale conversion unit 15. For example, when the guiding line is a straight line, the detection unit 16 may perform a Hough transform to detect the straight line. The detection unit 16 may also detect the guiding line by template matching or feature point extraction. As an example, when the guiding line is a straight line, the detection unit 16 may detect the guiding line by using a straight-line template image. In addition, when the feature point extraction is performed, the detection unit 16 may extract feature points such as SIFT key points or SURF key points, and detect the guiding line including the feature points. The detection result by the detection unit 16 may be, for example, information indicating the position of the guiding line in the image.

[0021] In addition, when the width of the guiding line is large in the captured image after conversion by the image conversion unit 12 and the grayscale conversion unit 15, the detection unit 16 may detect the guiding line after performing, for example, thinning processing. This is because thinner lines are more suitable for detection. The thinning processing may be, for example, image processing in which a line having a width is thinned by narrowing the line width, or edge detection. As the former thinning processing, for example, Tamura, Hilditch, Zhang-Suen, and other algorithms that thin an image after binarizing it are known. In the latter edge detection, edges on both sides of the width direction of the guiding line are usually detected, but, for example, edge detection may be performed so that only one edge is left. In order to leave only one edge, for example, when detecting an edge using a differential value such as a brightness value, only pixels whose differential value is greater than a positive threshold value may be detected as edges, and pixels whose differential value is less than a negative threshold value may not be detected as edges.

[0022] Also, when a plurality of guiding lines are included in the planar image, the moving body 1 may also detect guiding lines other than the guiding line currently used for movement. As a result, when the moving body 1 is moving according to a certain guiding line, there is a possibility that it may erroneously move according to a different guiding line. To avoid such inappropriate movement, the detection unit 16 may be configured to detect the guiding line only in the vicinity of the guiding line used in the current movement. In this case, the detection unit 16 may, for example, detect a new guiding line within a range where the detected guiding line is rotated by a predetermined angle around the moving body 1 and within a range where the detected guiding line is translated parallel by a predetermined distance. Note that the detected guiding line may be, for example, the guiding line detected immediately before. More precisely, the center around the moving body 1 may be, for example, the center of gravity of the moving body 1 or the turning center of the moving body 1.

[0023] FIG. 6 is a diagram for explaining the range in which the guide line is detected. In FIG. 6, it is assumed that the xy orthogonal coordinate system is the local coordinate system of the moving body 1. Also, it is assumed that the origin of the local coordinate system is the center of gravity of the moving body 1. In this case, when the detection unit 16 newly detects the guide line, in the grayscale image 30, the last detected guide line 31 is rotated around the origin of the local coordinate system of the moving body 1, that is, the moving body 1, within a predetermined angle range, for example, from -α (deg) to +α (deg), and the range 32, and the last detected guide line 31 is moved by -β to +β in the y-axis direction, which is perpendicular to the traveling direction (x-axis direction), and the range 33. The guide line may be detected within the merged range. α and β are, for example, positive real numbers that are not too large and may be set in advance. Note that the ranges 32 and 33 may be the ranges of the regions through which the guide line 31 passes when the detected guide line 31 is rotated or moved within a predetermined range. In this way, the range in which the guide line is detected can be limited, and it is possible to prevent the detection of guide lines other than the guide line used for the current movement. For example, when the guide line is detected within the range obtained by rotating the detected guide line by a predetermined angle around the center of gravity of the grayscale image 30, it is necessary to increase the angle by which the guide line is rotated to some extent. However, by detecting the guide line within the range obtained by rotating the detected guide line by a predetermined angle around the moving body 1, the angle by which the guide line is rotated can be made smaller, and the detection range of the guide line can be more limited.

[0024] The moving mechanism 17 moves the moving body 1. In the present embodiment, the case where the moving mechanism 17 is a mechanism for running the moving body 1 on the floor surface will be mainly described. The moving mechanism 17 may be, for example, capable of moving the moving body 1 in all directions, or may not be. Being able to move in all directions means being able to move in an arbitrary direction. The moving mechanism 17 may have, for example, a traveling unit (such as wheels) and a driving means (such as a motor or an engine) for driving the traveling unit. In addition, when the moving mechanism 17 is capable of moving the moving body 1 in all directions, the traveling unit may be an omnidirectional wheel (such as an omni wheel or a mecanum wheel). Since a known moving mechanism 17 can be used, a detailed description thereof will be omitted.

