JP6977921B2 - Mapping method, image collection processing system and positioning method - Google Patents

Description

The present invention relates to the field of intelligent warehouses, and more particularly to mapping methods, image acquisition processing systems and positioning methods for intelligent warehouses.

In a conventional intelligent warehouse, it is necessary to constantly measure the positioning location and create a physical coordinate system, and the physical coordinate system uses a general distance unit such as meters, decimeters, and centimeters as a measurement unit, for example. It can be described in the form of integers, fractions, fractions, such as 1 meter, 1 decimeter, 1 cm, 0.55 meter, 0.2 decimeter, 1.4 cm, 1/2 meter, etc. The direction is generally parallel to the walls of the building or parallel to the north, south, east, and west directions.

The automatic guided vehicle AGV, which transports cargo in an intelligent warehouse, always needs to accurately position its position. However, with conventional positioning methods, their accuracy usually does not meet the needs of the work, especially when it is necessary to accurately determine the position and orientation parameters of the AGV. This is very disadvantageous to the operation and control of the operator.

Therefore, in the prior art, there is a need for methods and devices capable of more accurate mapping and positioning.

The content of the background technology is only the technology known to the inventor, and of course, it does not represent the conventional technology in this technical field.

For one or more problems existing in the prior art, the present invention is a method of mapping a location by creating or acquiring a coordinate system of the location and scanning the location. Acquisition of the image of the control point, the image of the position to be positioned, the position parameter and the posture parameter corresponding to the image, the image of the control point, the image of the position to be the positioning target, the position parameter and the posture. Provided is a method including modifying the position parameter and the posture parameter of the image of the position to be positioned based on the parameter.

According to one aspect of the invention, the position parameter includes abscissa and coordinates, preferably vertical coordinates, and the attitude parameter includes a yaw angle, preferably a pitch angle and a roll angle. ..

According to one aspect of the invention, the modification step is a connection point including one image, the position parameter and the posture parameter corresponding to the one image, and whether the image corresponds to a control point. It includes creating the set of the above and modifying the position parameter and the attitude parameter of the image of the position to be positioned based on the set of the connection points.

According to one aspect of the present invention, the modification step obtains two connection points whose distances do not exceed a predetermined value from the set of connection points as one connection, and creates a set of connections. For two connection points included in each connection in the set of connections, the connection reliability between the two connection points is calculated, and the connection whose connection reliability is higher than a predetermined threshold is used as the mapping connection set. It includes filtering and modifying the position and orientation parameters of the image of the position to be positioned based on the mapping connection set.

According to one aspect of the invention, the modification further sets the position and orientation parameters of the image of the connection point of the non-localization point as the initial iteration parameters when performing the initialization step in the mapping connection set. Includes performing a gradient descent method.

According to one aspect of the invention, the modification further comprises performing the gradient descent method until the iterative rate of change is below a predetermined threshold.

According to one aspect of the present invention, image collection is performed a plurality of times for a part or all of the control points, and the position parameter and the posture parameter corresponding to each image collection are acquired.

According to one aspect of the present invention, in the method, the coordinate system, the image of the control point, the image of the position to be positioned, the position parameter and the posture parameter of the image of the control point, and the corrected positioning target. It further includes building a map library by storing the position and orientation parameters of the image at the position to be in a database or file.

According to one aspect of the present invention, the coordinate system is a physical coordinate system.

According to one aspect of the invention, the predetermined value is half the length or width of the image.

The present invention relates to a base, a camera attached to the base and configured to collect an image of an area below the base, and a position parameter of an automatic guided vehicle attached to the base and corresponding to the image. Also provided are automated guided vehicles for image acquisition, including measuring components configured to be able to measure or calculate attitude parameters.

According to one aspect of the invention, the automated guided vehicle further comprises a light emitting device attached to the base and configured to illuminate an area below the base for collecting images of the camera. ..

According to one aspect of the present invention, the automatic guided vehicle is attached to the base, the camera and the measuring component are both coupled to the automatic guided vehicle, and the automatic guided vehicle is controlled to be the control point and the positioning target. Further included is a control device configured to advance to a position and collect an image of the control point and an image of the position to be positioned.

According to one aspect of the present invention, the unmanned carrier is coupled to the camera and the measuring component, and based on the image, the position parameter and the posture parameter, the position parameter of the image of the position to be positioned and the position parameter of the image. It also includes a processing device that modifies the attitude parameters.

According to one aspect of the present invention, the processing apparatus includes one image, the position parameter corresponding to the one image, the attitude parameter, and a connection point including whether or not the image corresponds to a control point. To create a set of connections, to acquire two connection points whose distances do not exceed a predetermined value as one connection from the set of connection points, and to create a set of connections, and to create a set of connections. For the two connection points included in each connection, the connection reliability between the two connection points is calculated, and the connections whose connection reliability is higher than a predetermined threshold are filtered as a mapping connection set. In the mapping connection set, a gradient descent method is performed in which the position parameter and the attitude parameter of the image of the connection point of the non-local point are used as the initial iteration parameters when the initialization step is executed until the iteration rate of change becomes lower than a predetermined threshold. The position parameter and the attitude parameter of the image of the position to be positioned are modified by a method including the execution.

According to one aspect of the present invention, the automatic guided vehicle is attached to the base and further includes a lens hood for softening the light rays from the light emitting device, preferably, the light emitting device includes the lens hood. Surrounded and attached.

According to one aspect of the present invention, the measuring component is an inertial navigation measuring component.

According to one aspect of the invention, the position parameter includes abscissa and coordinates, preferably vertical coordinates, and the attitude parameter includes a yaw angle, preferably a pitch angle and a roll angle. ..

According to one aspect of the invention, the measuring component includes a laser SLAM measuring device and / or a visual SLAM measuring device.

According to one aspect of the present invention, the processing apparatus includes the coordinate system, the image of the control point, the image of the position to be positioned, the position parameter and the attitude parameter of the image of the control point, and the corrected positioning. It is configured to store the position parameter and the posture parameter of the image of the target position in a database or a file to construct a map library.

The present invention comprises an unmanned carrier as described above and a processing device that is coupled to the camera and the measuring component and modifies the position and attitude parameters of the image based on the image, the position parameters and the attitude parameters. Further provides an image acquisition processing system including.

According to one aspect of the present invention, the processing apparatus is configured to be capable of performing the mapping method as described above.

The present invention includes a camera configured to collect an image of the lower part of the automatic guided vehicle, a light emitting device configured to illuminate the lower part of the automatic guided vehicle, and position parameters of the automatic guided vehicle. The inertial navigation measuring component configured to measure the attitude parameter, the camera and the inertial navigation measuring component are both coupled to it, and the position parameter of the image is based on the image, the position parameter and the attitude parameter. Further provided is a mapping positioning system for automated guided vehicles, including a processing device configured to modify the attitude parameters.

According to one aspect of the present invention, the processing apparatus is configured to be able to execute the mapping method according to any one of claims 1 to 10.

The present invention comprises a device configured to create or acquire a location coordinate system, an image of a control point by scanning the location, an image of a plurality of positioning targets, and a position corresponding to the image. A device configured to acquire parameters and attitude parameters, and a device that corrects the position parameters and attitude parameters of the image of the position to be positioned based on the image, the position parameters, and the attitude parameters. Further provides devices that map locations, including.

The present invention loads or acquires a map obtained by the method according to any one of the above, and collects or acquires an image of a position to be positioned, a position parameter and an attitude parameter corresponding to the image. Further provided is a positioning method including searching for an image having the closest distance to an image at a position to be positioned based on the map.

According to one aspect of the present invention, the positioning method uses a phase correlation method to determine the reliability, position parameter offset, and attitude parameter offset between the image at the position to be positioned and the image at the closest distance. Further includes calculating.

According to one aspect of the present invention, when the reliability calculated by the phase correlation method is lower than a predetermined value, the image having the shortest distance is discarded, and the distance to the image at the position to be positioned is the shortest. Re-search for images that are close and have a higher reliability than the specified value.

The drawings are intended to provide a further understanding of the invention, which constitutes a portion of the specification to illustrate the invention along with embodiments of the invention and constitute limitations for the invention. It's not something to do.

It is a flowchart of the mapping method which concerns on one Embodiment of this invention. It is a schematic diagram of the physical coordinates which concerns on one Embodiment of this invention. It is a schematic diagram of the logical coordinates which concerns on one Embodiment of this invention. It is a schematic diagram of the connection point which concerns on one Embodiment of this invention. It is a schematic diagram of the control point which concerns on one Embodiment of this invention. It is a flowchart of the method of modifying the position parameter and the posture parameter of the image of the position to be the positioning target which concerns on one Embodiment of this invention. This is an example of superimposing images calculated by the phase correlation method according to the embodiment of the present invention. It is a schematic diagram of the connection which concerns on one Embodiment of this invention. It is a figure which shows the screenshot of the map after the mapping of the physical coordinate system and the logical coordinate system is completed. It is a schematic diagram of the automatic guided vehicle for image collection which concerns on one Embodiment of this invention. It is a flowchart of the positioning method which concerns on one Embodiment of this invention. It is a block diagram of the computer program product which concerns on one Embodiment of this invention.

In the following, only some exemplary embodiments will be briefly described. As one of ordinary skill in the art can conceive, the embodiments described may be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary rather than limiting in substance.

In the description of the present invention, "center", "vertical", "horizontal", "length", "width", "thickness", "top", "bottom", "front", "rear", "left" , "Right", "Vertical", "Horizontal", "Top", "Bottom", "Inside", "Outside", "Clockwise", "Counterclockwise", etc. Is based on the direction or positional relationship shown in the drawing. The present invention is merely intended to explain and simplify the description, as it does not imply or imply that the device or element must have a particular orientation, be configured in a particular orientation, and operate. It cannot be understood as a limitation on the invention. It should be noted that the terms "first" and "second" are used for explanatory purposes only and should be understood to indicate or suggest relative importance or indicate the quantity of technical features. is not it. Therefore, the features limited to "first" and "second" can explicitly or implicitly include one or more features. In the description of the present invention, the meaning of "plurality" is two or more unless otherwise specified.

In the description of the present invention, the terms "mounting", "connection", and "connection" should be broadly understood unless otherwise specified and limited, and may be, for example, a fixed connection. , It may be a removable connection, or it may be connected integrally. It may be a mechanical connection, an electrical connection, or it may be communicable with each other. It may be a direct connection, an indirect connection via an intermediate medium, an internal connection of the two elements, or an interaction relationship between the two elements. For those skilled in the art, the specific meanings of the above terms in the present invention may be understood depending on the specific circumstances.

In the present invention, unless otherwise specified and limited, the fact that the first feature is "above" or "below" the second feature is a direct contact between the first feature and the second feature. The first feature and the second feature may include contact with another feature between them rather than direct contact. Further, the fact that the first feature is "above", "above", and "upper surface" of the second feature includes that the first feature is directly above and diagonally above the second feature, or It only shows that the horizontal height of the first feature is higher than that of the second feature. The first feature being "below", "below", "bottom surface" of the second feature includes that the first feature is directly below and diagonally below the second feature, or first. It only shows that the horizontal height of the feature is lower than that of the second feature.

The following disclosures provide many different embodiments or examples for realizing the different structures of the invention. In order to simplify the disclosure of the present invention, the components and settings of a particular example will be described below. Of course, they are merely examples and are not intended to limit the invention. It should be noted that the present invention does not show the relationship between various embodiments and / or settings, and for simplification and clarification, reference numbers and / or reference alphabets can be used repeatedly in different examples. .. Further, while the present invention provides examples of various specific processes and materials, one of ordinary skill in the art can envision the application of other processes and / or the use of other materials.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings, but the preferred embodiments described herein are merely for explaining and interpreting the present invention, limiting the present invention. It should be understood that it is not something to do.

First, with reference to FIG. 1, for example, the mapping method 100 according to the first embodiment of the present invention, which maps a place, will be described.

In step S101, the coordinate system of the above location is created or acquired. The coordinate system may be a physical coordinate system or a logical coordinate system, both of which are within the scope of the present invention. The definition of the coordinate system generally includes the position of the origin, the direction of the XY coordinate axes, and the like.

As shown in FIG. 2, for example, a physical coordinate system is created by measuring a place where positioning is required, and the physical coordinate system uses general distance units such as meters, decimeters, and centimeters as measurement units. Can be described in the form of integers, fractions, fractions, such as 1 meter, 1 decimeter, 1 cm, 0.55 meters, 0.2 decimeters, 1.4 centimeters, 1/2 meter, etc., coordinates. The direction of the system is generally parallel to the wall of the building or parallel to the north, south, east, and west directions, and the coordinates created according to the above principles are called the physical coordinate system in this system.