[0025] The movement control unit 18 controls the moving mechanism 17 so that the moving body 1 moves according to the detected guiding line. For example, the moving body 1 moving according to the guiding line may mean that the moving body 1 moves along the guiding line. When the position of the guiding line in the image is specified by the detection unit 16, the position of the guiding line in the local coordinate system of the moving body 1 can be specified using the specification result. Therefore, the movement control unit 18 may control the moving mechanism 17 using the position of the guiding line in the local coordinate system of the moving body 1 so that movement according to the guiding line is performed.

[0026] How the moving body 1 moves along the guiding line may be set in advance. Then, the movement control unit 18 may control the movement according to the guiding line by using, for example, the movement distance obtained by using an encoder or the like provided in the movement mechanism 17 according to the setting. For example, the movement control unit 18 may move the moving body 1 along the guiding line by a predetermined distance, change the traveling direction of the moving body 1 to a predetermined direction at the branch point of the guiding line after the movement, and then repeat the process of moving the moving body 1 along the guiding line by a predetermined distance again. Further, the movement control unit 18 may stop the moving body 1 at a predetermined position. And at that position, for example, loading and unloading of the object to be conveyed may be performed.

[0027] Also, when a marker is arranged in the movement area of the moving body 1, the movement control unit 18 may perform movement control using the marker. The marker may indicate, for example, the stop position of the moving body 1 or the traveling direction of the moving body 1 at the branch point of the guiding line. In this case, for example, the movement control unit 18 may detect the marker by using template matching or the like in the captured image which is a planar image before grayscale conversion, and perform movement control using the detected marker. As an example, the marker may be arranged on the guiding line.

[0028] Movement along the guiding line may be, for example, moving along the guiding line on the guiding line. Further, movement along the guiding line may be moving along a virtual line parallel to the guiding line on the virtual line. The virtual line does not exist in the moving area of the moving body 1, that is, it is a line that cannot be visually observed in the real environment. In this case, the moving body 1 can move parallel to the guiding line at a position different from the guiding line. For example, even when using a partition line or the like provided near an arrangement in a factory or the like as the guiding line, by making the moving body 1 move on a virtual line parallelly moved in a direction away from the arrangement along the guiding line, the possibility of the moving body 1 contacting the arrangement can be reduced. As an example, the distance between the guiding line and the virtual line may be set in advance.

[0029] Next, a plurality of parameters used in grayscale conversion will be described. As an example, the plurality of parameters may each include a reference value that is the coordinate value of the reference color, a reference range that is a range related to the reference value, and a lower limit score that is a score of a coordinate value that is more than the reference range away from the reference value for each coordinate axis of the color space. The color space may be, for example, an RGB color space, a CMY color space, an HSV color space, an xyz color space, or the like. For example, the coordinate axes in the RGB color space may be the R (red) axis, the G (green) axis, and the B (blue) axis. For example, the coordinate axes in the HSV color space may be the H (hue) axis, the S (saturation) axis, and the V (brightness) axis. Here, the case where the color space is the RGB color space will be mainly described.

[0030] The plurality of parameters in the RGB color space may be, for example, the following nine parameters. That is, these parameters may be stored in the storage unit 13. R base : Reference value of red R range : Reference range related to the reference value of red V r base : Lower limit score that is the score of red more than the reference range away from the reference value G base : Reference value of green G range : Reference range for the green reference value V g base : Lower limit score which is the green score deviated from the reference value by more than the reference range B base : Blue reference value B range : Reference range for the blue reference value V b base : Lower limit score which is the blue score deviated from the reference value by more than the reference range

[0031] Also, let the values of the R-axis, G-axis, and B-axis in the RGB color space of each pixel of the image be R image 、G image 、B image respectively, and let the scores of red, green, and blue be V r 、V g 、V b respectively. Then, V r is as follows. V r =V r base (when │R base -R image │>R range ) V r =(1-|R base -R image | / R range )(1-V r base )+V r base (otherwise)

[0032] Figure 7 is a graph showing the change of the red score V r with respect to the value R image of the R-axis. In Figure 7, although the red score V r is shown, it is assumed that the green score V g and the blue score V b are the same. As shown in Figure 7, the red score V r becomes the maximum value "1" when the red value R image is the reference value R base , and the reference value Rbase From the reference value R base ± the reference range R range In the range up to, the red value R image is, the farther it is from the reference value R base the smaller the value becomes. In the above formula, the reference value R base From the reference value R base ± the reference range R range In the range up to, the red score V r is shown for the case where it changes linearly, but it doesn't have to be so. Thus, for each axis value in the RGB color space from the reference value to up to the reference value ± the reference range, the score for each axis monotonically decreases from "1" to the lower limit score. Also, when the absolute value of the difference between the red value R image and the reference value R base is greater than or equal to the reference range R range the red score V r becomes the lower limit score V r base That is, the reference color, which is the color of the guiding line, is indicated by the three reference values. Also, the reference range indicates the range from "1", which is the score corresponding to the reference value, to the lower limit score.

[0033] The score V for each pixel of the 8-bit grayscale is as follows. This score V may be the value of each pixel in the 8-bit grayscale image after grayscale conversion. When the image after grayscale conversion is an N-bit grayscale image, the coefficient "255" in the following formula may be replaced with "2 N -1". V = 255V r V g V b

[0034] The grayscale conversion unit 15 uses the above nine parameters stored in the storage unit 13 and the formula for calculating the scores V r , V g , V b to calculate the values R image , G image , B image of each pixel in the captured image before grayscale conversion.to score V r V g V b are calculated, and by substituting them into the formula for calculating the score V, the value V of each pixel in the captured image after grayscale conversion may be calculated. In this way, the greater the color difference from the reference color, which is the color of the guiding line, the greater the difference from the value of the pixel of the reference color, and thus the captured image can be grayscale-converted. In the captured image after grayscale conversion, it becomes easier to detect the guiding line. Here, performing grayscale conversion such that the greater the color difference from the reference color, the greater the difference from the value of the pixel of the reference color means that, for example, in at least a part of the color space, such a relationship may exist. For example, for each pixel included in the color planar image, as shown in FIG. 7, the scores of each coordinate axis in the RGB color space are calculated, and using the scores of each coordinate axis, the score V, that is, the value of the pixel in the captured image after grayscale conversion, is calculated as in the above formula. In this case, within the region where the values of each axis are within the reference range from the reference value, grayscale conversion is performed such that the greater the color difference from the reference color, the greater the difference from the value of the pixel of the reference color. Since the score V is usually an integer value of 0 or more, in the above formula, for the decimal part of the real value on the right side, rounding processing may be performed so that the value of V becomes an integer. The rounding processing may be, for example, rounding, truncation, or ceiling.

[0035] Next, the setting of a plurality of parameters will be described. By using a plurality of parameters, the captured image can be converted to grayscale as described above, and by using the grayscale-converted captured image, the guiding line can be detected. The setting unit 14 may calculate, for example, an evaluation score S for evaluating the plurality of parameters by using the value V of the pixel on the plane image after grayscale conversion corresponding to the guiding line detected based on the plurality of parameters. The pixel corresponding to the detected guiding line may be, for example, a pixel on the guiding line. The pixel on the guiding line may be, for example, a pixel included in the upper side of the guiding line or a pixel included in the lower side of the guiding line. The upper side and the lower side are the upper side and the lower side in a rectangle or a square corresponding to each pixel. The evaluation score S may be, for example, the sum of the scores V for a plurality of pixels on the plane image after grayscale conversion corresponding to the detected guiding line. For example, in FIG. 6, the sum of the values of each pixel of the grayscale image 30 on the detected guiding line 31 may be the evaluation score S. By doing so, for one set of a plurality of parameters, one evaluation score S can be obtained.