The coordinate system set according to the actual business situation is called a logical coordinate system in this system. As an example, but not a limitation, the difference between a logical coordinate system and a physical coordinate system is, for example, in a logical coordinate system, generally explained by integers such as (1, 2,), (5, 10), and the coordinate system. The direction of is not necessarily overlapped with the physical coordinate system, and the distance unit of the logical coordinate system is not a general physical unit but is defined according to the actual work demand. For example, point A in FIG. , The logical coordinates of points B are (3,7), the logical coordinates of point A are (3,8), and the logical coordinates of point C are (4,7). When calculated with the point in the lower left corner as the origin and each logical position interval as 1.35 meters, the physical coordinates of point A are (4.05, 9.45). Therefore, the logical position and the physical position may be completely the same, or both may have a certain conversion relationship. The reason why there is a logical position is that the position of the shelf is the position of the logical coordinate system, for example, (3, 7), for example, in order to facilitate the design of the business logic or the mapping calculation. It is stored at the position of, and if the physical position is used, there is an explanation of (4.05, 9.45) above, so it is difficult for the operator to understand and operate, and if the physical position is necessary, it is converted. The conversion is possible and the general conversion is to multiply by one coefficient called the logical position spacing, which may be different in the X and Y directions. For example, if the shelves in the warehouse are 1.3m * 1.3m and the shelf spacing is 0.05m, the logical position spacing can be defined as 1.35m, and the shelves are 1.2m * 1.0m. If so, by defining the logical position spacing as 1.25 m in the X-axis direction and 1.05 m in the Y-axis direction, devices requiring physical positioning can find shelves in the corresponding physical positions. can. The above conversion is only a normal conversion method, and there are more complicated conversion methods such as rotation conversion and non-linear conversion of the coordinate system, and the description is omitted here due to space limitations. The above description of the logical coordinate system is not limited but merely exemplary. The logical coordinate system is a coordinate system set according to the actual situation of business. In the concept of the present invention, the position parameter in the logical coordinate system is not limited to an integer and may have a decimal number. All of these are within the scope of protection of the present invention. If the physical or logical coordinate system of the location is created in advance, it can be obtained from the corresponding file or database. In the following, a physical coordinate system will be described as an example.

In step S102, the above-mentioned location is scanned to obtain an image of a control point (see below for a definition of a control point), an image of a position to be positioned (preferably an image of a plurality of positions to be positioned), and the above. The position parameter and the attitude parameter corresponding to the image of the control point and the image of the position to be positioned are acquired.

For example, an automatic guided vehicle equipped with the device of the present invention (described later) is used to scan the above location, and an image of a position to be positioned, an image of a control point, and a position parameter and a posture corresponding to the above two images. You can get the parameters. Here, the so-called positioning target position is determined by actual working conditions, and is, for example, a position where an automatic guided vehicle arrives.

Explaining with reference to FIG. 2, the above positional parameters are, for example, horizontal and vertical coordinates (that is, horizontal positions, for example, coordinates of the center of an image) in a physical coordinate system of an image at a certain control point or a position where positioning is required. Or the coordinates of a corner of the image), which may, of course, be the horizontal and vertical distances to a base point, where the attitude parameter is the angle of the acquired image, eg, the horizontal axis or the vertical axis. The angle with respect to (that is, the horizontal angle). According to a preferred embodiment of the present invention, parameters such as pitch angle, roll angle, and vertical height corresponding to the above image (that is, pitch angle, roll angle, vertical height, etc. when an automatic guided vehicle acquires a photograph). Can also be obtained. According to a preferred embodiment of the present invention, the above data can be provided by using the inertial navigation measuring device mounted on the automatic guided vehicle of the present invention. The inertial navigation measuring device includes, for example, a wheel encoder, an accelerometer (1 to 3 axes), a gyroscope (1 to 3 axes), a magnetic flux sensor (1 to 3 axes), a pressure sensor, a yaw angle, a pitch angle, and a roll angle. Includes a measuring device that can feed back the horizontal and vertical positions. Yaw angle (ie, the angle at which the image is on the horizontal or vertical axis), pitch angle, roll angle, horizontal by calculation using data obtained from wheel encoders, accelerometers, gyroscopes, magnetic flux sensors, and barometric pressure sensors. Positions and vertical positions can be obtained, and more data than obtained can be superimposed on the image (image, yaw angle (ie image angle), pitch angle, roll angle, horizontal position (ie x-axis horizontal coordinates and y). It forms a set of seven data combinations (axis vertical coordinates), vertical position, and whether it is a control point), and as shown in Fig. 4, it is called a connection point in this system, and it is used as an input for subsequent mapping. do. Naturally, as those skilled in the art can understand, the above connection points do not have to contain all the data, for example, a quadruple including (image, yaw angle, horizontal position, whether it is a control point). The object of the present invention can be achieved by including the data combination of. According to one preferred embodiment of the present invention, by collecting as many images of control points and corresponding position parameters and attitude parameters as possible, a positioning map can be created more accurately and positioning can be performed more accurately. At the time of collection, if the same area is passed through multiple times and collected multiple times, the positioning map can be made more accurate. As a matter of course, the protection range of the present invention is not limited to the coordinates in the physical coordinate system, but may be the coordinates in the logical coordinate system.

Represents a point where the coordinates of the control points are accurately determined. Like points A, B, and C shown in FIG. 3, the coordinates of these points have already been confirmed, artificially defined, and verified in advance.

FIG. 5 shows an example of the control point, and the control point A whose logical coordinates are (5, 8) and whose physical coordinates are (3.75, 4.10) is shown. As a matter of course, the present invention is not limited to a control point that must have both logical and physical coordinates at the same time. The control point can be identified and confirmed by various means. For example, one has a position-labeled cross on the image that, after collecting the image, can identify the control point and its position coordinates, and the other is code information, eg, on it. There is a bar code or a two-dimensional code, and after collecting the image, it can be decoded by a program, and the decoded content is the position coordinates of the control point. According to one embodiment of the present invention, since the coordinates of the control point are confirmed in advance, in step S102, the position parameter of the image of the control point is the position of the image of the control point measured by the inertial navigation measuring device. The position parameter of the control point is used instead of the parameter.

In step S103, the position parameter and the posture parameter of the image of the position to be positioned are modified based on the image of the control point, the image of the position to be positioned, the position parameter and the posture parameter.

For the image of the position to be positioned, the position parameter and attitude parameter are obtained by measurement, for example, they can be measured by an inertial navigation measuring device, and there is a measurement error in the working conditions at the site. Therefore, it is necessary to make further corrections to improve its accuracy. The image of the control point can be used as a good reference for modifying the position parameter and the attitude parameter of the image of the position to be positioned.

An embodiment of step S103 will be described with reference to FIG.

In step S1031, a set of connection points is created. As mentioned above, each connection point is a set of seven data combinations (image, yaw angle (ie image angle), pitch angle, roll angle, horizontal position, vertical position, whether it is a control point), or ( Includes a quartet of data combinations (image, yaw angle, horizontal position, whether it is a control point). A set of connection points is created using these connection points. Regarding the parameter "whether or not it is a control point", if a control point appears in the image and a pre-verified position parameter of the control point is normally obtained, this parameter becomes "control point". Otherwise, the parameter is "non-localized". It can also be represented by logic 0 or 1.

In step S1032, a connection set is created and output based on the set of connection points. A set of connection points is input, and a pairing operation is performed according to the horizontal position included in the connection points, that is, the xy-axis coordinates. As a principle of the pairing operation, for example, the distance between the display positions of two images is It does not exceed a predetermined value, for example, 50%, 30% or 20% of the length or width of the image. To explain with an example, if the horizontal position of the connection point A is (0,0) and the horizontal position of the connection point B is (5,0), the distance from A to B is 5, and the image. If the size of is 10 * 10, A and B meet the criteria that they do not exceed 50% of the size of the image and can be paired. In this system, such a combination is called a connection. Each connection contains two connection points and outputs all combinable connections called a connection set in the system.

In step S1033, the generated connection set is input, two connection points A and B in the connection are extracted for each connection in the connection set, and the connection point A is referred to as a reference point for convenience of explanation. The connection point B is called an adjacent point, the reference point is the origin, the adjacent point is the offset, and the image of the reference point and the image of the adjacent point are input. For example, a phase correlation method is executed to obtain a connection reliability (conf). (Characterizing the similarity between the two), x-direction relative displacement (delta_x), y-direction relative displacement (delta_y), relative rotation angle (theta) are obtained, and in this system, (conf, delta_x, delta_y, theta). A quadruple consisting of is called a cross-correlation result, which is stored in the corresponding connection and has a certain threshold of reliability (for example, 10 and the probability that the cross-correlation result appears randomly is a normal distribution at 10 sigma positions). It suspends connections that exceed (which can be understood to be smaller than the probability value represented), and outputs a new connection set, called a mapping connection set in this system, whose reliability after filtering is greater than the threshold and contains cross-correlation results. .. The connection reliability is the output of the phase correlation method, and is calculated by the sharpness of the peak value of the value calculated by the phase correlation method or the distribution near the peak, and it is assumed that the distribution is in a normal state. By knowing the peak value and the average value, the reliability can be calculated. The cross-correlation result is calculated by calculating the degree of correlation between the two images according to the above-mentioned phase correlation method. In the process of performing the phase correlation method, we are involved in the calculation of the cross-power spectrum, and we can use the cross-power spectrum function to obtain the cross-correlation levels under different displacement conditions, assuming that the cross-correlation levels follow a normal distribution. , The correlation parameter of the normal distribution can be calculated by the statistical method, and the connection reliability can be calculated by dividing the parameter by the maximum cross-correlation value.

According to one embodiment, the mapping connection set does not include connections where both points are all control points.

As shown in FIG. 7, the gray area in the figure is the image A, the green area is the image B, and the superimposed area of the two images calculated by the phase correlation is shown. For example, the calculated cross-correlation results of the two images A and B in FIG. 7 are reliability 131.5142, x-direction relative displacement 33.4, y-direction phase displacement 10.7, and rotation angle 0.3 degrees.

FIG. 8 shows a schematic diagram of a connection including a reference point and an adjacent point.

In step S1034, the gradient descent method is executed in the mapping connection set, and the position parameter and the attitude parameter of the image of the position to be positioned are corrected. According to one embodiment, the horizontal and vertical coordinates and angles of the image of the control point are invariant, and the gradient adjustment is made with the parameters of the image of the non-control point as variables, and the image of the control point is regarded as a constant. Alternatively, the mapping connection set can be defined as not including connections where both points are all control points, such adjustments are meaningless, the control points should not be adjusted originally, and the gradient is calculated. This is because it is not always required. The optimization function is shown in, for example, Equation 1.

・・・・（数式１）

・ ・ ・ ・ (Formula 1)

・・・・（数式２）

・ ・ ・ ・ (Formula 2)

・・・・（数式３）

・ ・ ・ ・ (Formula 3)

・・・・（数式４）

・ ・ ・ ・ (Formula 4)

・・・・（数式５）

・ ・ ・ ・ (Formula 5)

・・・・（数式６）

・ ・ ・ ・ (Formula 6)

・・・・（数式７）

・ ・ ・ ・ (Formula 7)

はマッピング接続集合に全部で

個の接続が含まれることを表し、

はマッピング接続集合中の

番目の接続を表し、

は

番目の接続の基準点を表し、

は

番目の接続の隣接点を表し、

は

番目の接続の相互相関結果を表し、

は基準点のヨー角を表し、

は隣接点のヨー角を表し、

は相互相関結果における相対回転角度を表し、

は基準点と隣接点の慣性航法測定部品での角度差として理解でき、

は慣性航法測定部品での角度差と相互相関結果における相対回転との角度差として理解でき（相互相関結果における回転角度は位相相関法により算出されたｔｈｅｔａであり、この値は、隣接点の画像がどれぐらいの角度を回転すれば基準点の画像と平行になるかを表す）、ここで、

はヨー角重み関数であり、ヨー角のフィッティング過程において、異なる接続点属性（例えば、標定点と非標定点）の地図反復における重みが異なること（一例として、一般的には、標定点の重みが大きく、例えば１０００であり、非標定点の重みが小さく、例えば１である）を表し、

は相互相関結果における角度差の重み関数であり、異なる接続属性（例えば、２つの非標定点の間の接続、標定点と非標定点の間の接続）の相互相関結果角度に対する重み（２つの非標定点の接続であれば、変化の度合いが対等又は均等になるはずであり、これは、２つのコードの地位は等しいが、標定点と非標定点の変化の度合いは対等ではなく、非標定点の変化の度合いが標定点より著しく大きいため、重みにより制御される必要があるからである。実際の状況に応じて重みを与えることができる）を表す。１つの好ましい実施形態によれば、２つの非標定点の接続について、重みは１とし、同じレベルで調整することができ、標定点と非標定点の接続についても、重みは１としてもよく、これは、標定点が定数であり、勾配計算に関与しないため、勾配が不変であると考えられるからである。標定点を微調整することを考慮すれば、標定点と非標定点との接続の重み付け比は９９：１に達することができる。 here,

Is all in the mapping connection set

Represents that it contains a number of connections

Is in the mapping connection set

Represents the second connection

teeth

Represents the reference point for the second connection

teeth

Represents the adjacency point of the second connection

teeth

Represents the cross-correlation result of the second connection

Represents the yaw angle of the reference point

Represents the yaw angle of adjacent points

Represents the relative rotation angle in the cross-correlation result

Can be understood as the angle difference between the reference point and the adjacent point in the inertial navigation measurement component.

Can be understood as the angle difference between the angle difference in the inertial navigation measurement component and the relative rotation in the cross-correlation result (the rotation angle in the cross-correlation result is theta calculated by the phase correlation method, and this value is the image of the adjacent point. Represents how much angle should be rotated to be parallel to the image of the reference point), where

Is a yaw angle weighting function, where different connection point attributes (eg, directed and non-elevated points) have different weights in map iterations in the yaw angle fitting process (as an example, generally, the weights of the directed points). Is large, for example 1000, and the weight of the non-local point is small, for example 1).