[0036] When the score V is calculated as described above, this evaluation score S indicates that the larger the value, the more appropriate the setting of the parameters. Therefore, the setting unit 14 may set the plurality of parameters so that the value of the pixel on the plane image after grayscale conversion corresponding to the guiding line detected based on the plurality of parameters is closer to the value corresponding to the reference color (in the 8-bit grayscale image described above, "255"). In this case, since the value of the pixel corresponding to the detected guiding line is specified by using the plane image after grayscale conversion, the setting of the plurality of parameters is performed by using the captured image which is the plane image after grayscale conversion. Also, in this way, the plurality of parameters can be set so that it becomes easier to detect the guiding line.

[0037] The setting unit 14 may perform the optimization regarding the evaluation score S by setting such a plurality of parameters. The optimization may be, for example, the maximization of the evaluation score S, or the minimization of the value obtained by substituting the evaluation score S into a decreasing function. The value obtained by substituting the evaluation score S into the decreasing function may be, for example, the reciprocal of the evaluation score S (1 / S).

[0038] The setting unit 14 may perform the optimization using, for example, the Nelder-Mead method, a genetic algorithm, or the like. The initial values of the plurality of parameters when performing the optimization may be, for example, set in advance, or may be set using the color of the guiding line included in the captured image before grayscale conversion. The latter case will be described later. Note that the initial values of the plurality of parameters set in advance may be, for example, the initial values of the plurality of parameters corresponding to the color of the guiding line provided on the floor surface. For example, when the guiding line is green, the initial values of the plurality of parameters regarding the green color may be set in advance. As an example, the initial value of the reference value may be set to a value corresponding to the color of the guiding line, and the initial values of the reference range and the lower limit score may be set to default values determined in advance. In this optimization, for each set of a plurality of parameters, grayscale conversion, detection of the guiding line, and calculation of the evaluation score S using the pixel values on the planar image after grayscale conversion corresponding to the detected guiding line, or the value obtained by substituting the evaluation score S into a decreasing function is performed, and optimization regarding the evaluation score S, or the value obtained by substituting the evaluation score S into a decreasing function may be performed.

[0039] When performing optimization using the Nelder-Mead method, as described above, when the number of parameters is 9, 10 sets of 9 parameters can be prepared by adding random values to the initial values of the 9 parameters respectively. In a nine-dimensional space with each of the 9 parameters as an axis, optimization may be performed by deforming the simplex consisting of 10 vertices corresponding to those 10 sets through expansion, reflection, contraction, etc. The setting unit 14 may, for example, identify new sets of a plurality of parameters through expansion or the like, and calculate a value obtained by substituting into a decreasing function an evaluation score S corresponding to the new sets of the plurality of parameters when gray-scale conversion or detection of induction lines is performed using the new sets of the plurality of parameters. Then, the setting unit 14 may sequentially update the sets of the plurality of parameters so that the value is minimized. The finally updated sets of the plurality of parameters become the plurality of parameters finally set by the setting unit 14. Here, the random value may be a value close to 0 that does not change the parameters significantly. When performing optimization using a genetic algorithm, the setting unit 14 may perform optimization, for example, by crossing 9 parameters or changing them by mutation.

[0040] The optimization termination condition may be, for example, when the change in the value to be optimized, such as the evaluation score S or the value obtained by substituting the evaluation score S into a decreasing function, becomes less than or equal to a certain level, or when parameter updates have been performed more than a predetermined number of times. Also, for example, when the optimization is maximization, the optimization may end when the value of the evaluation score S becomes greater than a threshold value, and when the optimization is minimization, the optimization may end when the value obtained by substituting the evaluation score S into a decreasing function becomes less than a threshold value. The plurality of parameters for which optimization has ended may be stored in the storage unit 13 and used for gray-scale conversion by the gray-scale conversion unit 15.

[0041] Next, the setting of the initial values of a plurality of parameters using the color of the guiding line included in the captured image before grayscale conversion will be described. When the moving body 1 is moving according to the guiding line, usually, the relative positional relationship between the moving body 1 and the guiding line becomes constant. Therefore, the position where the guiding line is included in the captured image is also determined. Accordingly, the setting unit 14 may acquire the value of each pixel in the region of the guiding line from the color captured image and use it to set the initial values of the plurality of parameters.