Is a weighting function of the angle difference in the cross-correlation result, and the weights for the cross-correlation result angles of different connection attributes (eg, the connection between two non-local points, the connection between the control points and the non-control points) (two). If the connection of non-local points, the degree of change should be equal or equal, which means that the positions of the two codes are equal, but the degree of change between the fixed point and the non-local point is not equal and non-directed. This is because the degree of change of the control point is significantly larger than that of the control point, so that it needs to be controlled by the weight. The weight can be given according to the actual situation). According to one preferred embodiment, the weight of the connection between the two non-local points can be set to 1 and can be adjusted at the same level, and the connection between the fixed point and the non-local point may also be set to a weight of 1. This is because the control point is a constant and does not participate in the gradient calculation, so the gradient is considered to be invariant. Considering fine-tuning the control points, the weighting ratio of the connection between the control points and the non-control points can reach 99: 1.

は基準点のｘ軸座標を表し、

は隣接点のｘ軸座標を表し、

は相互相関結果におけるｘ方向相対変位を表し、

は基準点と隣接点の慣性航法測定部品でのｘ方向座標の差として理解でき、

は慣性航法測定部品でのｘ方向座標の差と相互相関結果におけるｘ方向相対変位の差として理解でき（相互相関結果におけるｘ方向相対変位は、位相相関法により算出されたｄｅｌｔａ＿ｘであり、この値は、隣接点の画像がｘ方向に沿ってどのぐらいの距離を並進すれば基準点の画像に整列するかを表す）、ここで、

はｘ軸重み関数であり、ｘ軸座標のフィッティング過程において、異なる接続点属性（例えば、標定点と非標定点）の地図反復における重みが異なること（一例として、一般的には、標定点の重みが大きく、例えば１０００であり、非標定点の重みが小さく、例えば１である）を表し、

は相互相関結果のｘ軸相対変位に対する調整重みであり、例えば１をとすることができる。 The explanations of the other formulas are the same as the above explanations, the difference in the X-axis direction in the inertial navigation measurement component, the difference in the relative displacement in the X-axis direction in the mutual correlation result, and the difference in the Y-axis direction in the inertial navigation measurement component. And the difference between the mutual correlation result and the relative displacement in the Y-axis direction are calculated, and the weighting functions can be adjusted according to the business situation and the algorithm conformance situation.

Represents the x-axis coordinates of the reference point

Represents the x-axis coordinates of adjacent points

Represents the x-direction relative displacement in the cross-correlation result

Can be understood as the difference in x-direction coordinates between the reference point and the adjacent point in the inertial navigation measurement component.

Can be understood as the difference between the x-direction coordinates in the inertial navigation measurement component and the x-direction relative displacement in the cross-correlation result (the x-direction relative displacement in the cross-correlation result is delta_x calculated by the phase correlation method, and this value. Represents how far the adjacent point image should be translated along the x direction to align with the reference point image), where

Is an x-axis weighting function, in which, in the fitting process of x-axis coordinates, different connecting point attributes (eg, directed and non-elevated points) have different weights in map iterations (as an example, generally of directed points). The weight is large, for example 1000, and the weight of the non-local point is small, for example 1).

Is an adjustment weight for the x-axis relative displacement of the cross-correlation result, and can be set to 1, for example.

は基準点のｙ軸座標を表し、

は隣接点のｙ軸座標を表し、

は相互相関結果におけるｙ方向相対変位を表し、

は基準点と隣接点の慣性航法測定部品でのｙ方向座標の差として理解でき、

は慣性航法測定部品でのｙ方向座標の差と相互相関結果におけるｙ方向相対変位との差として理解でき（相互相関結果におけるｙ方向相対変位は、位相相関法により算出されたｄｅｌｔａ＿ｙであり、この値は、隣接点画像がｙ方向に沿ってどのぐらいの距離を並進すれば基準点の画像に整列するを表す）、ここで、

はｘ軸重み関数であり、ｙ軸座標フィッティング過程において、異なる接続点属性（例えば、標定点と非標定点）の地図反復における重みが異なること（一例として、一般的には、標定点の重みが大きく、例えば１０００であり、非標定点の重みが小さく、例えば１である）を表し、

は相互相関結果のｙ軸相対変位に対する調整重みであり、例えば１とすることができる。

Represents the y-axis coordinates of the reference point

Represents the y-axis coordinates of adjacent points

Represents the relative displacement in the y direction in the cross-correlation result.

Can be understood as the difference in y-direction coordinates between the reference point and the adjacent point in the inertial navigation measurement component.

Can be understood as the difference between the difference in the y-direction coordinates in the inertial navigation measurement component and the y-direction relative displacement in the cross-correlation result (the y-direction relative displacement in the cross-correlation result is delta_y calculated by the phase correlation method. The value represents how far the adjacent point image should be translated along the y direction to align with the reference point image), where.

Is an x-axis weight function, and in the y-axis coordinate fitting process, different connection point attributes (eg, control point and non-control point) have different weights in the map iteration (as an example, in general, the weight of the control point). Is large, for example 1000, and the weight of the non-local point is small, for example 1).

Is an adjustment weight for the y-axis relative displacement of the cross-correlation result, and can be set to 1, for example.

、

、

はそれぞれ、ｔｈｅｔａ、ｘ、ｙ変化量の最終フィッティング結果における重みを表し、あるシーンはｔｈｅｔａの変化に対して敏感であれば、

を上げることができる。１つの好ましい実施形態によれば、

、

、

はいずれも１である。

,

,

Represents the weights of theta, x, and y changes in the final fitting result, respectively, and if a scene is sensitive to changes in theta,

Can be raised. According to one preferred embodiment

,

,

Are all 1.

、

、

、

、

、

である。数式１の各独立変数を導出することにより、各独立変数の勾配方向、又は一組の勾配集合が得られ、勾配降下を行うために使用されている。 The independent variable in Equation 1 is

,

,

,

,

,

Is. By deriving each independent variable in Equation 1, the gradient direction of each independent variable or a set of gradient sets is obtained and used to perform gradient descent.

The initialization step of the gradient descent method is executed, and the position parameter and the attitude parameter labeled by the inertial navigation are set as the initial position of the image. For the input of the gradient descent method, one is the previous iterative set, one is the gradient, and one is the step size, where the gradient is obtained by finding the derivative from Equation 1 and iterating. The initial set is priced, for example, with position and attitude parameters labeled by inertial navigation, and the step size is fixed or variable.

After determining the gradient and the iterative initial set, the step size is reduced in the gradient direction and optimized using Equation 1. The step size algorithm can be customized as needed, and the system preferably uses a fixed step size to perform gradient descent. Iterative execution is repeated until the iterative change rate becomes lower than a predetermined threshold value, and the present system has, for example, a predetermined threshold value of 0.1%. The rate of change is, for example, the difference between the value calculated last time and the value obtained in this iterative calculation divided by the previous value. Finally, the physical coordinates and posture parameters of the base point (for example, the center point) of each image are obtained as the position parameter and the posture parameter of the position to be positioned as the corrected position.