[0042] For example, in the color planar image shown in FIG. 4, the guiding line 5 usually becomes a line extending in the vertical direction. Therefore, the offset amount, which is the distance from the center line extending in the vertical direction at the center in the left - right direction of the planar image to the guiding line 5, may be stored in advance in the storage unit 13 or the like. Also, in addition to the offset amount, information such as the width of the guiding line 5 may be stored in the storage unit 13. Then, the setting unit 14 uses the offset amount or the like to specify the position of the guiding line 5 in the planar image, and from the position of the guiding line 5, it may acquire information on each pixel of the guiding line 5, for example, the value for each coordinate axis in a predetermined color space. As an example, the setting unit 14 may use the information of each pixel in the region 3 of the guiding line 5 in the planar image shown in FIG. 4 to set the initial values of the plurality of parameters.

[0043] In this case, for example, the average value of the values of each pixel included in the region 3 (for example, the average value of R image ) may be the initial value of the reference value (for example, R base ). Also, the greater the variance of the values of each pixel included in the region 3 (for example, the variance of R image ), the greater the initial value of the reference range (for example, R range ) may be, and the greater the initial value of the lower - limit score (for example, V r base ) may be. Note that even when the initial values of the parameters are set manually, similarly, the initial value of the reference value, the initial value of the reference range, and the initial value of the lower - limit score may be set.

[0044] Here, the case where the initial values of a plurality of parameters are set using the color of the guiding line included in the captured image before grayscale conversion has been described. However, the setting unit 14 may similarly set a plurality of parameters. That is, the initial values of the plurality of parameters set as described above may be used as the plurality of parameters themselves. In this case, the setting unit 14 will set a plurality of parameters using, for example, the captured image before grayscale conversion. More specifically, a plurality of parameters will be set using the color of the guiding line included in the captured image before grayscale conversion.

[0045] Next, the operation of the moving body 1 will be described using the flowchart of FIG. 8. (Step S101) The image acquisition unit 11 determines whether to acquire a captured image. If a captured image is to be acquired, the process proceeds to step S102. Otherwise, the process of step S101 is repeated until it is determined to acquire a captured image. The image acquisition unit 11 may, for example, periodically determine whether to acquire a captured image.

[0046] (Step S102) The image acquisition unit 11 acquires a captured image. The image acquisition unit 11 may acquire a captured image, for example, by capturing an image, or may acquire a captured image by receiving a captured image. The captured image may be stored in a recording medium (not shown) or the like.

[0047] (Step S103) The image conversion unit 12 converts the captured image into a planar image that is the captured image viewed from above. Note that the image conversion unit 12 may convert all the acquired captured images into planar images, or may convert some of the captured images into planar images. This is because when captured images are acquired frequently, it is not necessarily required to convert all the captured images into planar images. The planar image may be stored in a recording medium (not shown) or the like.

[0048] (Step S104) The setting unit 14 determines whether to set parameters. The setting unit 14 may, for example, determine to set parameters at the start of movement, or may also determine to set parameters periodically. And if parameters are to be set, it proceeds to step S105; otherwise, it proceeds to step S106.

[0049] (Step S105) The setting unit 14 sets a plurality of parameters. The setting unit 14 may, for example, calculate the evaluation score S as described above and set a plurality of parameters so as to optimize the evaluation score S. The plurality of set parameters may be stored in the storage unit 13.

[0050] (Step S106) The grayscale conversion unit 15 performs grayscale conversion on the planar image using the plurality of parameters after the latest setting. The grayscale-converted planar image may be stored in a recording medium (not shown) or the like.

[0051] (Step S107) The detection unit 16 detects the guiding line in the captured image after grayscale conversion. Information indicating the position of the detected guiding line may be passed to, for example, the movement control unit 18. Then, it returns to step S101.

[0052] Note that although not included in the flowchart of FIG. 8, the movement control unit 18 may control the movement mechanism 17 so that the moving body 1 moves along the detected guiding line. Also, the order of processing in the flowchart of FIG. 8 is an example, and if the same result can be obtained, the order of each step may be changed. Further, in the flowchart of FIG. 8, the processing ends due to a power-off or an interruption of the end of processing. For example, when the moving body 1 arrives at the destination, the processing of the flowchart of FIG. 8 may end.

[0053] Next, the operation of the mobile body 1 according to the present embodiment will be described using a specific example. In this specific example, it is assumed that the mobile body 1 moves according to the guide wire 5 in the factory shown in FIG. 2. Further, the movement control unit 18 performs movement control according to a route along each guide wire from the departure point to the destination, which is stored in a recording medium (not shown) in advance. In this specific example, it is assumed that a plurality of parameters are set each time the movement starts.

[0054] First, it is assumed that the mobile body 1 exists at the movement start position. The mobile body 1 may move to its start position, for example, by a manual operation of the user. At the movement start position, it is assumed that the mobile body 1 and the guide wire have a predetermined positional relationship. After that, when receiving an instruction to start moving, the mobile body 1 starts a process of detecting the guide wire. Specifically, the image acquisition unit 11 acquires a captured image and passes the acquired captured image to the image conversion unit 12 (steps S101, S102). It is assumed that the captured image is, for example, the one shown in FIG. 3. When receiving the captured image, the image conversion unit 12 converts the captured image into a planar image viewed from above and passes it to the setting unit 14 and the grayscale conversion unit 15 (step S103). The planar image is, for example, the one shown in FIG. 4.

[0055] When receiving the planar image, since it is the start point of the movement, the setting unit 14 determines that a plurality of parameters are to be set (step S104), and sets initial values of the plurality of parameters using the values of each pixel in the region 3 of the guide wire 5 included in the planar image. Further, the setting unit 14 determines the plurality of parameters so as to optimize an evaluation score S and the like using the initial values of the plurality of parameters, and accumulates them in the storage unit 13 (step S105).

[0056] Thereafter, the grayscale conversion unit 15 performs grayscale conversion on the planar image received from the image conversion unit 12 using a plurality of parameters stored in the storage unit 13, and passes the captured image after the grayscale conversion to the detection unit 16 (step S106). In this grayscale conversion, the grayscale conversion is performed such that the difference from the pixel value of the reference color becomes larger as the color difference from the reference color, which is the color of the guiding line, becomes larger. Thus, it becomes easier to detect the guiding line. The captured image after the grayscale conversion is, for example, the one shown in FIG. 5.

[0057] Upon receiving the captured image after the grayscale conversion, the detection unit 16 detects the guiding line and passes the detection result of the guiding line to the movement control unit 18 (step S107). Upon receiving the detection result of the guiding line, the movement control unit 18 controls the movement mechanism 17 so that the moving body 1 moves according to the detected guiding line. As described above, the movement control unit 18 may appropriately change the moving direction or stop the moving body 1. In this way, by repeating processes such as acquisition of the captured image, conversion of the captured image, detection of the guiding line in the converted image, and movement control according to the detected guiding line, the moving body 1 can move to the destination along the guiding line. In this specific example, since a plurality of parameters are set each time the movement starts, once a plurality of parameters are set, thereafter, until the moving body 1 stops, grayscale conversion is performed using the set plurality of parameters.

[0058] As described above, according to the mobile body 1 of the present embodiment, even if the color of the guiding line in the captured image changes according to changes in lighting or the like, the guiding line can be stably detected by setting a plurality of parameters accordingly. Also, for example, by setting a plurality of parameters each time the movement starts, appropriate parameters can be used for each movement, and the guiding line can be detected more reliably. Further, for example, by setting a plurality of parameters at predetermined time intervals, it becomes possible to cope with changes in the color of the guiding line during movement. For example, when external light enters the movement environment of the mobile body 1, the appearance of the guiding line changes in the morning, at noon, and in the evening, but by setting parameters corresponding thereto, the guiding line can be detected more reliably.

[0059] In the present embodiment, as shown in FIG. 7, the case where scores regarding each coordinate axis of the color space are calculated has been described, but this is not necessary. In FIG. 7, the situation where the score (for example, V image ) becomes 1 only when the value of the coordinate axis (for example, R base ) is the reference value (for example, R r ) has been described, but the score may become 1 when the value of the coordinate axis is within a predetermined value range centered on the reference value. In this case, the shape of the graph in the range of ± reference range centered on the reference value may not be triangular as in FIG. 7, but may be trapezoidal, for example.