In the process of executing the gradient descent method in the mapping connection set, the position parameter and the attitude parameter of the image of the control point do not change.

In the execution of the gradient descent method described above, the x-axis coordinates, y-axis coordinates, and yaw angle of the image are used. According to one preferred embodiment of the invention, the vertical coordinates, pitch angle, and roll angle corresponding to the image may be included, which is very useful, especially if it is not flat in place. These are within the scope of protection of the present invention.

According to a preferred embodiment of the present invention, image collection is performed a plurality of times for a part or all of the control points, and the position parameter and the posture parameter corresponding to each image collection are acquired. By collecting images of control points multiple times, the iterative results are more accurate and the number of connections is increased.

According to one preferred embodiment of the present invention, the coordinate system, the image of the control point, the image of the position to be positioned, the position parameter and the posture parameter of the image of the control point, and the corrected positioning target. It further includes storing the position and orientation parameters of the image of the position in a database or file to build a map library. According to one preferred embodiment, the set of connections and / or the set of mapping connections are simultaneously stored in the database or file as part of the map. FIG. 9 shows a map constructed based on the present invention.

Preferably, when the repeated map is artificially checked and fine-tuned, stable mapping between the physical coordinate system and the logical coordinate system is completed and used for subsequent positioning.

Hereinafter, the automatic guided vehicle 10 for image collection according to another embodiment of the present invention will be described with reference to FIG. As shown in FIG. 10, the internal parts of the automatic guided vehicle 10 are shown, but the parts such as the case are omitted for the sake of clarity. The automatic guided vehicle 10 is attached to the base 6, a light emitting device 5-2 attached to the base and configured to illuminate the area below the base, and a region below the base attached to the base. An image, for example, a camera 5-3 configured to be able to collect an image of an area illuminated by the light emitting device, and a position parameter and an attitude parameter of the automatic guided vehicle attached to the base and corresponding to the image. Includes a measuring component 3 configured to be able to measure or calculate.

The drive wheel 1 is attached to the base 6 and can acquire the horizontal position of the automatic guided vehicle or the drive wheel by acquiring the rotation angle of the motor that provides the drive force, the speed reducer that amplifies the drive force, and the motor. Includes an encoder that can. The drive wheels 2 cooperate with the drive wheels 1 to achieve motion control. The measuring component 3 is, for example, an inertial navigation measuring device, and is, for example, among instantaneous speeds, instantaneous angles, and instantaneous positions such as abscissa, ordinate, vertical coordinates, yaw angle, pitch angle, and roll angle. One or more can be provided. According to one embodiment of the present invention, the drive wheel encoder may be a part of the measurement component 3. The control device 4 is attached to the base 6 and is coupled to the measuring component 3 and the camera 5-3. The control device 4 is configured to control the unmanned carrier to advance to a control point and a position to be positioned, and to collect an image of the control point and an image of the position to be positioned. By synchronizing the camera 5-3 with the measuring component 3, the measuring component 3 can measure the position parameter and the attitude parameter of the unmanned carrier at the same time as the camera collects the image, that is, corresponds to the image. Acquire the position parameter and attitude parameter to be used.

The camera 5-3 is, for example, a downward monitoring type camera that acquires an image of the lower part of an automatic guided vehicle, and is a light emitting device 5-2 and a lens hood 5-2 that are attached to a base and illuminate the shooting area of the downward monitoring type camera. The image pickup device 5 is formed together with 1. The lens hood 5-1 is attached to the base and is used to soften the light rays of the light emitting device and prevent the occurrence of the shiny phenomenon. The light emitting device is preferably attached so as to surround the lens hood.

According to a preferred embodiment of the present invention, the unmanned carrier 10 is coupled to the camera 5-3 and the measuring component 3 and receives an image collected by the camera and a position parameter and an attitude parameter measured by the measuring component. Further includes a processing device (not shown) that corrects the position parameter and the attitude parameter of the image of the position to be positioned based on the image, the position parameter and the attitude parameter. As can be understood by those skilled in the art, the processing device may be incorporated in the automatic guided vehicle 10 or may be physically separated from the automatic guided vehicle and communicate with other members by a wired or wireless method. good. All of these are within the scope of the present invention.

According to one preferred embodiment of the present invention, the processing apparatus determines one image, the position parameter corresponding to the one image, the attitude parameter, and whether the image corresponds to a control point. Creating a set of connection points including, and acquiring two connection points whose distances do not exceed a predetermined value as one connection from the set of connection points, and creating a set of connections, and the above connection For two connection points included in each connection in the set, the connection reliability between the above two connection points is calculated, and the connections whose connection reliability is higher than a predetermined threshold are filtered as a mapping connection set. And, in the mapping connection set, the gradient using the position parameter and the attitude parameter of the image of the connection point of the non-localization point as the initial repetition parameter when executing the initialization step until the repetition rate of change becomes lower than a predetermined threshold value. The position parameter and the attitude parameter of the image of the position to be positioned are modified by a method including executing the descent method. The specific calculation process is shown in Equation 1-7.

According to a preferred embodiment of the present invention, the measurement component is an inertial navigation measurement component, the position parameter includes abscissa and ordinate coordinates, preferably a vertical coordinate, and the attitude parameter is a yaw angle. , And preferably includes a pitch angle and a roll angle.

According to one preferred embodiment of the invention, the measuring component includes a laser SLAM measuring device and / or a visual SLAM measuring device.

According to one preferred embodiment of the present invention, the processing apparatus includes the coordinate system, the image of the control point, the image of the position to be positioned, the position parameter and the posture parameter of the image of the control point, and after modification. The position parameter and the posture parameter of the image of the position to be positioned are stored in a database or a file, and a map library is constructed.

The present invention is configured to communicate with the unmanned carrier as described above, the camera and the measurement component, and modify the position parameters and attitude parameters of the image based on the image, the position parameter and the attitude parameter. Further provided is an image acquisition processing system including the processing equipment being used. The processing device is not installed in the automatic guided vehicle, for example.

The processing apparatus is configured to be able to execute, for example, the mapping method 100 as described above.

The present invention includes a camera configured to collect an image of the lower part of the automatic guided vehicle, a light emitting device configured to illuminate the lower part of the automatic guided vehicle, and a position parameter of the automatic guided vehicle. And the inertial navigation measuring component configured to measure the attitude parameter, and the camera and the inertial navigation measuring component are both coupled to it, and the position of the image is based on the image, the position parameter and the attitude parameter. Further provided is a mapping positioning system for automated guided vehicles, including a processing device that modifies parameters and attitude parameters.

The processing apparatus is configured to, for example, execute the mapping method 100 as described above.

The present invention comprises a device configured to create or acquire a coordinate system for the location, an image of a control point by scanning the location, an image of a plurality of positioning targets, and a position corresponding to the image. A device configured to acquire parameters and attitude parameters, and a configuration to modify the position parameters and attitude parameters of the image of the position to be positioned based on the image, the position parameters, and the attitude parameters. Provides devices that map locations, including devices that have been used.

Based on the map created by method 100, the present invention further provides positioning method 200. Hereinafter, the positioning method 200 according to the present invention will be described with reference to FIG.

As shown in FIG. 11, step S201 can be performed by loading or acquiring the map obtained by the method 100 of the present invention, for example, by loading or reading a map file or database.

In step S202, an image of the position to be positioned, a position parameter corresponding to the image, and a posture parameter are collected or acquired. For example, while collecting images during the AGV operation, the position parameters and attitude parameters corresponding to the images are measured.

In step S203, the image having the closest distance to the image at the position to be positioned is searched for in the map.

According to one preferred embodiment of the present invention, the positioning method 200 uses a phase correlation method to ensure reliability and position parameter offset between an image at a position to be positioned and an image having the shortest distance. And to calculate the attitude parameter offset.

According to one preferred embodiment of the present invention, when the reliability calculated by the phase correlation method is lower than a predetermined value, the image having the closest distance is discarded and the distance from the image at the position to be positioned is set. Re-search for images that are closest (not including discarded images) and have a higher reliability than the specified value. If an image with the closest distance and a higher reliability than a predetermined value is found, the position parameter of the image to be positioned can be obtained by adding the offset amount of the phase correlation method to the position of the searched image, and then. If you update the position of the device, the positioning will be successful. After successful positioning, the next searched position is this position.

FIG. 12 is a block diagram of a computer program product 900 configured according to at least some embodiments of the present invention. The signal-carrying medium 902 can be realized or can include a computer-readable medium 906, a computer-recordable medium 908, a computer communication medium 910, or a combination thereof, and the processing unit is arranged before the signal-carrying medium 902. Stores all or part of the programming instructions 904 in the process described in. These instructions are, for example, a process of creating or acquiring a coordinate system of the above-mentioned location on one or more processors, an image of a control point by scanning the above-mentioned location, an image of a position to be positioned, and the above-mentioned image. The process of acquiring the position parameter and the posture parameter corresponding to the above, the image of the control point, the image of the position to be positioned, the image of the position to be positioned based on the position parameter and the posture parameter. It may include one or more executable instructions for executing the process of modifying the position parameter and the attitude parameter.

Although the above detailed description has described various examples of devices and / or methods using block diagrams, flowcharts and / or examples, such block diagrams, flowcharts and / or examples may be one or more. As will be appreciated by those skilled in the art, each function and / or operation in such a block diagram, flowchart or example will include a wide range of hardware, software, firmware, or them. Can be performed individually and / or collectively by virtually any combination of. In one example, some parts of the subject matter described herein are implemented by application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs), or other forms of integration. You may. However, one skilled in the art may implement the exemplary embodiments described herein equivalently or partially in an integrated circuit, one running on one or more computers. Alternatively, it may be implemented as multiple computer programs (eg, one or more computer programs running on one or more computer systems), or one or more running on one or more processors. Program (eg, one or more programs running on one or more computers), as firmware, or most combinations thereof. It is understandable that, with this disclosure, the circuit design and / or the creation of software and / or firmware code is within the skill of those skilled in the art. For example, the user can select the main hardware and / or firmware medium if speed and accuracy are of paramount importance, and if flexibility is paramount, the key software embodiments. It can be selected, and in the alternative, any combination of hardware, software, and / or firmware can be selected.
Further, as will be appreciated by those skilled in the art, the mechanisms of the subject matter described herein can be distributed as program products in various forms, and exemplary examples of the subject matter described herein are: It can be applied regardless of the specific type of signal-carrying medium for actually realizing the distribution. Examples of signal-carrying media include recordable media such as flexible discs, hard disk drives, compact discs (CDs), digital video discs (DVDs), digital tapes, computer memories, and digital and / or analog communication media (eg, optical). Includes, but is not limited to, transmission-type media such as fiber cables, waveguides, wired communication links, wireless communication links, etc.

Equipment and / or methods described herein may be described in a manner as described herein, and then the equipment and / or methods thus described may be integrated into a data processing system by engineering practice for those skilled in the art. It is common in this field. That is, at least some of the devices and / or methods described herein can be integrated into a data processing system by a reasonable amount of experimentation. As will be appreciated by those skilled in the art, typical data processing systems are generally system unit enclosures, video display devices, memories such as volatile and non-volatile memories, processors such as microprocessors and digital signal processors, operating systems and the like. One or more interactive devices such as computing entities, drives, graphical user interfaces, applications, touchpads or touch panels, and / or feedback loops and control motors (eg, feedback, components that sense position and / or speed). And / or includes one or more of control systems including a control motor) for moving and / or adjusting the amount. A typical data processing system can be implemented in any suitable commercially available unit, as is commonly found in data computation / communication and / or network computation / communication systems.

Finally, the above is merely a preferred embodiment of the present invention and does not limit the present invention, and the present invention has been described in detail with reference to the above-described embodiments. The technical means described in the embodiments can be modified or some technical features can be evenly replaced. Any modifications, even substitutions, improvements, etc. made within the spirit and principles of the invention should be included in the scope of protection of the invention.

Claims (29)