[0060] Also, when the captured image includes two or more guiding lines, the setting unit 14 may set a plurality of parameters, for example, using the total evaluation score S regarding the two or more guiding lines detected based on the plurality of parameters.

[0061] Also, in this embodiment, the case where the setting unit 14 uses the sum of the pixel values on the captured image after grayscale conversion corresponding to the detected guiding line as the evaluation score S has been described, but it doesn't have to be so. The setting unit 14 may, for example, use the result of dividing the sum of the pixel values on the captured image after grayscale conversion corresponding to the detected guiding line by the sum of the pixel values of all the pixels in the captured image after grayscale conversion as the evaluation score S. In this case, for example, even if the value of each pixel in the captured image after grayscale conversion is close to the maximum value (e.g., "255" in an 8-bit grayscale image), appropriate optimization can be performed.

[0062] Also, the setting unit 14 may, for example, use the average value of the pixel values on the captured image after grayscale conversion corresponding to the detected guiding line as the evaluation score S. Even in this case, appropriate optimization can be performed. When the guiding line passes through the black regions in the lower right or lower left in FIG. 5, that is, the regions not included in the captured image before conversion to the planar image, for example, when obtaining the evaluation score S, the pixel values of the regions not included in the captured image may not be used.

[0063] Also, in this embodiment, when calculating the evaluation score S, the case where the values of the pixels on the planar image after grayscale conversion corresponding to the detected guiding line are mainly described. However, in this case, the evaluation score S may also be calculated using a weight corresponding to the distance from a predetermined reference line. For example, the evaluation score S may be the sum of the results obtained by multiplying the values of the pixels corresponding to the detected guiding line by the weight corresponding to the distance between the pixel and the reference line, that is, the sum of the weighted values of the pixels corresponding to the detected guiding line. The weight of a certain pixel may increase as the distance between the pixel and the reference line decreases, and may decrease as the distance between the pixel and the reference line increases. The weight of the pixel may become 0 when the distance between the pixel and the reference line is equal to or greater than the threshold value. The reference line may be set, for example, at the position where the guiding line exists when the moving body 1 is moving ideally according to the guiding line. By doing so, when the guiding line does not exist at the ideal position, for example, when a line that is not a guiding line is erroneously detected as a guiding line, the score can be made lower.

[0064] In this embodiment, the case where a plurality of parameters related to the reference color of the guiding line used when converting the captured image into grayscale is mainly described as nine parameters, but it may not be so. The plurality of parameters may be reference values for each coordinate axis in the color space, for example, the reference value R of red base , the reference value G of green base , and the reference value B of blue base . In this case, for example, in the RGB color space, the distance from the reference color (R base , G base , B base ) of the guiding line is specified, and the value after conversion may be determined according to the specified distance. That is, the grayscale conversion may be performed so that the difference from the value of the pixel of the reference color becomes larger as the specified distance becomes larger. Also, for example, only the hue (H) in the HSV color space may be used as a parameter. In this case, the number of parameters related to the reference color of the guiding line may be one. Therefore, instead of the plurality of parameters described in this embodiment, one or more parameters may be used.

[0065] Also, in this embodiment, although the case where the guiding line is a straight line has been mainly described, the guiding line may be a curve. The curved guiding line may be, for example, a guiding line of a curve with a constant curvature. Also in this case, the detection unit 16 can detect, for example, a guiding line of a curve with a constant curvature by means of Hough transform.

[0066] Also, when detecting the guiding line using Hough transform, the result of the Hough transform may deviate. In order to avoid such a situation, a process for stabilizing the result may be performed. The process for stabilizing the result of Hough transform may be, for example, filtering using a Kalman filter or the like, or may be performing weighted addition or the like for excluding outliers or reducing the influence of outliers.

[0067] Also, when the moving body 1 is movable in a plurality of directions like an omnidirectional mobile cart, for example, the image acquisition unit 11 may be able to acquire a captured image in front of the moving direction for each of the plurality of moving directions. In this case, for example, in the moving body 1, cameras for capturing captured images for each of the plurality of directions may be provided. And the image acquisition unit 11 may acquire a captured image in front of the moving direction corresponding to the current moving direction.