The method comprising the steps of creating or acquiring a coordinate system of the location,
A step by scanning the location, an image of the orientation points, the position of the image to be positioning target, to obtain the positional parameters and attitude parameters corresponding to the image,
Image of the orientation point, the image position to be the positioning target, on the basis of the position parameter and the orientation parameter, and modifying step of modifying the position parameter and attitude parameters of the position of the image to be the positioning target, the free It ’s a way to map the location
The correction step is
Creating a set of connection points including one image, the position parameter and the attitude parameter corresponding to the one image, and whether or not the image corresponds to a control point, respectively.
From the set of connection points, two connection points whose distances do not exceed a predetermined value are acquired as one connection to create a set of connections.
For two connection points included in each connection in the set of connections, the connection reliability between the two connection points is calculated, and the connection whose connection reliability is higher than a predetermined threshold is used as the mapping connection set. Filtering and
A method of mapping a location, including modifying the position and orientation parameters of an image of the position to be positioned based on the mapping connection set . The location parameters include the abscissa and ordinate, before Symbol attitude parameters, including yaw angle, the method described in請Motomeko 1. The method according to claim 2, wherein the position parameter includes vertical coordinates, and the posture parameter includes a pitch angle and a roll angle. The modification step further
In the mapping connection set comprises performing a gradient descent for the location parameters and orientation parameters of the image of the connection point of the non-orientation points when performing an initialization step an initial iteration parameters, according to claim 1 the method of. The modification step further
The method of claim 4 , comprising performing the gradient descent method until the iterative rate of change is below a predetermined threshold. The aspect according to any one of claims 1 to 5 , wherein image collection is performed a plurality of times for a part or all of the control points, and the position parameter and the posture parameter corresponding to each image collection are acquired. Method. A database of the coordinate system, the image of the control point, the image of the position to be positioned, the position parameter and the posture parameter of the image of the control point, and the position parameter and the posture parameter of the image of the position to be the position after modification. or file to be stored to create a map, the method according to any one of請Motomeko 1-6. The method according to claim 7, wherein the set of connections and / or the mapping connection set is stored in the database or the file to create a map. The method according to any one of claims 1 to 8, wherein the coordinate system is a physical coordinate system. The method of claim 1 , wherein the predetermined value is half the length or width of the image. With the base
A camera mounted on the base and configured to collect images in the area below the base.
A measuring component mounted on the base and configured to measure or calculate the position parameter and attitude parameter of the automatic guided vehicle corresponding to the image .
Attached to the base, both the camera and the measuring component are coupled to it to control the automatic guided vehicle and advance it to a position to be a control point and a positioning target, and become an image of the control point and the positioning target. A controller that is configured to collect an image of the location,
For image acquisition, including a processing device coupled to the camera and the measuring component to modify the position and orientation parameters of the image at the position to be positioned based on the image, the position and orientation parameters. It ’s an unmanned carrier,
The processing device is
Creating a set of connection points including one image, the position parameter and the attitude parameter corresponding to the one image, and whether or not the image corresponds to a control point, respectively.
From the set of connection points, two connection points whose distances do not exceed a predetermined value are acquired as one connection to create a set of connections.
For two connection points included in each connection in the set of connections, the connection reliability between the two connection points is calculated, and the connection whose connection reliability is higher than a predetermined threshold is used as the mapping connection set. Filtering and
In the mapping connection set, a gradient descent method in which the position parameter and the attitude parameter of the image of the connection point of the non-localization point are used as the initial iteration parameters when the initialization step is executed until the repetition rate of change becomes lower than a predetermined threshold. An unmanned carrier , characterized in that the position parameter and the posture parameter of the image of the position to be positioned are modified by a method including the execution of. The automatic guided vehicle according to claim 11, further comprising a light emitting device attached to the base and configured to illuminate an area below the base for image acquisition by the camera. Wherein attached to the base, the light emitting device further including a lens hood to soften the light from the AGV according to請Motomeko 12 Section. The automatic guided vehicle according to claim 13, wherein the light emitting device is attached so as to surround the lens hood. The automatic guided vehicle according to any one of claims 11 to 14 , wherein the measuring component is an inertial navigation measuring component. The location parameters include the abscissa and ordinate, before Symbol pose parameters include yaw angle, AGV according to any one of請Motomeko 11-15. The automatic guided vehicle according to claim 16, wherein the position parameter includes vertical coordinates, and the attitude parameter includes a pitch angle and a roll angle. The automatic guided vehicle according to any one of claims 11 to 17 , wherein the measuring component includes a laser SLAM measuring device and / or a visual SLAM measuring device. The processing device includes a location coordinate system, an image of the control point, an image of the position to be positioned, a position parameter and a posture parameter of the image of the control point, and a position of an image of the position to be positioned after modification. store parameters and attitude parameters in a database or a file is by Uni configured to create a map, AGV of claim 11. The automatic guided vehicle according to claim 19, wherein the processing device stores the set of connections and / or the mapping connection set in the database or the file to create a map. The automatic guided vehicle according to claim 11 and
An image acquisition processing system comprising a processing device coupled to the camera and the measuring component to modify the position and orientation parameters of the image based on the image, the position and orientation parameters. The image acquisition processing system according to claim 19 or 20, wherein the processing apparatus is configured to be able to execute the mapping method according to any one of claims 1 to 10. With a camera configured to collect images below the automated guided vehicle,
A light emitting device configured to illuminate the lower part of the automatic guided vehicle, and
Inertial navigation measurement parts configured to measure the position and attitude parameters of the automated guided vehicle, and
A mapping positioning system for automated guided vehicles, including the camera and a processing device to which both the inertial navigation measuring components are coupled .
The processing device is
Creating a set of connection points including one image, the position parameter and the attitude parameter corresponding to the one image, and whether or not the image corresponds to a control point, respectively.
From the set of connection points, two connection points whose distances do not exceed a predetermined value are acquired as one connection to create a set of connections.
For two connection points included in each connection in the set of connections, the connection reliability between the two connection points is calculated, and the connection whose connection reliability is higher than a predetermined threshold is used as the mapping connection set. Filtering and
In the mapping connection set, a gradient descent method in which the position parameter and the attitude parameter of the image of the connection point of the non-localization point are used as the initial iteration parameters when the initialization step is executed until the repetition rate of change becomes lower than a predetermined threshold. A mapping positioning system characterized in that the position parameter and the posture parameter of the image of the position to be positioned are modified by a method including the execution of . The mapping positioning system according to claim 23 , wherein the processing apparatus is configured to be able to execute the mapping method according to any one of claims 1 to 10. A device configured to create or retrieve the coordinate system of location,
A device configured to scan the location to obtain an image of a control point, an image of a plurality of positioning targets, a position parameter corresponding to the image, and a posture parameter.
A device that maps a location, including a correction device that modifies the position and orientation parameters of the image of the position to be positioned based on the image, the position parameter, and the attitude parameter.
The correction device is
Creating a set of connection points including one image, the position parameter and the attitude parameter corresponding to the one image, and whether or not the image corresponds to a control point, respectively.
From the set of connection points, two connection points whose distances do not exceed a predetermined value are acquired as one connection to create a set of connections.
For two connection points included in each connection in the set of connections, the connection reliability between the two connection points is calculated, and the connection whose connection reliability is higher than a predetermined threshold is used as the mapping connection set. Filtering and
A device that maps a location, including modifying the position and orientation parameters of an image of the position to be positioned based on the mapping connection set . Loading or acquiring the map obtained by the method according to claim 7.
Collecting or acquiring an image of the position to be positioned, position parameters and attitude parameters corresponding to the image, and
A positioning method including searching for an image having the closest distance to an image at a position to be positioned based on the map. 26. Positioning method. When the reliability calculated by the phase correlation method is lower than the predetermined value, the image having the closest distance is discarded, the distance to the image at the position to be positioned is the shortest, and the reliability is higher than the predetermined value. The positioning method according to claim 26, wherein the image is re-searched. A computer-readable storage medium that stores computer-executable instructions that perform the mapping method according to any one of claims 1-10, when executed by a processor.

Images