[0068] Also, in the above embodiment, the case where the guiding line detection device 2 is a stand-alone device has been described, but the guiding line detection device 2 may be a stand-alone device or may be a server device in a server-client system. In the latter case, the image acquisition unit 11 may receive the captured image captured in the moving body 1 from the moving body 1. Also, information regarding the guiding line detected by the detection unit 16 may be transmitted to the moving body 1 by a transmission unit (not shown) provided in the guiding line detection device 2. In this case, the moving body 1 may move according to the guiding line detected by the guiding line detection device 2 which is a server device.

[0069] In addition, in the above-described embodiment, each process or each function may be realized by being centrally processed by a single device or a single system, or may be realized by being distributively processed by a plurality of devices or a plurality of systems.

[0070] In addition, in the above-described embodiment, each component may be constituted by dedicated hardware, or for components that can be realized by software, they may be realized by executing a program. For example, by a program execution unit such as a CPU reading out a software program recorded on a recording medium such as a hard disk or a semiconductor memory and executing it, each component can be realized. At the time of its execution, the program execution unit may execute the program while accessing a storage unit or a recording medium. Further, the program may be executed by being downloaded from a server or the like, or may be executed by reading out a program recorded on a predetermined recording medium (for example, an optical disk, a magnetic disk, a semiconductor memory, etc.). Further, this program may be used as a program constituting a program product. Also, the computer that executes the program may be singular or plural. That is, centralized processing may be performed, or distributive processing may be performed.

[0071] In addition, the above embodiments are examples for specifically implementing the present invention and do not limit the technical scope of the present invention. The technical scope of the present invention is indicated by the claims rather than the description of the embodiments, and it is intended that changes within the scope of the literal meaning of the claims and the scope of equivalent meaning are included.

Explanation of Reference Numerals

[0072] 1 Mobile body, 2 Inductive line detection device, 11 Image acquisition unit, 12 Image conversion unit, 13 Storage unit, 14 Setting unit, 15 Grayscale conversion unit, 16 Detection unit, 17 Moving mechanism, 18 Movement control unit

Claims

1. An image acquisition unit that acquires a captured image by photographing the front of a moving body that moves according to a visually recognizable guiding line provided on a floor surface; An image conversion unit that converts the captured image into a captured image viewed from above; A setting unit that sets one or more parameters related to a reference color that is the color of the guiding line, which is used when converting the captured image into grayscale; A grayscale conversion unit that converts the captured image using the one or more parameters set by the setting unit such that the difference from the value of the pixel of the reference color becomes larger as the color difference from the reference color, which is the color of the guiding line, becomes larger; A detection unit that detects a guiding line in the captured image that has been subjected to the image conversion by the image conversion unit and the grayscale conversion by the grayscale conversion unit; and The setting unit is a guiding line detection device that sets one or more parameters using the captured image.

2. The one or more parameters are a plurality of parameters, The plurality of parameters each include a reference value that is the coordinate value of the reference color, a reference range that is a range related to the reference value, and a lower limit score that is a score of a coordinate value that is more than the reference range away from the reference value, for each coordinate axis of the color space. The guiding line detection device according to Claim 1.

3. The setting unit sets one or more parameters such that the value of the pixel on the captured image that has been subjected to the image conversion by the image conversion unit and the grayscale conversion by the grayscale conversion unit, corresponding to the guiding line detected based on the one or more parameters, becomes closer to the value corresponding to the reference color. The guiding line detection device according to Claim 1.

4. The setting unit sets the one or more parameters each time the moving body starts moving. The guiding line detection device according to any one of Claims 1 to 3.

5. The setting unit further sets the one or more parameters at predetermined time intervals. The guiding line detection device according to Claim 4.

6. The detection unit performs detection of a new guiding line within a range where the detected guiding line is rotated by a predetermined angle around the moving body, and within a range where the detected guiding line is translated parallel by a predetermined distance. The guiding line detection device according to any one of Claims 1 to 3.

7. A guiding line detection device according to any one of Claims 1 to 3; A moving mechanism that moves the moving body; A moving body comprising: a movement control unit that controls the movement mechanism so that the moving body moves according to the guiding line detected by the detection unit.

Images